Individuals with cancer have an elevated risk of mortality following acute myocardial infarction (AMI), yet selecting optimal dual antiplatelet therapy (DAPT) is challenging due to competing risks of thrombosis and bleeding. We evaluated patterns of DAPT use and associated outcomes in this population. Using the TriNetX global registry, we identified adults hospitalized with AMI and active cancer who were prescribed DAPT between January 2015 and January 2020. The primary outcome was all-cause mortality at 1 and 5 years. Secondary outcomes were major bleeding events and AMI readmission up to 5 years. Adjusted hazard ratios (aHRs) were estimated using Cox proportional hazards models. Clopidogrel was the most frequently prescribed P2Y12 inhibitor (79%), followed by ticagrelor (16%) and prasugrel (4%). Patients prescribed clopidogrel were older and had greater cardiovascular comorbidity. In a propensity-matched cohort of 8,000 patients, 5-year mortality was 28% with clopidogrel versus 27% with ticagrelor (aHR 1.11, 95% CI 1.01 to 1.23; p = 0.04) and 20% with prasugrel (aHR 1.42, 95% CI 1.12 to 1.81; p = 0.004). Ticagrelor was associated with higher 5-year mortality compared to prasugrel (26% vs 20%; aHR 1.49, 95% CI 1.14 to 1.85; p = 0.003). Major bleeding rates did not differ significantly between treatment groups. The risk of readmission with AMI was lower in the clopidogrel group compared to ticagrelor, aHR 0.91 (0.84, 0.99), p = 0.03. In conclusion, clopidogrel remains the predominant P2Y12 inhibitor used in patients with active cancer presenting with AMI. However, ticagrelor and prasugrel were associated with better long-term survival without increased major bleeding. These findings support further evaluation of potent P2Y12 inhibitors in this high-risk population.
Acute myocardial infarction (AMI) remains a leading cause of death worldwide. Individuals with cancer experience a higher incidence of AMI, reflecting shared cardiovascular risk factors, cardiotoxic effects of cancer therapies and overlapping pathophysiological mechanisms. , Although AMI hospitalizations have generally declined, they are increasing among individuals with cancer, who also receive lower quality care and experience higher cardiovascular mortality. Optimizing AMI management in this high-risk group is therefore a clinical priority. Dual antiplatelet therapy (DAPT), consisting of aspirin and a P2Y12 inhibitor, is central to AMI treatment. Clopidogrel demonstrated benefit in both medically and invasively managed patients, , while newer agents such as ticagrelor and prasugrel provide greater antithrombotic efficacy at the expense of higher bleeding risk. , Although contemporary guidelines generally favor ticagrelor or prasugrel over clopidogrel, selecting an appropriate DAPT regimen in patients with active cancer is challenging because malignancy confers heightened risk of both thrombosis and bleeding. , Evidence to guide antiplatelet selection in patients with cancer is sparse as they are underrepresented in randomized antiplatelet trials. We therefore used the TriNetX global registry to evaluate contemporary patterns of DAPT prescribing in patients with cancer presenting with AMI and examined the impact of different regimens on short- and long-term clinical outcomes.
Methods
We conducted a retrospective cohort study using the TriNetX Global Analytics Network, a federated platform aggregating anonymized electronic health record data (EHR) from 160 health care organizations and more than 163 million patients at the time of analysis. The database includes demographics, comorbidities (ICD-9/ICD-10 codes), procedures (Current Procedural Terminology), medications (Veterans Affairs National Formulary), laboratory values (Logical Observation Identifiers Names and Codes [LOINC]), and patient encounter types. Analysis was performed on November 12, 2025 within the TriNetX analytics environment, which supports patient-level data generation, cohort selection, propensity score matching (PSM), and outcome comparisons.
Study population
Adults (≥18 years) hospitalized with a primary diagnosis of ST-elevation and non-ST-elevation AMI, between January 1, 2015 and January 1, 2020 were included if they had a diagnosis of active malignancy within the preceding year. Patients were stratified according to DAPT regimen: aspirin plus clopidogrel, ticagrelor, or prasugrel. Individuals prescribed anticoagulants or additional antiplatelet agents were excluded ( Supplementary Table 1 ). Active cancer diagnosis was identified using predefined ICD-10 codes ( Supplementary Table 2 ).
Outcomes
The primary outcome was all-cause mortality, at 1 and 5-years following the index AMI. Follow up commenced at 30 days after admission to reduce misclassification between incident and outcome events. Shorter washout periods produced directionally similar but statistically unstable estimates (data not shown). Mortality is recorded within TrinetX using a variety of sources including health care organization (HCO) death records (EHR source), billable codes from closed claims, Social Security Administration Master Death File, private obituaries, and private insurance claims.
