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Original Investigation | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period Vasily Giannakeas, MPH; Joanne Kotsopoulos, PhD; Matthew C. Cheung, MD; Laura Rosella, PhD; Jennifer D. Brooks, PhD; Lorraine Lipscombe, MD; Mohammad R. Akbari, MD, PhD; Peter C. Austin, PhD; Steven A. Narod, MD Abstract IMPORTANCE Individuals with cancer often have an elevated platelet count at the time of diagnosis. The extent to which an elevated platelet count is an indicator of cancer is unclear. OBJECTIVE To evaluate the association of an elevated platelet count with a cancer diagnosis. DESIGN, SETTING, AND PARTICIPANTS This nested case-control study included Ontario residents enrolled in the provincial health insurance plan who had 1 or more routine complete blood count (CBC) tests performed between January 1, 2007, and December 31, 2017, with follow-up through December 31, 2018. Case patients were individuals with a new cancer diagnosis during the observation period. Eligible control individuals were cancer free before the date of diagnosis for a case patient to whom they were matched. One case patient was matched to 3 controls based on sex, age, and health care use patterns. Data were analyzed from September 24, 2020, to July 13, 2021. EXPOSURES Case patients and controls were assigned to 1 of 5 exposure groups based on age- and sex-specific platelet count distributions in the control population: very low (ⱕ10th percentile), low (>10th to 25th percentile), medium (>25th to <75th percentile), high (75th to <90th percentile), and very high (ⱖ90th percentile). MAIN OUTCOMES AND MEASURES Odds ratios (ORs) were estimated for specific cancer sites for each category of platelet count at intervals up to 10 years after a blood test. RESULTS Of the 8 917 187 eligible Ontario residents with a routine CBC record available, 4 971 578 (55.8%) were women; the median age at the first CBC was 46.4 years (IQR, 32.5-59.5 years). Among individuals with a routine CBC record available, 495 341 (5.6%) received a diagnosis of first primary cancer during the 10-year observation period. The OR for a solid tumor diagnosis associated with a very high platelet count vs a medium platelet count in the 6-month period before the diagnosis was 2.32 (95% CI, 2.28-2.35). A very high platelet count was associated with colon (OR, 4.38; 95% CI, 4.22-4.54), lung (OR, 4.37; 95% CI, 4.22-4.53), ovarian (OR, 4.62; 95% CI, 4.19-5.09), and stomach (OR, 4.27; 95% CI, 3.91-4.66) cancers. Odds ratios attenuated with increasing time from CBC test to cancer diagnosis. CONCLUSIONS AND RELEVANCE In this nested case-control study, an elevated platelet count was associated with increased risk of cancer at several sites. Our findings suggest that an elevated platelet count could potentially serve as a marker for the presence of some cancer types. JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 Key Points Question Is a high platelet count associated with an increased risk of cancer? Findings In this nested case-control study of 8 917 187 Ontario residents who had 1 or more routine complete blood count tests performed, an elevated platelet count was associated with a diagnosis of cancer within 10 years after the blood test. The magnitude of the association varied by cancer type and time elapsed since the blood test. Meaning The findings suggest that a high platelet count is associated with increased cancer risk. + Supplemental content Author affiliations and article information are listed at the end of this article. Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 1/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
Introduction Patients with cancer often have an abnormally high platelet count at the time of diagnosis (thrombocytosis), defined as a platelet count greater than 450 × 109 /L (to convert to ×103 per microliter, divide by 1.0).1 A normal platelet count falls between 150 and 450 × 109 /L and varies with the age and sex of the individual.1,2 Several conditions that commonly cause an elevated platelet count include acute blood loss, infection, and inflammation.3 Solid tumor cancers can sometimes lead to an elevated platelet count to the extent that an undiagnosed cancer is often considered in the diagnostic workup of a patient with thrombocytosis.3 Cancer is believed to induce platelet formation through the release of interleukin 6, a proinflammatory cytokine that stimulates the production of thrombopoietin hormone.4 Elevated levels of thrombopoietin have a direct effect on increased platelet production. Excess levels of thrombopoietin in the blood stimulate megakaryocyte cell division in the bone marrow, which in turn leads to platelet formation.5 An elevated platelet count has been shown to be associated with short-term risk of cancer in the general population.6-8 Prospective studies evaluating platelet count and survival among patients with newly diagnosed cancer have also noted a high proportion of patients who presented with thrombocytosis.9-12 The excess risk associated with an elevated platelet count varies by cancer site but has been most studied for lung, colon, and gastric cancers. The full range of cancers associated with a high platelet count and whether risks associated with platelet counts within the high-normal range exist remain unclear. Furthermore, it is unclear whether the association between a high platelet count and cancer is transient or prolonged. Based on results of previous studies,6-8 a high platelet count may be a risk factor for developing cancer or, alternatively, a marker indicative of an undetected cancer. It is also not clear whether an increasing platelet count is a better indicator of a new cancer than is a high but steady platelet count. We identified a cohort of adult residents in Ontario, Canada, who had 1 or more routine blood tests performed for a complete blood count (CBC) including platelet counts and subsequently received a diagnosis of cancer to assess the range of cancers associated with a high platelet count. We also examined whether an increasing platelet count is associated with an increased cancer risk. Methods Study Design, Population, and Data Ontario is the most populous province in Canada, with a population of 14.5 million. Ontario residents are covered under the universal health insurance program, which includes coverage for primary care services, emergency visits, hospitalizations, and (among older adults) medication. This nested case- control study used data from ICES, a nonprofit organization that provides researchers with deidentified data that can be used for research purposes. ICES is a prescribed entity under §45 of Ontario’s Personal Health Information Protection Act, which allows for research conduct without a research ethics board review and without the need for informed consent. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for case-control studies. ICES data include results of laboratory tests conducted in Ontario from January 2007 to present. The Ontario Laboratory Information System data set includes more than 85 million CBC test records, including those for 9.5 million (of the 14.5 million) Ontario residents. The CBC records include the date of laboratory analysis, the platelet count, and other standard blood parameters. Incident cancers in Ontario are recorded in the Ontario Cancer Registry, which was started in January 1964. This study also used data on physician billing (Ontario Health Insurance Plan claims database), emergency department visits (National Ambulatory Care and Reporting System database), acute care hospitalizations (Discharge Abstract Database), and dispensed medications among adults aged 65 years or older (Ontario Drug Benefit Claims database). These datasets were linked using unique encoded identifiers and analyzed at ICES. JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 2/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
Construction of the Cohort The nesting cohort consisted of 8 917 187 Ontario residents who had at least 1 routine CBC test ordered by a practicing physician in a community health setting from January 1, 2007, through December 31, 2017. Cohort entry date was the date of the first eligible CBC test. Patients with cancer before the cohort entry date were excluded. Patients were observed from the date of their first routine blood test to the first date of any cancer diagnosis, death from any cause, end of Ontario Health Insurance Plan eligibility, or the end of the observation period (December 31, 2018) (eFigure 1 in the Supplement). Details on the inclusion criteria, exclusion criteria, and the study cohort are available in eTables 1-3 in the Supplement. Baseline Variables Baseline information was obtained and updated at the time of each CBC test. We included information on general demographic characteristics, health services use, comorbidities and chronic conditions, medication use (among individuals aged ⱖ66 years), and additional CBC test results. The Johns Hopkins ACG System software, version 10,13 was used to obtain aggregate diagnosis groups and resource utilization bands. Case Patients Case patients were defined as individuals who received a cancer diagnosis after the date of cohort entry. Data on first primary cancer diagnoses during the observation period were captured from the Ontario Cancer Registry. The Ontario Cancer Registry is a validated cancer registry that provides information on the date of diagnosis, cancer site, and tumor-specific data, such as morphologic features, stage, grade, lymph node involvement, and for certain cancers, hormone receptor status.14 We restricted the interpretation of our findings to solid cancers other than liver cancer because both liver and hematologic cancers may have a direct effect on platelet count; thrombopoietin production occurs in the liver, and megakaryocyte production occurs in the bone marrow. For case patients, the index date was defined as the date of diagnosis of cancer. Matching We hard-matched 3 control individuals to each case patient. Each matched control was alive and cancer free on the date of diagnosis of the case patient (eFigure 1 in the Supplement). Case patients and controls were matched based on sex, calendar date of CBC test (±30 days), age (±2 years), years of coverage by the Ontario Health Insurance Plan (±2 years), and the patient’s resource utilization band. Incidence density sampling was used such that case patients could serve as potential controls at prior time points. Exposure We assigned a categorical value to each platelet count based on the percentile distribution for the cancer-free controls. Five mutually exclusive categories were created: very low (ⱕ10th percentile), low (>10th to 25th percentile), medium (>25th to <75th percentile), high (75th to <90th percentile), and very high (ⱖ90th percentile). To account for variation in platelet count by sex and age, we defined categories of platelet count using reference distributions that were standardized according to age and sex from the pool of control patients (eFigure 2 in the Supplement). Statistical Analysis Primary Analysis We performed a series of (nested) matched case-control analyses to measure the association of platelet count with risk of cancer at various time intervals before the index date. Each matched quadruplet of case patients and controls (3:1) was assessed at 7 time intervals before the index date: 0 to 6 months, 6 to 12 months, 12 to 18 months, 18 to 24 months, 2 to 3 years, 3 to 5 years, and 5 to 10 years. Each case patient could contribute to up to 7 observations (1 for each time interval). If JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 3/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
multiple routine CBC tests were performed within a given period, 1 was chosen at random. For each cancer site and for each time point, an odds ratio (OR) was estimated using conditional logistic regression. At each time point, the medium platelet count category was used as the reference group and ORs were estimated for very high, high, low, and very low counts compared with the reference group. Information on tumor stage was available for several sites. A subanalysis was conducted after stratifying cancers by stage for these sites. In a thrombocytosis sensitivity analysis, we assigned platelet levels using clinical cutoffs: thrombocytopenia (<150 ×109 platelets/L), normal level (150 to 450 ×109 platelets/L), and thrombocytosis (>450 ×109 platelets/L). Secondary Analysis As a secondary objective, we sought to assess whether a change in platelet count over time was associated with a diagnosis of cancer. To study this, we selected individuals who had 2 routine CBC tests recorded 9 to 15 months apart. If multiple CBC records were available in the 9- to 15-month period, 1 was selected at random. A second iteration of matching (using the same matching criteria) was done using this subset of individuals (n = 4 372 288 [49% of the primary cohort]). A difference in platelet count was measured by subtracting the first platelet count from the second platelet count. Sex- and age-standardized reference distributions for change in platelet count were created (eFigure 3 in the Supplement). Five categories were created to classify the change in platelet count: large decrease (ⱕ10th percentile), small decrease (>10th to 25th percentile), no substantial change (>25 to <75th percentile [reference group]), small increase (75th to <90th percentile), and large increase (ⱖ90th percentile). All statistical analyses were performed using SAS software, version 9.4 (SAS Institute Inc). Data were analyzed from September 24, 2020, to July 13, 2021. Results Of the 8 917 187 eligible individuals with 1 or more routine CBC tests identified in Ontario during the accrual period, 4 971 578 (55.8%) were women; the median age at the first CBC was 46.4 years (IQR, 32.5-59.5 years) (Table 1). Of the entire cohort, 495 341 individuals (5.6%) received a cancer diagnosis during the observation period. We successfully matched 491 779 case patients with cancer (99.3%) to 3 controls in 1 or more predefined time intervals. Case patients were similar to controls with respect to their demographic information, health services use, medication use, and comorbidity variables (eTable 4 in the Supplement). The mean platelet count at the most recent blood test was higher among case patients with cancer than among matched controls (245.7 × 109 /L vs 237.0 × 109 /L). Case patients diagnosed with a solid tumor were more likely to have a recent platelet count in the highest category compared with cancer-free controls (44 344 [19.5%] vs 65 626 [9.6%]). For blood samples obtained during the 6 months before a cancer diagnosis, the OR for any solid cancer associated with a very high platelet count (ⱖ90th percentile) vs a medium platelet count (reference, >25th to <75th percentile) was 2.32 (95% CI, 2.28-2.35) (Table 2). The OR for this association attenuated with increasing time from blood test to cancer diagnosis (Table 2); the ORs for the very high platelet category were 1.41 (95% CI, 1.39-1.44) for 6 to less than 12 months before diagnosis, 1.20 (95% CI, 1.18-1.22) for 12 to less than 24 months before diagnosis, 1.15 (95% CI, 1.13-1.17) for 24 to less than 60 months before diagnosis, and 1.13 (95% CI, 1.10-1.15) for 60 to 120 months before diagnosis. The ORs for the association of a high platelet count with a cancer diagnosis were greatest for patients with cancers of the colon, lung, ovary, and stomach (Figure 1). During the 0- to 6-month period before a cancer diagnosis, the ORs for the very high platelet count category were 4.38 (95% CI, 4.22-4.54) for colon cancer, 4.37 (95% CI, 4.22-4.53) for lung cancer, 4.62 (95% CI, 4.19-5.09) for ovarian cancer, and 4.27 (95% CI, 3.91-4.66) for stomach cancer (Figure 1 and eTable 5 in the Supplement). Significant associations were also observed for esophageal cancer (OR, 3.18; 95% CI, 2.81-3.60), other gastrointestinal tract cancers (OR, 3.10; 95% CI, 2.75-3.49), and kidney cancer (OR, JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 4/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
Table 1. Characteristics of the Study Cohort at the First Eligible Routine CBC Test Description Individuals (N = 8 917 187)a Sex Female 4 971 578 (55.8) Male 3 945 609 (44.2) Age, y Mean (SD) 47.0 (17.8) Median (IQR) 46.4 (32.5-59.5) Residence location Urban 8 084 848 (90.7) Rural 820 419 (9.2) Missing 11 920 (0.1) Core primary care visits to general practitioner or family practitioner in previous 2 y, No. Mean (SD) 2.8 (3.4) Median (IQR) 2 (1-3) Rostered to family physician 6 940 867 (77.8) Comorbidities and chronic conditions Asthma 796 810 (8.9) Congestive heart failure 172 576 (1.9) COPD 192 482 (2.2) Hypertension 2 139 804 (24.0) Diabetes 666 477 (7.5) Kidney disease 88 520 (1.0) Chronic coronary syndrome 321 278 (3.6) Hemoglobin concentration, g/L Mean (SD) 139.5 (14.9) Median (IQR) 140 (130-150) Platelet count, 109 /L Mean (SD) 247.2 (64.5) Median (IQR) 241 (205-282) Observation time, yb Mean (SD) 6.8 (3.0) Median (IQR) 7.3 (4.4-9.3) Routine CBC tests in observation period, No. Mean (SD) 4.3 (6.3) Median (IQR) 3 (1-6) Cancer diagnosisb,c Any 492 691 (5.5) Solid tumor 429 222 (4.8) Colon 51 521 (0.6) Lung 56 724 (0.6) Breastd 65 721 (1.3) Ovaryd 7661 (0.2) Cervicald 3494 (0.1) Endometriald 17 101 (0.3) Prostatee 62 946 (1.6) Thyroid 21 478 (0.2) Pancreas 12 021 (0.1) Stomach 9195 (0.1) Kidney 14 063 (0.2) Bladder 23 344 (0.3) Liver 7696 (0.1) Esophagus 4712 (0.1) Other gastrointestinal tract 5255 (0.1) Brain 5724 (0.1) Melanoma 20 192 (0.2) (continued) JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 5/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
Table 1. Characteristics of the Study Cohort at the First Eligible Routine CBC Test (continued) Description Individuals (N = 8 917 187)a Head and neck 13 363 (0.1) Other 27 011 (0.3) Hematologic tumor 63 469 (0.7) Leukemia 5154 (0.1) Lymphoma 33 827 (0.4) Multiple myeloma 8274 (0.1) Other 16 214 (0.2) Abbreviations: CBC, complete blood count; COPD, chronic obstructive pulmonary disease; OHIP, Ontario Health Insurance Plan. SI conversion factors: To convert hemoglobin concentration to grams per deciliter, divide by 10.0; platelet count to 103 per microliter, divide by 1.0. a Data are presented as number (percentage) of individuals unless otherwise indicated. b Period of observation was from the first eligible CBC test to the earliest date of death, end of OHIP eligibility, or end of the observation period (December 31, 2018). c Data are from the Ontario Cancer Registry. d Women only. e Men only. Table 2. Odds Ratios of Any Solid Tumor Diagnosis by Platelet Count Category and Time From Complete Blood Count Test to Cancer Diagnosisa Platelet count percentile category by time to cancer diagnosisb No. (%) Odds ratio (95% CI)c Case patients Control individuals <6 mo Very low 19 161 (8.4) 74 891 (11.0) 0.87 (0.86-0.89) Low 27 308 (12.0) 106 707 (15.6) 0.87 (0.86-0.89) Medium 98 480 (43.3) 336 232 (49.2) 1 [Reference] High 38 372 (16.9) 99 539 (14.6) 1.32 (1.30-1.34) Very high 44 344 (19.5) 65 626 (9.6) 2.32 (2.28-2.35) 6 to <12 mo Very low 14 870 (10.1) 48 700 (11.0) 0.95 (0.93-0.97) Low 20 716 (14.0) 69 561 (15.7) 0.93 (0.91-0.95) Medium 70 078 (47.4) 219 039 (49.4) 1 [Reference] High 23 209 (15.7) 64 288 (14.5) 1.13 (1.11-1.15) Very high 19 038 (12.9) 42 145 (9.5) 1.41 (1.39-1.44) 12 to <24 mo Very low 22 086 (10.2) 70 743 (10.9) 0.95 (0.93-0.96) Low 32 018 (14.7) 103 336 (15.9) 0.94 (0.93-0.95) Medium 106 239 (48.9) 322 348 (49.5) 1 [Reference] High 32 952 (15.2) 94 872 (14.6) 1.05 (1.04-1.07) Very high 23 942 (11.0) 60 412 (9.3) 1.20 (1.18-1.22) 24 to <60 mo Very low 27 116 (10.1) 87 869 (10.9) 0.93 (0.92-0.95) Low 40 852 (15.2) 127 941 (15.9) 0.97 (0.95-0.98) Medium 132 330 (49.4) 400 393 (49.8) 1 [Reference] High 40 363 (15.1) 115 881 (14.4) 1.05 (1.04-1.07) Very high 27 481 (10.2) 72 342 (9.0) 1.15 (1.13-1.17) 60-120 mo Very low 15 744 (10.1) 49 761 (10.7) 0.96 (0.94-0.98) Low 23 750 (15.3) 74 880 (16.1) 0.96 (0.94-0.97) Medium 76 963 (49.5) 232 828 (49.9) 1 [Reference] High 23 340 (15.0) 66 787 (14.3) 1.06 (1.04-1.08) Very high 15 655 (10.1) 42 100 (9.0) 1.13 (1.10-1.15) a Liver cancer was excluded. b Platelet count percentile categories were defined as follows: very low (ⱕ10th percentile), low (>10th to 25th percentile), medium (>25th to <75th percentile), high (75th to <90th percentile), and very high (ⱖ90th percentile). c P < .001 for all. JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 6/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
2.55; 95% CI, 2.38-2.74) (eFigure 4 in the Supplement). The associations attenuated with increasing time to diagnosis to varying degrees. In addition, high platelet count was associated with risk of breast cancer (OR, 1.05; 95% CI, 1.01- 1.10) and prostate cancer (OR, 1.24; 95% CI, 1.19-1.29) but was not associated with risk of melanoma (OR, 1.06; 95% CI, 0.97-1.15) or thyroid cancer (OR, 1.01; 95% CI, 0.94-1.09) (eFigure 4 in the Supplement). A low platelet count and a very low platelet count were associated with a decreased risk of breast and prostate cancer. In a sensitivity analysis, the ORs for the association of thrombocytosis and increased cancer risk were greatest for colon cancer, lung cancer, ovarian cancer, stomach cancer, esophageal cancer, and kidney cancer (eFigure 7 in the Supplement). We also studied the associations between a high platelet count and risk of solid tumors by stage at diagnosis (when data were available). There was a significant association across all stages of colon cancer, but the OR for the association was greatest for metastatic disease (stage IV) (OR, 7.96; 95% CI, 7.26-8.72) (Figure 2). Data for the other cancer sites by stage are presented in eFigure 6 in the Supplement. We also examined whether a substantial increase in platelet count (compared with a platelet count measured in the previous 9 to 15 months) was associated with an risk of cancer. Case patients diagnosed with a solid tumor were more likely to have a recent increase in platelet count (ⱖ90th percentile) than were cancer-free controls (19 750[21.8%] vs 27 530 [10.2%]) (eTable 6 in the Supplement). A recent increase in the platelet count was associated with risk of colon cancer (OR, 5.52; 95% CI, 5.21-5.86), lung cancer (OR, 4.77; 95% CI, 4.51-5.04), ovarian cancer (OR, 7.23; 95% CI, 6.12-8.53), and stomach cancer (OR, 5.51; 95% CI, 4.82-6.29) (Figure 3 and eTable 7 in the Supplement). No associations were observed between a recent increase in the platelet count and Figure 1. Odds Ratios of Cancer by Platelet Count Category and Time From Complete Blood Count Test to Cancer Diagnosis Very low (≤10th percentile) Low (>10th to 25th percentile) Medium (>25th to <75th percentile) High (75th to <90th percentile) Very high (≥90th percentile) 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Colon cancer A 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Lung cancer B 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Ovarian cancer C 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stomach cancer D JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 7/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
