Abstract
Background:
Black individuals undergoing percutaneous coronary intervention (PCI) experience higher rates of major adverse cardiovascular events (MACE) than non-Black individuals. This study assessed the racial differences in platelet reactivity and clinical outcomes among clopidogrel-treated participants.
Methods:
Two cohorts were analyzed. The pharmacodynamic (PD) cohort involved patients with atherosclerotic cardiovascular disease on maintenance clopidogrel therapy undergoing platelet function testing. The primary outcome was high platelet reactivity (HPR, i.e. P2Y12 reaction unit [PRU] >208). The PCI cohort included participants undergoing PCI on clopidogrel-based dual antiplatelet therapy. The primary outcome was 1-year MACE, defined as the composite of cardiovascular death, myocardial infarction (MI), ischemic stroke, or stent thrombosis. Data on clinically significant bleeding and CYP2C19 genotyping alleles were collected.
Results:
The PD and PCI cohorts included 728 (32.1% Black) and 2,770 (20.5% Black) participants, respectively. Black participants had higher PRU levels (183 [IQR 128–234] vs. 144 [IQR 88–195]; P<0.001) and higher prevalence of HPR (39.3% vs. 20.6%; P<0.001). Independent predictors of HPR included Black race, hemoglobin levels, and presence of CYP2C19 loss-of-function allele. In the PCI cohort, Black participants had a higher risk of MACE (HR 1.47; 95% CI 1.02–2.11; P=0.037), primarily driven by MI (HR 1.71; 95% CI 1.09–2.67; P=0.019), with no significant difference in clinically significant bleeding (HR 1.08; 95% CI 0.65–1.80; P=0.768).
Conclusions:
Black participants on clopidogrel exhibit higher platelet reactivity, increased rates of HPR, and an elevated risk of MACE within 1-year after PCI, without significant differences in bleeding compared to non-Black participants.
Clinical Trial Registration:
http://www.clinicaltrials.gov Unique Identifier: NCT01852175, NCT02287909, NCT02548650, NCT03437044, NCT03718429, NCT03096288, NCT04006288, NCT06143709, NCT02567461, NCT02539160.
Keywords: Clopidogrel, Platelet Function Tests, Pharmacogenetics, Cytochrome P-450 CYP2C19, Percutaneous Coronary Intervention, Race Factors, Cardiovascular Diseases, Major Adverse Cardiovascular Events, Antiplatelet Therapy, Thrombosis
INTRODUCTION
Clopidogrel is the most widely used oral P2Y12 receptor inhibitor for patients with atherosclerotic cardiovascular disease (ASCVD), including those undergoing percutaneous coronary intervention (PCI).1 However, pharmacodynamic (PD) studies reveal significant interindividual variability in clopidogrel response, often leading to high platelet reactivity (HPR) and an increased thrombotic risk.2 Risk factors for HPR in clopidogrel-treated individuals include both clinical and genetic factors, such as polymorphisms in the cytochrome P450 2C19 (CYP2C19) gene.3
Black individuals are underrepresented in clinical studies with clopidogrel.4,5 As a result, few studies have evaluated the role of race in platelet reactivity profiles and clinical outcomes among clopidogrel-treated participants.6–8 While existing studies in clopidogrel-treated participants suggest differences in the prevalence of HPR and clinical outcomes after PCI when stratified by self-reported race, they are limited by sample size and methodological issues related to platelet reactivity assessment.6–8 Moreover, previous outcome studies did not consider the type of P2Y12 inhibitor used or the presence of CYP2C19 polymorphisms.9,10
Currently, the association between platelet reactivity and worse clinical outcomes according to self-reported race has not yet been fully established. Clarifying this association is essential, as platelet reactivity represents a potential therapeutic target for reducing disparities in outcomes between Black and non-Black individuals undergoing PCI.
We aimed to evaluate the impact of race on platelet reactivity profiles and clinical outcomes in clopidogrel-treated participants undergoing PCI, with consideration of CYP2C19 genotype.
METHODS
This study comprises two distinct cohorts: 1) a pharmacodynamic (PD) cohort, which was used to compare platelet reactivity profiles of participants on clopidogrel stratified according to race; and 2) a PCI cohort, which was used to assess differences in ischemic and bleeding outcomes among participants who underwent PCI and were treated with clopidogrel, stratified by race.