Secondary outcomes were major bleeding events and readmission with AMI over 5 years of follow up. Major bleeding was identified using ICD-10 codes ( Supplementary Table 3 ). Readmission with AMI was defined as a subsequent hospitalization coded as I21.
Statistical analysis
Continuous variables are reported as medians with interquartile ranges and compared using Student’s t tests. Categorical variables are presented as proportions and compared using chi-square test. To account for baseline differences, 1:1 propensity score matching was performed using logistical regression and nearest-neighbor matching with a caliper of 0.1-pooled standard deviation and a tolerance level of 0.01. Matching variables included gender, ethnicity, age, cancer type, hypertension, cerebrovascular disease, diabetes mellitus, chronic kidney disease, chronic obstructive airways disease, asthma, peripheral vascular disease, invasive angiogram, statins, β-blockers, loop diuretics, potassium sparing diuretics, angiotensin-converting enzyme inhibitors, left ventricular ejection fraction, heart rate, body mass index, blood pressure, cardiac arrest. Survival analyzes were conducted using Cox proportional hazards models, with results reported as hazard ratios (HRs) and 95% confidence intervals (CIs). Two falsification end points; nephrolithiasis and cholecystitis were included (when cohort sizes were large enough to test for significance) to validate our model. A sensitivity analysis was also performed in a cohort restricted to patients who underwent percutaneous coronary intervention. Computational analysis was completed proprietary TriNetX LIVE platform, which generates statistical analyzes using the following: Java 11.0.16 (including Apache Commons Math 3.6.1), R 4.0.2 (with Hmisc1-1 and Survival 3.2-3), and Python 3.7 (utilizing lifelines 0.22.4, matplotlib 3.5.1, numpy 1.21.5, pandas 1.3.5, scipy 1.7.3, and statsmodels 0.13.2). Statistical significance was defined as p ≤ 0.05.
Ethics
This retrospective study is exempt from informed consent. The data reviewed is a secondary analysis of existing data, does not involve intervention or interaction with human subjects, and is deidentified per the deidentification standard defined in Section §164.514(a) of the HIPAA Privacy Rule. The process by which the data is deidentified is attested to through a formal determination by a qualified expert as defined in Section §164.514(b)(1) of the HIPAA Privacy Rule. This formal determination by a qualified expert refreshed on December 2020. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.
Results
A total of 18,186 patients with AMI and active cancer were identified. Clopidogrel plus aspirin was prescribed in 14,422 patients (79%), ticagrelor in 2,971 (16%), and prasugrel in 793 (4%). After propensity score matching, 2,844 clopidogrel and ticagrelor pairs, 605 clopidogrel and prasugrel pairs, and 573 ticagrelor and prasugrel pairs were generated ( Supplementary Figure 1 ).
Baseline characteristics
Table 1 summarizes baseline differences between treatment groups after application of our propensity score matching model. Supplementary Table 4 shows the crude demographic data. Patients prescribed clopidogrel were older (clopidogrel: 72 ± 11 years; ticagrelor: 69 ± 11; prasugrel: 68 ± 11; p < 0.001) and had a higher prevalence of traditional cardiovascular comorbidities, including hypercholesterolemia (clopidogrel: 62%, ticagrelor: 51% prasugrel: 57%), cerebrovascular disease (clopidogrel: 28%, ticagrelor: 16% prasugrel: 21%), chronic kidney disease (clopidogrel: 32%, ticagrelor: 24% prasugrel: 19%), previous heart failure (clopidogrel: 38%, ticagrelor: 24% prasugrel: 35%), and hypertension (clopidogrel: 77%, ticagrelor: 69% prasugrel: 73%), respectively.