breast cancer (OR, 1.01; 95% CI, 0.94-1.09), melanoma (OR, 1.01; 95% CI, 0.89-1.15), or thyroid cancer (OR, 0.97; 95% CI, 0.86-1.09) (eFigure 5 in the Supplement). Discussion In this large, nested case-control study, we found that an elevated platelet count identified during a routine blood examination was associated with an increased risk of developing a range of solid tumors. The OR for the association was greatest for a diagnosis of cancer within 6 months of a blood test. For several cancer sites (lung, colon, stomach, esophagus, and kidney), a high platelet count was associated with a cancer diagnosis in the following 3 or more years. For lung cancer, a significant association was present 10 years before diagnosis. Long-term associations were also seen for kidney cancer and esophageal cancer. In contrast, for ovarian cancer, there was an association only in the 6 months before a diagnosis. Overall, given the transient nature of the association with platelet count, our findings suggest that an elevated platelet count detected through routine blood examination may be a consequence of the presence of cancer rather than being a risk factor for the disease. The physiologic basis for the association is not clear but may be multifactorial. Platelets are produced in the bone marrow in response to thrombopoietin, which is upregulated by interleukin 6, primarily produced in the liver.15 It is possible that the increase in platelet count is a response to circulating factors produced by the cancer cells or is a local response to inflammation induced by the cancer cell mass. Various mechanisms have been proposed to explain the association between high platelet count and cancer, Figure 2. Odds Ratios of Colon Cancer by Platelet Count Category and Time From Complete Blood Count Test to Cancer Diagnosis by Cancer Stage 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage I colon cancer A 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage II colon cancer B 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage III colon cancer C 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage IV colon cancer D Very low (≤10th percentile) Low (>10th to 25th percentile) Medium (>25th to <75th percentile) High (75th to <90th percentile) Very high (≥90th percentile) JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 8/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
including the aggregation of cancer cells by platelets, increased extravasation or enhanced permeability of the basement membrane, and shielding cancer cells from immune attack in the bloodstream.16-18 Other possible mechanisms include iron deficiency, bleeding (among patients with colon cancer),19 abnormal platelet counts, and the infiltration of disseminated cancer cells in the bone marrow.20 Several studies have demonstrated an association between an elevated platelet count (thrombocytosis) and cancer risk. In general, these studies have either measured platelet counts at the time of diagnosis or had a short follow-up period subsequent to a CBC test.6-8 Pharmacoepidemiologic studies have further shown a lower incidence of certain cancer types among patients receiving platelet-inhibiting medications. For example, there is an established relationship between aspirin use (an antiplatelet drug) and decreased incidence of colon cancer.21-23 A protective effect of low-dose aspirin against ovarian cancer has also been suggested.24 Although antiplatelet medications inhibit platelet function as opposed to lowering the platelet count, the decreased incidence of cancer associated with aspirin use suggests the potential role functional platelets have in cancer risk. Our study findings suggest that individuals with a high platelet count might be candidates for investigation for the presence of an occult cancer after other nonmalignant causes of an elevated platelet count have been ruled out. Of individuals who had a cancer diagnosed within 6 months after the blood test, 19.5% had a very high platelet count (top 10 percentile). In a sensitivity analysis, we observed similar findings, with an association with some cancers among individuals with thrombocytosis. Giannakeas and Narod25 recently reported an association between thrombocytosis and incident cancers using the same data from the present study. The findings of the present study Figure 3. Odds Ratios of Cancer by Change in Platelet Count Category and Time From Complete Blood Count Test to Diagnosis 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Colon cancer A 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Lung cancer B 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Ovarian cancer C 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stomach cancer D Large decrease (≤10th percentile) Small decrease (>10th to 25th percentile) No substantial change (>25th to <75th percentile) Small increase (75th to <90th percentile) Large increase (≥90th percentile) JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 9/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
suggest that platelet counts might be useful as a cancer screening tool alone or in combination with other cancer screening modalities, in particular spiral computed tomography for lung cancer, colonoscopy for colon cancer, and a cancer antigen 125 test or transvaginal ultrasonography for ovarian cancer. Novel screening tests that incorporate cell-free DNA and methylation signatures have shown promising results in identifying site-specific cancers.26 Platelet count could potentially be used as an affordable screening test to improve the predictive value of other screening modalities. Particular attention should be given to individuals who have an increasing platelet count (Figure 3). A relative increase in platelet count that exceeded 1.5 SDs (ie, ⱖ90th percentile) was associated with risk for many cancer types. The associations found in this study were based on a single marker (platelet count) as a 1-time measurement and as a change over time. In future studies, we plan to investigate the clinical utility of platelet count testing as a screening test. We will incorporate additional blood count elements in combination with platelet count in a model to maximize predictive ability. Limitations This study has limitations. The extent to which unmeasured confounders influenced the association of platelet count with cancer diagnosis is unclear. For lung cancer, we observed a prolonged association with elevated platelet count throughout the 10-year observation period (Figure 1). Smoking status was not available through administrative data sources. Platelet counts have been shown to differ among smokers and nonsmokers.27 Body mass index was also not available and has been shown to be associated with platelet counts among women.28 Additional variables that are likely to influence platelet count include alcohol consumption, family history, and genetics. These variables were not attainable in our study because of the limitations of administrative health data. However, given the transient association observed between platelet count and a cancer diagnosis in this study, it is unlikely that prolonged exposures would be attributed to these variables. Moreover, the secondary analysis of the change in platelet count in an individual (in whom confounders were presumed to be fixed) over time revealed findings comparable to those seen in the primary analysis. Conclusions In this nested case-control study, an elevated platelet count was associated with increased risk of cancer at several sites. The association was transient and attenuated with increasing time from CBC test to the date of the cancer diagnosis. Odds ratios were greatest for colon, lung, ovary, gastroesophageal, and kidney cancers. Our findings suggest that an elevated platelet count could potentially serve as a marker for the presence of some cancer types. ARTICLE INFORMATION Accepted for Publication: November 8, 2021. Published: January 11, 2022. doi:10.1001/jamanetworkopen.2021.41633 Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Giannakeas V et al. JAMA Network Open. Corresponding Author: Steven A. Narod, MD, Women’s College Research Institute, Women’s College Hospital, 76 Grenville St, Sixth Floor, Toronto, ON M5S 1B2, Canada (steven.narod@wchospital.ca). Author Affiliations: Women’s College Research Institute, Women’s College Hospital, Toronto, Ontario, Canada (Giannakeas, Kotsopoulos, Lipscombe, Akbari, Narod); Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada (Giannakeas, Kotsopoulos, Rosella, Brooks, Akbari, Narod); ICES, Toronto, Ontario, Canada (Giannakeas, Cheung, Lipscombe, Austin); Division of Hematology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada (Cheung); Department of Medicine, University of Toronto, Toronto, Ontario, Canada (Lipscombe); Division of Endocrinology, Women’s College Hospital, Toronto, Ontario, Canada (Lipscombe); Institute of Medical Science, University of Toronto, Toronto, JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 10/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
Ontario, Canada (Akbari, Narod); Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada (Austin). Author Contributions: Mr Giannakeas had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Giannakeas, Kotsopoulos, Rosella, Brooks, Akbari, Narod. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Giannakeas, Kotsopoulos, Brooks. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Giannakeas, Kotsopoulos, Rosella. Obtained funding: Giannakeas, Kotsopoulos. Administrative, technical, or material support: Giannakeas, Kotsopoulos, Akbari. Supervision: Kotsopoulos, Cheung, Brooks, Lipscombe, Narod. Conflict of Interest Disclosures: Mr Giannakeas reported receiving financial support through the Canadian Institutes of Health Research Frederick Banting and Charles Best Doctoral Research Award during the conduct of the study. Dr Lipscombe reported receiving grants from the Canadian Institutes of Health Research, personal fees from Diabetes Canada, and salary support from the University of Toronto Novo Nordisk Network for Healthy Populations outside the submitted work. Dr Austin reported receiving financial support through a Mid-Career Investigator Award from the Heart and Stroke Foundation. Dr Narod reported being a recipient of the tier I Canada Research Chair in Breast Cancer. Dr Kotsopoulos reported being a recipient of a tier II Canada Research Chair. No other disclosures were reported. Funding/Support: This work was supported by the Peter Gilgan Centre for Women’s Cancers at Women’s College Hospital in partnership with the Canadian Cancer Society and by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: The analysis, results, conclusions, and opinions herein are solely those of the authors and do not reflect those of the funding or data sources. No endorsement by ICES, the Ontario MOHLTC, the Canadian Institutes of Health Research, or Cancer Care Ontario is intended or should be inferred. Additional Information: Parts of the study data are based on data and/or information compiled and provided by the MOHLTC; the Canadian Institute for Health Information; Immigration, Refugees and Citizenship Canada; and Cancer Care Ontario. IQVIA Solutions Canada Inc allowed use of their Drug Information File. REFERENCES 1. Tefferi A. Approach to the patient with thrombocytosis. UpToDate. 2020. Accessed May 19, 2021. https://www. uptodate.com/contents/approach-to-the-patient-with-thrombocytosis 2. Segal JB, Moliterno AR. Platelet counts differ by sex, ethnicity, and age in the United States. Ann Epidemiol. 2006;16(2):123-130. doi:10.1016/j.annepidem.2005.06.052 3. Harrison CN, Bareford D, Butt N, et al; British Committee for Standards in Haematology. Guideline for investigation and management of adults and children presenting with a thrombocytosis. Br J Haematol. 2010;149 (3):352-375. doi:10.1111/j.1365-2141.2010.08122.x 4. Stone RL, Nick AM, McNeish IA, et al. Paraneoplastic thrombocytosis in ovarian cancer. N Engl J Med. 2012;366 (7):610-618. doi:10.1056/NEJMoa1110352 5. Schafer AI. Thrombocytosis. N Engl J Med. 2004;350(12):1211-1219. doi:10.1056/NEJMra035363 6. Bailey SE, Ukoumunne OC, Shephard EA, Hamilton W. Clinical relevance of thrombocytosis in primary care: a prospective cohort study of cancer incidence using English electronic medical records and cancer registry data. Br J Gen Pract. 2017;67(659):e405-e413. doi:10.3399/bjgp17X691109 7. Ankus E, Price SJ, Ukoumunne OC, Hamilton W, Bailey SER. Cancer incidence in patients with a high normal platelet count: a cohort study using primary care data. Fam Pract. 2018;35(6):671-675. doi:10.1093/fampra/ cmy018 8. Mounce LT, Hamilton W, Bailey SE. Cancer incidence following a high-normal platelet count: cohort study using electronic healthcare records from English primary care. Br J Gen Pract. 2020;70(698):e622-e628. doi:10.3399/ bjgp20X710957 JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 11/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
9. Taucher S, Salat A, Gnant M, et al; Austrian Breast and Colorectal Cancer Study Group. Impact of pretreatment thrombocytosis on survival in primary breast cancer. Thromb Haemost. 2003;89(6):1098-1106. doi:10.1055/s- 0037-1613413 10. Bensalah K, Leray E, Fergelot P, et al. Prognostic value of thrombocytosis in renal cell carcinoma. J Urol. 2006;175(3, pt 1):859-863. doi:10.1016/S0022-5347(05)00526-4 11. Pedersen LM, Milman N. Prognostic significance of thrombocytosis in patients with primary lung cancer. Eur Respir J. 1996;9(9):1826-1830. doi:10.1183/09031936.96.09091826 12. Ishizuka M, Nagata H, Takagi K, Iwasaki Y, Kubota K. Preoperative thrombocytosis is associated with survival after surgery for colorectal cancer. J Surg Oncol. 2012;106(7):887-891. doi:10.1002/jso.23163 13. The Johns Hopkins ACG System, version 10.0. Technical reference guide. Accessed September 24 2020. https:// www.hopkinsacg.org/document/acg-system-version-10-0-technical-reference-guide/ 14. Robles SC, Marrett LD, Clarke EA, Risch HA. An application of capture-recapture methods to the estimation of completeness of cancer registration. J Clin Epidemiol. 1988;41(5):495-501. doi:10.1016/0895-4356(88)90052-2 15. Kaser A, Brandacher G, Steered W, et al. Interleukin-6 stimulates thrombopoiesis through thrombopoietin: role in inflammatory thrombocytosis. Blood. 2001;98(9):2720-2725. doi:10.1182/blood.V98.9.2720 16. Gay LJ, Felding-Habermann B. Contribution of platelets to tumour metastasis. Nat Rev Cancer. 2011;11(2): 123-134. doi:10.1038/nrc3004 17. Menter DG, Tucker SC, Kopetz S, Sood AK, Crissman JD, Honn KV. Platelets and cancer: a casual or causal relationship: revisited. Cancer Metastasis Rev. 2014;33(1):231-269. doi:10.1007/s10555-014-9498-0 18. Sylman JL, Mitrugno A, Tormoen GW, Wagner TH, Mallick P, McCarty OJT. Platelet count as a predictor of metastasis and venous thromboembolism in patients with cancer. Converg Sci Phys Oncol. 2017;3(2):023001. doi: 10.1088/2057-1739/aa6c05 19. Thompson MR, O’Leary DP, Flashman K, Asiimwe A, Ellis BG, Senapati A. Clinical assessment to determine the risk of bowel cancer using Symptoms, Age, Mass and Iron deficiency anaemia (SAMI). Br J Surg. 2017;104(10): 1393-1404. doi:10.1002/bjs.10573 20. George JN. Systemic malignancies as a cause of unexpected microangiopathic hemolytic anemia and thrombocytopenia. Oncology (Williston Park). 2011;25(10):908-914. 21. Cook NR, Lee IM, Zhang SM, Moorthy MV, Buring JE. Alternate-day, low-dose aspirin and cancer risk: long-term observational follow-up of a randomized trial. Ann Intern Med. 2013;159(2):77-85. doi:10.7326/0003-4819-159-2- 201307160-00002 22. Burn J, Sheth H, Elliott F, et al; CAPP2 Investigators. Cancer prevention with aspirin in hereditary colorectal cancer (Lynch syndrome), 10-year follow-up and registry-based 20-year data in the CAPP2 study: a double-blind, randomised, placebo-controlled trial. Lancet. 2020;395(10240):1855-1863. doi:10.1016/S0140-6736(20) 30366-4 23. Lin HD, Vora P, Soriano-Gabarró M, Chan KA. Association between low-dose aspirin use and colorectal cancer incidence in Taiwan. JAMA Netw Open. 2020;3(11):e2026494. doi:10.1001/jamanetworkopen.2020.26494 24. Barnard ME, Poole EM, Curhan GC, et al. Association of analgesic use with risk of ovarian cancer in the Nurses’ Health Studies. JAMA Oncol. 2018;4(12):1675-1682. doi:10.1001/jamaoncol.2018.4149 25. Giannakeas V, Narod SA. Incidence of cancer among adults with thrombocytosis in Ontario, Canada. JAMA Netw Open. 2021;4(8):e2120633. doi:10.1001/jamanetworkopen.2021.20633 26. Klein EA, Richards D, Cohn A, et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann Oncol. 2021;32(9):1167-1177. doi:10.1016/j.annonc.2021. 05.806 27. Green MS, Peled I, Najenson T. Gender differences in platelet count and its association with cigarette smoking in a large cohort in Israel. J Clin Epidemiol. 1992;45(1):77-84. doi:10.1016/0895-4356(92)90191-O 28. Samocha-Bonet D, Justo D, Rogowski O, et al. Platelet counts and platelet activation markers in obese subjects. Mediators Inflamm. 2008;2008:834153. doi:10.1155/2008/834153 SUPPLEMENT. eTable 1. Inclusion Table for CBC Tests eTable 2. Exclusion Table for Study Cohort eTable 3. Detailed Descriptive Table of Eligible Subjects, Measured at First Eligible Routine CBC Test (Cohort Entry Date) eTable 4. Descriptive Table of Matched Subjects (Primary Analysis), Variables Measured on Index CBC eTable 5. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 12/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
eTable 6. Odds Ratio of Any Solid Tumour Diagnosis (Excluding Liver) by Change in Platelet Count Category and Time From Cancer Diagnosis eTable 7. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Diagnosis. Select Cancer Sites eFigure 1. Study Design Criteria Among Matched Individuals eFigure 2. Age- and Sex-Specific Platelet Count Reference Distributions for Exposure Definition eFigure 3. Age- and Sex-Specific Platelet Count Reference Distributions for Secondary Exposure Definition eFigure 4. Odds Ratio of Cancer by Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 5. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 6. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites by Cancer Stage eFigure 7. Odds Ratio of Cancer by Platelet Count Category (Clinical Definition) and Time From Diagnosis JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 13/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
© 2022 Giannakeas V et al. JAMA Network Open. Supplementary Online Content Giannakeas V, Kotsopoulos J, Cheung MC, et al. Analysis of platelet count and new cancer diagnosis over a 10-year period. JAMA Netw Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 eTable 1. Inclusion Table for CBC Tests eTable 2. Exclusion Table for Study Cohort eTable 3. Detailed Descriptive Table of Eligible Subjects, Measured at First Eligible Routine CBC Test (Cohort Entry Date) eTable 4. Descriptive Table of Matched Subjects (Primary Analysis), Variables Measured on Index CBC eTable 5. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites eTable 6. Odds Ratio of Any Solid Tumour Diagnosis (Excluding Liver) by Change in Platelet Count Category and Time From Cancer Diagnosis eTable 7. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Diagnosis. Select Cancer Sites eFigure 1. Study Design Criteria Among Matched Individuals eFigure 2. Age- and Sex-Specific Platelet Count Reference Distributions for Exposure Definition eFigure 3. Age- and Sex-Specific Platelet Count Reference Distributions for Secondary Exposure Definition eFigure 4. Odds Ratio of Cancer by Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 5. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 6. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites by Cancer Stage eFigure 7. Odds Ratio of Cancer by Platelet Count Category (Clinical Definition) and Time From Diagnosis This supplementary material has been provided by the authors to give readers additional information about their work.
© 2022 Giannakeas V et al. JAMA Network Open. eTable 1. Inclusion table for CBC tests Frequency Percent Total CBC observations in accrual period 85,868,893 Exclusion 1. Priority of blood test not routine 14,033,973 16.34 2. Patient class not in community 15,163,171 17.66 3. Ordering practitioner not an MD 1,416,014 1.65 Eligible CBC observations for inclusion cohort 55,255,735 64.35
© 2022 Giannakeas V et al. JAMA Network Open. eTable 2. Exclusion table for study cohort Frequency Percent Total CBC observations meeting inclusion criteria 55,255,735 Exclusion 1. Missing date of birth 34 0 2. Missing sex - 0 3. Age <18 on CBC date 2,151,138 3.89 4. Age >100 on CBC date 24,801 0.04 5. Death date prior to CBC date 13,661 0.02 6. OHIP ineligible on CBC date 55,740 0.1 7. Multiple CBC tests on same day 246,020 0.44 8. History of cancer in the Ontario Cancer Registry 5,144,653 9.31 Eligible CBC observations in study 47,373,668 85.73 Number of unique individuals 8,917,187
© 2022 Giannakeas V et al. JAMA Network Open. eTable 3. Detailed descriptive table of eligible subjects, measured at first eligible routine CBC test (cohort entry date) Description Value Total Overall 8,917,187 General demographics Calendar year Mean (SD) 2011.1 (2.7) Median (IQR) 2011 (2009-2013) Sex Female 4,971,578 (55.8%) Male 3,945,609 (44.2%) Age Mean (SD) 47.0 (17.8) Median (IQR) 46.4 (32.5-59.5) Neighborhood income quintile 1 - Low 1,696,790 (19.0%) 2 1,761,615 (19.8%) 3 1,781,901 (20.0%) 4 1,853,508 (20.8%) 5 - High 1,784,803 (20.0%) Missing 38,570 (0.4%) Residence location Urban 8,084,848 (90.7%) Rural 820,419 (9.2%) Missing 11,920 (0.1%) Landed immigrant Non-immigrant 7,266,961 (81.5%) Recent immigrant (10 years or less) 742,701 (8.3%) Past immigrant (more than 10 years) 907,525 (10.2%) Time eligible in OHIP (years) Mean (SD) 11.6 (7.3) Median (IQR) 11.2 (5.3-17.4) Health service utilization Core primary care visits to GP/FP (2 years prior) Mean (SD) 2.8 (3.4) Median (IQR) 2 (1-3) 0 564,943 (6.3%) 1 - 2 4,903,886 (55.0%) 3 - 4 1,824,321 (20.5%) 5 - 9 1,285,001 (14.4%) 10+ 339,036 (3.8%) ED visits (2 years prior) 0 5,817,079 (65.2%) 1 1,672,061 (18.8%) 2 680,835 (7.6%) 3+ 747,212 (8.4%) Inpatient hospitalization episodes (2 years prior) 0 8,413,664 (94.4%) 1 396,207 (4.4%) 2 71,531 (0.8%) 3+ 35,785 (0.4%)