Study design and participants
Pharmacodynamic cohort
This retrospective pooled analysis included individual participant data from PD studies conducted at the University of Florida College of Medicine–Jacksonville between 2012 and 2024, and from the Precision Antiplatelet Therapy after Percutaneous Coronary Intervention (Precision PCI) registry (NCT06143709).11 Eligible participants were individuals with ASCVD, including coronary artery disease, prior stroke, or peripheral artery disease, who were on maintenance antiplatelet therapy with clopidogrel (≥14 days), either alone or in combination with low-dose aspirin (81 mg once daily). Participants were required to have P2Y12 reaction units (PRU) measured using the VerifyNow system (Wefren, MA, USA) at trough levels (i.e., 24±2 hours after the last maintenance dose of clopidogrel). Additional merged baseline data included clinical characteristics, concomitant medications, levels of hemoglobin, platelet count, serum creatinine, and CYP2C19 genotype. Methods used for blood sampling and platelet reactivity testing, and CYP2C19 genotyping are reported in the Supplementary Appendix. The data were combined into a single pooled database, checked for completeness and consistency, and compared with the original databases. Missing values from the original study datasets were considered permanently missing. The cleaned database was then used to perform the analyses. All eligible studies complied with the Declaration of Helsinki and were approved by the local or Western Institutional Review Board. Written informed consent was obtained from all participants.
Percutaneous coronary intervention cohort
Clinical outcomes data were obtained from the Precision PCI registry (NCT06143709).11 Five institutions contributed clinical outcomes data: the University of North Carolina at Chapel Hill; the University of Florida, Jacksonville; the University of Florida, Gainesville; the University of Maryland, Baltimore; and the University of Illinois Chicago, Chicago, Illinois. Eligible participants were adults (≥18 years of age) who underwent emergent or elective PCI, were clinically genotyped for CYP2C19, and were treated with clopidogrel-based DAPT (aspirin 81 mg daily plus clopidogrel 75 mg daily). Medical record data were abstracted from the time of the index PCI for up to 12 months post-PCI, with a portion had data collected prospectively through telephone calls. Data abstraction ceased when patients either completed the 12-month follow-up, discontinued P2Y12 inhibitor therapy, or expired. Methods for blood sampling and CYP2C19 genotyping are described in the Supplementary Appendix. All data collection and processing procedures were approved by the institutional review boards at each participating institution.
Outcomes and definitions
Pharmacodynamic cohort
The primary outcome was the prevalence of HPR based on P2Y12 reaction unit (PRU) levels assessed using the VerifyNow system, stratified by race. HPR was defined as PRU >208, according to the currently recommended cutoffs and consensus definitions.12
Percutaneous coronary intervention cohort
The primary outcome was major adverse cardiovascular events (MACE), stratified by race, and defined as a composite of cardiovascular death, myocardial infarction (MI), ischemic stroke, or stent thrombosis, based on the definitions established by the Academic Research Consortium.13,14 Clinically significant bleeding was assessed as a secondary outcome, defined as a composite of moderate or severe bleeding or life-threatening bleeding based on the GUSTO (Global Use of Strategies to Open Occluded Arteries) criteria.15 Both cardiovascular and bleeding events were assessed within the 12-month follow-up period. All events were adjudicated by a cardiologist or reviewed by a clinical pharmacist.
Both cohorts
Self-reported race and ethnicity were documented as recorded in the electronic health record (EHR), following the recommendations of the Office of Management and Budget.16 Race options included White, Black or African American, Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native, and Other. Ethnicity options included Non-Hispanic or Latino and Hispanic or Latino. If race or ethnicity data were not available in the EHR, the information was directly requested from the participants. Self-reported race was used to classify participants into two groups: those who self-reported as Black or African American and those who self-reported as non-Black (e.g., White, Asian, other racial groups, mixed ancestry or unknown).
In terms of CYP2C19 genotype, participants were classified into two groups based on the presence or absence of a LOF (e.g., *2 or *3) allele: carriers of a CYP2C19 LOF allele and non-carriers.
Statistical analysis
In both cohorts, continuous variables were expressed as mean±SD or median [IQR] and compared across groups using Student’s t-test or Mann-Whitney U test depending on the conformity to the normal distribution, which was evaluated through the Shapiro-Wilk test. Categorical variables were expressed as frequencies and percentages and compared across groups using either the Chi-squared test or Fisher’s exact test, as appropriate.
Independent correlates of HPR were identified using univariable mixed-effects logistic regression models with a random intercept to account for the original trial cohort. Significant variables from univariable analyses were included in a multivariable model. Clinical characteristic variables were preferred over medication variables to ensure model convergence and avoid overfitting. Multiple models were constructed and compared using the Akaike Information Criterion (AIC) to evaluate the goodness-of-fit of each model.