Table 1
Demographic and management strategy comparison between dual antiplatelet regimes in patients presenting with acute myocardial infarction with active cancer
| Variable | Clopidogrel + Aspirin (n = 2,844) | Ticagrelor + Aspirin (n = 2,844) | p Value | Clopidogrel + Aspirin (n = 605) | Prasugrel + Aspirin (n = 605) | p Value | Ticagrelor +Aspirin (n573) | Prasugrel + Aspirin (n = 573) | p Value |
|---|---|---|---|---|---|---|---|---|---|
| Age (years) | 69 ± 11 | 70 ± 11 | 0.78 | 66 ± 11 | 66 ± 11 | 0.85 | 66 ± 11 | 67 ± 11 | 0.49 |
| Female | 935 (33%) | 961 (34%) | 0.47 | 162 (27%) | 177 (29%) | 0.34 | 169 (30%) | 167 (29%) | 0.90 |
| BMI (kg/m 2) | 28 ± 6 | 28 ± 6 | 0.59 | 29 ± 6 | 29 ± 6 | 0.31 | 29 ± 6 | 29 ± 6 | 0.53 |
| Ethnicity | |||||||||
| White | 1,947 (69%) | 1,959 (69%) | 0.73 | 436 (72%) | 422 (70%) | 0.38 | 375 (65%) | 397 (69%) | 0.17 |
| Asian | 143 (5%) | 204 (7%) | 0.001 | 21 (4%) | 10 (2%) | 0.05 | 38 (7%) | 10 (2%) | <0.001 |
| Black | 411 (15%) | 349 (12%) | 0.005 | 86 (14%) | 58 (10%) | 0.01 | 95 (17%) | 52 (9%) | <0.001 |
| Unknown | 246 (9%) | 261 (9%) | 0.49 | 44 (7%) | 100 (17%) | <0.001 | 48 (8%) | 100 (18%) | <0.001 |
| CCF | 756 (27%) | 685 (24%) | 0.03 | 169 (28%) | 184 (30%) | 0.34 | 144 (25%) | 175 (31%) | 0.04 |
| LVEF | 52 ± 16 | 53 ± 15 | 0.58 | 52 ± 15 | 52 ± 18 | 0.95 | 56 ± 14 | 51 ± 18 | 0.13 |
| Hypercholesterolemia | 1,476 (52%) | 1,506 (53%) | 0.43 | 368 (61%) | 385 (64%) | 0.31 | 345 (60%) | 360 (63%) | 0.36 |
| Cerebrovascular disease | 489 (17%) | 468 (17%) | 0.46 | 106 (18%) | 118 (20%) | 0.37 | 111 (19%) | 112 (20%) | 0.94 |
| CKD | 688 (24%) | 685 (24%) | 0.93 | 142 (24%) | 136 (23%) | 0.68 | 134 (23%) | 131 (23%) | 0.83 |
| Diabetes mellitus | 1,010 (36%) | 967 (34%) | 0.23 | 254 (42%) | 263 (44%) | 0.60 | 257 (45%) | 249 (44%) | 0.63 |
| History of angina | 453 (16%) | 407 (14%) | 0.09 | 115 (19%) | 163 (27%) | 0.001 | 98 (17%) | 159 (28%) | <0.001 |
| Peripheral vascular disease | 266 (9%) | 269 (10%) | 0.89 | 60 (10%) | 63 (10%) | 0.78 | 59 (10%) | 61 (11%) | 0.85 |
| Hypertension | 1,949 (69%) | 1,964 (69%) | 0.67 | 469 (78%) | 466 (77%) | 0.84 | 443 (77%) | 442 (77%) | 0.94 |
| Asthma | 260 (9%) | 257 (9%) | 0.89 | 61 (10%) | 73 (12%) | 0.27 | 79 (14%) | 70 (12%) | 0.43 |
| COPD | 548 (19%) | 524 (18%) | 0.42 | 94 (16%) | 113 (19%) | 0.15 | 108 (19%) | 109 (19%) | 0.94 |
| Heart rate, (bpm) | 77 ± 16 | 78 ± 17 | 0.59 | 76 ± 16 | 75 ± 14 | 0.20 | 77 ± 17 | 75 ± 14 | 0.02 |
| Systolic BP (mm Hg) | 128 ± 23 | 130 ± 23 | 0.04 | 128 ± 21 | 129 ± 21 | 0.41 | 130 ± 23 | 129 ± 21 | 0.72 |
| Cardiac arrest | 70 (3%) | 77 (3%) | 0.56 | 28 (5%) | 16 (3%) | 0.07 | 14 (2%) | 15 (3%) | 0.85 |
| NSTEMI | 1,101 (39%) | 942 (33%) | <0.001 | 240 (40%) | 218 (36%) | 0.19 | 219 (38%) | 211 (37%) | 0.63 |
| Loop Diuretics | 819 (29%) | 836 (29%) | 0.62 | 169 (28%) | 168 (28%) | 0.95 | 167 (29%) | 158 (28%) | 0.56 |
| MRA | 605 (21%) | 640 (23%) | 0.26 | 135 (22%) | 131 (22%) | 0.78 | 140 (24%) | 122 (21%) | 0.21 |