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Rostered to family physician Yes 6,940,867 (77.8%) Up to date on cancer screening Pap smear (females age 18 to 70) Yes 2,583,203 (59.0%) Mammogram (females age 50 to 70) Yes 823,747 (58.2%) FOBT/sigmoidoscopy/colonoscopy (age 50 to 70) Yes 1,333,036 (47.8%) Comorbidities and chronic conditions Resource utilization band 0 - No or invalid diagnosis 279,791 (3.1%) 1 - Healthy user 464,794 (5.2%) 2 - Low user 1,653,945 (18.5%) 3 - Moderate user 4,736,581 (53.1%) 4 - High user 1,367,006 (15.3%) 5 - Very high user 415,070 (4.7%) Chronic conditions Asthma Yes 796,810 (8.9%) Congestive heart failure Yes 172,576 (1.9%) Inflammatory bowel disease Yes 29,509 (0.3%) Chronic obstructive pulmonary disease Yes 192,482 (2.2%) HIV Yes 11,242 (0.1%) Hypertension Yes 2,139,804 (24.0%) Dementia Yes 113,493 (1.3%) Diabetes Yes 666,477 (7.5%) Chronic rheumatoid arthritis Yes 74,781 (0.8%) Osteoarthritis Yes 869,722 (9.8%) Mood disorder Yes 1,093,308 (12.3%) Other mental health disorder Yes 356,591 (4.0%) Osteoporosis Yes 65,463 (0.7%) Renal disease Yes 88,520 (1.0%) Stroke Yes 62,149 (0.7%) Chronic coronary syndrome Yes 321,278 (3.6%) Acute myocardial infarction Yes 83,489 (0.9%) Medication use (age 66+) Concurrent medication use Number of concurrent medications Mean (SD) 3.7 (3.1) Median (IQR) 3 (1-6) Recent medication use Antiplatelet Nonsteroidal anti-inflammatory (ASA- based) Yes 67,300 (4.8%) Nonsteroidal anti-inflammatory (non-ASA- based) Yes 290,436 (20.8%) Adenosine disphosphonate inhibitor Yes 75,213 (5.4%) Cardiovascular Coronary vasodilator (nitrate) Yes 113,508 (8.1%) Beta blocker Yes 360,850 (25.9%)
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Calcium channel blocker Yes 381,621 (27.4%) ACE inhibitor Yes 423,063 (30.4%) Angiotensin receptor agonist Yes 286,627 (20.6%) Lipid-lowering Statin Yes 623,653 (44.7%) Psychotropics Tricyclic antidepressant Yes 68,640 (4.9%) Selective serotonin reuptake inhibitor Yes 150,581 (10.8%) Complete blood count Hemoglobin concentration [g/L] Mean (SD) 139.5 (14.9) Median (IQR) 140 (130-150) Hematocrit ratio [L/L] Mean (SD) 0.4 (0.0) Median (IQR) 0.4 (0.4-0.4) Platelet count [109 cells/L] Mean (SD) 247.2 (64.5) Median (IQR) 241 (205-282) Observation period* Observation time (years) Mean (SD) 6.8 (3.0) Median (IQR) 7.3 (4.4-9.3) Number of routine CBC tests Mean (SD) 4.3 (6.3) Median (IQR) 3 (1-6) Incident cancer events (Ontario Cancer Registry) Any cancer diagnosis Yes 492,691 (5.5%) Solid tumour Yes 429,222 (4.8%) Colon Yes 51,521 (0.6%) Lung Yes 56,724 (0.6%) Breast (female only) Yes 65,721 (1.3%) Ovary (female only) Yes 7,661 (0.2%) Cervical (female only) Yes 3,494 (0.1%) Endometrial (female only) Yes 17,101 (0.3%) Prostate (male only) Yes 62,946 (1.6%) Thyroid Yes 21,478 (0.2%) Pancreas Yes 12,021 (0.1%) Stomach Yes 9,195 (0.1%) Kidney Yes 14,063 (0.2%) Bladder Yes 23,344 (0.3%) Liver Yes 7,696 (0.1%) Esophagus Yes 4,712 (0.1%) Other GI Yes 5,255 (0.1%) Brain Yes 5,724 (0.1%) Melanoma Yes 20,192 (0.2%) Head and neck Yes 13,363 (0.1%) Other solid tumour Yes 27,011 (0.3%) Hematologic tumour Yes 63,469 (0.7%)
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Leukemia Yes 5,154 (0.1%) Lymphoma Yes 33,827 (0.4%) Multiple myeloma Yes 8,274 (0.1%) Other hematologic tumour Yes 16,214 (0.2%) *Period of observation is from first eligible CBC to the earliest date for: death, end of OHIP eligibility, or end of observation period (December 31 2018)
© 2022 Giannakeas V et al. JAMA Network Open. eTable 4. Descriptive table of matched subjects (primary analysis), variables measured on index CBC. Description Value Total Case Control Standardiz ed Difference Overall 5,677,304 1,419,326 (25.0%) 4,257,978 (75.0%) General demographics Calendar year (cont.) Mean (SD) 2012.2 (2.6) 2012.2 (2.6) 2012.2 (2.6) Median (IQR) 2012 (2010-2014) 2012 (2010-2014) 2012 (2010-2014) Calendar year (cat.) 2007-2009 1,091,243 (19.2%) 272,743 (19.2%) 818,500 (19.2%) 0 2010-2012 2,020,199 (35.6%) 505,028 (35.6%) 1,515,171 (35.6%) 0 2013-2015 1,777,747 (31.3%) 444,546 (31.3%) 1,333,201 (31.3%) 0 2016-2017 788,115 (13.9%) 197,009 (13.9%) 591,106 (13.9%) 0 Sex Female 2,885,112 (50.8%) 721,278 (50.8%) 2,163,834 (50.8%) 0 Male 2,792,192 (49.2%) 698,048 (49.2%) 2,094,144 (49.2%) 0 Age (cont.) Mean (SD) 65.9 (13.6) 66.0 (13.6) 65.9 (13.6) 0 Median (IQR) 67.0 (57.4-75.9) 67.0 (57.4-76.0) 67.1 (57.4-75.9) Age (cat.) 18-29 66,388 (1.2%) 16,491 (1.2%) 49,897 (1.2%) 0 30-39 172,563 (3.0%) 43,121 (3.0%) 129,442 (3.0%) 0 40-49 468,186 (8.2%) 116,702 (8.2%) 351,484 (8.3%) 0 50-59 1,045,696 (18.4%) 260,604 (18.4%) 785,092 (18.4%) 0 60-69 1,604,177 (28.3%) 400,653 (28.2%) 1,203,524 (28.3%) 0 70-79 1,437,081 (25.3%) 359,683 (25.3%) 1,077,398 (25.3%) 0 80-89 786,528 (13.9%) 197,074 (13.9%) 589,454 (13.8%) 0 90+ 96,685 (1.7%) 24,998 (1.8%) 71,687 (1.7%) 0.01 Neighbourhood income quintile 1 - Low 1,012,719 (17.8%) 259,849 (18.3%) 752,870 (17.7%) 0.02 2 1,133,326 (20.0%) 285,773 (20.1%) 847,553 (19.9%) 0.01 3 1,133,021 (20.0%) 282,123 (19.9%) 850,898 (20.0%) 0 4 1,180,388 (20.8%) 291,594 (20.5%) 888,794 (20.9%) 0.01 5 - High 1,201,075 (21.2%) 295,892 (20.8%) 905,183 (21.3%) 0.01 Missing 16,775 (0.3%) 4,095 (0.3%) 12,680 (0.3%) Low-income senior (age 66+) Yes 468,941 (15.6%) 111,694 (14.9%) 357,247 (15.9%) 0.03 Residence location Urban 5,051,855 (89.0%) 1,256,231 (88.5%) 3,795,624 (89.1%) 0.02 Rural 620,875 (10.9%) 161,995 (11.4%) 458,880 (10.8%) 0.02 Missing 4,574 (0.1%) 1,100 (0.1%) 3,474 (0.1%) Recently living in Long-Term Care Yes 115,231 (2.0%) 20,896 (1.5%) 94,335 (2.2%) 0.06 Landed immigrant (cat.) Non-immigrant 5,024,782 (88.5%) 1,273,254 (89.7%) 3,751,528 (88.1%) 0.05 Recent immigrant (10 years or less) 164,498 (2.9%) 37,357 (2.6%) 127,141 (3.0%) 0.02 Past immigrant (more than 10 years) 488,024 (8.6%) 108,715 (7.7%) 379,309 (8.9%) 0.05 Ethnicity General Population 5,302,511 (93.4%) 1,344,594 (94.7%) 3,957,917 (93.0%) 0.07 Chinese 224,715 (4.0%) 49,099 (3.5%) 175,616 (4.1%) 0.03
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference South Asian 150,078 (2.6%) 25,633 (1.8%) 124,445 (2.9%) 0.07 Time eligible in OHIP (years) Mean (SD) 20.6 (5.3) 20.5 (5.3) 20.6 (5.3) 0 Median (IQR) 21.5 (19.1-24.0) 21.5 (19.1-24.0) 21.5 (19.1-24.0) Health Services Utilization Any OHIP billings in the year prior Yes 5,598,849 (98.6%) 1,399,563 (98.6%) 4,199,286 (98.6%) 0 Any ODB records on/in the year prior (age 66+) Yes 2,917,066 (97.3%) 728,501 (97.2%) 2,188,565 (97.3%) 0.01 Physician Billings (2 years prior) Any core primary care visits to GP/FP Yes 5,510,087 (97.1%) 1,378,052 (97.1%) 4,132,035 (97.0%) 0 Core primary care visits to GP/FP (cont.) Mean (SD) 3.0 (3.7) 2.9 (3.6) 3.0 (3.8) 0.02 Median (IQR) 2 (1-4) 1 (1-3) 2 (1-4) Core primary care visits to GP/FP (cat.) 0 167,217 (2.9%) 41,274 (2.9%) 125,943 (3.0%) 0 1 - 2 3,198,252 (56.3%) 811,039 (57.1%) 2,387,213 (56.1%) 0.02 3 - 4 1,201,970 (21.2%) 299,530 (21.1%) 902,440 (21.2%) 0 5 - 9 846,965 (14.9%) 205,911 (14.5%) 641,054 (15.1%) 0.02 10+ 262,900 (4.6%) 61,572 (4.3%) 201,328 (4.7%) 0.02 Specialist visits (2 years prior) Dermatologist Yes 877,189 (15.5%) 224,227 (15.8%) 652,962 (15.3%) 0.01 General surgeon Yes 1,143,210 (20.1%) 298,490 (21.0%) 844,720 (19.8%) 0.03 Orthopedic surgeon Yes 797,962 (14.1%) 194,499 (13.7%) 603,463 (14.2%) 0.01 Geriatrician Yes 106,833 (1.9%) 23,349 (1.6%) 83,484 (2.0%) 0.02 Internal medicine specialist Yes 3,366,565 (59.3%) 836,840 (59.0%) 2,529,725 (59.4%) 0.01 Endocrinologist Yes 190,580 (3.4%) 49,507 (3.5%) 141,073 (3.3%) 0.01 Nephrologist Yes 155,201 (2.7%) 39,497 (2.8%) 115,704 (2.7%) 0 Neurologist Yes 504,083 (8.9%) 119,942 (8.5%) 384,141 (9.0%) 0.02 Psychiatrist Yes 317,703 (5.6%) 73,949 (5.2%) 243,754 (5.7%) 0.02 OBGYN Yes 498,801 (8.8%) 125,025 (8.8%) 373,776 (8.8%) 0 Geneticist Yes 5,598 (0.1%) 1,409 (0.1%) 4,189 (0.1%) 0 ENT Yes 688,708 (12.1%) 174,743 (12.3%) 513,965 (12.1%) 0.01 Urologist Yes 675,709 (11.9%) 186,833 (13.2%) 488,876 (11.5%) 0.05 Gastroenterologist Yes 546,089 (9.6%) 137,358 (9.7%) 408,731 (9.6%) 0 Oncologist Yes 14,865 (0.3%) 5,388 (0.4%) 9,477 (0.2%) 0.03 Respirologist Yes 378,174 (6.7%) 102,015 (7.2%) 276,159 (6.5%) 0.03 Rheumatologist Yes 278,374 (4.9%) 64,510 (4.5%) 213,864 (5.0%) 0.02 Cardiologist Yes 1,790,248 (31.5%) 438,440 (30.9%) 1,351,808 (31.7%) 0.02 Hematologist Yes 160,143 (2.8%) 52,001 (3.7%) 108,142 (2.5%) 0.06 Emergency and inpatient admissions (2 years prior) Any unscheduled ED visits Yes 2,374,409 (41.8%) 601,600 (42.4%) 1,772,809 (41.6%) 0.02 Unscheduled ED visits (cont.) Mean (SD) 1.0 (2.0) 1.0 (2.0) 1.0 (2.1) 0.01
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Median (IQR) 0 (0-1) 0 (0-1) 0 (0-1) Unscheduled ED visits (cat.) 0 3,302,895 (58.2%) 817,726 (57.6%) 2,485,169 (58.4%) 0.02 1 1,175,254 (20.7%) 296,130 (20.9%) 879,124 (20.6%) 0.01 2 534,449 (9.4%) 135,339 (9.5%) 399,110 (9.4%) 0.01 3+ 664,706 (11.7%) 170,131 (12.0%) 494,575 (11.6%) 0.01 Any inpatient hospitalization episodes Yes 663,502 (11.7%) 169,981 (12.0%) 493,521 (11.6%) 0.01 Inpatient hospitalization episodes (cont.) Mean (SD) 0.2 (0.6) 0.2 (0.6) 0.2 (0.6) 0.01 Median (IQR) 0 (0-0) 0 (0-0) 0 (0-0) Inpatient hospitalization episodes (cat.) 0 5,013,802 (88.3%) 1,249,345 (88.0%) 3,764,457 (88.4%) 0.01 1 485,938 (8.6%) 123,488 (8.7%) 362,450 (8.5%) 0.01 2 115,033 (2.0%) 30,075 (2.1%) 84,958 (2.0%) 0.01 3+ 62,531 (1.1%) 16,418 (1.2%) 46,113 (1.1%) 0.01 Primary care provider Rostered to family physician Yes 4,868,959 (85.8%) 1,214,998 (85.6%) 3,653,961 (85.8%) 0.01 CBC test ordered by rostered family physician Yes 3,925,398 (69.1%) 974,826 (68.7%) 2,950,572 (69.3%) 0.01 Up to date on cancer screening Pap smear (females age 18 to 70) Yes 1,134,728 (64.2%) 276,006 (62.5%) 858,722 (64.7%) 0.05 Mammogram (females age 50 to 70) Yes 868,591 (68.3%) 209,221 (65.9%) 659,370 (69.1%) 0.07 FOBT/sigmoidoscopy/colonoscopy (age 50 to 70) Yes 1,721,945 (65.0%) 415,145 (62.8%) 1,306,800 (65.7%) 0.06 Comorbidities and chronic conditions Comorbidities Aggregate diagnosis groups (cont.) Mean (SD) 7.1 (3.7) 7.1 (3.7) 7.1 (3.7) 0 Median (IQR) 7 (4-10) 7 (4-10) 7 (4-10) Resource utilization band 0 - No or invalid diagnosis 33,804 (0.6%) 8,451 (0.6%) 25,353 (0.6%) 0 1 - Healthy user 70,952 (1.2%) 17,738 (1.2%) 53,214 (1.2%) 0 2 - Low user 415,228 (7.3%) 103,807 (7.3%) 311,421 (7.3%) 0 3 - Moderate user 3,050,604 (53.7%) 762,651 (53.7%) 2,287,953 (53.7%) 0 4 - High user 1,296,080 (22.8%) 324,020 (22.8%) 972,060 (22.8%) 0 5 - Very high user 810,636 (14.3%) 202,659 (14.3%) 607,977 (14.3%) 0 Charlson score (cont.) Mean (SD) 0.3 (0.9) 0.3 (0.9) 0.3 (0.8) 0.02 Median (IQR) 0 (0-0) 0 (0-0) 0 (0-0) Charlson comorbidities (cat.) 0 4,882,890 (86.0%) 1,214,684 (85.6%) 3,668,206 (86.1%) 0.02 1 385,248 (6.8%) 97,912 (6.9%) 287,336 (6.7%) 0.01 2 187,718 (3.3%) 48,646 (3.4%) 139,072 (3.3%) 0.01 3+ 221,448 (3.9%) 58,084 (4.1%) 163,364 (3.8%) 0.01 Chronic conditions Asthma Yes 537,653 (9.5%) 135,029 (9.5%) 402,624 (9.5%) 0
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Congestive heart failure Yes 393,049 (6.9%) 101,252 (7.1%) 291,797 (6.9%) 0.01 Inflammatory bowel disease Yes 30,431 (0.5%) 7,410 (0.5%) 23,021 (0.5%) 0 Chronic obstructive pulmonary disease Yes 386,047 (6.8%) 119,986 (8.5%) 266,061 (6.2%) 0.08 HIV Yes 6,691 (0.1%) 1,885 (0.1%) 4,806 (0.1%) 0.01 Hypertension Yes 3,306,541 (58.2%) 830,089 (58.5%) 2,476,452 (58.2%) 0.01 Dementia Yes 223,044 (3.9%) 43,311 (3.1%) 179,733 (4.2%) 0.06 Diabetes Yes 1,238,703 (21.8%) 303,166 (21.4%) 935,537 (22.0%) 0.01 Chronic rheumatoid arthritis Yes 176,681 (3.1%) 41,026 (2.9%) 135,655 (3.2%) 0.02 Osteoarthritis Yes 1,210,650 (21.3%) 292,529 (20.6%) 918,121 (21.6%) 0.02 Mood disorder Yes 798,619 (14.1%) 191,338 (13.5%) 607,281 (14.3%) 0.02 Other mental health disorder Yes 305,798 (5.4%) 77,442 (5.5%) 228,356 (5.4%) 0 Osteoporosis Yes 103,466 (1.8%) 23,060 (1.6%) 80,406 (1.9%) 0.02 Renal disease Yes 250,967 (4.4%) 63,041 (4.4%) 187,926 (4.4%) 0 Stroke Yes 109,143 (1.9%) 25,536 (1.8%) 83,607 (2.0%) 0.01 Chronic coronary syndrome Yes 660,914 (11.6%) 159,315 (11.2%) 501,599 (11.8%) 0.02 Acute myocardial infarction Yes 139,154 (2.5%) 33,439 (2.4%) 105,715 (2.5%) 0.01 Medication use (age 66+) Concurrent medication use Number of concurrent medications being used (cont.) Mean (SD) 4.4 (3.2) 4.4 (3.2) 4.4 (3.2) 0.01 Median (IQR) 4 (2-6) 4 (2-6) 4 (2-6) Number of concurrent medications being used (cat.) 0 287,337 (9.6%) 72,453 (9.7%) 214,884 (9.6%) 0 1 - 4 1,418,824 (47.3%) 355,321 (47.4%) 1,063,503 (47.3%) 0 5 - 9 1,080,885 (36.0%) 269,166 (35.9%) 811,719 (36.1%) 0 10+ 212,374 (7.1%) 52,915 (7.1%) 159,459 (7.1%) 0 Recent medication use Antiplatelet Nonsteroidal anti-inflammatory (ASA- based) Yes 113,066 (3.8%) 26,908 (3.6%) 86,158 (3.8%) 0.01 Nonsteroidal anti-inflammatory (non- ASA-based) Yes 619,744 (20.7%) 151,206 (20.2%) 468,538 (20.8%) 0.02 Adenosine disphosphonate inhibitor Yes 218,919 (7.3%) 54,120 (7.2%) 164,799 (7.3%) 0 Cardiovascular Coronary vasodilator (nitrate) Yes 264,859 (8.8%) 64,685 (8.6%) 200,174 (8.9%) 0.01 Beta blocker Yes 903,836 (30.1%) 223,369 (29.8%) 680,467 (30.2%) 0.01 Calcium channel blocker Yes 937,762 (31.3%) 236,718 (31.6%) 701,044 (31.2%) 0.01 ACE inhibitor Yes 987,543 (32.9%) 246,558 (32.9%) 740,985 (32.9%) 0 Angiotensin receptor agonist Yes 754,041 (25.1%) 184,836 (24.6%) 569,205 (25.3%) 0.02 Lipid-lowering
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Statin Yes 1,705,822 (56.9%) 414,870 (55.3%) 1,290,952 (57.4%) 0.04 Psychotropics Tricyclic antidepressant Yes 151,967 (5.1%) 37,807 (5.0%) 114,160 (5.1%) 0 Selective serotonin reuptake inhibitor Yes 351,210 (11.7%) 83,934 (11.2%) 267,276 (11.9%) 0.02 Platelet count (exposure definition) Continuous value for platelet count Mean (SD) 239.1 (73.2) 245.7 (89.1) 237.0 (66.9) 0.11 Median (IQR) 231 (193-274) 234 (194-282) 230 (193-272) Categorical platelet count (definition 1) 1 - Very low (≤10th percentile) 636,092 (11.2%) 170,382 (12.0%) 465,710 (10.9%) 0.03 2 - Low (>10 to 25th percentile) 878,655 (15.5%) 203,017 (14.3%) 675,638 (15.9%) 0.04 3 - Medium (>25 to <75th percentile) 2,756,889 (48.6%) 649,305 (45.7%) 2,107,584 (49.5%) 0.08 4 - High (75 to <90th percentile) 823,871 (14.5%) 209,023 (14.7%) 614,848 (14.4%) 0.01 5 - Very high (≥90th percentile) 581,797 (10.2%) 187,599 (13.2%) 394,198 (9.3%) 0.13 Categorical platelet count (definition 2) 1 - Thrombocytopenia (<150) 354,236 (6.2%) 103,239 (7.3%) 250,997 (5.9%) 0.06 2 - Low normal (150 to 33.3rd percentile) 1,346,199 (23.7%) 312,501 (22.0%) 1,033,698 (24.3%) 0.05 3 - Medium normal (>33.4 to <66.6th percentile) 2,602,504 (45.8%) 614,613 (43.3%) 1,987,891 (46.7%) 0.07 4 - High normal (66.6th percentile to 450) 1,308,241 (23.0%) 356,063 (25.1%) 952,178 (22.4%) 0.06 5 - Thrombocytosis (>450) 66,124 (1.2%) 32,910 (2.3%) 33,214 (0.8%) 0.12 Observation period Years from index CBC to outcome (cont.) Mean (SD) 2.4 (2.1) 2.4 (2.1) Median (IQR) 1.8 (0.7-3.5) 1.8 (0.7-3.5) Years from index CBC to outcome (cat.) 0-6 months 273,042 (19.2%) 273,042 (19.2%) 6-12 months 177,460 (12.5%) 177,460 (12.5%) 12-18 months 170,915 (12.0%) 170,915 (12.0%) 18-24 months 152,076 (10.7%) 152,076 (10.7%) 2-3 years 220,742 (15.6%) 220,742 (15.6%) 3-5 years 242,367 (17.1%) 242,367 (17.1%) 5-10 years 182,724 (12.9%) 182,724 (12.9%) Incident cancer events (Ontario Cancer Registry) Any cancer diagnosis in the OCR Yes 1,419,326 (25.0%) 1,419,326 (100.0%) Solid tumour Yes 1,219,140 (21.5%) 1,219,140 (85.9%) Colon Yes 143,349 (2.5%) 143,349 (10.1%) Lung Yes 167,823 (3.0%) 167,823 (11.8%) Breast (female only) Yes 181,706 (6.3%) 181,706 (25.2%) Ovary (female only) Yes 21,203 (0.7%) 21,203 (2.9%) Cervical (female only) Yes 7,923 (0.3%) 7,923 (1.1%) Endometrial (female only) Yes 48,759 (1.7%) 48,759 (6.8%)
© 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Prostate (male only) Yes 174,026 (6.2%) 174,026 (24.9%) Thyroid Yes 58,931 (1.0%) 58,931 (4.2%) Pancreas Yes 36,861 (0.6%) 36,861 (2.6%) Stomach Yes 27,590 (0.5%) 27,590 (1.9%) Kidney Yes 41,248 (0.7%) 41,248 (2.9%) Bladder Yes 70,164 (1.2%) 70,164 (4.9%) Liver Yes 24,809 (0.4%) 24,809 (1.7%) Esophagus Yes 13,351 (0.2%) 13,351 (0.9%) Other GI Yes 15,674 (0.3%) 15,674 (1.1%) Brain Yes 15,363 (0.3%) 15,363 (1.1%) Melanoma Yes 56,460 (1.0%) 56,460 (4.0%) Head and neck Yes 36,705 (0.6%) 36,705 (2.6%) Other solid tumour Yes 77,195 (1.4%) 77,195 (5.4%) Hematologic tumour Yes 200,186 (3.5%) 200,186 (14.1%) Leukemia Yes 15,699 (0.3%) 15,699 (1.1%) Lymphoma Yes 101,343 (1.8%) 101,343 (7.1%) Multiple myeloma Yes 26,882 (0.5%) 26,882 (1.9%) Other hematologic tumour Yes 56,262 (1.0%) 56,262 (4.0%)
© 2022 Giannakeas V et al. JAMA Network Open. eTable 5. Odds ratio of cancer by platelet count category and time from diagnosis. Select cancer sites. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Very low (≤10th percentile) 1,820 (5.83%) 10,092 (10.77%) 0.73 (0.69- 0.77) <.0001 2,148 (6.61%) 11,045 (11.34%) 0.79 (0.75- 0.83) <.0001 2 - Low (>10 to 25th percentile) 2,688 (8.60%) 14,722 (15.71%) 0.74 (0.70- 0.77) <.0001 2,748 (8.46%) 15,224 (15.63%) 0.74 (0.70- 0.77) <.0001 3 - Medium (>25 to <75th percentile) 11,393 (36.47%) 46,289 (49.39%) 1.00 [Reference] 11,595 (35.70%) 47,505 (48.76%) 1.00 [Reference] 4 - High (75 to <90th percentile) 5,719 (18.31%) 13,688 (14.60%) 1.71 (1.65- 1.78) <.0001 6,005 (18.49%) 14,299 (14.68%) 1.73 (1.67- 1.80) <.0001 5 - Very high (≥90th percentile) 9,621 (30.80%) 8,932 (9.53%) 4.38 (4.22- 4.54) <.0001 9,979 (30.73%) 9,352 (9.60%) 4.37 (4.22- 4.53) <.0001 6-12 months 1 - Very low (≤10th percentile) 1,473 (8.32%) 5,754 (10.84%) 0.86 (0.81- 0.91) <.0001 1,869 (8.76%) 7,291 (11.39%) 0.86 (0.81- 0.90) <.0001 2 - Low (>10 to 25th percentile) 2,134 (12.06%) 8,385 (15.80%) 0.86 (0.81- 0.90) <.0001 2,489 (11.67%) 10,007 (15.63%) 0.83 (0.79- 0.87) <.0001 3 - Medium (>25 to <75th percentile) 7,787 (44.01%) 26,259 (49.47%) 1.00 [Reference] 9,447 (44.28%) 31,548 (49.29%) 1.00 [Reference] 4 - High (75 to <90th percentile) 3,219 (18.19%) 7,755 (14.61%) 1.40 (1.33- 1.47) <.0001 3,630 (17.01%) 9,171 (14.33%) 1.32 (1.26- 1.38) <.0001 5 - Very high (≥90th percentile) 3,082 (17.42%) 4,932 (9.29%) 2.11 (2.01- 2.23) <.0001 3,902 (18.29%) 5,994 (9.36%) 2.18 (2.08- 2.29) <.0001 12-18 months 1 - Very low (≤10th percentile) 1,643 (9.64%) 5,487 (10.74%) 0.95 (0.90- 1.01) 0.1268 1,922 (9.46%) 6,691 (10.98%) 0.93 (0.88- 0.98) 0.0087 2 - Low (>10 to 25th percentile) 2,357 (13.83%) 8,179 (16.00%) 0.92 (0.87- 0.96) 0.001 2,562 (12.61%) 9,760 (16.01%) 0.85 (0.81- 0.89) <.0001 3 - Medium (>25 to <75th percentile) 7,977 (46.82%) 25,404 (49.70%) 1.00 [Reference] 9,241 (45.49%) 29,890 (49.04%) 1.00 [Reference] 4 - High (75 to <90th percentile) 2,804 (16.46%) 7,439 (14.55%) 1.20 (1.14- 1.26) <.0001 3,327 (16.38%) 8,785 (14.41%) 1.22 (1.17- 1.28) <.0001 5 - Very high (≥90th percentile) 2,256 (13.24%) 4,602 (9.00%) 1.56 (1.48- 1.66) <.0001 3,264 (16.07%) 5,822 (9.55%) 1.82 (1.73- 1.91) <.0001 18-24 months 1 - Very low (≤10th percentile) 1,546 (10.38%) 4,882 (10.93%) 0.99 (0.93- 1.06) 0.7936 1,828 (9.87%) 6,246 (11.25%) 0.94 (0.89- 1.00) 0.0351 2 - Low (>10 to 25th percentile) 2,169 (14.57%) 7,192 (16.10%) 0.94 (0.89- 1.00) 0.0401 2,387 (12.89%) 8,929 (16.08%) 0.86 (0.81- 0.90) <.0001 3 - Medium (>25 to <75th percentile) 7,067 (47.46%) 22,125 (49.53%) 1.00 [Reference] 8,444 (45.61%) 27,132 (48.85%) 1.00 [Reference] 4 - High (75 to <90th percentile) 2,342 (15.73%) 6,463 (14.47%) 1.14 (1.08- 1.20) <.0001 3,080 (16.64%) 8,085 (14.56%) 1.23 (1.17- 1.29) <.0001
© 2022 Giannakeas V et al. JAMA Network Open. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 5 - Very high (≥90th percentile) 1,765 (11.85%) 4,005 (8.97%) 1.38 (1.29- 1.47) <.0001 2,774 (14.98%) 5,147 (9.27%) 1.74 (1.65- 1.83) <.0001 2-3 years 1 - Very low (≤10th percentile) 2,276 (10.50%) 6,963 (10.71%) 1.01 (0.96- 1.07) 0.6282 2,516 (9.62%) 8,589 (10.95%) 0.94 (0.90- 0.99) 0.0229 2 - Low (>10 to 25th percentile) 3,357 (15.49%) 10,309 (15.86%) 1.01 (0.96- 1.05) 0.7113 3,504 (13.40%) 12,509 (15.94%) 0.90 (0.86- 0.94) <.0001 3 - Medium (>25 to <75th percentile) 10,482 (48.37%) 32,488 (49.97%) 1.00 [Reference] 12,147 (46.44%) 39,114 (49.84%) 1.00 [Reference] 4 - High (75 to <90th percentile) 3,345 (15.44%) 9,447 (14.53%) 1.10 (1.05- 1.15) <.0001 4,264 (16.30%) 11,172 (14.24%) 1.23 (1.18- 1.28) <.0001 5 - Very high (≥90th percentile) 2,210 (10.20%) 5,803 (8.93%) 1.18 (1.12- 1.25) <.0001 3,727 (14.25%) 7,090 (9.03%) 1.70 (1.62- 1.78) <.0001 3-5 years 1 - Very low (≤10th percentile) 2,622 (11.13%) 7,716 (10.92%) 1.04 (0.99- 1.09) 0.1338 2,648 (9.39%) 9,235 (10.92%) 0.91 (0.87- 0.96) 0.0002 2 - Low (>10 to 25th percentile) 3,672 (15.59%) 11,431 (16.18%) 0.98 (0.94- 1.02) 0.3889 3,832 (13.59%) 13,687 (16.18%) 0.89 (0.86- 0.93) <.0001 3 - Medium (>25 to <75th percentile) 11,521 (48.91%) 35,208 (49.82%) 1.00 [Reference] 13,184 (46.75%) 42,028 (49.67%) 1.00 [Reference] 4 - High (75 to <90th percentile) 3,467 (14.72%) 10,153 (14.37%) 1.04 (1.00- 1.09) 0.0569 4,657 (16.51%) 12,077 (14.27%) 1.23 (1.19- 1.28) <.0001 5 - Very high (≥90th percentile) 2,273 (9.65%) 6,157 (8.71%) 1.13 (1.07- 1.19) <.0001 3,881 (13.76%) 7,579 (8.96%) 1.64 (1.57- 1.71) <.0001 5-10 years 1 - Very low (≤10th percentile) 1,833 (10.62%) 5,456 (10.54%) 1.03 (0.97- 1.09) 0.3722 1,925 (9.25%) 6,646 (10.64%) 0.92 (0.87- 0.97) 0.0037 2 - Low (>10 to 25th percentile) 2,725 (15.79%) 8,183 (15.80%) 1.02 (0.97- 1.07) 0.4886 2,752 (13.22%) 10,169 (16.28%) 0.86 (0.82- 0.90) <.0001 3 - Medium (>25 to <75th percentile) 8,494 (49.21%) 25,963 (50.14%) 1.00 [Reference] 9,767 (46.91%) 31,089 (49.77%) 1.00 [Reference] 4 - High (75 to <90th percentile) 2,551 (14.78%) 7,502 (14.49%) 1.04 (0.99- 1.09) 0.1368 3,549 (17.04%) 8,913 (14.27%) 1.27 (1.21- 1.33) <.0001 5 - Very high (≥90th percentile) 1,659 (9.61%) 4,682 (9.04%) 1.08 (1.02- 1.15) 0.0101 2,829 (13.59%) 5,649 (9.04%) 1.60 (1.52- 1.69) <.0001