In the PCI cohort, MACE and bleeding event rates were calculated by self-reported race, reported per 100 patient-years, and compared by means of the log-rank test. Adjusted Kaplan-Meier curves were used to estimate event-free survival in Black and non-Black patients. To examine the association between self-reported race and the risk of clinical outcomes, a multivariable Cox proportional hazards model was constructed to adjust for CYP2C19 LOF status and any variables with a P-value of <0.1 between groups, including institution of enrollment, medical history, baseline and procedural characteristics and medication at discharge. Scaled Schoenfeld residuals were examined to assess the proportional hazards assumption, and an additional Cox model was stratified by covariates with non-proportional hazards.
The direct and indirect effects of self-reported race-mediated causal pathways leading to HPR status and MACE were assessed using natural effect model mediation analysis, with clinical variables significantly differing between racial groups (i.e., Black vs. non-Black) serving as mediators.17
All analyses were performed using SPSS version 29.0 software (SPSS Inc., Chicago, Illinois) and R version 4.4.2 (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed p-value <0.05 was considered statistically significant for all analyses, except in cases of multiple comparisons, where Bonferroni adjustment was applied.
RESULTS
Pharmacodynamic cohort
A total of 728 clopidogrel-treated participants underwent platelet function testing by means of VerifyNow system and were included in the analysis (Figure S1). The methodological characteristics of the originating studies are detailed in Table S1. In the overall population, the median PRU was 156 (IQR 100–211). Participants with HPR (n=194) had a significantly higher median PRU compared to those without HPR (n=534) (242 [IQR 223–268] vs. 128 [IQR 83–166], P <0.001) (Figure 1). The baseline characteristics of the cohort, stratified by platelet reactivity status, are shown in Table 1. Participants with HPR were more frequently female (47.4% vs. 32.0%, P<0.001) and Black (47.4% vs. 26.6%, P<0.001) compared to those without HPR. Participants with HPR also had a greater prevalence of obesity (59.3% vs. 46.4%, P=0.004) and diabetes mellitus (59.3% vs. 40.8%, P<0.001) and lower hemoglobin levels (12.6 [IQR 11.4–13.5] vs. 13.5 [IQR 12.5–14.7] g/dL, P<0.001) compared to those without HPR. CYP2C19 LOF alleles were more frequently observed in participants with HPR than in those without (25.3% vs. 16.7%, P=0.037). A higher proportion of participants with HPR were on calcium channel blockers (36.6% vs. 25.7%, P=0.034) and insulin (25.8% vs. 14.4%, P<0.001) compared to those without HPR. Several significant differences were observed in baseline characteristics according to race (Table S2).
Figure 1. PRU distribution across the population stratified according to race.
The figure displays the distribution of platelet activity according to PRU. Blue and red shaded areas under the curve represent the density of patients with normal platelet reactivity and high platelet reactivity, respectively. The density curve is accompanied by the density histogram. Dashed blue and red lines represent the median PRU of the population and the high platelet reactivity threshold, respectively, with specific numbers reported on top. PRU, P2Y12 receptor units.
Table 1.
Baseline characteristics in the pharmacodynamic cohort stratified according to platelet reactivity.