| Statins | 1,857 (65%) | 1,803 (63%) | 0.14 | 462 (76%) | 459 (76%) | 0.84 | 446 (78%) | 430 (75%) | 0.27 |
| ACE inhibitors | 976 (34%) | 983 (35%) | 0.85 | 239 (40%) | 231 (38%) | 0.64 | 214 (37%) | 214 (37%) | 1 |
| ARB | 653 (23%) | 633 (22%) | 0.53 | 133 (22%) | 155 (26%) | 0.14 | 147 (26%) | 146 (26%) | 0.95 |
| β-blockers | 1,742 (61%) | 1,706 (60%) | 0.33 | 420 (69%) | 426 (70%) | 0.71 | 408 (71%) | 399 (70%) | 0.56 |
| Echocardiogram | 1,125 (40%) | 1,119 (39%) | 0.87 | 290 (48%) | 258 (43%) | 0.07 | 283 (49%) | 241 (42%) | 0.01 |
| Coronary angiogram | 661 (23%) | 635 (22%) | 0.41 | 206 (34%) | 191 (32%) | 0.36 | 179 (31%) | 182 (32%) | 0.85 |
| Percutaneous coronary intervention | 400 (14%) | 427 (15%) | 0.31 | 121 (20%) | 146 (24%) | 0.08 | 112 (20%) | 141 (25%) | 0.04 |
| CABG surgery | 52 (2%) | 26 (1%) | 0.003 | 15 (3%) | 10 (2%) | 0.31 | 10 (2%) | 10 (2%) | 1 |
| Malignancy type | |||||||||
| Malignant neoplasm of lip, oral cavity and pharynx | 177 (6%) | 163 (6%) | 0.43 | 26 (4%) | 26 (4%) | 1 | 21 (4%) | 26 (5%) | 0.46 |
| Malignant neoplasm of digestive organs | 483 (17%) | 475 (17%) | 0.78 | 112 (19%) | 110 (18%) | 0.88 | 94 (16%) | 110 (19%) | 0.22 |
| Malignant neoplasm of respiratory and intrathoracic organs | 431 (15%) | 402 (14%) | 0.28 | 75 (12%) | 88 (15%) | 0.27 | 67 (12%) | 87 (15%) | 0.08 |
| Malignant neoplasm of bone and articular cartilage | 38 (1%) | 37 (1%) | 0.91 | 10 (2%) | 10 (2%) | 1 | 10 (2%) | 10 (2%) | 1 |
| Malignant neoplasm of mesothelial and soft tissue | 85 (3%) | 81 (3%) | 0.75 | 14 (2%) | 14 (2%) | 1 | 13 (2%) | 14 (2%) | 0.85 |
| Malignant neoplasm of breast | 335 (12%) | 349 (12%) | 0.57 | 59 (10%) | 68 (11%) | 0.40 | 72 (13%) | 65 (11%) | 0.52 |
| Malignant neoplasm of female genital organs | 103 (4%) | 110 (4%) | 0.63 | 28 (5%) | 25 (4%) | 0.67 | 22 (4%) | 23 (4%) | 0.88 |
| Malignant neoplasm of male genital organs | 692 (24%) | 672 (24%) | 0.54 | 170 (28%) | 160 (26%) | 0.52 | 144 (25%) | 150 (26%) | 0.69 |
| Malignant neoplasm of urinary tract | 353 (12%) | 358 (13%) | 0.84 | 80 (13%) | 80 (13%) | 1 | 71 (12%) | 72 (13%) | 0.93 |
| Malignant neoplasm of eye, brain and other parts of the central nervous system | 33 (1%) | 39 (1%) | 0.48 | 10 (2%) | 10 (2%) | 1 | 10 (2%) | 10 (2%) | 1 |
| Malignant neoplasm of thyroid and other endocrine glands | 43 (2%) | 50 (2%) | 0.46 | 19 (3%) | 30 (5%) | 0.11 | 19 (3%) | 23 (4%) | 0.53 |
| Malignant neuroendocrine tumors | 26 (1%) | 29 (1%) | 0.68 | 10 (2%) | 10 (2%) | 1 | 10 (2%) | 10 (2%) | 1 |
| Malignant neoplasm of lymphoid, haemopoietic and related tissue | 512 (18%) | 492 (17%) | 0.49 | 133 (22%) | 123 (20%) | 0.48 | 133 (23%) | 119 (21%) | 0.32 |
| GFR | 68 ± 31 | 67 ± 28 | 0.29 | 69 ± 28 | 69 ± 29 | 0.89 | 70 ± 29 | 69 ± 29 | 0.77 |
| CRP | 35 ± 53 | 26 ± 49 | 0.003 | 47 ± 80 | 21 ± 43 | 0.001 | 26 ± 55 | 20 ± 40 | 0.25 |
| BNP | 4,870 ± 9,910 | 4,543 ± 9,463 | 0.64 | 3,896 ± 8,752 | 4,126 ± 12,370 | 0.88 | 2,527 ± 5,486 | 3,792 ± 11,820 | 0.40 |
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