© 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Very low (≤10th percentile) 243 (5.48%) 1,392 (10.46%) 0.72 (0.62- 0.84) <.0001 414 (7.37%) 1,898 (11.26%) 0.91 (0.81- 1.02) 0.1017 2 - Low (>10 to 25th percentile) 350 (7.89%) 2,077 (15.61%) 0.69 (0.61- 0.78) <.0001 503 (8.95%) 2,598 (15.41%) 0.79 (0.71- 0.88) <.0001 3 - Medium (>25 to <75th percentile) 1,615 (36.42%) 6,666 (50.11%) 1.00 [Reference] 2,039 (36.29%) 8,332 (49.44%) 1.00 [Reference] 4 - High (75 to <90th percentile) 830 (18.72%) 1,896 (14.25%) 1.82 (1.65- 2.01) <.0001 1,058 (18.83%) 2,452 (14.55%) 1.79 (1.64- 1.95) <.0001 5 - Very high (≥90th percentile) 1,396 (31.48%) 1,271 (9.55%) 4.62 (4.19- 5.09) <.0001 1,604 (28.55%) 1,574 (9.34%) 4.27 (3.91- 4.66) <.0001 6-12 months 1 - Very low (≤10th percentile) 233 (9.17%) 804 (10.54%) 0.88 (0.75- 1.04) 0.1262 336 (9.47%) 1,155 (10.85%) 0.95 (0.83- 1.09) 0.498 2 - Low (>10 to 25th percentile) 344 (13.53%) 1,188 (15.58%) 0.88 (0.77- 1.01) 0.0695 513 (14.45%) 1,723 (16.18%) 0.97 (0.87- 1.09) 0.6389 3 - Medium (>25 to <75th percentile) 1,242 (48.86%) 3,787 (49.66%) 1.00 [Reference] 1,619 (45.62%) 5,299 (49.77%) 1.00 [Reference] 4 - High (75 to <90th percentile) 435 (17.11%) 1,091 (14.31%) 1.21 (1.07- 1.38) 0.0031 612 (17.24%) 1,529 (14.36%) 1.31 (1.18- 1.46) <.0001 5 - Very high (≥90th percentile) 288 (11.33%) 756 (9.91%) 1.16 (1.00- 1.35) 0.0497 469 (13.21%) 941 (8.84%) 1.64 (1.44- 1.85) <.0001 12-18 months 1 - Very low (≤10th percentile) 218 (8.93%) 758 (10.35%) 0.84 (0.72- 0.99) 0.0416 384 (11.73%) 1,072 (10.92%) 1.14 (1.00- 1.29) 0.0546 2 - Low (>10 to 25th percentile) 338 (13.84%) 1,145 (15.63%) 0.86 (0.75- 0.99) 0.0352 481 (14.70%) 1,636 (16.66%) 0.93 (0.83- 1.05) 0.2399 3 - Medium (>25 to <75th percentile) 1,228 (50.29%) 3,597 (49.10%) 1.00 [Reference] 1,531 (46.78%) 4,856 (49.46%) 1.00 [Reference] 4 - High (75 to <90th percentile) 380 (15.56%) 1,122 (15.32%) 0.99 (0.87- 1.14) 0.9202 498 (15.22%) 1,353 (13.78%) 1.17 (1.04- 1.31) 0.0099 5 - Very high (≥90th percentile) 278 (11.38%) 704 (9.61%) 1.16 (0.99- 1.35) 0.0623 379 (11.58%) 902 (9.19%) 1.34 (1.17- 1.53) <.0001 18-24 months 1 - Very low (≤10th percentile) 222 (10.11%) 654 (9.93%) 1.02 (0.87- 1.21) 0.7721 313 (10.34%) 1,001 (11.02%) 0.95 (0.83- 1.09) 0.47 2 - Low (>10 to 25th percentile) 355 (16.17%) 998 (15.16%) 1.07 (0.93- 1.23) 0.3159 431 (14.24%) 1,450 (15.97%) 0.90 (0.80- 1.02) 0.1096 3 - Medium (>25 to <75th percentile) 1,105 (50.34%) 3,333 (50.62%) 1.00 [Reference] 1,480 (48.89%) 4,507 (49.63%) 1.00 [Reference] 4 - High (75 to <90th percentile) 298 (13.58%) 941 (14.29%) 0.95 (0.82- 1.11) 0.5358 474 (15.66%) 1,270 (13.99%) 1.14 (1.01- 1.28) 0.039
© 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 5 - Very high (≥90th percentile) 215 (9.79%) 659 (10.01%) 0.98 (0.83- 1.16) 0.8472 329 (10.87%) 853 (9.39%) 1.18 (1.02- 1.35) 0.0248 2-3 years 1 - Very low (≤10th percentile) 327 (10.06%) 1,017 (10.42%) 0.96 (0.84- 1.10) 0.5943 482 (11.47%) 1,345 (10.67%) 1.14 (1.01- 1.28) 0.0292 2 - Low (>10 to 25th percentile) 511 (15.71%) 1,518 (15.56%) 1.01 (0.90- 1.13) 0.8836 656 (15.62%) 2,018 (16.01%) 1.03 (0.93- 1.14) 0.5571 3 - Medium (>25 to <75th percentile) 1,628 (50.06%) 4,879 (50.01%) 1.00 [Reference] 1,971 (46.92%) 6,262 (49.69%) 1.00 [Reference] 4 - High (75 to <90th percentile) 506 (15.56%) 1,398 (14.33%) 1.09 (0.97- 1.22) 0.1662 629 (14.97%) 1,852 (14.69%) 1.08 (0.97- 1.20) 0.1452 5 - Very high (≥90th percentile) 280 (8.61%) 944 (9.68%) 0.89 (0.77- 1.03) 0.1055 463 (11.02%) 1,126 (8.93%) 1.31 (1.16- 1.47) <.0001 3-5 years 1 - Very low (≤10th percentile) 374 (10.33%) 1,201 (11.06%) 0.91 (0.80- 1.04) 0.1559 506 (11.10%) 1,531 (11.19%) 1.01 (0.91- 1.13) 0.8204 2 - Low (>10 to 25th percentile) 560 (15.47%) 1,839 (16.93%) 0.89 (0.80- 0.99) 0.0379 730 (16.01%) 2,226 (16.27%) 1.01 (0.91- 1.11) 0.9072 3 - Medium (>25 to <75th percentile) 1,819 (50.23%) 5,321 (48.98%) 1.00 [Reference] 2,223 (48.75%) 6,818 (49.84%) 1.00 [Reference] 4 - High (75 to <90th percentile) 539 (14.89%) 1,505 (13.85%) 1.05 (0.94- 1.17) 0.4019 618 (13.55%) 1,920 (14.04%) 0.99 (0.89- 1.09) 0.817 5 - Very high (≥90th percentile) 329 (9.09%) 997 (9.18%) 0.97 (0.84- 1.11) 0.6412 483 (10.59%) 1,185 (8.66%) 1.25 (1.11- 1.41) 0.0002 5-10 years 1 - Very low (≤10th percentile) 272 (10.01%) 898 (11.02%) 0.90 (0.77- 1.04) 0.1524 393 (11.69%) 1,083 (10.74%) 1.12 (0.98- 1.27) 0.0845 2 - Low (>10 to 25th percentile) 423 (15.57%) 1,324 (16.24%) 0.95 (0.83- 1.07) 0.3873 541 (16.09%) 1,636 (16.22%) 1.02 (0.91- 1.14) 0.7301 3 - Medium (>25 to <75th percentile) 1,372 (50.50%) 4,064 (49.86%) 1.00 [Reference] 1,630 (48.48%) 5,028 (49.85%) 1.00 [Reference] 4 - High (75 to <90th percentile) 385 (14.17%) 1,162 (14.26%) 0.98 (0.86- 1.12) 0.8008 481 (14.31%) 1,449 (14.37%) 1.02 (0.91- 1.15) 0.6883 5 - Very high (≥90th percentile) 265 (9.75%) 703 (8.62%) 1.12 (0.96- 1.31) 0.1539 317 (9.43%) 890 (8.82%) 1.10 (0.96- 1.26) 0.189
© 2022 Giannakeas V et al. JAMA Network Open. eTable 6. Odds ratio of any solid tumour diagnosis (excluding liver) by change in platelet count category and time from cancer diagnosis. Time from cancer diagnosis Change in Platelet Count Percentile Value N, % (Case) N, % (Control) OR (95% CI) P-Value 0-6 months 1 - Large decrease (≤10th percentile) 8,494 (9.4%) 28,643 (10.6%) 1.08 (1.05- 1.11) <.0001 2 - Small decrease (>10 to 25th percentile) 10,990 (12.2%) 42,253 (15.6%) 0.94 (0.92- 0.96) <.0001 3 - No significant change (>25 to <75th percentile) 36,283 (40.1%) 131,443 (48.5%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 14,887 (16.5%) 41,343 (15.2%) 1.31 (1.28- 1.34) <.0001 5 - Large increase (≥90th percentile) 19,750 (21.8%) 27,530 (10.2%) 2.62 (2.56- 2.68) <.0001 6-12 months 1 - Large decrease (≤10th percentile) 7,020 (10.3%) 21,563 (10.6%) 1.05 (1.02- 1.09) 0.0008 2 - Small decrease (>10 to 25th percentile) 9,790 (14.4%) 31,848 (15.6%) 0.99 (0.97- 1.02) 0.5287 3 - No significant change (>25 to <75th percentile) 30,695 (45.2%) 99,042 (48.7%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 11,268 (16.6%) 31,008 (15.2%) 1.18 (1.15- 1.21) <.0001 5 - Large increase (≥90th percentile) 9,081 (13.4%) 20,101 (9.9%) 1.46 (1.42- 1.51) <.0001 1-2 years 1 - Large decrease (≤10th percentile) 10,404 (10.3%) 30,958 (10.3%) 1.03 (1.01- 1.06) 0.0113 2 - Small decrease (>10 to 25th percentile) 15,050 (15.0%) 47,148 (15.6%) 0.98 (0.96- 1.00) 0.0535 3 - No significant change (>25 to <75th percentile) 48,403 (48.1%) 148,583 (49.2%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 15,763 (15.7%) 46,051 (15.3%) 1.05 (1.03- 1.07) <.0001 5 - Large increase (≥90th percentile) 11,024 (11.0%) 29,192 (9.7%) 1.16 (1.13- 1.19) <.0001 2-5 years 1 - Large decrease (≤10th percentile) 12,076 (10.1%) 36,007 (10.0%) 1.02 (1.00- 1.04) 0.1094 2 - Small decrease (>10 to 25th percentile) 18,452 (15.4%) 55,580 (15.4%) 1.01 (0.99- 1.03) 0.4105 3 - No significant change (>25 to <75th percentile) 58,748 (48.9%) 178,385 (49.5%) 1.00 [Reference]
© 2022 Giannakeas V et al. JAMA Network Open. Time from cancer diagnosis Change in Platelet Count Percentile Value N, % (Case) N, % (Control) OR (95% CI) P-Value 4 - Small increase (75 to <90th percentile) 18,538 (15.4%) 55,595 (15.4%) 1.01 (0.99- 1.03) 0.1875 5 - Large increase (≥90th percentile) 12,229 (10.2%) 34,562 (9.6%) 1.08 (1.05- 1.10) <.0001 5-10 years 1 - Large decrease (≤10th percentile) 6,539 (11.5%) 19,425 (11.4%) 1.01 (0.98- 1.04) 0.4869 2 - Small decrease (>10 to 25th percentile) 10,002 (17.6%) 30,704 (18.1%) 0.98 (0.95- 1.00) 0.102 3 - No significant change (>25 to <75th percentile) 28,116 (49.6%) 84,446 (49.7%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 7,399 (13.1%) 22,136 (13.0%) 1.00 (0.97- 1.03) 0.78 5 - Large increase (≥90th percentile) 4,615 (8.1%) 13,302 (7.8%) 1.04 (1.01- 1.08) 0.0239
© 2022 Giannakeas V et al. JAMA Network Open. eTable 7. Odds ratio of cancer by change in platelet count category and time from diagnosis. Select cancer sites. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Large decrease (≤10th pctl) 794 (6.59%) 3,660 (10.13%) 1.02 (0.93- 1.11) 0.7074 1,335 (9.72%) 4,591 (11.14%) 1.33 (1.24- 1.43) <.0001 2 - Small decrease (>10 to 25th pctl) 999 (8.29%) 5,645 (15.62%) 0.84 (0.77- 0.90) <.0001 1,332 (9.70%) 6,348 (15.40%) 0.96 (0.89- 1.02) 0.1953 3 - No significant change (>25 to <75th pctl) 3,792 (31.48%) 17,663 (48.88%) 1.00 [Reference] 4,330 (31.52%) 19,677 (47.74%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 2,169 (18.01%) 5,499 (15.22%) 1.87 (1.76- 1.99) <.0001 2,314 (16.84%) 6,299 (15.28%) 1.70 (1.61- 1.81) <.0001 5 - Large increase (≥90th pctl) 4,292 (35.63%) 3,671 (10.16%) 5.52 (5.21- 5.86) <.0001 4,427 (32.22%) 4,299 (10.43%) 4.77 (4.51- 5.04) <.0001 6-12 months 1 - Large decrease (≤10th pctl) 738 (8.99%) 2,572 (10.45%) 1.05 (0.96- 1.15) 0.3158 1,196 (11.34%) 3,336 (10.54%) 1.29 (1.20- 1.39) <.0001 2 - Small decrease (>10 to 25th pctl) 906 (11.04%) 3,839 (15.59%) 0.86 (0.79- 0.93) 0.0003 1,420 (13.46%) 4,930 (15.58%) 1.03 (0.96- 1.10) 0.4622 3 - No significant change (>25 to <75th pctl) 3,317 (40.42%) 12,045 (48.92%) 1.00 [Reference] 4,313 (40.89%) 15,368 (48.57%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,584 (19.30%) 3,764 (15.29%) 1.54 (1.43- 1.65) <.0001 1,783 (16.91%) 4,831 (15.27%) 1.32 (1.24- 1.41) <.0001 5 - Large increase (≥90th pctl) 1,662 (20.25%) 2,401 (9.75%) 2.55 (2.37- 2.75) <.0001 1,835 (17.40%) 3,176 (10.04%) 2.07 (1.93- 2.21) <.0001 12-18 months 1 - Large decrease (≤10th pctl) 793 (9.83%) 2,506 (10.35%) 1.04 (0.95- 1.14) 0.3568 1,301 (12.91%) 3,323 (10.99%) 1.37 (1.27- 1.47) <.0001 2 - Small decrease (>10 to 25th pctl) 1,114 (13.81%) 3,774 (15.59%) 0.97 (0.90- 1.05) 0.4754 1,523 (15.11%) 4,730 (15.64%) 1.11 (1.04- 1.19) 0.0016 3 - No significant change (>25 to <75th pctl) 3,630 (44.99%) 11,959 (49.40%) 1.00 [Reference] 4,242 (42.09%) 14,665 (48.50%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,413 (17.51%) 3,729 (15.40%) 1.25 (1.16- 1.34) <.0001 1,562 (15.50%) 4,535 (15.00%) 1.19 (1.12- 1.28) <.0001 5 - Large increase (≥90th pctl) 1,119 (13.87%) 2,239 (9.25%) 1.65 (1.52- 1.79) <.0001 1,451 (14.40%) 2,984 (9.87%) 1.70 (1.58- 1.82) <.0001 18-24 months 1 - Large decrease (≤10th pctl) 693 (10.28%) 2,029 (10.03%) 1.11 (1.01- 1.22) 0.0289 1,153 (12.88%) 2,877 (10.71%) 1.34 (1.24- 1.44) <.0001 2 - Small decrease (>10 to 25th pctl) 955 (14.16%) 3,180 (15.72%) 0.97 (0.90- 1.06) 0.5415 1,301 (14.53%) 4,194 (15.62%) 1.03 (0.96- 1.10) 0.4549 3 - No significant change (>25 to <75th pctl) 3,115 (46.20%) 10,125 (50.06%) 1.00 [Reference] 3,944 (44.06%) 13,051 (48.60%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,169 (17.34%) 3,038 (15.02%) 1.25 (1.16- 1.35) <.0001 1,390 (15.53%) 4,059 (15.11%) 1.14 (1.06- 1.22) 0.0004
© 2022 Giannakeas V et al. JAMA Network Open. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 5 - Large increase (≥90th pctl) 810 (12.01%) 1,854 (9.17%) 1.42 (1.30- 1.56) <.0001 1,164 (13.00%) 2,675 (9.96%) 1.45 (1.34- 1.57) <.0001 2-3 years 1 - Large decrease (≤10th pctl) 904 (9.56%) 2,792 (9.84%) 0.98 (0.90- 1.06) 0.6224 1,550 (12.70%) 3,799 (10.37%) 1.35 (1.26- 1.44) <.0001 2 - Small decrease (>10 to 25th pctl) 1,343 (14.20%) 4,469 (15.75%) 0.91 (0.85- 0.97) 0.0062 1,840 (15.07%) 5,810 (15.86%) 1.04 (0.98- 1.11) 0.1718 3 - No significant change (>25 to <75th pctl) 4,690 (49.58%) 14,197 (50.02%) 1.00 [Reference] 5,394 (44.18%) 17,723 (48.39%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,542 (16.30%) 4,286 (15.10%) 1.09 (1.02- 1.17) 0.0103 1,903 (15.59%) 5,655 (15.44%) 1.11 (1.04- 1.18) 0.0009 5 - Large increase (≥90th pctl) 981 (10.37%) 2,636 (9.29%) 1.13 (1.04- 1.22) 0.0031 1,521 (12.46%) 3,637 (9.93%) 1.38 (1.29- 1.48) <.0001 3-5 years 1 - Large decrease (≤10th pctl) 969 (10.05%) 2,798 (9.68%) 1.06 (0.98- 1.15) 0.1457 1,501 (12.19%) 3,797 (10.27%) 1.29 (1.21- 1.38) <.0001 2 - Small decrease (>10 to 25th pctl) 1,501 (15.57%) 4,536 (15.69%) 1.01 (0.95- 1.08) 0.6904 1,867 (15.16%) 5,685 (15.38%) 1.07 (1.01- 1.13) 0.0311 3 - No significant change (>25 to <75th pctl) 4,772 (49.51%) 14,617 (50.55%) 1.00 [Reference] 5,624 (45.66%) 18,288 (49.49%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,457 (15.12%) 4,313 (14.92%) 1.03 (0.97- 1.11) 0.3237 1,920 (15.59%) 5,664 (15.33%) 1.10 (1.04- 1.17) 0.0013 5 - Large increase (≥90th pctl) 939 (9.74%) 2,650 (9.17%) 1.09 (1.00- 1.18) 0.0464 1,406 (11.41%) 3,520 (9.53%) 1.31 (1.22- 1.40) <.0001 5-10 years 1 - Large decrease (≤10th pctl) 695 (11.33%) 2,104 (11.44%) 0.99 (0.90- 1.09) 0.8018 1,050 (13.03%) 2,851 (11.79%) 1.17 (1.08- 1.27) 0.0001 2 - Small decrease (>10 to 25th pctl) 1,031 (16.81%) 3,292 (17.89%) 0.94 (0.86- 1.01) 0.1094 1,378 (17.09%) 4,355 (18.01%) 1.00 (0.93- 1.08) 0.963 3 - No significant change (>25 to <75th pctl) 3,118 (50.84%) 9,323 (50.67%) 1.00 [Reference] 3,766 (46.72%) 11,927 (49.32%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 766 (12.49%) 2,315 (12.58%) 0.99 (0.90- 1.08) 0.8309 1,101 (13.66%) 3,199 (13.23%) 1.09 (1.01- 1.18) 0.0269 5 - Large increase (≥90th pctl) 523 (8.53%) 1,365 (7.42%) 1.15 (1.03- 1.28) 0.0142 766 (9.50%) 1,851 (7.65%) 1.32 (1.20- 1.45) <.0001
© 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P-value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Large decrease (≤10th pctl) 97 (6.07%) 480 (10.01%) 1.01 (0.79- 1.29) 0.9506 185 (7.80%) 738 (10.37%) 1.16 (0.96- 1.39) 0.1218 2 - Small decrease (>10 to 25th pctl) 136 (8.51%) 741 (15.46%) 0.90 (0.73- 1.11) 0.3245 172 (7.25%) 1,136 (15.96%) 0.69 (0.58- 0.83) <.0001 3 - No significant change (>25 to <75th pctl) 462 (28.91%) 2,359 (49.21%) 1.00 [Reference] 745 (31.41%) 3,437 (48.30%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 248 (15.52%) 736 (15.35%) 1.71 (1.43- 2.05) <.0001 407 (17.16%) 1,068 (15.01%) 1.77 (1.54- 2.04) <.0001 5 - Large increase (≥90th pctl) 655 (40.99%) 478 (9.97%) 7.23 (6.12- 8.53) <.0001 863 (36.38%) 737 (10.36%) 5.51 (4.82- 6.29) <.0001 6-12 months 1 - Large decrease (≤10th pctl) 119 (10.54%) 351 (10.36%) 1.08 (0.86- 1.35) 0.5295 167 (9.56%) 585 (11.17%) 0.98 (0.81- 1.18) 0.8258 2 - Small decrease (>10 to 25th pctl) 130 (11.51%) 566 (16.71%) 0.72 (0.58- 0.90) 0.0037 252 (14.43%) 806 (15.39%) 1.06 (0.91- 1.25) 0.4461 3 - No significant change (>25 to <75th pctl) 518 (45.88%) 1,653 (48.80%) 1.00 [Reference] 746 (42.73%) 2,557 (48.82%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 210 (18.60%) 504 (14.88%) 1.33 (1.10- 1.61) 0.0029 298 (17.07%) 769 (14.68%) 1.33 (1.14- 1.56) 0.0003 5 - Large increase (≥90th pctl) 152 (13.46%) 313 (9.24%) 1.55 (1.25- 1.93) <.0001 283 (16.21%) 521 (9.95%) 1.87 (1.58- 2.21) <.0001 12-18 months 1 - Large decrease (≤10th pctl) 87 (8.15%) 335 (10.47%) 0.80 (0.62- 1.03) 0.0861 171 (10.48%) 505 (10.32%) 1.04 (0.86- 1.26) 0.6826 2 - Small decrease (>10 to 25th pctl) 142 (13.31%) 486 (15.18%) 0.90 (0.73- 1.11) 0.3115 211 (12.94%) 730 (14.92%) 0.88 (0.74- 1.05) 0.1689 3 - No significant change (>25 to <75th pctl) 519 (48.64%) 1,591 (49.70%) 1.00 [Reference] 797 (48.87%) 2,444 (49.95%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 191 (17.90%) 477 (14.90%) 1.22 (1.00- 1.48) 0.0453 258 (15.82%) 727 (14.86%) 1.09 (0.92- 1.28) 0.308 5 - Large increase (≥90th pctl) 128 (12.00%) 312 (9.75%) 1.25 (1.00- 1.57) 0.0533 194 (11.89%) 487 (9.95%) 1.22 (1.02- 1.47) 0.0334 18-24 months 1 - Large decrease (≤10th pctl) 96 (10.01%) 278 (9.66%) 1.01 (0.79- 1.31) 0.9115 174 (11.73%) 437 (9.82%) 1.29 (1.06- 1.57) 0.0127 2 - Small decrease (>10 to 25th pctl) 146 (15.22%) 433 (15.05%) 0.99 (0.80- 1.23) 0.9258 198 (13.34%) 683 (15.34%) 0.93 (0.78- 1.11) 0.4262 3 - No significant change (>25 to <75th pctl) 486 (50.68%) 1,426 (49.57%) 1.00 [Reference] 684 (46.09%) 2,191 (49.21%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 142 (14.81%) 425 (14.77%) 0.98 (0.79- 1.22) 0.8563 255 (17.18%) 697 (15.66%) 1.18 (0.99- 1.39) 0.0581 5 - Large increase (≥90th pctl) 89 (9.28%) 315 (10.95%) 0.83 (0.64- 1.07) 0.1469 173 (11.66%) 444 (9.97%) 1.26 (1.03- 1.53) 0.0225
© 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P-value N, % (Case) N, % (Control) OR (95% CI) P- value 2-3 years 1 - Large decrease (≤10th pctl) 137 (9.88%) 425 (10.21%) 0.93 (0.75- 1.15) 0.4994 211 (10.65%) 586 (9.86%) 1.11 (0.93- 1.33) 0.23 2 - Small decrease (>10 to 25th pctl) 208 (15.00%) 639 (15.36%) 0.94 (0.79- 1.12) 0.4929 312 (15.75%) 925 (15.56%) 1.04 (0.90- 1.21) 0.5961 3 - No significant change (>25 to <75th pctl) 712 (51.33%) 2,056 (49.41%) 1.00 [Reference] 961 (48.51%) 2,964 (49.87%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 201 (14.49%) 627 (15.07%) 0.93 (0.77- 1.11) 0.4019 311 (15.70%) 921 (15.50%) 1.04 (0.90- 1.21) 0.5785 5 - Large increase (≥90th pctl) 129 (9.30%) 414 (9.95%) 0.90 (0.72- 1.12) 0.3319 186 (9.39%) 547 (9.20%) 1.05 (0.88- 1.26) 0.5972 3-5 years 1 - Large decrease (≤10th pctl) 132 (9.07%) 420 (9.62%) 0.96 (0.78- 1.19) 0.7121 174 (8.59%) 608 (10.00%) 0.86 (0.71- 1.03) 0.1026 2 - Small decrease (>10 to 25th pctl) 234 (16.08%) 685 (15.69%) 1.04 (0.88- 1.24) 0.6237 342 (16.88%) 911 (14.99%) 1.13 (0.97- 1.30) 0.1069 3 - No significant change (>25 to <75th pctl) 721 (49.55%) 2,203 (50.47%) 1.00 [Reference] 1,011 (49.90%) 3,025 (49.77%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 224 (15.40%) 654 (14.98%) 1.05 (0.88- 1.24) 0.6099 290 (14.31%) 966 (15.89%) 0.90 (0.77- 1.04) 0.1554 5 - Large increase (≥90th pctl) 144 (9.90%) 403 (9.23%) 1.09 (0.89- 1.35) 0.4079 209 (10.32%) 568 (9.35%) 1.10 (0.92- 1.31) 0.2946 5-10 years 1 - Large decrease (≤10th pctl) 113 (11.58%) 334 (11.41%) 0.99 (0.78- 1.25) 0.9316 151 (11.30%) 449 (11.20%) 1.04 (0.85- 1.28) 0.7091 2 - Small decrease (>10 to 25th pctl) 174 (17.83%) 533 (18.20%) 0.96 (0.78- 1.17) 0.6571 241 (18.04%) 720 (17.96%) 1.03 (0.87- 1.22) 0.7195 3 - No significant change (>25 to <75th pctl) 489 (50.10%) 1,432 (48.91%) 1.00 [Reference] 658 (49.25%) 2,032 (50.70%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 131 (13.42%) 393 (13.42%) 0.98 (0.78- 1.22) 0.8315 174 (13.02%) 527 (13.15%) 1.02 (0.84- 1.24) 0.8269 5 - Large increase (≥90th pctl) 69 (7.07%) 236 (8.06%) 0.85 (0.64- 1.14) 0.2854 112 (8.38%) 280 (6.99%) 1.24 (0.98- 1.57) 0.0792
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 1. Study design criteria among matched individuals
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 2. Age- and sex-specific platelet count reference distributions for exposure definition Note: Observations inversely weighted based on the number of CBC tests per-subject, for each sex-age category
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 3. Age- and sex-specific platelet count reference distributions for secondary exposure definition Male Female Change in platelet count observation percentile Change in platelet count observation percentile Age N 10th 25th 50th 75th 90th Age N 10th 25th 50th 75th 90th 18-29 239,713 -39 -19 -1 17 37 18-29 762,668 -49 -24 0 24 48 30-39 407,352 -36 -18 -1 16 34 30-39 1,267,171 -48 -23 0 23 47 40-49 870,005 -35 -17 -1 15 32 40-49 1,664,504 -44 -21 0 21 43 50-59 1,559,807 -35 -17 -1 15 33 50-59 2,144,471 -41 -20 -1 17 37 60-69 1,950,142 -36 -17 -1 15 33 60-69 2,246,168 -38 -19 -1 17 37 70-79 1,588,074 -36 -17 -1 15 35 70-79 1,907,064 -41 -19 -1 18 40 80-89 835,988 -40 -18 0 18 42 80-89 1,300,664 -47 -21 -1 21 47 90-100 125,702 -44 -19 1 22 52 90-100 334,804 -53 -24 0 25 58 Note: Observations inversely weighted based on the number of CBC tests per-subject, for each sex-age category 0 5 10 15 20 25 30 -200 -150 -100 -50 0 50 100 150 200 Percent (%) Change in platelet count (platelets per nL) 18-29 30-39 40-49 50-59 60-69 70-79 80-89 90-100 0 5 10 15 20 25 30 -200 -150 -100 -50 0 50 100 150 200 Percent (%) Change in platelet count (platelets per nL) 18-29 30-39 40-49 50-59 60-69 70-79 80-89 90-100
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 4. Odds ratio of cancer by platelet count category and time from cancer diagnosis. Additional cancer sites. Breast (N = 65,703) Prostate (N = 62,770) Melanoma (N = 20,167) Thyroid (N = 21,559)
© 2022 Giannakeas V et al. JAMA Network Open. Esophagus (N = 4,691) Kidney (N = 14,057) Pancreas (N = 12,009) Other GI (N = 5,259)
© 2022 Giannakeas V et al. JAMA Network Open. Cervix (N = 3,493) Endometrium (N = 17,124) Bladder (N = 23,267) Liver (N = 7,651)
© 2022 Giannakeas V et al. JAMA Network Open. Brain (N = 5,721) Head and neck (N = 13,318) Other solid tumour (N = 26,907)
© 2022 Giannakeas V et al. JAMA Network Open. Leukemia (N = 5,157) Lymphoma (N = 33,785) Multiple myeloma (N = 8,265) Other hematologic tumour (N = 16,195)
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 5. Odds ratio of cancer by change in platelet count category and time from cancer diagnosis. Additional cancer sites. Breast (N = 32,650) Prostate (N = 30,994) Melanoma (N = 9,957) Thyroid (N = 10,176)
© 2022 Giannakeas V et al. JAMA Network Open. Esophagus (N = 2,307) Kidney (N = 7,149) Pancreas (N = 6,667) Other GI (N = 2,816) Cervix (N = 1,192) Endometrium (N = 8,597)
© 2022 Giannakeas V et al. JAMA Network Open. Bladder (N = 12,895) Liver (N = 4,489)
© 2022 Giannakeas V et al. JAMA Network Open. Brain (N = 2,648) Head and neck (N = 6,393) Other solid tumour (N = 13,624)
© 2022 Giannakeas V et al. JAMA Network Open. Leukemia (N = 2,834) Lymphoma (N = 17,736) Multiple myeloma (N = 4,877) Other hematologic tumour (N = 10,306)
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 6. Odds ratio of cancer by platelet count category and time from diagnosis. Select cancer sites by cancer stage. Lung stage I (N = 9,697) Lung stage II (N = 3,921) Lung stage III (N = 9,911) Lung stage IV (N = 24,390)
© 2022 Giannakeas V et al. JAMA Network Open. Ovary stage I (N = 1,196) Ovary stage II (N = 543) Ovary stage III (N = 2,315) Ovary stage IV (N = 926)
© 2022 Giannakeas V et al. JAMA Network Open. Stomach stage I (N = 600) Stomach stage II (N = 678) Stomach stage III (N = 799) Stomach stage IV (N = 1,673)
© 2022 Giannakeas V et al. JAMA Network Open. Breast stage I (N = 28,646) Breast stage II (N = 22,577) Breast stage III (N = 7,740) Breast stage IV (N = 2,672)
© 2022 Giannakeas V et al. JAMA Network Open. Prostate stage I (N = 12,383) Prostate stage II (N = 30,688) Prostate stage III (N = 8,137) Prostate stage IV (N = 5,797)
© 2022 Giannakeas V et al. JAMA Network Open. eFigure 7. Odds ratio of cancer by platelet count category (clinical definition) and time from diagnosis. Colon (N = 51,271) Lung (N = 56,586) Ovary (N = 7,658) Stomach (N = 9,166)
© 2022 Giannakeas V et al. JAMA Network Open. Breast (N = 65,703) Prostate (N = 62,770) Melanoma (N = 20,167) Thyroid (N = 21,559)
© 2022 Giannakeas V et al. JAMA Network Open. Esophagus (N = 4,691) Kidney (N = 14,057) Pancreas (N = 12,009) Other GI (N = 5,259)
© 2022 Giannakeas V et al. JAMA Network Open. Cervix (N = 3,493) Endometrium (N = 17,124) Bladder (N = 23,267) Liver (N = 7,651)
© 2022 Giannakeas V et al. JAMA Network Open. Brain (N = 5,721) Head and neck (N = 13,318) Other solid tumour (N = 26,907)
© 2022 Giannakeas V et al. JAMA Network Open. Leukemia (N = 5,157) Lymphoma (N = 33,785) Multiple myeloma (N = 8,265) Other hematologic tumour (N = 16,195)