| Overall (N=728) | HPR (N=194) | Non-HPR (N=534) | P-value | |
|---|---|---|---|---|
| Age, median (IQR) | 63.00 (56.00, 70.00) | 63.00 (56.00, 70.00) | 63.00 (55.00, 70.00) | 0.873 |
| >75 years, N (%) | 62 (8.5) | 16 (8.2) | 46 (8.6) | 0.949 |
| Female sex, N (%) | 263 (36.1) | 92 (47.4) | 171 (32.0) | <0.001 |
| Race, N (%) | ||||
| White | 466 (64.0) | 93 (47.9) | 373 (69.9) | <0.001 |
| Black | 234 (32.1) | 92 (47.4) | 142 (26.6) | |
| Other or Unknown Racea | 28 (3.8) | 9 (4.6) | 19 (3.6) | |
| Ethnicity, N (%) | ||||
| Non-Hispanic or Latino | 702 (96.4) | 189 (97.4) | 513 (96.1) | 0.252 |
| Hispanic or Latino | 22 (3.0) | 3 (1.5) | 19 (3.6) | |
| BMI, kg/m2, median (IQR) | 30.07 (26.63, 34.81) | 31.62 (27.07, 36.83) | 29.58 (26.50, 34.00) | 0.003 |
| Obesity (BMI ≥30), N (%) | 363 (49.9) | 115 (59.3) | 248 (46.4) | 0.004 |
| Current smoker, N (%) | 146 (20.1) | 39 (20.1) | 107 (20.0) | 0.563 |
| Medical history, N (%) | ||||
| Hypertension | 658 (90.4) | 183 (94.3) | 475 (89.0) | 0.042 |
| Hyperlipidemia | 651 (89.4) | 179 (92.3) | 472 (88.4) | 0.171 |
| Diabetes mellitus | 333 (45.7) | 115 (59.3) | 218 (40.8) | <0.001 |
| Family history of CAD | 306 (42.0) | 87 (44.8) | 219 (41.0) | 0.351 |
| Prior CVA | 154 (21.2) | 47 (24.2) | 107 (20.0) | 0.262 |
| PAD | 181 (24.9) | 52 (26.8) | 129 (24.2) | 0.526 |
| Prior MI | 337 (46.3) | 102 (52.6) | 235 (44.0) | 0.052 |
| Prior PCI | 469 (64.4) | 136 (70.1) | 333 (62.4) | 0.070 |
| Prior CABG | 154 (21.2) | 44 (22.7) | 110 (20.6) | 0.599 |
| Hemoglobin, g/dL, median (IQR) | 13.20 (12.10, 14.40) | 12.65 (11.43, 13.47) | 13.50 (12.50, 14.70) | <0.001 |
| Hemoglobin <11g/dL | 68 (9.3) | 32 (16.5) | 36 (6.7) | <0.001 |
| Platelets, 103/μL, median (IQR) | 228.00 (185.00, 276.00) | 226.00 (184.00, 267.00) | 229.00 (185.00, 280.00) | 0.450 |
| Creatinine, mg/dL median (IQR) | 0.97 (0.82, 1.17) | 0.99 (0.81, 1.17) | 0.97 (0.82, 1.17) | 0.862 |
| eGFR b , mL/min/1.73 m2, median (IQR) | 81.84 (64.00, 96.89) | 80.00 (60.62, 97.00) | 82.00 (65.07, 96.69) | 0.215 |
| LVEF, median (IQR) | 55.00 (45.00, 60.00) | 55.00 (41.00, 61.00) | 55.00 (45.00, 60.00) | 0.211 |
| CYP2C19 Genotyped, N (%) | ||||
| *1/*1 | 163 (22.4) | 42 (21.6) | 121 (22.7) | 0.120 |
| *1/*17 | 128 (17.6) | 33 (17.0) | 95 (17.8) | |
| *1/*2 | 89 (12.2) | 29 (14.9) | 60 (11.2) | |
| *1/*3 | 1 (0.1) | 0 (0.0) | 1 (0.2) | |
| *17/*17 | 17 (2.3) | 3 (1.5) | 14 (2.6) | |
| *2/*17 | 41 (5.6) | 17 (8.8) | 24 (4.5) | |
| *2/*2 | 7 (1.0) | 3 (1.5) | 4 (0.7) | |
| Missing | 282 (38.7) | 67 (34.5) | 215 (40.3) | |
| CYP2C19 LOF alleles, N (%) | 138 (19.0) | 49 (25.3) | 89 (16.7) | 0.037 |
| Discharge medications, N (%) | ||||
| Aspirin | 609 (83.7) | 171 (88.1) | 438 (82.0) | 0.027 |
| β-blocker | 534 (73.4) | 155 (79.9) | 379 (71.0) | 0.015 |
| ACE inhibitor or ARB | 495 (68.0) | 148 (76.3) | 347 (65.0) | 0.005 |
| Nitrates | 223 (30.6) | 71 (36.6) | 152 (28.5) | 0.057 |
| PPI | 210 (28.8) | 52 (26.8) | 158 (29.6) | 0.522 |
| Statin | 702 (96.4) | 188 (96.9) | 514 (96.3) | 0.846 |
| CCB | 208 (28.6) | 71 (36.6) | 137 (25.7) | 0.034 |
| Oral hypoglycemic | 239 (32.8) | 77 (39.7) | 162 (30.3) | 0.023 |
| Insulin | 127 (17.4) | 50 (25.8) | 77 (14.4) | 0.001 |
| OAC | 39 (5.4) | 11 (5.7) | 28 (5.2) | 0.852 |
| PRU, median (IQR) | 156.00 (100.00, 211.00) | 241.50 (223.00, 267.75) | 128.00 (83.25, 166.00) | <0.001 |
Detailed breakdown includes patients of the following ancestries: American Indian or Alaska Native (n=2), Asian (n=7), other (n=18), or unknown (n=1).