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  • 1. Original Investigation | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period Vasily Giannakeas, MPH; Joanne Kotsopoulos, PhD; Matthew C. Cheung, MD; Laura Rosella, PhD; Jennifer D. Brooks, PhD; Lorraine Lipscombe, MD; Mohammad R. Akbari, MD, PhD; Peter C. Austin, PhD; Steven A. Narod, MD Abstract IMPORTANCE Individuals with cancer often have an elevated platelet count at the time of diagnosis. The extent to which an elevated platelet count is an indicator of cancer is unclear. OBJECTIVE To evaluate the association of an elevated platelet count with a cancer diagnosis. DESIGN, SETTING, AND PARTICIPANTS This nested case-control study included Ontario residents enrolled in the provincial health insurance plan who had 1 or more routine complete blood count (CBC) tests performed between January 1, 2007, and December 31, 2017, with follow-up through December 31, 2018. Case patients were individuals with a new cancer diagnosis during the observation period. Eligible control individuals were cancer free before the date of diagnosis for a case patient to whom they were matched. One case patient was matched to 3 controls based on sex, age, and health care use patterns. Data were analyzed from September 24, 2020, to July 13, 2021. EXPOSURES Case patients and controls were assigned to 1 of 5 exposure groups based on age- and sex-specific platelet count distributions in the control population: very low (ⱕ10th percentile), low (>10th to 25th percentile), medium (>25th to <75th percentile), high (75th to <90th percentile), and very high (ⱖ90th percentile). MAIN OUTCOMES AND MEASURES Odds ratios (ORs) were estimated for specific cancer sites for each category of platelet count at intervals up to 10 years after a blood test. RESULTS Of the 8 917 187 eligible Ontario residents with a routine CBC record available, 4 971 578 (55.8%) were women; the median age at the first CBC was 46.4 years (IQR, 32.5-59.5 years). Among individuals with a routine CBC record available, 495 341 (5.6%) received a diagnosis of first primary cancer during the 10-year observation period. The OR for a solid tumor diagnosis associated with a very high platelet count vs a medium platelet count in the 6-month period before the diagnosis was 2.32 (95% CI, 2.28-2.35). A very high platelet count was associated with colon (OR, 4.38; 95% CI, 4.22-4.54), lung (OR, 4.37; 95% CI, 4.22-4.53), ovarian (OR, 4.62; 95% CI, 4.19-5.09), and stomach (OR, 4.27; 95% CI, 3.91-4.66) cancers. Odds ratios attenuated with increasing time from CBC test to cancer diagnosis. CONCLUSIONS AND RELEVANCE In this nested case-control study, an elevated platelet count was associated with increased risk of cancer at several sites. Our findings suggest that an elevated platelet count could potentially serve as a marker for the presence of some cancer types. JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 Key Points Question Is a high platelet count associated with an increased risk of cancer? Findings In this nested case-control study of 8 917 187 Ontario residents who had 1 or more routine complete blood count tests performed, an elevated platelet count was associated with a diagnosis of cancer within 10 years after the blood test. The magnitude of the association varied by cancer type and time elapsed since the blood test. Meaning The findings suggest that a high platelet count is associated with increased cancer risk. + Supplemental content Author affiliations and article information are listed at the end of this article. Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 1/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 2. Introduction Patients with cancer often have an abnormally high platelet count at the time of diagnosis (thrombocytosis), defined as a platelet count greater than 450 × 109 /L (to convert to ×103 per microliter, divide by 1.0).1 A normal platelet count falls between 150 and 450 × 109 /L and varies with the age and sex of the individual.1,2 Several conditions that commonly cause an elevated platelet count include acute blood loss, infection, and inflammation.3 Solid tumor cancers can sometimes lead to an elevated platelet count to the extent that an undiagnosed cancer is often considered in the diagnostic workup of a patient with thrombocytosis.3 Cancer is believed to induce platelet formation through the release of interleukin 6, a proinflammatory cytokine that stimulates the production of thrombopoietin hormone.4 Elevated levels of thrombopoietin have a direct effect on increased platelet production. Excess levels of thrombopoietin in the blood stimulate megakaryocyte cell division in the bone marrow, which in turn leads to platelet formation.5 An elevated platelet count has been shown to be associated with short-term risk of cancer in the general population.6-8 Prospective studies evaluating platelet count and survival among patients with newly diagnosed cancer have also noted a high proportion of patients who presented with thrombocytosis.9-12 The excess risk associated with an elevated platelet count varies by cancer site but has been most studied for lung, colon, and gastric cancers. The full range of cancers associated with a high platelet count and whether risks associated with platelet counts within the high-normal range exist remain unclear. Furthermore, it is unclear whether the association between a high platelet count and cancer is transient or prolonged. Based on results of previous studies,6-8 a high platelet count may be a risk factor for developing cancer or, alternatively, a marker indicative of an undetected cancer. It is also not clear whether an increasing platelet count is a better indicator of a new cancer than is a high but steady platelet count. We identified a cohort of adult residents in Ontario, Canada, who had 1 or more routine blood tests performed for a complete blood count (CBC) including platelet counts and subsequently received a diagnosis of cancer to assess the range of cancers associated with a high platelet count. We also examined whether an increasing platelet count is associated with an increased cancer risk. Methods Study Design, Population, and Data Ontario is the most populous province in Canada, with a population of 14.5 million. Ontario residents are covered under the universal health insurance program, which includes coverage for primary care services, emergency visits, hospitalizations, and (among older adults) medication. This nested case- control study used data from ICES, a nonprofit organization that provides researchers with deidentified data that can be used for research purposes. ICES is a prescribed entity under §45 of Ontario’s Personal Health Information Protection Act, which allows for research conduct without a research ethics board review and without the need for informed consent. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for case-control studies. ICES data include results of laboratory tests conducted in Ontario from January 2007 to present. The Ontario Laboratory Information System data set includes more than 85 million CBC test records, including those for 9.5 million (of the 14.5 million) Ontario residents. The CBC records include the date of laboratory analysis, the platelet count, and other standard blood parameters. Incident cancers in Ontario are recorded in the Ontario Cancer Registry, which was started in January 1964. This study also used data on physician billing (Ontario Health Insurance Plan claims database), emergency department visits (National Ambulatory Care and Reporting System database), acute care hospitalizations (Discharge Abstract Database), and dispensed medications among adults aged 65 years or older (Ontario Drug Benefit Claims database). These datasets were linked using unique encoded identifiers and analyzed at ICES. JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 2/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 3. Construction of the Cohort The nesting cohort consisted of 8 917 187 Ontario residents who had at least 1 routine CBC test ordered by a practicing physician in a community health setting from January 1, 2007, through December 31, 2017. Cohort entry date was the date of the first eligible CBC test. Patients with cancer before the cohort entry date were excluded. Patients were observed from the date of their first routine blood test to the first date of any cancer diagnosis, death from any cause, end of Ontario Health Insurance Plan eligibility, or the end of the observation period (December 31, 2018) (eFigure 1 in the Supplement). Details on the inclusion criteria, exclusion criteria, and the study cohort are available in eTables 1-3 in the Supplement. Baseline Variables Baseline information was obtained and updated at the time of each CBC test. We included information on general demographic characteristics, health services use, comorbidities and chronic conditions, medication use (among individuals aged ⱖ66 years), and additional CBC test results. The Johns Hopkins ACG System software, version 10,13 was used to obtain aggregate diagnosis groups and resource utilization bands. Case Patients Case patients were defined as individuals who received a cancer diagnosis after the date of cohort entry. Data on first primary cancer diagnoses during the observation period were captured from the Ontario Cancer Registry. The Ontario Cancer Registry is a validated cancer registry that provides information on the date of diagnosis, cancer site, and tumor-specific data, such as morphologic features, stage, grade, lymph node involvement, and for certain cancers, hormone receptor status.14 We restricted the interpretation of our findings to solid cancers other than liver cancer because both liver and hematologic cancers may have a direct effect on platelet count; thrombopoietin production occurs in the liver, and megakaryocyte production occurs in the bone marrow. For case patients, the index date was defined as the date of diagnosis of cancer. Matching We hard-matched 3 control individuals to each case patient. Each matched control was alive and cancer free on the date of diagnosis of the case patient (eFigure 1 in the Supplement). Case patients and controls were matched based on sex, calendar date of CBC test (±30 days), age (±2 years), years of coverage by the Ontario Health Insurance Plan (±2 years), and the patient’s resource utilization band. Incidence density sampling was used such that case patients could serve as potential controls at prior time points. Exposure We assigned a categorical value to each platelet count based on the percentile distribution for the cancer-free controls. Five mutually exclusive categories were created: very low (ⱕ10th percentile), low (>10th to 25th percentile), medium (>25th to <75th percentile), high (75th to <90th percentile), and very high (ⱖ90th percentile). To account for variation in platelet count by sex and age, we defined categories of platelet count using reference distributions that were standardized according to age and sex from the pool of control patients (eFigure 2 in the Supplement). Statistical Analysis Primary Analysis We performed a series of (nested) matched case-control analyses to measure the association of platelet count with risk of cancer at various time intervals before the index date. Each matched quadruplet of case patients and controls (3:1) was assessed at 7 time intervals before the index date: 0 to 6 months, 6 to 12 months, 12 to 18 months, 18 to 24 months, 2 to 3 years, 3 to 5 years, and 5 to 10 years. Each case patient could contribute to up to 7 observations (1 for each time interval). If JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 3/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 4. multiple routine CBC tests were performed within a given period, 1 was chosen at random. For each cancer site and for each time point, an odds ratio (OR) was estimated using conditional logistic regression. At each time point, the medium platelet count category was used as the reference group and ORs were estimated for very high, high, low, and very low counts compared with the reference group. Information on tumor stage was available for several sites. A subanalysis was conducted after stratifying cancers by stage for these sites. In a thrombocytosis sensitivity analysis, we assigned platelet levels using clinical cutoffs: thrombocytopenia (<150 ×109 platelets/L), normal level (150 to 450 ×109 platelets/L), and thrombocytosis (>450 ×109 platelets/L). Secondary Analysis As a secondary objective, we sought to assess whether a change in platelet count over time was associated with a diagnosis of cancer. To study this, we selected individuals who had 2 routine CBC tests recorded 9 to 15 months apart. If multiple CBC records were available in the 9- to 15-month period, 1 was selected at random. A second iteration of matching (using the same matching criteria) was done using this subset of individuals (n = 4 372 288 [49% of the primary cohort]). A difference in platelet count was measured by subtracting the first platelet count from the second platelet count. Sex- and age-standardized reference distributions for change in platelet count were created (eFigure 3 in the Supplement). Five categories were created to classify the change in platelet count: large decrease (ⱕ10th percentile), small decrease (>10th to 25th percentile), no substantial change (>25 to <75th percentile [reference group]), small increase (75th to <90th percentile), and large increase (ⱖ90th percentile). All statistical analyses were performed using SAS software, version 9.4 (SAS Institute Inc). Data were analyzed from September 24, 2020, to July 13, 2021. Results Of the 8 917 187 eligible individuals with 1 or more routine CBC tests identified in Ontario during the accrual period, 4 971 578 (55.8%) were women; the median age at the first CBC was 46.4 years (IQR, 32.5-59.5 years) (Table 1). Of the entire cohort, 495 341 individuals (5.6%) received a cancer diagnosis during the observation period. We successfully matched 491 779 case patients with cancer (99.3%) to 3 controls in 1 or more predefined time intervals. Case patients were similar to controls with respect to their demographic information, health services use, medication use, and comorbidity variables (eTable 4 in the Supplement). The mean platelet count at the most recent blood test was higher among case patients with cancer than among matched controls (245.7 × 109 /L vs 237.0 × 109 /L). Case patients diagnosed with a solid tumor were more likely to have a recent platelet count in the highest category compared with cancer-free controls (44 344 [19.5%] vs 65 626 [9.6%]). For blood samples obtained during the 6 months before a cancer diagnosis, the OR for any solid cancer associated with a very high platelet count (ⱖ90th percentile) vs a medium platelet count (reference, >25th to <75th percentile) was 2.32 (95% CI, 2.28-2.35) (Table 2). The OR for this association attenuated with increasing time from blood test to cancer diagnosis (Table 2); the ORs for the very high platelet category were 1.41 (95% CI, 1.39-1.44) for 6 to less than 12 months before diagnosis, 1.20 (95% CI, 1.18-1.22) for 12 to less than 24 months before diagnosis, 1.15 (95% CI, 1.13-1.17) for 24 to less than 60 months before diagnosis, and 1.13 (95% CI, 1.10-1.15) for 60 to 120 months before diagnosis. The ORs for the association of a high platelet count with a cancer diagnosis were greatest for patients with cancers of the colon, lung, ovary, and stomach (Figure 1). During the 0- to 6-month period before a cancer diagnosis, the ORs for the very high platelet count category were 4.38 (95% CI, 4.22-4.54) for colon cancer, 4.37 (95% CI, 4.22-4.53) for lung cancer, 4.62 (95% CI, 4.19-5.09) for ovarian cancer, and 4.27 (95% CI, 3.91-4.66) for stomach cancer (Figure 1 and eTable 5 in the Supplement). Significant associations were also observed for esophageal cancer (OR, 3.18; 95% CI, 2.81-3.60), other gastrointestinal tract cancers (OR, 3.10; 95% CI, 2.75-3.49), and kidney cancer (OR, JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 4/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 5. Table 1. Characteristics of the Study Cohort at the First Eligible Routine CBC Test Description Individuals (N = 8 917 187)a Sex Female 4 971 578 (55.8) Male 3 945 609 (44.2) Age, y Mean (SD) 47.0 (17.8) Median (IQR) 46.4 (32.5-59.5) Residence location Urban 8 084 848 (90.7) Rural 820 419 (9.2) Missing 11 920 (0.1) Core primary care visits to general practitioner or family practitioner in previous 2 y, No. Mean (SD) 2.8 (3.4) Median (IQR) 2 (1-3) Rostered to family physician 6 940 867 (77.8) Comorbidities and chronic conditions Asthma 796 810 (8.9) Congestive heart failure 172 576 (1.9) COPD 192 482 (2.2) Hypertension 2 139 804 (24.0) Diabetes 666 477 (7.5) Kidney disease 88 520 (1.0) Chronic coronary syndrome 321 278 (3.6) Hemoglobin concentration, g/L Mean (SD) 139.5 (14.9) Median (IQR) 140 (130-150) Platelet count, 109 /L Mean (SD) 247.2 (64.5) Median (IQR) 241 (205-282) Observation time, yb Mean (SD) 6.8 (3.0) Median (IQR) 7.3 (4.4-9.3) Routine CBC tests in observation period, No. Mean (SD) 4.3 (6.3) Median (IQR) 3 (1-6) Cancer diagnosisb,c Any 492 691 (5.5) Solid tumor 429 222 (4.8) Colon 51 521 (0.6) Lung 56 724 (0.6) Breastd 65 721 (1.3) Ovaryd 7661 (0.2) Cervicald 3494 (0.1) Endometriald 17 101 (0.3) Prostatee 62 946 (1.6) Thyroid 21 478 (0.2) Pancreas 12 021 (0.1) Stomach 9195 (0.1) Kidney 14 063 (0.2) Bladder 23 344 (0.3) Liver 7696 (0.1) Esophagus 4712 (0.1) Other gastrointestinal tract 5255 (0.1) Brain 5724 (0.1) Melanoma 20 192 (0.2) (continued) JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 5/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 6. Table 1. Characteristics of the Study Cohort at the First Eligible Routine CBC Test (continued) Description Individuals (N = 8 917 187)a Head and neck 13 363 (0.1) Other 27 011 (0.3) Hematologic tumor 63 469 (0.7) Leukemia 5154 (0.1) Lymphoma 33 827 (0.4) Multiple myeloma 8274 (0.1) Other 16 214 (0.2) Abbreviations: CBC, complete blood count; COPD, chronic obstructive pulmonary disease; OHIP, Ontario Health Insurance Plan. SI conversion factors: To convert hemoglobin concentration to grams per deciliter, divide by 10.0; platelet count to 103 per microliter, divide by 1.0. a Data are presented as number (percentage) of individuals unless otherwise indicated. b Period of observation was from the first eligible CBC test to the earliest date of death, end of OHIP eligibility, or end of the observation period (December 31, 2018). c Data are from the Ontario Cancer Registry. d Women only. e Men only. Table 2. Odds Ratios of Any Solid Tumor Diagnosis by Platelet Count Category and Time From Complete Blood Count Test to Cancer Diagnosisa Platelet count percentile category by time to cancer diagnosisb No. (%) Odds ratio (95% CI)c Case patients Control individuals <6 mo Very low 19 161 (8.4) 74 891 (11.0) 0.87 (0.86-0.89) Low 27 308 (12.0) 106 707 (15.6) 0.87 (0.86-0.89) Medium 98 480 (43.3) 336 232 (49.2) 1 [Reference] High 38 372 (16.9) 99 539 (14.6) 1.32 (1.30-1.34) Very high 44 344 (19.5) 65 626 (9.6) 2.32 (2.28-2.35) 6 to <12 mo Very low 14 870 (10.1) 48 700 (11.0) 0.95 (0.93-0.97) Low 20 716 (14.0) 69 561 (15.7) 0.93 (0.91-0.95) Medium 70 078 (47.4) 219 039 (49.4) 1 [Reference] High 23 209 (15.7) 64 288 (14.5) 1.13 (1.11-1.15) Very high 19 038 (12.9) 42 145 (9.5) 1.41 (1.39-1.44) 12 to <24 mo Very low 22 086 (10.2) 70 743 (10.9) 0.95 (0.93-0.96) Low 32 018 (14.7) 103 336 (15.9) 0.94 (0.93-0.95) Medium 106 239 (48.9) 322 348 (49.5) 1 [Reference] High 32 952 (15.2) 94 872 (14.6) 1.05 (1.04-1.07) Very high 23 942 (11.0) 60 412 (9.3) 1.20 (1.18-1.22) 24 to <60 mo Very low 27 116 (10.1) 87 869 (10.9) 0.93 (0.92-0.95) Low 40 852 (15.2) 127 941 (15.9) 0.97 (0.95-0.98) Medium 132 330 (49.4) 400 393 (49.8) 1 [Reference] High 40 363 (15.1) 115 881 (14.4) 1.05 (1.04-1.07) Very high 27 481 (10.2) 72 342 (9.0) 1.15 (1.13-1.17) 60-120 mo Very low 15 744 (10.1) 49 761 (10.7) 0.96 (0.94-0.98) Low 23 750 (15.3) 74 880 (16.1) 0.96 (0.94-0.97) Medium 76 963 (49.5) 232 828 (49.9) 1 [Reference] High 23 340 (15.0) 66 787 (14.3) 1.06 (1.04-1.08) Very high 15 655 (10.1) 42 100 (9.0) 1.13 (1.10-1.15) a Liver cancer was excluded. b Platelet count percentile categories were defined as follows: very low (ⱕ10th percentile), low (>10th to 25th percentile), medium (>25th to <75th percentile), high (75th to <90th percentile), and very high (ⱖ90th percentile). c P < .001 for all. JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 6/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 7. 2.55; 95% CI, 2.38-2.74) (eFigure 4 in the Supplement). The associations attenuated with increasing time to diagnosis to varying degrees. In addition, high platelet count was associated with risk of breast cancer (OR, 1.05; 95% CI, 1.01- 1.10) and prostate cancer (OR, 1.24; 95% CI, 1.19-1.29) but was not associated with risk of melanoma (OR, 1.06; 95% CI, 0.97-1.15) or thyroid cancer (OR, 1.01; 95% CI, 0.94-1.09) (eFigure 4 in the Supplement). A low platelet count and a very low platelet count were associated with a decreased risk of breast and prostate cancer. In a sensitivity analysis, the ORs for the association of thrombocytosis and increased cancer risk were greatest for colon cancer, lung cancer, ovarian cancer, stomach cancer, esophageal cancer, and kidney cancer (eFigure 7 in the Supplement). We also studied the associations between a high platelet count and risk of solid tumors by stage at diagnosis (when data were available). There was a significant association across all stages of colon cancer, but the OR for the association was greatest for metastatic disease (stage IV) (OR, 7.96; 95% CI, 7.26-8.72) (Figure 2). Data for the other cancer sites by stage are presented in eFigure 6 in the Supplement. We also examined whether a substantial increase in platelet count (compared with a platelet count measured in the previous 9 to 15 months) was associated with an risk of cancer. Case patients diagnosed with a solid tumor were more likely to have a recent increase in platelet count (ⱖ90th percentile) than were cancer-free controls (19 750[21.8%] vs 27 530 [10.2%]) (eTable 6 in the Supplement). A recent increase in the platelet count was associated with risk of colon cancer (OR, 5.52; 95% CI, 5.21-5.86), lung cancer (OR, 4.77; 95% CI, 4.51-5.04), ovarian cancer (OR, 7.23; 95% CI, 6.12-8.53), and stomach cancer (OR, 5.51; 95% CI, 4.82-6.29) (Figure 3 and eTable 7 in the Supplement). No associations were observed between a recent increase in the platelet count and Figure 1. Odds Ratios of Cancer by Platelet Count Category and Time From Complete Blood Count Test to Cancer Diagnosis Very low (≤10th percentile) Low (>10th to 25th percentile) Medium (>25th to <75th percentile) High (75th to <90th percentile) Very high (≥90th percentile) 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Colon cancer A 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Lung cancer B 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Ovarian cancer C 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stomach cancer D JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 7/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 8. breast cancer (OR, 1.01; 95% CI, 0.94-1.09), melanoma (OR, 1.01; 95% CI, 0.89-1.15), or thyroid cancer (OR, 0.97; 95% CI, 0.86-1.09) (eFigure 5 in the Supplement). Discussion In this large, nested case-control study, we found that an elevated platelet count identified during a routine blood examination was associated with an increased risk of developing a range of solid tumors. The OR for the association was greatest for a diagnosis of cancer within 6 months of a blood test. For several cancer sites (lung, colon, stomach, esophagus, and kidney), a high platelet count was associated with a cancer diagnosis in the following 3 or more years. For lung cancer, a significant association was present 10 years before diagnosis. Long-term associations were also seen for kidney cancer and esophageal cancer. In contrast, for ovarian cancer, there was an association only in the 6 months before a diagnosis. Overall, given the transient nature of the association with platelet count, our findings suggest that an elevated platelet count detected through routine blood examination may be a consequence of the presence of cancer rather than being a risk factor for the disease. The physiologic basis for the association is not clear but may be multifactorial. Platelets are produced in the bone marrow in response to thrombopoietin, which is upregulated by interleukin 6, primarily produced in the liver.15 It is possible that the increase in platelet count is a response to circulating factors produced by the cancer cells or is a local response to inflammation induced by the cancer cell mass. Various mechanisms have been proposed to explain the association between high platelet count and cancer, Figure 2. Odds Ratios of Colon Cancer by Platelet Count Category and Time From Complete Blood Count Test to Cancer Diagnosis by Cancer Stage 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage I colon cancer A 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage II colon cancer B 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage III colon cancer C 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stage IV colon cancer D Very low (≤10th percentile) Low (>10th to 25th percentile) Medium (>25th to <75th percentile) High (75th to <90th percentile) Very high (≥90th percentile) JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 8/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 9. including the aggregation of cancer cells by platelets, increased extravasation or enhanced permeability of the basement membrane, and shielding cancer cells from immune attack in the bloodstream.16-18 Other possible mechanisms include iron deficiency, bleeding (among patients with colon cancer),19 abnormal platelet counts, and the infiltration of disseminated cancer cells in the bone marrow.20 Several studies have demonstrated an association between an elevated platelet count (thrombocytosis) and cancer risk. In general, these studies have either measured platelet counts at the time of diagnosis or had a short follow-up period subsequent to a CBC test.6-8 Pharmacoepidemiologic studies have further shown a lower incidence of certain cancer types among patients receiving platelet-inhibiting medications. For example, there is an established relationship between aspirin use (an antiplatelet drug) and decreased incidence of colon cancer.21-23 A protective effect of low-dose aspirin against ovarian cancer has also been suggested.24 Although antiplatelet medications inhibit platelet function as opposed to lowering the platelet count, the decreased incidence of cancer associated with aspirin use suggests the potential role functional platelets have in cancer risk. Our study findings suggest that individuals with a high platelet count might be candidates for investigation for the presence of an occult cancer after other nonmalignant causes of an elevated platelet count have been ruled out. Of individuals who had a cancer diagnosed within 6 months after the blood test, 19.5% had a very high platelet count (top 10 percentile). In a sensitivity analysis, we observed similar findings, with an association with some cancers among individuals with thrombocytosis. Giannakeas and Narod25 recently reported an association between thrombocytosis and incident cancers using the same data from the present study. The findings of the present study Figure 3. Odds Ratios of Cancer by Change in Platelet Count Category and Time From Complete Blood Count Test to Diagnosis 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Colon cancer A 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Lung cancer B 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Ovarian cancer C 10 1 0.5 Odds ratio Time to cancer diagnosis, mo 60-120 36-60 24-36 12-18 18-24 6-12 0-6 Stomach cancer D Large decrease (≤10th percentile) Small decrease (>10th to 25th percentile) No substantial change (>25th to <75th percentile) Small increase (75th to <90th percentile) Large increase (≥90th percentile) JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 9/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 10. suggest that platelet counts might be useful as a cancer screening tool alone or in combination with other cancer screening modalities, in particular spiral computed tomography for lung cancer, colonoscopy for colon cancer, and a cancer antigen 125 test or transvaginal ultrasonography for ovarian cancer. Novel screening tests that incorporate cell-free DNA and methylation signatures have shown promising results in identifying site-specific cancers.26 Platelet count could potentially be used as an affordable screening test to improve the predictive value of other screening modalities. Particular attention should be given to individuals who have an increasing platelet count (Figure 3). A relative increase in platelet count that exceeded 1.5 SDs (ie, ⱖ90th percentile) was associated with risk for many cancer types. The associations found in this study were based on a single marker (platelet count) as a 1-time measurement and as a change over time. In future studies, we plan to investigate the clinical utility of platelet count testing as a screening test. We will incorporate additional blood count elements in combination with platelet count in a model to maximize predictive ability. Limitations This study has limitations. The extent to which unmeasured confounders influenced the association of platelet count with cancer diagnosis is unclear. For lung cancer, we observed a prolonged association with elevated platelet count throughout the 10-year observation period (Figure 1). Smoking status was not available through administrative data sources. Platelet counts have been shown to differ among smokers and nonsmokers.27 Body mass index was also not available and has been shown to be associated with platelet counts among women.28 Additional variables that are likely to influence platelet count include alcohol consumption, family history, and genetics. These variables were not attainable in our study because of the limitations of administrative health data. However, given the transient association observed between platelet count and a cancer diagnosis in this study, it is unlikely that prolonged exposures would be attributed to these variables. Moreover, the secondary analysis of the change in platelet count in an individual (in whom confounders were presumed to be fixed) over time revealed findings comparable to those seen in the primary analysis. Conclusions In this nested case-control study, an elevated platelet count was associated with increased risk of cancer at several sites. The association was transient and attenuated with increasing time from CBC test to the date of the cancer diagnosis. Odds ratios were greatest for colon, lung, ovary, gastroesophageal, and kidney cancers. Our findings suggest that an elevated platelet count could potentially serve as a marker for the presence of some cancer types. ARTICLE INFORMATION Accepted for Publication: November 8, 2021. Published: January 11, 2022. doi:10.1001/jamanetworkopen.2021.41633 Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Giannakeas V et al. JAMA Network Open. Corresponding Author: Steven A. Narod, MD, Women’s College Research Institute, Women’s College Hospital, 76 Grenville St, Sixth Floor, Toronto, ON M5S 1B2, Canada (steven.narod@wchospital.ca). Author Affiliations: Women’s College Research Institute, Women’s College Hospital, Toronto, Ontario, Canada (Giannakeas, Kotsopoulos, Lipscombe, Akbari, Narod); Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada (Giannakeas, Kotsopoulos, Rosella, Brooks, Akbari, Narod); ICES, Toronto, Ontario, Canada (Giannakeas, Cheung, Lipscombe, Austin); Division of Hematology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada (Cheung); Department of Medicine, University of Toronto, Toronto, Ontario, Canada (Lipscombe); Division of Endocrinology, Women’s College Hospital, Toronto, Ontario, Canada (Lipscombe); Institute of Medical Science, University of Toronto, Toronto, JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 10/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 11. Ontario, Canada (Akbari, Narod); Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada (Austin). Author Contributions: Mr Giannakeas had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Giannakeas, Kotsopoulos, Rosella, Brooks, Akbari, Narod. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Giannakeas, Kotsopoulos, Brooks. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Giannakeas, Kotsopoulos, Rosella. Obtained funding: Giannakeas, Kotsopoulos. Administrative, technical, or material support: Giannakeas, Kotsopoulos, Akbari. Supervision: Kotsopoulos, Cheung, Brooks, Lipscombe, Narod. Conflict of Interest Disclosures: Mr Giannakeas reported receiving financial support through the Canadian Institutes of Health Research Frederick Banting and Charles Best Doctoral Research Award during the conduct of the study. Dr Lipscombe reported receiving grants from the Canadian Institutes of Health Research, personal fees from Diabetes Canada, and salary support from the University of Toronto Novo Nordisk Network for Healthy Populations outside the submitted work. Dr Austin reported receiving financial support through a Mid-Career Investigator Award from the Heart and Stroke Foundation. Dr Narod reported being a recipient of the tier I Canada Research Chair in Breast Cancer. Dr Kotsopoulos reported being a recipient of a tier II Canada Research Chair. No other disclosures were reported. Funding/Support: This work was supported by the Peter Gilgan Centre for Women’s Cancers at Women’s College Hospital in partnership with the Canadian Cancer Society and by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: The analysis, results, conclusions, and opinions herein are solely those of the authors and do not reflect those of the funding or data sources. No endorsement by ICES, the Ontario MOHLTC, the Canadian Institutes of Health Research, or Cancer Care Ontario is intended or should be inferred. Additional Information: Parts of the study data are based on data and/or information compiled and provided by the MOHLTC; the Canadian Institute for Health Information; Immigration, Refugees and Citizenship Canada; and Cancer Care Ontario. IQVIA Solutions Canada Inc allowed use of their Drug Information File. REFERENCES 1. Tefferi A. Approach to the patient with thrombocytosis. UpToDate. 2020. Accessed May 19, 2021. https://www. uptodate.com/contents/approach-to-the-patient-with-thrombocytosis 2. Segal JB, Moliterno AR. Platelet counts differ by sex, ethnicity, and age in the United States. Ann Epidemiol. 2006;16(2):123-130. doi:10.1016/j.annepidem.2005.06.052 3. Harrison CN, Bareford D, Butt N, et al; British Committee for Standards in Haematology. Guideline for investigation and management of adults and children presenting with a thrombocytosis. Br J Haematol. 2010;149 (3):352-375. doi:10.1111/j.1365-2141.2010.08122.x 4. Stone RL, Nick AM, McNeish IA, et al. Paraneoplastic thrombocytosis in ovarian cancer. N Engl J Med. 2012;366 (7):610-618. doi:10.1056/NEJMoa1110352 5. Schafer AI. Thrombocytosis. N Engl J Med. 2004;350(12):1211-1219. doi:10.1056/NEJMra035363 6. Bailey SE, Ukoumunne OC, Shephard EA, Hamilton W. Clinical relevance of thrombocytosis in primary care: a prospective cohort study of cancer incidence using English electronic medical records and cancer registry data. Br J Gen Pract. 2017;67(659):e405-e413. doi:10.3399/bjgp17X691109 7. Ankus E, Price SJ, Ukoumunne OC, Hamilton W, Bailey SER. Cancer incidence in patients with a high normal platelet count: a cohort study using primary care data. Fam Pract. 2018;35(6):671-675. doi:10.1093/fampra/ cmy018 8. Mounce LT, Hamilton W, Bailey SE. Cancer incidence following a high-normal platelet count: cohort study using electronic healthcare records from English primary care. Br J Gen Pract. 2020;70(698):e622-e628. doi:10.3399/ bjgp20X710957 JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 11/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 12. 9. Taucher S, Salat A, Gnant M, et al; Austrian Breast and Colorectal Cancer Study Group. Impact of pretreatment thrombocytosis on survival in primary breast cancer. Thromb Haemost. 2003;89(6):1098-1106. doi:10.1055/s- 0037-1613413 10. Bensalah K, Leray E, Fergelot P, et al. Prognostic value of thrombocytosis in renal cell carcinoma. J Urol. 2006;175(3, pt 1):859-863. doi:10.1016/S0022-5347(05)00526-4 11. Pedersen LM, Milman N. Prognostic significance of thrombocytosis in patients with primary lung cancer. Eur Respir J. 1996;9(9):1826-1830. doi:10.1183/09031936.96.09091826 12. Ishizuka M, Nagata H, Takagi K, Iwasaki Y, Kubota K. Preoperative thrombocytosis is associated with survival after surgery for colorectal cancer. J Surg Oncol. 2012;106(7):887-891. doi:10.1002/jso.23163 13. The Johns Hopkins ACG System, version 10.0. Technical reference guide. Accessed September 24 2020. https:// www.hopkinsacg.org/document/acg-system-version-10-0-technical-reference-guide/ 14. Robles SC, Marrett LD, Clarke EA, Risch HA. An application of capture-recapture methods to the estimation of completeness of cancer registration. J Clin Epidemiol. 1988;41(5):495-501. doi:10.1016/0895-4356(88)90052-2 15. Kaser A, Brandacher G, Steered W, et al. Interleukin-6 stimulates thrombopoiesis through thrombopoietin: role in inflammatory thrombocytosis. Blood. 2001;98(9):2720-2725. doi:10.1182/blood.V98.9.2720 16. Gay LJ, Felding-Habermann B. Contribution of platelets to tumour metastasis. Nat Rev Cancer. 2011;11(2): 123-134. doi:10.1038/nrc3004 17. Menter DG, Tucker SC, Kopetz S, Sood AK, Crissman JD, Honn KV. Platelets and cancer: a casual or causal relationship: revisited. Cancer Metastasis Rev. 2014;33(1):231-269. doi:10.1007/s10555-014-9498-0 18. Sylman JL, Mitrugno A, Tormoen GW, Wagner TH, Mallick P, McCarty OJT. Platelet count as a predictor of metastasis and venous thromboembolism in patients with cancer. Converg Sci Phys Oncol. 2017;3(2):023001. doi: 10.1088/2057-1739/aa6c05 19. Thompson MR, O’Leary DP, Flashman K, Asiimwe A, Ellis BG, Senapati A. Clinical assessment to determine the risk of bowel cancer using Symptoms, Age, Mass and Iron deficiency anaemia (SAMI). Br J Surg. 2017;104(10): 1393-1404. doi:10.1002/bjs.10573 20. George JN. Systemic malignancies as a cause of unexpected microangiopathic hemolytic anemia and thrombocytopenia. Oncology (Williston Park). 2011;25(10):908-914. 21. Cook NR, Lee IM, Zhang SM, Moorthy MV, Buring JE. Alternate-day, low-dose aspirin and cancer risk: long-term observational follow-up of a randomized trial. Ann Intern Med. 2013;159(2):77-85. doi:10.7326/0003-4819-159-2- 201307160-00002 22. Burn J, Sheth H, Elliott F, et al; CAPP2 Investigators. Cancer prevention with aspirin in hereditary colorectal cancer (Lynch syndrome), 10-year follow-up and registry-based 20-year data in the CAPP2 study: a double-blind, randomised, placebo-controlled trial. Lancet. 2020;395(10240):1855-1863. doi:10.1016/S0140-6736(20) 30366-4 23. Lin HD, Vora P, Soriano-Gabarró M, Chan KA. Association between low-dose aspirin use and colorectal cancer incidence in Taiwan. JAMA Netw Open. 2020;3(11):e2026494. doi:10.1001/jamanetworkopen.2020.26494 24. Barnard ME, Poole EM, Curhan GC, et al. Association of analgesic use with risk of ovarian cancer in the Nurses’ Health Studies. JAMA Oncol. 2018;4(12):1675-1682. doi:10.1001/jamaoncol.2018.4149 25. Giannakeas V, Narod SA. Incidence of cancer among adults with thrombocytosis in Ontario, Canada. JAMA Netw Open. 2021;4(8):e2120633. doi:10.1001/jamanetworkopen.2021.20633 26. Klein EA, Richards D, Cohn A, et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann Oncol. 2021;32(9):1167-1177. doi:10.1016/j.annonc.2021. 05.806 27. Green MS, Peled I, Najenson T. Gender differences in platelet count and its association with cigarette smoking in a large cohort in Israel. J Clin Epidemiol. 1992;45(1):77-84. doi:10.1016/0895-4356(92)90191-O 28. Samocha-Bonet D, Justo D, Rogowski O, et al. Platelet counts and platelet activation markers in obese subjects. Mediators Inflamm. 2008;2008:834153. doi:10.1155/2008/834153 SUPPLEMENT. eTable 1. Inclusion Table for CBC Tests eTable 2. Exclusion Table for Study Cohort eTable 3. Detailed Descriptive Table of Eligible Subjects, Measured at First Eligible Routine CBC Test (Cohort Entry Date) eTable 4. Descriptive Table of Matched Subjects (Primary Analysis), Variables Measured on Index CBC eTable 5. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 12/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 13. eTable 6. Odds Ratio of Any Solid Tumour Diagnosis (Excluding Liver) by Change in Platelet Count Category and Time From Cancer Diagnosis eTable 7. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Diagnosis. Select Cancer Sites eFigure 1. Study Design Criteria Among Matched Individuals eFigure 2. Age- and Sex-Specific Platelet Count Reference Distributions for Exposure Definition eFigure 3. Age- and Sex-Specific Platelet Count Reference Distributions for Secondary Exposure Definition eFigure 4. Odds Ratio of Cancer by Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 5. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 6. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites by Cancer Stage eFigure 7. Odds Ratio of Cancer by Platelet Count Category (Clinical Definition) and Time From Diagnosis JAMA Network Open | Oncology Analysis of Platelet Count and New Cancer Diagnosis Over a 10-Year Period JAMA Network Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 (Reprinted) January 11, 2022 13/13 Downloaded From: https://jamanetwork.com/ on 05/19/2022
  • 14. © 2022 Giannakeas V et al. JAMA Network Open. Supplementary Online Content Giannakeas V, Kotsopoulos J, Cheung MC, et al. Analysis of platelet count and new cancer diagnosis over a 10-year period. JAMA Netw Open. 2022;5(1):e2141633. doi:10.1001/jamanetworkopen.2021.41633 eTable 1. Inclusion Table for CBC Tests eTable 2. Exclusion Table for Study Cohort eTable 3. Detailed Descriptive Table of Eligible Subjects, Measured at First Eligible Routine CBC Test (Cohort Entry Date) eTable 4. Descriptive Table of Matched Subjects (Primary Analysis), Variables Measured on Index CBC eTable 5. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites eTable 6. Odds Ratio of Any Solid Tumour Diagnosis (Excluding Liver) by Change in Platelet Count Category and Time From Cancer Diagnosis eTable 7. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Diagnosis. Select Cancer Sites eFigure 1. Study Design Criteria Among Matched Individuals eFigure 2. Age- and Sex-Specific Platelet Count Reference Distributions for Exposure Definition eFigure 3. Age- and Sex-Specific Platelet Count Reference Distributions for Secondary Exposure Definition eFigure 4. Odds Ratio of Cancer by Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 5. Odds Ratio of Cancer by Change in Platelet Count Category and Time From Cancer Diagnosis. Additional Cancer Sites eFigure 6. Odds Ratio of Cancer by Platelet Count Category and Time From Diagnosis. Select Cancer Sites by Cancer Stage eFigure 7. Odds Ratio of Cancer by Platelet Count Category (Clinical Definition) and Time From Diagnosis This supplementary material has been provided by the authors to give readers additional information about their work.
  • 15. © 2022 Giannakeas V et al. JAMA Network Open. eTable 1. Inclusion table for CBC tests Frequency Percent Total CBC observations in accrual period 85,868,893 Exclusion 1. Priority of blood test not routine 14,033,973 16.34 2. Patient class not in community 15,163,171 17.66 3. Ordering practitioner not an MD 1,416,014 1.65 Eligible CBC observations for inclusion cohort 55,255,735 64.35
  • 16. © 2022 Giannakeas V et al. JAMA Network Open. eTable 2. Exclusion table for study cohort Frequency Percent Total CBC observations meeting inclusion criteria 55,255,735 Exclusion 1. Missing date of birth 34 0 2. Missing sex - 0 3. Age <18 on CBC date 2,151,138 3.89 4. Age >100 on CBC date 24,801 0.04 5. Death date prior to CBC date 13,661 0.02 6. OHIP ineligible on CBC date 55,740 0.1 7. Multiple CBC tests on same day 246,020 0.44 8. History of cancer in the Ontario Cancer Registry 5,144,653 9.31 Eligible CBC observations in study 47,373,668 85.73 Number of unique individuals 8,917,187
  • 17. © 2022 Giannakeas V et al. JAMA Network Open. eTable 3. Detailed descriptive table of eligible subjects, measured at first eligible routine CBC test (cohort entry date) Description Value Total Overall 8,917,187 General demographics Calendar year Mean (SD) 2011.1 (2.7) Median (IQR) 2011 (2009-2013) Sex Female 4,971,578 (55.8%) Male 3,945,609 (44.2%) Age Mean (SD) 47.0 (17.8) Median (IQR) 46.4 (32.5-59.5) Neighborhood income quintile 1 - Low 1,696,790 (19.0%) 2 1,761,615 (19.8%) 3 1,781,901 (20.0%) 4 1,853,508 (20.8%) 5 - High 1,784,803 (20.0%) Missing 38,570 (0.4%) Residence location Urban 8,084,848 (90.7%) Rural 820,419 (9.2%) Missing 11,920 (0.1%) Landed immigrant Non-immigrant 7,266,961 (81.5%) Recent immigrant (10 years or less) 742,701 (8.3%) Past immigrant (more than 10 years) 907,525 (10.2%) Time eligible in OHIP (years) Mean (SD) 11.6 (7.3) Median (IQR) 11.2 (5.3-17.4) Health service utilization Core primary care visits to GP/FP (2 years prior) Mean (SD) 2.8 (3.4) Median (IQR) 2 (1-3) 0 564,943 (6.3%) 1 - 2 4,903,886 (55.0%) 3 - 4 1,824,321 (20.5%) 5 - 9 1,285,001 (14.4%) 10+ 339,036 (3.8%) ED visits (2 years prior) 0 5,817,079 (65.2%) 1 1,672,061 (18.8%) 2 680,835 (7.6%) 3+ 747,212 (8.4%) Inpatient hospitalization episodes (2 years prior) 0 8,413,664 (94.4%) 1 396,207 (4.4%) 2 71,531 (0.8%) 3+ 35,785 (0.4%)