Calculation based on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation refit without adjustment for race. ACE/ARB= Angiotensin-Converting Enzyme Inhibitor/Angiotensin Receptor Blocker; BMI= Body Mass Index; CABG= Coronary Artery Bypass Grafting; CAD= Coronary Artery Disease; CCB= Calcium Channel Blocker; CVA= Cerebrovascular Accident; CYP2C19= Cytochrome P450 2C19; eGFR= Estimated Glomerular Filtration Rate; HPR= High Platelet Reactivity; LVEF= Left Ventricular Ejection Fraction; LOF= Loss-of-Function; MI= Myocardial Infarction; N= Number; PAD= Peripheral Artery Disease; PPI= Proton Pump Inhibitor; PRU= P2Y12 Reaction Units.
Black participants (32.1%) exhibited significantly higher PRU values (183 [IQR 128–238] vs. 144 [IQR 88–195], P<0.001) and a higher prevalence of HPR (39.3% vs. 20.6%, P<0.001) compared to non-Black participants (Figure S2).
Independent predictors of HPR status
Results from univariate analysis are reported in Table S3. Multivariable mixed-effect regression analysis identified several predictors of HPR status (Table S4). The model with the best fit (AIC: 339.2) revealed that Black race (OR 2.06; 95% CI 1.12–3.81; P=0.020), hemoglobin levels (OR 0.60; 95% CI 0.48–0.73; P<0.001), and the presence of an CYP2C19 LOF allele (OR 2.79; 95% CI 1.53–5.20; P=0.001) were independently associated with HPR. (Table 2).
Table 2.
Predictors of HPR according to multivariable mixed-effect regression analysis.
| OR (95% CI) | P-value | |
|---|---|---|
| Female sex | 1.37 (0.67 – 2.50) | 0.316 |
| Black race | 2.06 (1.12 – 3.81) | 0.020 |
| BMI | 1.04 (1.00 – 1.09) | 0.051 |
| Hypertension | 0.80 (0.31 – 2.18) | 0.648 |
| Diabetes mellitus | 1.37 (0.72 – 2.57) | 0.328 |
| Prior CVA | 2.03 (0.98 – 4.24) | 0.058 |
| Hemoglobin, g/dL | 0.60 (0.48 – 0.73) | <0.001 |
| CYP2C19 LOF alleles | 2.79 (1.53 – 5.20) | 0.001 |
BMI = Body Mass Index; CI = Confidence Interval; CVA = Cerebrovascular Accident; IQR = Interquartile Range; LOF = Loss of Function; OR = Odds Ratio.
In the mediation analysis, hemoglobin levels (35.7%, P<0.001) and diabetes mellitus (4.3%, P=0.040) partially mediated the relationship between Black race and HPR status (Table S5). In contrast, hypertension, family history of CAD, creatinine levels, CYP2C19 LOF allele status, and other factors demonstrated minimal or no significant mediation effects. The direct effects of race on HPR status remained strong across all models (P<0.001).
Percutaneous coronary intervention cohort
A total of 2,770 clopidogrel-treated participants from the Precision PCI registry were included in this analysis, of whom 567 (20.5%) self-reported as Black (Figure S3). Other antiplatelet agents, such as cilostazol and dipyridamole, were used in 0.3% of patients, with no significant differences between groups. Clinical characteristics stratified by race are presented in Table 3. MACE occurred at a significantly higher rate in Black clopidogrel-treated participants compared to non-Black clopidogrel-treated participants (13.9 vs. 9.8 per 100 patient-years; adjusted HR 1.47; 95% CI 1.02–2.11); P=0.037) (Figure 2; Table 4). Similar results were observed after Cox model stratification for variables with non-proportional hazards (adjusted HR 1.46; 95% CI 1.01–2.10). Difference in MACE was primarily driven by a higher rate of MI in Black participants compared to non-Black participants (adjusted HR 1.71; 95% CI 1.09–2.67). Clinically significant bleeding rates did not differ between Black and non-Black participants (6.6 vs. 5.0 per 100 patient-years; adjusted HR 1.08; 95% CI 0.65–1.80; P=0.768) (Figure 3; Table 4).
Table 3.
Baseline characteristics in the PCI cohort stratified according to race.
| Overall (n=2,770) | Black (n=567) | Non-Black (n=2,203) | P-value | |
|---|---|---|---|---|
| Age, years, median (IQR) | 64.0 (56.0, 73.0) | 62.0 (54.0, 69.0) | 65.0 (57.0, 74.0) | <0.001 |
| >75, N (%) | 499 (18.0) | 62 (10.9) | 437 (19.8) | <0.001 |
| Female sex, N (%) | 968 (34.9) | 259 (45.7) | 709 (32.2) | <0.001 |
| Race | ||||
| White | 2040 (73.6) | 0 (0.0) | 2040 (92.6) | <0.001 |
| Black | 567 (20.5) | 567 (100.0) | 0 (0.0) | |
| Other or Unknown Racea | 163 (5.9) | 0 (0.0) | 163 (7.4) | |
| Hispanic ethnicity, N (%) | 98 (3.5) | 2 (0.4) | 96 (4.4) | <0.001 |
| BMI, kg/m2, median (IQR) | 29.1 (25.3, 33.5) | 30.4 (25.1, 34.9) | 28.9 (25.3, 33.1) | 0.004 |
| Obesity (BMI≥30), N (%) | 1229 (44.4) | 294 (51.9) | 935 (42.4) | <0.001 |
| Institution | ||||
| University of North Carolina, Chapel Hill | 1135 (41.0) | 246 (43.4) | 889 (40.4) | <0.001 |
| University of Florida, Gainesville | 661 (23.9) | 84 (14.8) | 577 (26.2) | |
| University of Florida, Jacksonville | 555 (20.0) | 127 (22.4) | 428 (19.4) | |
| University of Maryland, Baltimore | 361 (13.0) | 84 (14.8) | 277 (12.6) | |
| University of Illinois Chicago | 58 (2.1) | 26 (4.6) | 32 (1.5) | |
| Current smoker, N (%) | 782 (28.2) | 193 (34.0) | 589 (26.7) | 0.001 |
| PCI Indication b , N (%) | ||||
| STEMI | 479 (17.3) | 91 (16.0) | 388 (17.6) | 0.325 |
| NSTEMI | 816 (29.5) | 185 (32.6) | 631 (28.6) | |
| UA | 605 (21.8) | 122 (21.5) | 483 (21.9) | |
| Stable CAD/Elective | 870 (31.4) | 169 (29.8) | 701 (31.8) | |
| PCI Strategy c , N (%) | ||||
| Drug-eluting stent | 2373 (85.7) | 476 (84.0) | 1897 (86.1) | 0.022 |
| Bare metal stent | 289 (10.4) | 59 (10.4) | 230 (10.4) | |
| PTCA | 108 (3.9) | 32 (5.6) | 76 (3.4) | |
| Medical history, N (%) | ||||
| Diabetes mellitus | 1168 (42.2) | 296 (52.2) | 872 (39.6) | <0.001 |
| Hypertension | 2308 (83.3) | 505 (89.1) | 1803 (81.8) | <0.001 |
| Dyslipidemia | 1844 (66.6) | 360 (63.5) | 1484 (67.4) | 0.091 |
| CKDd | 687 (24.8) | 187 (33.0) | 500 (22.7) | <0.001 |
| Prior MI | 718 (25.9) | 137 (24.2) | 581 (26.4) | 0.309 |
| Prior Revascularization | 1236 (44.6) | 213 (37.6) | 1023 (46.4) | <0.001 |
| Prior Stent | 856 (30.9) | 150 (26.5) | 706 (32.0) | 0.012 |
| Prior CABG | 460 (16.6) | 71 (12.5) | 389 (17.7) | 0.004 |
| Prior PTCA | 70 (2.5) | 14 (2.5) | 56 (2.5) | 0.999 |
| Stroke/TIA | 348 (12.6) | 95 (16.8) | 253 (11.5) | 0.001 |
| PVD | 270 (9.7) | 60 (10.6) | 210 (9.5) | 0.502 |
| Heart failure | 471 (17.0) | 124 (21.9) | 347 (15.8) | 0.001 |
| Atrial fibrillation | 293 (10.6) | 46 (8.1) | 247 (11.2) | 0.039 |
| Gastrointestinal or intracranial hemorrhage | 93 (3.4) | 20 (3.5) | 73 (3.3) | 0.904 |
| Cancer | 159 (5.7) | 25 (4.4) | 134 (6.1) | 0.154 |
| CYP2C19 Genotype, N (%) | ||||
| *1/*1 | 1299 (46.9) | 237 (41.8) | 1062 (48.2) | 0.280 |
| *1/*2 | 364 (13.1) | 82 (14.5) | 282 (12.8) | |
| *1/*17 | 797 (28.8) | 179 (31.6) | 618 (28.1) | |
| *2/*2 | 28 (1.0) | 7 (1.2) | 21 (1.0) | |
| *2/*3 | 0 (0.0) | 0 (0.0) | 0 (0.0) | |
| *2/*17 | 138 (5.0) | 32 (5.6) | 106 (4.8) | |
| *17/*17 | 131 (4.7) | 26 (4.6) | 105 (4.8) | |
| *1/*3 | 3 (0.1) | 0 (0.0) | 3 (0.1) | |
| Othere | 13 (0.5%) | 4 (0.7%) | 9 (0.4%) | 0.563 |
| CYP2C19 LOF alleles, N (%) | 543 (19.6) | 125 (22.0) | 418 (19.0) | 0.113 |
| Discharge medication, N (%) | ||||
| Aspirin | 2697 (97.4) | 549 (96.8) | 2148 (97.5) | 0.452 |
| Statin | 2578 (93.1) | 543 (95.8) | 2035 (92.4) | 0.006 |
| β-blocker | 2367 (85.5) | 491 (86.6) | 1876 (85.2) | 0.424 |
| ACE inhibitor or ARB | 1850 (66.8) | 407 (71.8) | 1443 (65.5) | 0.005 |
| MRA | 124 (4.5) | 33 (5.8) | 91 (4.1) | 0.105 |
| OAC | 310 (11.2) | 59 (10.4) | 251 (11.4) | 0.555 |
| PPI | 900 (32.5) | 164 (28.9) | 736 (33.4) | 0.047 |
Detailed breakdown includes patients of the following ancestries: American Indian or Alaska Native (n=37), Asian (n=22), mixed ancestry (n=4), Native Hawaiian or Other Pacific Islander (n=3), or unknown (n=97).