  • 18. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Rostered to family physician Yes 6,940,867 (77.8%) Up to date on cancer screening Pap smear (females age 18 to 70) Yes 2,583,203 (59.0%) Mammogram (females age 50 to 70) Yes 823,747 (58.2%) FOBT/sigmoidoscopy/colonoscopy (age 50 to 70) Yes 1,333,036 (47.8%) Comorbidities and chronic conditions Resource utilization band 0 - No or invalid diagnosis 279,791 (3.1%) 1 - Healthy user 464,794 (5.2%) 2 - Low user 1,653,945 (18.5%) 3 - Moderate user 4,736,581 (53.1%) 4 - High user 1,367,006 (15.3%) 5 - Very high user 415,070 (4.7%) Chronic conditions Asthma Yes 796,810 (8.9%) Congestive heart failure Yes 172,576 (1.9%) Inflammatory bowel disease Yes 29,509 (0.3%) Chronic obstructive pulmonary disease Yes 192,482 (2.2%) HIV Yes 11,242 (0.1%) Hypertension Yes 2,139,804 (24.0%) Dementia Yes 113,493 (1.3%) Diabetes Yes 666,477 (7.5%) Chronic rheumatoid arthritis Yes 74,781 (0.8%) Osteoarthritis Yes 869,722 (9.8%) Mood disorder Yes 1,093,308 (12.3%) Other mental health disorder Yes 356,591 (4.0%) Osteoporosis Yes 65,463 (0.7%) Renal disease Yes 88,520 (1.0%) Stroke Yes 62,149 (0.7%) Chronic coronary syndrome Yes 321,278 (3.6%) Acute myocardial infarction Yes 83,489 (0.9%) Medication use (age 66+) Concurrent medication use Number of concurrent medications Mean (SD) 3.7 (3.1) Median (IQR) 3 (1-6) Recent medication use Antiplatelet Nonsteroidal anti-inflammatory (ASA- based) Yes 67,300 (4.8%) Nonsteroidal anti-inflammatory (non-ASA- based) Yes 290,436 (20.8%) Adenosine disphosphonate inhibitor Yes 75,213 (5.4%) Cardiovascular Coronary vasodilator (nitrate) Yes 113,508 (8.1%) Beta blocker Yes 360,850 (25.9%)
  • 19. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Calcium channel blocker Yes 381,621 (27.4%) ACE inhibitor Yes 423,063 (30.4%) Angiotensin receptor agonist Yes 286,627 (20.6%) Lipid-lowering Statin Yes 623,653 (44.7%) Psychotropics Tricyclic antidepressant Yes 68,640 (4.9%) Selective serotonin reuptake inhibitor Yes 150,581 (10.8%) Complete blood count Hemoglobin concentration [g/L] Mean (SD) 139.5 (14.9) Median (IQR) 140 (130-150) Hematocrit ratio [L/L] Mean (SD) 0.4 (0.0) Median (IQR) 0.4 (0.4-0.4) Platelet count [109 cells/L] Mean (SD) 247.2 (64.5) Median (IQR) 241 (205-282) Observation period* Observation time (years) Mean (SD) 6.8 (3.0) Median (IQR) 7.3 (4.4-9.3) Number of routine CBC tests Mean (SD) 4.3 (6.3) Median (IQR) 3 (1-6) Incident cancer events (Ontario Cancer Registry) Any cancer diagnosis Yes 492,691 (5.5%) Solid tumour Yes 429,222 (4.8%) Colon Yes 51,521 (0.6%) Lung Yes 56,724 (0.6%) Breast (female only) Yes 65,721 (1.3%) Ovary (female only) Yes 7,661 (0.2%) Cervical (female only) Yes 3,494 (0.1%) Endometrial (female only) Yes 17,101 (0.3%) Prostate (male only) Yes 62,946 (1.6%) Thyroid Yes 21,478 (0.2%) Pancreas Yes 12,021 (0.1%) Stomach Yes 9,195 (0.1%) Kidney Yes 14,063 (0.2%) Bladder Yes 23,344 (0.3%) Liver Yes 7,696 (0.1%) Esophagus Yes 4,712 (0.1%) Other GI Yes 5,255 (0.1%) Brain Yes 5,724 (0.1%) Melanoma Yes 20,192 (0.2%) Head and neck Yes 13,363 (0.1%) Other solid tumour Yes 27,011 (0.3%) Hematologic tumour Yes 63,469 (0.7%)
  • 20. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Leukemia Yes 5,154 (0.1%) Lymphoma Yes 33,827 (0.4%) Multiple myeloma Yes 8,274 (0.1%) Other hematologic tumour Yes 16,214 (0.2%) *Period of observation is from first eligible CBC to the earliest date for: death, end of OHIP eligibility, or end of observation period (December 31 2018)
  • 21. © 2022 Giannakeas V et al. JAMA Network Open. eTable 4. Descriptive table of matched subjects (primary analysis), variables measured on index CBC. Description Value Total Case Control Standardiz ed Difference Overall 5,677,304 1,419,326 (25.0%) 4,257,978 (75.0%) General demographics Calendar year (cont.) Mean (SD) 2012.2 (2.6) 2012.2 (2.6) 2012.2 (2.6) Median (IQR) 2012 (2010-2014) 2012 (2010-2014) 2012 (2010-2014) Calendar year (cat.) 2007-2009 1,091,243 (19.2%) 272,743 (19.2%) 818,500 (19.2%) 0 2010-2012 2,020,199 (35.6%) 505,028 (35.6%) 1,515,171 (35.6%) 0 2013-2015 1,777,747 (31.3%) 444,546 (31.3%) 1,333,201 (31.3%) 0 2016-2017 788,115 (13.9%) 197,009 (13.9%) 591,106 (13.9%) 0 Sex Female 2,885,112 (50.8%) 721,278 (50.8%) 2,163,834 (50.8%) 0 Male 2,792,192 (49.2%) 698,048 (49.2%) 2,094,144 (49.2%) 0 Age (cont.) Mean (SD) 65.9 (13.6) 66.0 (13.6) 65.9 (13.6) 0 Median (IQR) 67.0 (57.4-75.9) 67.0 (57.4-76.0) 67.1 (57.4-75.9) Age (cat.) 18-29 66,388 (1.2%) 16,491 (1.2%) 49,897 (1.2%) 0 30-39 172,563 (3.0%) 43,121 (3.0%) 129,442 (3.0%) 0 40-49 468,186 (8.2%) 116,702 (8.2%) 351,484 (8.3%) 0 50-59 1,045,696 (18.4%) 260,604 (18.4%) 785,092 (18.4%) 0 60-69 1,604,177 (28.3%) 400,653 (28.2%) 1,203,524 (28.3%) 0 70-79 1,437,081 (25.3%) 359,683 (25.3%) 1,077,398 (25.3%) 0 80-89 786,528 (13.9%) 197,074 (13.9%) 589,454 (13.8%) 0 90+ 96,685 (1.7%) 24,998 (1.8%) 71,687 (1.7%) 0.01 Neighbourhood income quintile 1 - Low 1,012,719 (17.8%) 259,849 (18.3%) 752,870 (17.7%) 0.02 2 1,133,326 (20.0%) 285,773 (20.1%) 847,553 (19.9%) 0.01 3 1,133,021 (20.0%) 282,123 (19.9%) 850,898 (20.0%) 0 4 1,180,388 (20.8%) 291,594 (20.5%) 888,794 (20.9%) 0.01 5 - High 1,201,075 (21.2%) 295,892 (20.8%) 905,183 (21.3%) 0.01 Missing 16,775 (0.3%) 4,095 (0.3%) 12,680 (0.3%) Low-income senior (age 66+) Yes 468,941 (15.6%) 111,694 (14.9%) 357,247 (15.9%) 0.03 Residence location Urban 5,051,855 (89.0%) 1,256,231 (88.5%) 3,795,624 (89.1%) 0.02 Rural 620,875 (10.9%) 161,995 (11.4%) 458,880 (10.8%) 0.02 Missing 4,574 (0.1%) 1,100 (0.1%) 3,474 (0.1%) Recently living in Long-Term Care Yes 115,231 (2.0%) 20,896 (1.5%) 94,335 (2.2%) 0.06 Landed immigrant (cat.) Non-immigrant 5,024,782 (88.5%) 1,273,254 (89.7%) 3,751,528 (88.1%) 0.05 Recent immigrant (10 years or less) 164,498 (2.9%) 37,357 (2.6%) 127,141 (3.0%) 0.02 Past immigrant (more than 10 years) 488,024 (8.6%) 108,715 (7.7%) 379,309 (8.9%) 0.05 Ethnicity General Population 5,302,511 (93.4%) 1,344,594 (94.7%) 3,957,917 (93.0%) 0.07 Chinese 224,715 (4.0%) 49,099 (3.5%) 175,616 (4.1%) 0.03
  • 22. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference South Asian 150,078 (2.6%) 25,633 (1.8%) 124,445 (2.9%) 0.07 Time eligible in OHIP (years) Mean (SD) 20.6 (5.3) 20.5 (5.3) 20.6 (5.3) 0 Median (IQR) 21.5 (19.1-24.0) 21.5 (19.1-24.0) 21.5 (19.1-24.0) Health Services Utilization Any OHIP billings in the year prior Yes 5,598,849 (98.6%) 1,399,563 (98.6%) 4,199,286 (98.6%) 0 Any ODB records on/in the year prior (age 66+) Yes 2,917,066 (97.3%) 728,501 (97.2%) 2,188,565 (97.3%) 0.01 Physician Billings (2 years prior) Any core primary care visits to GP/FP Yes 5,510,087 (97.1%) 1,378,052 (97.1%) 4,132,035 (97.0%) 0 Core primary care visits to GP/FP (cont.) Mean (SD) 3.0 (3.7) 2.9 (3.6) 3.0 (3.8) 0.02 Median (IQR) 2 (1-4) 1 (1-3) 2 (1-4) Core primary care visits to GP/FP (cat.) 0 167,217 (2.9%) 41,274 (2.9%) 125,943 (3.0%) 0 1 - 2 3,198,252 (56.3%) 811,039 (57.1%) 2,387,213 (56.1%) 0.02 3 - 4 1,201,970 (21.2%) 299,530 (21.1%) 902,440 (21.2%) 0 5 - 9 846,965 (14.9%) 205,911 (14.5%) 641,054 (15.1%) 0.02 10+ 262,900 (4.6%) 61,572 (4.3%) 201,328 (4.7%) 0.02 Specialist visits (2 years prior) Dermatologist Yes 877,189 (15.5%) 224,227 (15.8%) 652,962 (15.3%) 0.01 General surgeon Yes 1,143,210 (20.1%) 298,490 (21.0%) 844,720 (19.8%) 0.03 Orthopedic surgeon Yes 797,962 (14.1%) 194,499 (13.7%) 603,463 (14.2%) 0.01 Geriatrician Yes 106,833 (1.9%) 23,349 (1.6%) 83,484 (2.0%) 0.02 Internal medicine specialist Yes 3,366,565 (59.3%) 836,840 (59.0%) 2,529,725 (59.4%) 0.01 Endocrinologist Yes 190,580 (3.4%) 49,507 (3.5%) 141,073 (3.3%) 0.01 Nephrologist Yes 155,201 (2.7%) 39,497 (2.8%) 115,704 (2.7%) 0 Neurologist Yes 504,083 (8.9%) 119,942 (8.5%) 384,141 (9.0%) 0.02 Psychiatrist Yes 317,703 (5.6%) 73,949 (5.2%) 243,754 (5.7%) 0.02 OBGYN Yes 498,801 (8.8%) 125,025 (8.8%) 373,776 (8.8%) 0 Geneticist Yes 5,598 (0.1%) 1,409 (0.1%) 4,189 (0.1%) 0 ENT Yes 688,708 (12.1%) 174,743 (12.3%) 513,965 (12.1%) 0.01 Urologist Yes 675,709 (11.9%) 186,833 (13.2%) 488,876 (11.5%) 0.05 Gastroenterologist Yes 546,089 (9.6%) 137,358 (9.7%) 408,731 (9.6%) 0 Oncologist Yes 14,865 (0.3%) 5,388 (0.4%) 9,477 (0.2%) 0.03 Respirologist Yes 378,174 (6.7%) 102,015 (7.2%) 276,159 (6.5%) 0.03 Rheumatologist Yes 278,374 (4.9%) 64,510 (4.5%) 213,864 (5.0%) 0.02 Cardiologist Yes 1,790,248 (31.5%) 438,440 (30.9%) 1,351,808 (31.7%) 0.02 Hematologist Yes 160,143 (2.8%) 52,001 (3.7%) 108,142 (2.5%) 0.06 Emergency and inpatient admissions (2 years prior) Any unscheduled ED visits Yes 2,374,409 (41.8%) 601,600 (42.4%) 1,772,809 (41.6%) 0.02 Unscheduled ED visits (cont.) Mean (SD) 1.0 (2.0) 1.0 (2.0) 1.0 (2.1) 0.01
  • 23. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Median (IQR) 0 (0-1) 0 (0-1) 0 (0-1) Unscheduled ED visits (cat.) 0 3,302,895 (58.2%) 817,726 (57.6%) 2,485,169 (58.4%) 0.02 1 1,175,254 (20.7%) 296,130 (20.9%) 879,124 (20.6%) 0.01 2 534,449 (9.4%) 135,339 (9.5%) 399,110 (9.4%) 0.01 3+ 664,706 (11.7%) 170,131 (12.0%) 494,575 (11.6%) 0.01 Any inpatient hospitalization episodes Yes 663,502 (11.7%) 169,981 (12.0%) 493,521 (11.6%) 0.01 Inpatient hospitalization episodes (cont.) Mean (SD) 0.2 (0.6) 0.2 (0.6) 0.2 (0.6) 0.01 Median (IQR) 0 (0-0) 0 (0-0) 0 (0-0) Inpatient hospitalization episodes (cat.) 0 5,013,802 (88.3%) 1,249,345 (88.0%) 3,764,457 (88.4%) 0.01 1 485,938 (8.6%) 123,488 (8.7%) 362,450 (8.5%) 0.01 2 115,033 (2.0%) 30,075 (2.1%) 84,958 (2.0%) 0.01 3+ 62,531 (1.1%) 16,418 (1.2%) 46,113 (1.1%) 0.01 Primary care provider Rostered to family physician Yes 4,868,959 (85.8%) 1,214,998 (85.6%) 3,653,961 (85.8%) 0.01 CBC test ordered by rostered family physician Yes 3,925,398 (69.1%) 974,826 (68.7%) 2,950,572 (69.3%) 0.01 Up to date on cancer screening Pap smear (females age 18 to 70) Yes 1,134,728 (64.2%) 276,006 (62.5%) 858,722 (64.7%) 0.05 Mammogram (females age 50 to 70) Yes 868,591 (68.3%) 209,221 (65.9%) 659,370 (69.1%) 0.07 FOBT/sigmoidoscopy/colonoscopy (age 50 to 70) Yes 1,721,945 (65.0%) 415,145 (62.8%) 1,306,800 (65.7%) 0.06 Comorbidities and chronic conditions Comorbidities Aggregate diagnosis groups (cont.) Mean (SD) 7.1 (3.7) 7.1 (3.7) 7.1 (3.7) 0 Median (IQR) 7 (4-10) 7 (4-10) 7 (4-10) Resource utilization band 0 - No or invalid diagnosis 33,804 (0.6%) 8,451 (0.6%) 25,353 (0.6%) 0 1 - Healthy user 70,952 (1.2%) 17,738 (1.2%) 53,214 (1.2%) 0 2 - Low user 415,228 (7.3%) 103,807 (7.3%) 311,421 (7.3%) 0 3 - Moderate user 3,050,604 (53.7%) 762,651 (53.7%) 2,287,953 (53.7%) 0 4 - High user 1,296,080 (22.8%) 324,020 (22.8%) 972,060 (22.8%) 0 5 - Very high user 810,636 (14.3%) 202,659 (14.3%) 607,977 (14.3%) 0 Charlson score (cont.) Mean (SD) 0.3 (0.9) 0.3 (0.9) 0.3 (0.8) 0.02 Median (IQR) 0 (0-0) 0 (0-0) 0 (0-0) Charlson comorbidities (cat.) 0 4,882,890 (86.0%) 1,214,684 (85.6%) 3,668,206 (86.1%) 0.02 1 385,248 (6.8%) 97,912 (6.9%) 287,336 (6.7%) 0.01 2 187,718 (3.3%) 48,646 (3.4%) 139,072 (3.3%) 0.01 3+ 221,448 (3.9%) 58,084 (4.1%) 163,364 (3.8%) 0.01 Chronic conditions Asthma Yes 537,653 (9.5%) 135,029 (9.5%) 402,624 (9.5%) 0
  • 24. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Congestive heart failure Yes 393,049 (6.9%) 101,252 (7.1%) 291,797 (6.9%) 0.01 Inflammatory bowel disease Yes 30,431 (0.5%) 7,410 (0.5%) 23,021 (0.5%) 0 Chronic obstructive pulmonary disease Yes 386,047 (6.8%) 119,986 (8.5%) 266,061 (6.2%) 0.08 HIV Yes 6,691 (0.1%) 1,885 (0.1%) 4,806 (0.1%) 0.01 Hypertension Yes 3,306,541 (58.2%) 830,089 (58.5%) 2,476,452 (58.2%) 0.01 Dementia Yes 223,044 (3.9%) 43,311 (3.1%) 179,733 (4.2%) 0.06 Diabetes Yes 1,238,703 (21.8%) 303,166 (21.4%) 935,537 (22.0%) 0.01 Chronic rheumatoid arthritis Yes 176,681 (3.1%) 41,026 (2.9%) 135,655 (3.2%) 0.02 Osteoarthritis Yes 1,210,650 (21.3%) 292,529 (20.6%) 918,121 (21.6%) 0.02 Mood disorder Yes 798,619 (14.1%) 191,338 (13.5%) 607,281 (14.3%) 0.02 Other mental health disorder Yes 305,798 (5.4%) 77,442 (5.5%) 228,356 (5.4%) 0 Osteoporosis Yes 103,466 (1.8%) 23,060 (1.6%) 80,406 (1.9%) 0.02 Renal disease Yes 250,967 (4.4%) 63,041 (4.4%) 187,926 (4.4%) 0 Stroke Yes 109,143 (1.9%) 25,536 (1.8%) 83,607 (2.0%) 0.01 Chronic coronary syndrome Yes 660,914 (11.6%) 159,315 (11.2%) 501,599 (11.8%) 0.02 Acute myocardial infarction Yes 139,154 (2.5%) 33,439 (2.4%) 105,715 (2.5%) 0.01 Medication use (age 66+) Concurrent medication use Number of concurrent medications being used (cont.) Mean (SD) 4.4 (3.2) 4.4 (3.2) 4.4 (3.2) 0.01 Median (IQR) 4 (2-6) 4 (2-6) 4 (2-6) Number of concurrent medications being used (cat.) 0 287,337 (9.6%) 72,453 (9.7%) 214,884 (9.6%) 0 1 - 4 1,418,824 (47.3%) 355,321 (47.4%) 1,063,503 (47.3%) 0 5 - 9 1,080,885 (36.0%) 269,166 (35.9%) 811,719 (36.1%) 0 10+ 212,374 (7.1%) 52,915 (7.1%) 159,459 (7.1%) 0 Recent medication use Antiplatelet Nonsteroidal anti-inflammatory (ASA- based) Yes 113,066 (3.8%) 26,908 (3.6%) 86,158 (3.8%) 0.01 Nonsteroidal anti-inflammatory (non- ASA-based) Yes 619,744 (20.7%) 151,206 (20.2%) 468,538 (20.8%) 0.02 Adenosine disphosphonate inhibitor Yes 218,919 (7.3%) 54,120 (7.2%) 164,799 (7.3%) 0 Cardiovascular Coronary vasodilator (nitrate) Yes 264,859 (8.8%) 64,685 (8.6%) 200,174 (8.9%) 0.01 Beta blocker Yes 903,836 (30.1%) 223,369 (29.8%) 680,467 (30.2%) 0.01 Calcium channel blocker Yes 937,762 (31.3%) 236,718 (31.6%) 701,044 (31.2%) 0.01 ACE inhibitor Yes 987,543 (32.9%) 246,558 (32.9%) 740,985 (32.9%) 0 Angiotensin receptor agonist Yes 754,041 (25.1%) 184,836 (24.6%) 569,205 (25.3%) 0.02 Lipid-lowering
  • 25. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Statin Yes 1,705,822 (56.9%) 414,870 (55.3%) 1,290,952 (57.4%) 0.04 Psychotropics Tricyclic antidepressant Yes 151,967 (5.1%) 37,807 (5.0%) 114,160 (5.1%) 0 Selective serotonin reuptake inhibitor Yes 351,210 (11.7%) 83,934 (11.2%) 267,276 (11.9%) 0.02 Platelet count (exposure definition) Continuous value for platelet count Mean (SD) 239.1 (73.2) 245.7 (89.1) 237.0 (66.9) 0.11 Median (IQR) 231 (193-274) 234 (194-282) 230 (193-272) Categorical platelet count (definition 1) 1 - Very low (≤10th percentile) 636,092 (11.2%) 170,382 (12.0%) 465,710 (10.9%) 0.03 2 - Low (>10 to 25th percentile) 878,655 (15.5%) 203,017 (14.3%) 675,638 (15.9%) 0.04 3 - Medium (>25 to <75th percentile) 2,756,889 (48.6%) 649,305 (45.7%) 2,107,584 (49.5%) 0.08 4 - High (75 to <90th percentile) 823,871 (14.5%) 209,023 (14.7%) 614,848 (14.4%) 0.01 5 - Very high (≥90th percentile) 581,797 (10.2%) 187,599 (13.2%) 394,198 (9.3%) 0.13 Categorical platelet count (definition 2) 1 - Thrombocytopenia (<150) 354,236 (6.2%) 103,239 (7.3%) 250,997 (5.9%) 0.06 2 - Low normal (150 to 33.3rd percentile) 1,346,199 (23.7%) 312,501 (22.0%) 1,033,698 (24.3%) 0.05 3 - Medium normal (>33.4 to <66.6th percentile) 2,602,504 (45.8%) 614,613 (43.3%) 1,987,891 (46.7%) 0.07 4 - High normal (66.6th percentile to 450) 1,308,241 (23.0%) 356,063 (25.1%) 952,178 (22.4%) 0.06 5 - Thrombocytosis (>450) 66,124 (1.2%) 32,910 (2.3%) 33,214 (0.8%) 0.12 Observation period Years from index CBC to outcome (cont.) Mean (SD) 2.4 (2.1) 2.4 (2.1) Median (IQR) 1.8 (0.7-3.5) 1.8 (0.7-3.5) Years from index CBC to outcome (cat.) 0-6 months 273,042 (19.2%) 273,042 (19.2%) 6-12 months 177,460 (12.5%) 177,460 (12.5%) 12-18 months 170,915 (12.0%) 170,915 (12.0%) 18-24 months 152,076 (10.7%) 152,076 (10.7%) 2-3 years 220,742 (15.6%) 220,742 (15.6%) 3-5 years 242,367 (17.1%) 242,367 (17.1%) 5-10 years 182,724 (12.9%) 182,724 (12.9%) Incident cancer events (Ontario Cancer Registry) Any cancer diagnosis in the OCR Yes 1,419,326 (25.0%) 1,419,326 (100.0%) Solid tumour Yes 1,219,140 (21.5%) 1,219,140 (85.9%) Colon Yes 143,349 (2.5%) 143,349 (10.1%) Lung Yes 167,823 (3.0%) 167,823 (11.8%) Breast (female only) Yes 181,706 (6.3%) 181,706 (25.2%) Ovary (female only) Yes 21,203 (0.7%) 21,203 (2.9%) Cervical (female only) Yes 7,923 (0.3%) 7,923 (1.1%) Endometrial (female only) Yes 48,759 (1.7%) 48,759 (6.8%)
  • 26. © 2022 Giannakeas V et al. JAMA Network Open. Description Value Total Case Control Standardiz ed Difference Prostate (male only) Yes 174,026 (6.2%) 174,026 (24.9%) Thyroid Yes 58,931 (1.0%) 58,931 (4.2%) Pancreas Yes 36,861 (0.6%) 36,861 (2.6%) Stomach Yes 27,590 (0.5%) 27,590 (1.9%) Kidney Yes 41,248 (0.7%) 41,248 (2.9%) Bladder Yes 70,164 (1.2%) 70,164 (4.9%) Liver Yes 24,809 (0.4%) 24,809 (1.7%) Esophagus Yes 13,351 (0.2%) 13,351 (0.9%) Other GI Yes 15,674 (0.3%) 15,674 (1.1%) Brain Yes 15,363 (0.3%) 15,363 (1.1%) Melanoma Yes 56,460 (1.0%) 56,460 (4.0%) Head and neck Yes 36,705 (0.6%) 36,705 (2.6%) Other solid tumour Yes 77,195 (1.4%) 77,195 (5.4%) Hematologic tumour Yes 200,186 (3.5%) 200,186 (14.1%) Leukemia Yes 15,699 (0.3%) 15,699 (1.1%) Lymphoma Yes 101,343 (1.8%) 101,343 (7.1%) Multiple myeloma Yes 26,882 (0.5%) 26,882 (1.9%) Other hematologic tumour Yes 56,262 (1.0%) 56,262 (4.0%)
  • 27. © 2022 Giannakeas V et al. JAMA Network Open. eTable 5. Odds ratio of cancer by platelet count category and time from diagnosis. Select cancer sites. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Very low (≤10th percentile) 1,820 (5.83%) 10,092 (10.77%) 0.73 (0.69- 0.77) <.0001 2,148 (6.61%) 11,045 (11.34%) 0.79 (0.75- 0.83) <.0001 2 - Low (>10 to 25th percentile) 2,688 (8.60%) 14,722 (15.71%) 0.74 (0.70- 0.77) <.0001 2,748 (8.46%) 15,224 (15.63%) 0.74 (0.70- 0.77) <.0001 3 - Medium (>25 to <75th percentile) 11,393 (36.47%) 46,289 (49.39%) 1.00 [Reference] 11,595 (35.70%) 47,505 (48.76%) 1.00 [Reference] 4 - High (75 to <90th percentile) 5,719 (18.31%) 13,688 (14.60%) 1.71 (1.65- 1.78) <.0001 6,005 (18.49%) 14,299 (14.68%) 1.73 (1.67- 1.80) <.0001 5 - Very high (≥90th percentile) 9,621 (30.80%) 8,932 (9.53%) 4.38 (4.22- 4.54) <.0001 9,979 (30.73%) 9,352 (9.60%) 4.37 (4.22- 4.53) <.0001 6-12 months 1 - Very low (≤10th percentile) 1,473 (8.32%) 5,754 (10.84%) 0.86 (0.81- 0.91) <.0001 1,869 (8.76%) 7,291 (11.39%) 0.86 (0.81- 0.90) <.0001 2 - Low (>10 to 25th percentile) 2,134 (12.06%) 8,385 (15.80%) 0.86 (0.81- 0.90) <.0001 2,489 (11.67%) 10,007 (15.63%) 0.83 (0.79- 0.87) <.0001 3 - Medium (>25 to <75th percentile) 7,787 (44.01%) 26,259 (49.47%) 1.00 [Reference] 9,447 (44.28%) 31,548 (49.29%) 1.00 [Reference] 4 - High (75 to <90th percentile) 3,219 (18.19%) 7,755 (14.61%) 1.40 (1.33- 1.47) <.0001 3,630 (17.01%) 9,171 (14.33%) 1.32 (1.26- 1.38) <.0001 5 - Very high (≥90th percentile) 3,082 (17.42%) 4,932 (9.29%) 2.11 (2.01- 2.23) <.0001 3,902 (18.29%) 5,994 (9.36%) 2.18 (2.08- 2.29) <.0001 12-18 months 1 - Very low (≤10th percentile) 1,643 (9.64%) 5,487 (10.74%) 0.95 (0.90- 1.01) 0.1268 1,922 (9.46%) 6,691 (10.98%) 0.93 (0.88- 0.98) 0.0087 2 - Low (>10 to 25th percentile) 2,357 (13.83%) 8,179 (16.00%) 0.92 (0.87- 0.96) 0.001 2,562 (12.61%) 9,760 (16.01%) 0.85 (0.81- 0.89) <.0001 3 - Medium (>25 to <75th percentile) 7,977 (46.82%) 25,404 (49.70%) 1.00 [Reference] 9,241 (45.49%) 29,890 (49.04%) 1.00 [Reference] 4 - High (75 to <90th percentile) 2,804 (16.46%) 7,439 (14.55%) 1.20 (1.14- 1.26) <.0001 3,327 (16.38%) 8,785 (14.41%) 1.22 (1.17- 1.28) <.0001 5 - Very high (≥90th percentile) 2,256 (13.24%) 4,602 (9.00%) 1.56 (1.48- 1.66) <.0001 3,264 (16.07%) 5,822 (9.55%) 1.82 (1.73- 1.91) <.0001 18-24 months 1 - Very low (≤10th percentile) 1,546 (10.38%) 4,882 (10.93%) 0.99 (0.93- 1.06) 0.7936 1,828 (9.87%) 6,246 (11.25%) 0.94 (0.89- 1.00) 0.0351 2 - Low (>10 to 25th percentile) 2,169 (14.57%) 7,192 (16.10%) 0.94 (0.89- 1.00) 0.0401 2,387 (12.89%) 8,929 (16.08%) 0.86 (0.81- 0.90) <.0001 3 - Medium (>25 to <75th percentile) 7,067 (47.46%) 22,125 (49.53%) 1.00 [Reference] 8,444 (45.61%) 27,132 (48.85%) 1.00 [Reference] 4 - High (75 to <90th percentile) 2,342 (15.73%) 6,463 (14.47%) 1.14 (1.08- 1.20) <.0001 3,080 (16.64%) 8,085 (14.56%) 1.23 (1.17- 1.29) <.0001
  • 28. © 2022 Giannakeas V et al. JAMA Network Open. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 5 - Very high (≥90th percentile) 1,765 (11.85%) 4,005 (8.97%) 1.38 (1.29- 1.47) <.0001 2,774 (14.98%) 5,147 (9.27%) 1.74 (1.65- 1.83) <.0001 2-3 years 1 - Very low (≤10th percentile) 2,276 (10.50%) 6,963 (10.71%) 1.01 (0.96- 1.07) 0.6282 2,516 (9.62%) 8,589 (10.95%) 0.94 (0.90- 0.99) 0.0229 2 - Low (>10 to 25th percentile) 3,357 (15.49%) 10,309 (15.86%) 1.01 (0.96- 1.05) 0.7113 3,504 (13.40%) 12,509 (15.94%) 0.90 (0.86- 0.94) <.0001 3 - Medium (>25 to <75th percentile) 10,482 (48.37%) 32,488 (49.97%) 1.00 [Reference] 12,147 (46.44%) 39,114 (49.84%) 1.00 [Reference] 4 - High (75 to <90th percentile) 3,345 (15.44%) 9,447 (14.53%) 1.10 (1.05- 1.15) <.0001 4,264 (16.30%) 11,172 (14.24%) 1.23 (1.18- 1.28) <.0001 5 - Very high (≥90th percentile) 2,210 (10.20%) 5,803 (8.93%) 1.18 (1.12- 1.25) <.0001 3,727 (14.25%) 7,090 (9.03%) 1.70 (1.62- 1.78) <.0001 3-5 years 1 - Very low (≤10th percentile) 2,622 (11.13%) 7,716 (10.92%) 1.04 (0.99- 1.09) 0.1338 2,648 (9.39%) 9,235 (10.92%) 0.91 (0.87- 0.96) 0.0002 2 - Low (>10 to 25th percentile) 3,672 (15.59%) 11,431 (16.18%) 0.98 (0.94- 1.02) 0.3889 3,832 (13.59%) 13,687 (16.18%) 0.89 (0.86- 0.93) <.0001 3 - Medium (>25 to <75th percentile) 11,521 (48.91%) 35,208 (49.82%) 1.00 [Reference] 13,184 (46.75%) 42,028 (49.67%) 1.00 [Reference] 4 - High (75 to <90th percentile) 3,467 (14.72%) 10,153 (14.37%) 1.04 (1.00- 1.09) 0.0569 4,657 (16.51%) 12,077 (14.27%) 1.23 (1.19- 1.28) <.0001 5 - Very high (≥90th percentile) 2,273 (9.65%) 6,157 (8.71%) 1.13 (1.07- 1.19) <.0001 3,881 (13.76%) 7,579 (8.96%) 1.64 (1.57- 1.71) <.0001 5-10 years 1 - Very low (≤10th percentile) 1,833 (10.62%) 5,456 (10.54%) 1.03 (0.97- 1.09) 0.3722 1,925 (9.25%) 6,646 (10.64%) 0.92 (0.87- 0.97) 0.0037 2 - Low (>10 to 25th percentile) 2,725 (15.79%) 8,183 (15.80%) 1.02 (0.97- 1.07) 0.4886 2,752 (13.22%) 10,169 (16.28%) 0.86 (0.82- 0.90) <.0001 3 - Medium (>25 to <75th percentile) 8,494 (49.21%) 25,963 (50.14%) 1.00 [Reference] 9,767 (46.91%) 31,089 (49.77%) 1.00 [Reference] 4 - High (75 to <90th percentile) 2,551 (14.78%) 7,502 (14.49%) 1.04 (0.99- 1.09) 0.1368 3,549 (17.04%) 8,913 (14.27%) 1.27 (1.21- 1.33) <.0001 5 - Very high (≥90th percentile) 1,659 (9.61%) 4,682 (9.04%) 1.08 (1.02- 1.15) 0.0101 2,829 (13.59%) 5,649 (9.04%) 1.60 (1.52- 1.69) <.0001