P-value for comparison of primary PCI indication categories (i.e., STEMI/NSTEMI vs. UA or Stable CAD/Elective) between groups.
P-value for comparison of PCI strategy (i.e., any stent type vs. PTCA) between groups.
CKD was defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2.
Rare CYP2C19 genotypes among Black and non-Black participants are presented in the Supplementary Appendix (Table S6). Data are presented as median [IQR] or number (%). ACE, angiotensin converting enzyme; ARB, angiotensin receptor blocker; BMI, body mass index; CABG, coronary artery bypass grafting; MI, myocardial infarction; MRA, mineralocorticoid receptor antagonist; OAC; oral anticoagulation; PCI, percutaneous coronary intervention; PPI, proton pump inhibitor; PTCA, percutaneous transluminal coronary angioplasty; PVD, peripheral vascular disease; STEMI, ST-segment elevation myocardial infarction; TIA, transient ischemic attack.
Figure 2. Adjusted survival curves for MACE-free survival in clopidogrel-treated participants undergoing PCI stratified according to race.
Survival curves were adjusted for CYP2C19 LOF status, along with the following patient characteristics: age, body mass index, sex, current smoking status, institution; medical history: diabetes; hypertension; dyslipidemia; stroke or transient ischemic attack; heart failure; atrial fibrillation; prior coronary revascularization; chronic kidney disease; receipt of DES or BMS stent for index PCI, and discharge medications: statin; ACE inhibitor or ARB; proton pump inhibitor.
Table 4.
Cardiovascular and bleeding outcomes stratified according to race.
| Outcome | Blacks participants (N=567) | Non-Blacks participants (N=2,203) | Adjusted HRa (95% CI) | P-value | ||
|---|---|---|---|---|---|---|
| No. of events | Event rate per 100 person-year (95% CI) | No. of events | Event rate per 100 person-year (95% CI) | |||
| MACE | 47 | 13.9 (9.9–17.9) | 121 | 9.8 (8.0–11.5) | 1.47 (1.02–2.11) | 0.037 |
| Cardiovascular death | 10 | 3.0 (1.1–4.8) | 43 | 3.5 (2.4–4.5) | 1.06 (0.51–2.24) | 0.872 |
| Myocardial infarction | 32 | 9.5 (6.2–12.7) | 72 | 5.8 (4.5–7.2) | 1.71 (1.09–2.67) | 0.019 |
| Ischemic stroke | 7 | 2.1 (0.5–3.6) | 11 | 0.9 (0.4–1.4) | 1.80 (0.59–5.46) | 0.302 |
| Stent thrombosis | 5 | 1.5 (0.2–2.8) | 22 | 1.8 (1.0–2.5) | 0.65 (0.22–1.90) | 0.429 |
| Clinically significant bleeding | 23 | 6.6 (3.9–9.3) | 63 | 5.0 (3.8–6.3) | 1.08 (0.65–1.80) | 0.768 |
The Cox Proportional Hazards model was adjusted for: CYP2C19 loss-of-function status, age, body mass index, sex, current smoking status, institution; medical history: diabetes; hypertension; dyslipidemia; stroke or transient ischemic attack; heart failure; atrial fibrillation; prior coronary revascularization; chronic kidney disease (defined as estimated glomerular filtration rate <60 mL/min/1.73m2); receipt of drug-eluting or bare metal stent for index PCI, and discharge medications: statin; angiotensin-converting enzyme inhibitor or angiotensin receptor blocker; proton pump inhibitor.