  • 29. © 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Very low (≤10th percentile) 243 (5.48%) 1,392 (10.46%) 0.72 (0.62- 0.84) <.0001 414 (7.37%) 1,898 (11.26%) 0.91 (0.81- 1.02) 0.1017 2 - Low (>10 to 25th percentile) 350 (7.89%) 2,077 (15.61%) 0.69 (0.61- 0.78) <.0001 503 (8.95%) 2,598 (15.41%) 0.79 (0.71- 0.88) <.0001 3 - Medium (>25 to <75th percentile) 1,615 (36.42%) 6,666 (50.11%) 1.00 [Reference] 2,039 (36.29%) 8,332 (49.44%) 1.00 [Reference] 4 - High (75 to <90th percentile) 830 (18.72%) 1,896 (14.25%) 1.82 (1.65- 2.01) <.0001 1,058 (18.83%) 2,452 (14.55%) 1.79 (1.64- 1.95) <.0001 5 - Very high (≥90th percentile) 1,396 (31.48%) 1,271 (9.55%) 4.62 (4.19- 5.09) <.0001 1,604 (28.55%) 1,574 (9.34%) 4.27 (3.91- 4.66) <.0001 6-12 months 1 - Very low (≤10th percentile) 233 (9.17%) 804 (10.54%) 0.88 (0.75- 1.04) 0.1262 336 (9.47%) 1,155 (10.85%) 0.95 (0.83- 1.09) 0.498 2 - Low (>10 to 25th percentile) 344 (13.53%) 1,188 (15.58%) 0.88 (0.77- 1.01) 0.0695 513 (14.45%) 1,723 (16.18%) 0.97 (0.87- 1.09) 0.6389 3 - Medium (>25 to <75th percentile) 1,242 (48.86%) 3,787 (49.66%) 1.00 [Reference] 1,619 (45.62%) 5,299 (49.77%) 1.00 [Reference] 4 - High (75 to <90th percentile) 435 (17.11%) 1,091 (14.31%) 1.21 (1.07- 1.38) 0.0031 612 (17.24%) 1,529 (14.36%) 1.31 (1.18- 1.46) <.0001 5 - Very high (≥90th percentile) 288 (11.33%) 756 (9.91%) 1.16 (1.00- 1.35) 0.0497 469 (13.21%) 941 (8.84%) 1.64 (1.44- 1.85) <.0001 12-18 months 1 - Very low (≤10th percentile) 218 (8.93%) 758 (10.35%) 0.84 (0.72- 0.99) 0.0416 384 (11.73%) 1,072 (10.92%) 1.14 (1.00- 1.29) 0.0546 2 - Low (>10 to 25th percentile) 338 (13.84%) 1,145 (15.63%) 0.86 (0.75- 0.99) 0.0352 481 (14.70%) 1,636 (16.66%) 0.93 (0.83- 1.05) 0.2399 3 - Medium (>25 to <75th percentile) 1,228 (50.29%) 3,597 (49.10%) 1.00 [Reference] 1,531 (46.78%) 4,856 (49.46%) 1.00 [Reference] 4 - High (75 to <90th percentile) 380 (15.56%) 1,122 (15.32%) 0.99 (0.87- 1.14) 0.9202 498 (15.22%) 1,353 (13.78%) 1.17 (1.04- 1.31) 0.0099 5 - Very high (≥90th percentile) 278 (11.38%) 704 (9.61%) 1.16 (0.99- 1.35) 0.0623 379 (11.58%) 902 (9.19%) 1.34 (1.17- 1.53) <.0001 18-24 months 1 - Very low (≤10th percentile) 222 (10.11%) 654 (9.93%) 1.02 (0.87- 1.21) 0.7721 313 (10.34%) 1,001 (11.02%) 0.95 (0.83- 1.09) 0.47 2 - Low (>10 to 25th percentile) 355 (16.17%) 998 (15.16%) 1.07 (0.93- 1.23) 0.3159 431 (14.24%) 1,450 (15.97%) 0.90 (0.80- 1.02) 0.1096 3 - Medium (>25 to <75th percentile) 1,105 (50.34%) 3,333 (50.62%) 1.00 [Reference] 1,480 (48.89%) 4,507 (49.63%) 1.00 [Reference] 4 - High (75 to <90th percentile) 298 (13.58%) 941 (14.29%) 0.95 (0.82- 1.11) 0.5358 474 (15.66%) 1,270 (13.99%) 1.14 (1.01- 1.28) 0.039
  • 30. © 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 5 - Very high (≥90th percentile) 215 (9.79%) 659 (10.01%) 0.98 (0.83- 1.16) 0.8472 329 (10.87%) 853 (9.39%) 1.18 (1.02- 1.35) 0.0248 2-3 years 1 - Very low (≤10th percentile) 327 (10.06%) 1,017 (10.42%) 0.96 (0.84- 1.10) 0.5943 482 (11.47%) 1,345 (10.67%) 1.14 (1.01- 1.28) 0.0292 2 - Low (>10 to 25th percentile) 511 (15.71%) 1,518 (15.56%) 1.01 (0.90- 1.13) 0.8836 656 (15.62%) 2,018 (16.01%) 1.03 (0.93- 1.14) 0.5571 3 - Medium (>25 to <75th percentile) 1,628 (50.06%) 4,879 (50.01%) 1.00 [Reference] 1,971 (46.92%) 6,262 (49.69%) 1.00 [Reference] 4 - High (75 to <90th percentile) 506 (15.56%) 1,398 (14.33%) 1.09 (0.97- 1.22) 0.1662 629 (14.97%) 1,852 (14.69%) 1.08 (0.97- 1.20) 0.1452 5 - Very high (≥90th percentile) 280 (8.61%) 944 (9.68%) 0.89 (0.77- 1.03) 0.1055 463 (11.02%) 1,126 (8.93%) 1.31 (1.16- 1.47) <.0001 3-5 years 1 - Very low (≤10th percentile) 374 (10.33%) 1,201 (11.06%) 0.91 (0.80- 1.04) 0.1559 506 (11.10%) 1,531 (11.19%) 1.01 (0.91- 1.13) 0.8204 2 - Low (>10 to 25th percentile) 560 (15.47%) 1,839 (16.93%) 0.89 (0.80- 0.99) 0.0379 730 (16.01%) 2,226 (16.27%) 1.01 (0.91- 1.11) 0.9072 3 - Medium (>25 to <75th percentile) 1,819 (50.23%) 5,321 (48.98%) 1.00 [Reference] 2,223 (48.75%) 6,818 (49.84%) 1.00 [Reference] 4 - High (75 to <90th percentile) 539 (14.89%) 1,505 (13.85%) 1.05 (0.94- 1.17) 0.4019 618 (13.55%) 1,920 (14.04%) 0.99 (0.89- 1.09) 0.817 5 - Very high (≥90th percentile) 329 (9.09%) 997 (9.18%) 0.97 (0.84- 1.11) 0.6412 483 (10.59%) 1,185 (8.66%) 1.25 (1.11- 1.41) 0.0002 5-10 years 1 - Very low (≤10th percentile) 272 (10.01%) 898 (11.02%) 0.90 (0.77- 1.04) 0.1524 393 (11.69%) 1,083 (10.74%) 1.12 (0.98- 1.27) 0.0845 2 - Low (>10 to 25th percentile) 423 (15.57%) 1,324 (16.24%) 0.95 (0.83- 1.07) 0.3873 541 (16.09%) 1,636 (16.22%) 1.02 (0.91- 1.14) 0.7301 3 - Medium (>25 to <75th percentile) 1,372 (50.50%) 4,064 (49.86%) 1.00 [Reference] 1,630 (48.48%) 5,028 (49.85%) 1.00 [Reference] 4 - High (75 to <90th percentile) 385 (14.17%) 1,162 (14.26%) 0.98 (0.86- 1.12) 0.8008 481 (14.31%) 1,449 (14.37%) 1.02 (0.91- 1.15) 0.6883 5 - Very high (≥90th percentile) 265 (9.75%) 703 (8.62%) 1.12 (0.96- 1.31) 0.1539 317 (9.43%) 890 (8.82%) 1.10 (0.96- 1.26) 0.189
  • 31. © 2022 Giannakeas V et al. JAMA Network Open. eTable 6. Odds ratio of any solid tumour diagnosis (excluding liver) by change in platelet count category and time from cancer diagnosis. Time from cancer diagnosis Change in Platelet Count Percentile Value N, % (Case) N, % (Control) OR (95% CI) P-Value 0-6 months 1 - Large decrease (≤10th percentile) 8,494 (9.4%) 28,643 (10.6%) 1.08 (1.05- 1.11) <.0001 2 - Small decrease (>10 to 25th percentile) 10,990 (12.2%) 42,253 (15.6%) 0.94 (0.92- 0.96) <.0001 3 - No significant change (>25 to <75th percentile) 36,283 (40.1%) 131,443 (48.5%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 14,887 (16.5%) 41,343 (15.2%) 1.31 (1.28- 1.34) <.0001 5 - Large increase (≥90th percentile) 19,750 (21.8%) 27,530 (10.2%) 2.62 (2.56- 2.68) <.0001 6-12 months 1 - Large decrease (≤10th percentile) 7,020 (10.3%) 21,563 (10.6%) 1.05 (1.02- 1.09) 0.0008 2 - Small decrease (>10 to 25th percentile) 9,790 (14.4%) 31,848 (15.6%) 0.99 (0.97- 1.02) 0.5287 3 - No significant change (>25 to <75th percentile) 30,695 (45.2%) 99,042 (48.7%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 11,268 (16.6%) 31,008 (15.2%) 1.18 (1.15- 1.21) <.0001 5 - Large increase (≥90th percentile) 9,081 (13.4%) 20,101 (9.9%) 1.46 (1.42- 1.51) <.0001 1-2 years 1 - Large decrease (≤10th percentile) 10,404 (10.3%) 30,958 (10.3%) 1.03 (1.01- 1.06) 0.0113 2 - Small decrease (>10 to 25th percentile) 15,050 (15.0%) 47,148 (15.6%) 0.98 (0.96- 1.00) 0.0535 3 - No significant change (>25 to <75th percentile) 48,403 (48.1%) 148,583 (49.2%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 15,763 (15.7%) 46,051 (15.3%) 1.05 (1.03- 1.07) <.0001 5 - Large increase (≥90th percentile) 11,024 (11.0%) 29,192 (9.7%) 1.16 (1.13- 1.19) <.0001 2-5 years 1 - Large decrease (≤10th percentile) 12,076 (10.1%) 36,007 (10.0%) 1.02 (1.00- 1.04) 0.1094 2 - Small decrease (>10 to 25th percentile) 18,452 (15.4%) 55,580 (15.4%) 1.01 (0.99- 1.03) 0.4105 3 - No significant change (>25 to <75th percentile) 58,748 (48.9%) 178,385 (49.5%) 1.00 [Reference]
  • 32. © 2022 Giannakeas V et al. JAMA Network Open. Time from cancer diagnosis Change in Platelet Count Percentile Value N, % (Case) N, % (Control) OR (95% CI) P-Value 4 - Small increase (75 to <90th percentile) 18,538 (15.4%) 55,595 (15.4%) 1.01 (0.99- 1.03) 0.1875 5 - Large increase (≥90th percentile) 12,229 (10.2%) 34,562 (9.6%) 1.08 (1.05- 1.10) <.0001 5-10 years 1 - Large decrease (≤10th percentile) 6,539 (11.5%) 19,425 (11.4%) 1.01 (0.98- 1.04) 0.4869 2 - Small decrease (>10 to 25th percentile) 10,002 (17.6%) 30,704 (18.1%) 0.98 (0.95- 1.00) 0.102 3 - No significant change (>25 to <75th percentile) 28,116 (49.6%) 84,446 (49.7%) 1.00 [Reference] 4 - Small increase (75 to <90th percentile) 7,399 (13.1%) 22,136 (13.0%) 1.00 (0.97- 1.03) 0.78 5 - Large increase (≥90th percentile) 4,615 (8.1%) 13,302 (7.8%) 1.04 (1.01- 1.08) 0.0239
  • 33. © 2022 Giannakeas V et al. JAMA Network Open. eTable 7. Odds ratio of cancer by change in platelet count category and time from diagnosis. Select cancer sites. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Large decrease (≤10th pctl) 794 (6.59%) 3,660 (10.13%) 1.02 (0.93- 1.11) 0.7074 1,335 (9.72%) 4,591 (11.14%) 1.33 (1.24- 1.43) <.0001 2 - Small decrease (>10 to 25th pctl) 999 (8.29%) 5,645 (15.62%) 0.84 (0.77- 0.90) <.0001 1,332 (9.70%) 6,348 (15.40%) 0.96 (0.89- 1.02) 0.1953 3 - No significant change (>25 to <75th pctl) 3,792 (31.48%) 17,663 (48.88%) 1.00 [Reference] 4,330 (31.52%) 19,677 (47.74%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 2,169 (18.01%) 5,499 (15.22%) 1.87 (1.76- 1.99) <.0001 2,314 (16.84%) 6,299 (15.28%) 1.70 (1.61- 1.81) <.0001 5 - Large increase (≥90th pctl) 4,292 (35.63%) 3,671 (10.16%) 5.52 (5.21- 5.86) <.0001 4,427 (32.22%) 4,299 (10.43%) 4.77 (4.51- 5.04) <.0001 6-12 months 1 - Large decrease (≤10th pctl) 738 (8.99%) 2,572 (10.45%) 1.05 (0.96- 1.15) 0.3158 1,196 (11.34%) 3,336 (10.54%) 1.29 (1.20- 1.39) <.0001 2 - Small decrease (>10 to 25th pctl) 906 (11.04%) 3,839 (15.59%) 0.86 (0.79- 0.93) 0.0003 1,420 (13.46%) 4,930 (15.58%) 1.03 (0.96- 1.10) 0.4622 3 - No significant change (>25 to <75th pctl) 3,317 (40.42%) 12,045 (48.92%) 1.00 [Reference] 4,313 (40.89%) 15,368 (48.57%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,584 (19.30%) 3,764 (15.29%) 1.54 (1.43- 1.65) <.0001 1,783 (16.91%) 4,831 (15.27%) 1.32 (1.24- 1.41) <.0001 5 - Large increase (≥90th pctl) 1,662 (20.25%) 2,401 (9.75%) 2.55 (2.37- 2.75) <.0001 1,835 (17.40%) 3,176 (10.04%) 2.07 (1.93- 2.21) <.0001 12-18 months 1 - Large decrease (≤10th pctl) 793 (9.83%) 2,506 (10.35%) 1.04 (0.95- 1.14) 0.3568 1,301 (12.91%) 3,323 (10.99%) 1.37 (1.27- 1.47) <.0001 2 - Small decrease (>10 to 25th pctl) 1,114 (13.81%) 3,774 (15.59%) 0.97 (0.90- 1.05) 0.4754 1,523 (15.11%) 4,730 (15.64%) 1.11 (1.04- 1.19) 0.0016 3 - No significant change (>25 to <75th pctl) 3,630 (44.99%) 11,959 (49.40%) 1.00 [Reference] 4,242 (42.09%) 14,665 (48.50%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,413 (17.51%) 3,729 (15.40%) 1.25 (1.16- 1.34) <.0001 1,562 (15.50%) 4,535 (15.00%) 1.19 (1.12- 1.28) <.0001 5 - Large increase (≥90th pctl) 1,119 (13.87%) 2,239 (9.25%) 1.65 (1.52- 1.79) <.0001 1,451 (14.40%) 2,984 (9.87%) 1.70 (1.58- 1.82) <.0001 18-24 months 1 - Large decrease (≤10th pctl) 693 (10.28%) 2,029 (10.03%) 1.11 (1.01- 1.22) 0.0289 1,153 (12.88%) 2,877 (10.71%) 1.34 (1.24- 1.44) <.0001 2 - Small decrease (>10 to 25th pctl) 955 (14.16%) 3,180 (15.72%) 0.97 (0.90- 1.06) 0.5415 1,301 (14.53%) 4,194 (15.62%) 1.03 (0.96- 1.10) 0.4549 3 - No significant change (>25 to <75th pctl) 3,115 (46.20%) 10,125 (50.06%) 1.00 [Reference] 3,944 (44.06%) 13,051 (48.60%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,169 (17.34%) 3,038 (15.02%) 1.25 (1.16- 1.35) <.0001 1,390 (15.53%) 4,059 (15.11%) 1.14 (1.06- 1.22) 0.0004
  • 34. © 2022 Giannakeas V et al. JAMA Network Open. Colon Lung Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P- value N, % (Case) N, % (Control) OR (95% CI) P- value 5 - Large increase (≥90th pctl) 810 (12.01%) 1,854 (9.17%) 1.42 (1.30- 1.56) <.0001 1,164 (13.00%) 2,675 (9.96%) 1.45 (1.34- 1.57) <.0001 2-3 years 1 - Large decrease (≤10th pctl) 904 (9.56%) 2,792 (9.84%) 0.98 (0.90- 1.06) 0.6224 1,550 (12.70%) 3,799 (10.37%) 1.35 (1.26- 1.44) <.0001 2 - Small decrease (>10 to 25th pctl) 1,343 (14.20%) 4,469 (15.75%) 0.91 (0.85- 0.97) 0.0062 1,840 (15.07%) 5,810 (15.86%) 1.04 (0.98- 1.11) 0.1718 3 - No significant change (>25 to <75th pctl) 4,690 (49.58%) 14,197 (50.02%) 1.00 [Reference] 5,394 (44.18%) 17,723 (48.39%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,542 (16.30%) 4,286 (15.10%) 1.09 (1.02- 1.17) 0.0103 1,903 (15.59%) 5,655 (15.44%) 1.11 (1.04- 1.18) 0.0009 5 - Large increase (≥90th pctl) 981 (10.37%) 2,636 (9.29%) 1.13 (1.04- 1.22) 0.0031 1,521 (12.46%) 3,637 (9.93%) 1.38 (1.29- 1.48) <.0001 3-5 years 1 - Large decrease (≤10th pctl) 969 (10.05%) 2,798 (9.68%) 1.06 (0.98- 1.15) 0.1457 1,501 (12.19%) 3,797 (10.27%) 1.29 (1.21- 1.38) <.0001 2 - Small decrease (>10 to 25th pctl) 1,501 (15.57%) 4,536 (15.69%) 1.01 (0.95- 1.08) 0.6904 1,867 (15.16%) 5,685 (15.38%) 1.07 (1.01- 1.13) 0.0311 3 - No significant change (>25 to <75th pctl) 4,772 (49.51%) 14,617 (50.55%) 1.00 [Reference] 5,624 (45.66%) 18,288 (49.49%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 1,457 (15.12%) 4,313 (14.92%) 1.03 (0.97- 1.11) 0.3237 1,920 (15.59%) 5,664 (15.33%) 1.10 (1.04- 1.17) 0.0013 5 - Large increase (≥90th pctl) 939 (9.74%) 2,650 (9.17%) 1.09 (1.00- 1.18) 0.0464 1,406 (11.41%) 3,520 (9.53%) 1.31 (1.22- 1.40) <.0001 5-10 years 1 - Large decrease (≤10th pctl) 695 (11.33%) 2,104 (11.44%) 0.99 (0.90- 1.09) 0.8018 1,050 (13.03%) 2,851 (11.79%) 1.17 (1.08- 1.27) 0.0001 2 - Small decrease (>10 to 25th pctl) 1,031 (16.81%) 3,292 (17.89%) 0.94 (0.86- 1.01) 0.1094 1,378 (17.09%) 4,355 (18.01%) 1.00 (0.93- 1.08) 0.963 3 - No significant change (>25 to <75th pctl) 3,118 (50.84%) 9,323 (50.67%) 1.00 [Reference] 3,766 (46.72%) 11,927 (49.32%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 766 (12.49%) 2,315 (12.58%) 0.99 (0.90- 1.08) 0.8309 1,101 (13.66%) 3,199 (13.23%) 1.09 (1.01- 1.18) 0.0269 5 - Large increase (≥90th pctl) 523 (8.53%) 1,365 (7.42%) 1.15 (1.03- 1.28) 0.0142 766 (9.50%) 1,851 (7.65%) 1.32 (1.20- 1.45) <.0001
  • 35. © 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P-value N, % (Case) N, % (Control) OR (95% CI) P- value 0-6 months 1 - Large decrease (≤10th pctl) 97 (6.07%) 480 (10.01%) 1.01 (0.79- 1.29) 0.9506 185 (7.80%) 738 (10.37%) 1.16 (0.96- 1.39) 0.1218 2 - Small decrease (>10 to 25th pctl) 136 (8.51%) 741 (15.46%) 0.90 (0.73- 1.11) 0.3245 172 (7.25%) 1,136 (15.96%) 0.69 (0.58- 0.83) <.0001 3 - No significant change (>25 to <75th pctl) 462 (28.91%) 2,359 (49.21%) 1.00 [Reference] 745 (31.41%) 3,437 (48.30%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 248 (15.52%) 736 (15.35%) 1.71 (1.43- 2.05) <.0001 407 (17.16%) 1,068 (15.01%) 1.77 (1.54- 2.04) <.0001 5 - Large increase (≥90th pctl) 655 (40.99%) 478 (9.97%) 7.23 (6.12- 8.53) <.0001 863 (36.38%) 737 (10.36%) 5.51 (4.82- 6.29) <.0001 6-12 months 1 - Large decrease (≤10th pctl) 119 (10.54%) 351 (10.36%) 1.08 (0.86- 1.35) 0.5295 167 (9.56%) 585 (11.17%) 0.98 (0.81- 1.18) 0.8258 2 - Small decrease (>10 to 25th pctl) 130 (11.51%) 566 (16.71%) 0.72 (0.58- 0.90) 0.0037 252 (14.43%) 806 (15.39%) 1.06 (0.91- 1.25) 0.4461 3 - No significant change (>25 to <75th pctl) 518 (45.88%) 1,653 (48.80%) 1.00 [Reference] 746 (42.73%) 2,557 (48.82%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 210 (18.60%) 504 (14.88%) 1.33 (1.10- 1.61) 0.0029 298 (17.07%) 769 (14.68%) 1.33 (1.14- 1.56) 0.0003 5 - Large increase (≥90th pctl) 152 (13.46%) 313 (9.24%) 1.55 (1.25- 1.93) <.0001 283 (16.21%) 521 (9.95%) 1.87 (1.58- 2.21) <.0001 12-18 months 1 - Large decrease (≤10th pctl) 87 (8.15%) 335 (10.47%) 0.80 (0.62- 1.03) 0.0861 171 (10.48%) 505 (10.32%) 1.04 (0.86- 1.26) 0.6826 2 - Small decrease (>10 to 25th pctl) 142 (13.31%) 486 (15.18%) 0.90 (0.73- 1.11) 0.3115 211 (12.94%) 730 (14.92%) 0.88 (0.74- 1.05) 0.1689 3 - No significant change (>25 to <75th pctl) 519 (48.64%) 1,591 (49.70%) 1.00 [Reference] 797 (48.87%) 2,444 (49.95%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 191 (17.90%) 477 (14.90%) 1.22 (1.00- 1.48) 0.0453 258 (15.82%) 727 (14.86%) 1.09 (0.92- 1.28) 0.308 5 - Large increase (≥90th pctl) 128 (12.00%) 312 (9.75%) 1.25 (1.00- 1.57) 0.0533 194 (11.89%) 487 (9.95%) 1.22 (1.02- 1.47) 0.0334 18-24 months 1 - Large decrease (≤10th pctl) 96 (10.01%) 278 (9.66%) 1.01 (0.79- 1.31) 0.9115 174 (11.73%) 437 (9.82%) 1.29 (1.06- 1.57) 0.0127 2 - Small decrease (>10 to 25th pctl) 146 (15.22%) 433 (15.05%) 0.99 (0.80- 1.23) 0.9258 198 (13.34%) 683 (15.34%) 0.93 (0.78- 1.11) 0.4262 3 - No significant change (>25 to <75th pctl) 486 (50.68%) 1,426 (49.57%) 1.00 [Reference] 684 (46.09%) 2,191 (49.21%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 142 (14.81%) 425 (14.77%) 0.98 (0.79- 1.22) 0.8563 255 (17.18%) 697 (15.66%) 1.18 (0.99- 1.39) 0.0581 5 - Large increase (≥90th pctl) 89 (9.28%) 315 (10.95%) 0.83 (0.64- 1.07) 0.1469 173 (11.66%) 444 (9.97%) 1.26 (1.03- 1.53) 0.0225
  • 36. © 2022 Giannakeas V et al. JAMA Network Open. Ovary Stomach Categorical Time Value N, % (Case) N, % (Control) OR (95% CI) P-value N, % (Case) N, % (Control) OR (95% CI) P- value 2-3 years 1 - Large decrease (≤10th pctl) 137 (9.88%) 425 (10.21%) 0.93 (0.75- 1.15) 0.4994 211 (10.65%) 586 (9.86%) 1.11 (0.93- 1.33) 0.23 2 - Small decrease (>10 to 25th pctl) 208 (15.00%) 639 (15.36%) 0.94 (0.79- 1.12) 0.4929 312 (15.75%) 925 (15.56%) 1.04 (0.90- 1.21) 0.5961 3 - No significant change (>25 to <75th pctl) 712 (51.33%) 2,056 (49.41%) 1.00 [Reference] 961 (48.51%) 2,964 (49.87%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 201 (14.49%) 627 (15.07%) 0.93 (0.77- 1.11) 0.4019 311 (15.70%) 921 (15.50%) 1.04 (0.90- 1.21) 0.5785 5 - Large increase (≥90th pctl) 129 (9.30%) 414 (9.95%) 0.90 (0.72- 1.12) 0.3319 186 (9.39%) 547 (9.20%) 1.05 (0.88- 1.26) 0.5972 3-5 years 1 - Large decrease (≤10th pctl) 132 (9.07%) 420 (9.62%) 0.96 (0.78- 1.19) 0.7121 174 (8.59%) 608 (10.00%) 0.86 (0.71- 1.03) 0.1026 2 - Small decrease (>10 to 25th pctl) 234 (16.08%) 685 (15.69%) 1.04 (0.88- 1.24) 0.6237 342 (16.88%) 911 (14.99%) 1.13 (0.97- 1.30) 0.1069 3 - No significant change (>25 to <75th pctl) 721 (49.55%) 2,203 (50.47%) 1.00 [Reference] 1,011 (49.90%) 3,025 (49.77%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 224 (15.40%) 654 (14.98%) 1.05 (0.88- 1.24) 0.6099 290 (14.31%) 966 (15.89%) 0.90 (0.77- 1.04) 0.1554 5 - Large increase (≥90th pctl) 144 (9.90%) 403 (9.23%) 1.09 (0.89- 1.35) 0.4079 209 (10.32%) 568 (9.35%) 1.10 (0.92- 1.31) 0.2946 5-10 years 1 - Large decrease (≤10th pctl) 113 (11.58%) 334 (11.41%) 0.99 (0.78- 1.25) 0.9316 151 (11.30%) 449 (11.20%) 1.04 (0.85- 1.28) 0.7091 2 - Small decrease (>10 to 25th pctl) 174 (17.83%) 533 (18.20%) 0.96 (0.78- 1.17) 0.6571 241 (18.04%) 720 (17.96%) 1.03 (0.87- 1.22) 0.7195 3 - No significant change (>25 to <75th pctl) 489 (50.10%) 1,432 (48.91%) 1.00 [Reference] 658 (49.25%) 2,032 (50.70%) 1.00 [Reference] 4 - Small increase (75 to <90th pctl) 131 (13.42%) 393 (13.42%) 0.98 (0.78- 1.22) 0.8315 174 (13.02%) 527 (13.15%) 1.02 (0.84- 1.24) 0.8269 5 - Large increase (≥90th pctl) 69 (7.07%) 236 (8.06%) 0.85 (0.64- 1.14) 0.2854 112 (8.38%) 280 (6.99%) 1.24 (0.98- 1.57) 0.0792
  • 37. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 1. Study design criteria among matched individuals
  • 38. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 2. Age- and sex-specific platelet count reference distributions for exposure definition Note: Observations inversely weighted based on the number of CBC tests per-subject, for each sex-age category
  • 39. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 3. Age- and sex-specific platelet count reference distributions for secondary exposure definition Male Female Change in platelet count observation percentile Change in platelet count observation percentile Age N 10th 25th 50th 75th 90th Age N 10th 25th 50th 75th 90th 18-29 239,713 -39 -19 -1 17 37 18-29 762,668 -49 -24 0 24 48 30-39 407,352 -36 -18 -1 16 34 30-39 1,267,171 -48 -23 0 23 47 40-49 870,005 -35 -17 -1 15 32 40-49 1,664,504 -44 -21 0 21 43 50-59 1,559,807 -35 -17 -1 15 33 50-59 2,144,471 -41 -20 -1 17 37 60-69 1,950,142 -36 -17 -1 15 33 60-69 2,246,168 -38 -19 -1 17 37 70-79 1,588,074 -36 -17 -1 15 35 70-79 1,907,064 -41 -19 -1 18 40 80-89 835,988 -40 -18 0 18 42 80-89 1,300,664 -47 -21 -1 21 47 90-100 125,702 -44 -19 1 22 52 90-100 334,804 -53 -24 0 25 58 Note: Observations inversely weighted based on the number of CBC tests per-subject, for each sex-age category 0 5 10 15 20 25 30 -200 -150 -100 -50 0 50 100 150 200 Percent (%) Change in platelet count (platelets per nL) 18-29 30-39 40-49 50-59 60-69 70-79 80-89 90-100 0 5 10 15 20 25 30 -200 -150 -100 -50 0 50 100 150 200 Percent (%) Change in platelet count (platelets per nL) 18-29 30-39 40-49 50-59 60-69 70-79 80-89 90-100
  • 40. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 4. Odds ratio of cancer by platelet count category and time from cancer diagnosis. Additional cancer sites. Breast (N = 65,703) Prostate (N = 62,770) Melanoma (N = 20,167) Thyroid (N = 21,559)
  • 41. © 2022 Giannakeas V et al. JAMA Network Open. Esophagus (N = 4,691) Kidney (N = 14,057) Pancreas (N = 12,009) Other GI (N = 5,259)
  • 42. © 2022 Giannakeas V et al. JAMA Network Open. Cervix (N = 3,493) Endometrium (N = 17,124) Bladder (N = 23,267) Liver (N = 7,651)
  • 43. © 2022 Giannakeas V et al. JAMA Network Open. Brain (N = 5,721) Head and neck (N = 13,318) Other solid tumour (N = 26,907)
  • 44. © 2022 Giannakeas V et al. JAMA Network Open. Leukemia (N = 5,157) Lymphoma (N = 33,785) Multiple myeloma (N = 8,265) Other hematologic tumour (N = 16,195)
  • 45. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 5. Odds ratio of cancer by change in platelet count category and time from cancer diagnosis. Additional cancer sites. Breast (N = 32,650) Prostate (N = 30,994) Melanoma (N = 9,957) Thyroid (N = 10,176)
  • 46. © 2022 Giannakeas V et al. JAMA Network Open. Esophagus (N = 2,307) Kidney (N = 7,149) Pancreas (N = 6,667) Other GI (N = 2,816) Cervix (N = 1,192) Endometrium (N = 8,597)
  • 47. © 2022 Giannakeas V et al. JAMA Network Open. Bladder (N = 12,895) Liver (N = 4,489)
  • 48. © 2022 Giannakeas V et al. JAMA Network Open. Brain (N = 2,648) Head and neck (N = 6,393) Other solid tumour (N = 13,624)
  • 49. © 2022 Giannakeas V et al. JAMA Network Open. Leukemia (N = 2,834) Lymphoma (N = 17,736) Multiple myeloma (N = 4,877) Other hematologic tumour (N = 10,306)
  • 50. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 6. Odds ratio of cancer by platelet count category and time from diagnosis. Select cancer sites by cancer stage. Lung stage I (N = 9,697) Lung stage II (N = 3,921) Lung stage III (N = 9,911) Lung stage IV (N = 24,390)
  • 51. © 2022 Giannakeas V et al. JAMA Network Open. Ovary stage I (N = 1,196) Ovary stage II (N = 543) Ovary stage III (N = 2,315) Ovary stage IV (N = 926)
  • 52. © 2022 Giannakeas V et al. JAMA Network Open. Stomach stage I (N = 600) Stomach stage II (N = 678) Stomach stage III (N = 799) Stomach stage IV (N = 1,673)
  • 53. © 2022 Giannakeas V et al. JAMA Network Open. Breast stage I (N = 28,646) Breast stage II (N = 22,577) Breast stage III (N = 7,740) Breast stage IV (N = 2,672)
  • 54. © 2022 Giannakeas V et al. JAMA Network Open. Prostate stage I (N = 12,383) Prostate stage II (N = 30,688) Prostate stage III (N = 8,137) Prostate stage IV (N = 5,797)
  • 55. © 2022 Giannakeas V et al. JAMA Network Open. eFigure 7. Odds ratio of cancer by platelet count category (clinical definition) and time from diagnosis. Colon (N = 51,271) Lung (N = 56,586) Ovary (N = 7,658) Stomach (N = 9,166)
  • 56. © 2022 Giannakeas V et al. JAMA Network Open. Breast (N = 65,703) Prostate (N = 62,770) Melanoma (N = 20,167) Thyroid (N = 21,559)
  • 57. © 2022 Giannakeas V et al. JAMA Network Open. Esophagus (N = 4,691) Kidney (N = 14,057) Pancreas (N = 12,009) Other GI (N = 5,259)
  • 58. © 2022 Giannakeas V et al. JAMA Network Open. Cervix (N = 3,493) Endometrium (N = 17,124) Bladder (N = 23,267) Liver (N = 7,651)
  • 59. © 2022 Giannakeas V et al. JAMA Network Open. Brain (N = 5,721) Head and neck (N = 13,318) Other solid tumour (N = 26,907)
  • 60. © 2022 Giannakeas V et al. JAMA Network Open. Leukemia (N = 5,157) Lymphoma (N = 33,785) Multiple myeloma (N = 8,265) Other hematologic tumour (N = 16,195)