Figure 3. Adjusted survival curves for bleed-free survival in clopidogrel-treated participants undergoing PCI stratified according to race.
Survival curves were adjusted for CYP2C19 LOF status, along with the following patient characteristics: age, body mass index, sex, current smoking status, institution; medical history: diabetes; hypertension; dyslipidemia; stroke or transient ischemic attack; heart failure; atrial fibrillation; prior coronary revascularization; chronic kidney disease; receipt of DES or BMS stent for index PCI, and discharge medications: statin; ACE inhibitor or ARB; proton pump inhibitor.
In the mediation analysis, chronic kidney disease (CKD) contributed the most to the effect of Black race on MACE, mediating 17.2% (P<0.001), followed by prior heart failure, which mediated 7.8% (P<0.001), and prior stroke/transient ischemic attack (TIA), which accounted for 5.9% (P=0.005) (Table S7). CYP2C19 LOF alleles showed no significant mediation effects (P=0.189).
DISCUSSION
The present study provides a comprehensive analysis, incorporating both PD and PCI cohorts, to evaluate the impact of self-reported race on platelet reactivity profiles and clinical outcomes in clopidogrel-treated participants undergoing PCI. Key findings include: 1) Black participants exhibited significantly higher platelet reactivity compared to non-Black participants; 2) Black race independently predicted HPR status, irrespective of clinical variables or CYP2C19 LOF alleles; 3) within one year post-PCI, Black participants had a significantly higher risk of MACE, primarily driven by MI, even after adjustment for clinical variables and CYP2C19 LOF alleles, compared to non-Black participants; and 4) within one year post-PCI, there were no differences in clinically significant bleeding stratified according to race.
Although alternative P2Y12 inhibitors (e.g., prasugrel and ticagrelor) are more potent than clopidogrel in inhibiting platelet aggregation, they carry a higher bleeding risk.1 Moreover, data showing that prasugrel and ticagrelor do not reduce ischemic events but increase bleeding compared with responders to clopidogrel support the rationale for using of genetic testing to guide the selection of P2Y12 inhibitors.12,18,19 Clopidogrel remains the only guideline-recommended P2Y12 inhibitor for stable coronary artery disease, stroke, and peripheral artery disease, making it the most widely used agent.1 The PD response to clopidogrel exhibits significant variability, influenced by clinical and genetic factors, while the impact of non-conventional factors, such as self-reported race, remains uncertain.2,3
Black individuals are generally underrepresented in clinical studies, including those with clopidogrel and CYP2C19 genotype testing.4,5 Prior studies examining race and platelet reactivity have reported mixed results and were limited by small sample sizes and methodological issues.6–8 In particular, two studies assessed platelet reactivity, but the proportion of Black participants was low, and the timing of blood draws for platelet function testing relative to clopidogrel doses was either not described or conducted early after the loading dose, limiting interpretability.7,8
In this study, we included the largest reported PD cohort, consisting of participants on maintenance clopidogrel treatment (≥14 days), with blood sampling standardized using trough levels for consistency. Platelet reactivity was assessed using PRU measured by the VerifyNow system, a Food and Drug Administration-approved test that specifically targets P2Y12 receptor signaling and is supported by extensive clinical evidence.12,20 CYP2C19 genotyping results were available in 61.3%. Additionally, the PCI cohort included over 2,700 participants from five centers with available CYP2C19 genotype data, representing a cohort with a high proportion of Black participants undergoing PCI (n=567) and 1-year follow-up data with adjudicated events.
The CYP2C19 gene is crucial for the PD response of clopidogrel, as it codifies the enzyme that converts clopidogrel to its active metabolite. CYP2C19 LOF allele carriers exhibit lower bioavailability of its active metabolite, reduced platelet inhibition, and an increased risk of adverse cardiovascular outcomes, including stent thrombosis.2 In the PD cohort, Black participants on clopidogrel exhibit higher platelet reactivity and increased rates of HPR. Black race was independently associated with HPR status, even after adjusting for clinical variables and CYP2C19 LOF alleles. Notably, hemoglobin levels and diabetes mellitus partially mediated the relationship between Black race and HPR status, whereas CYP2C19 LOF alleles did not. These findings suggest that the difference in HPR status between Black and non-Black participants is primarily mediated by clinical factors rather than CYP2C19 LOF allele status. Prior studies have showed the role of clinical factors and CYP2C19 LOF allele status as independent risk factors for HPR in clopidogrel treated individuals.3 However, our study is the first large, well-conducted study to propose that self-reported race should be considered an independent risk factor associated with the PD response to clopidogrel.
Genetic variants unrelated to CYP2C19 gene may potentially explain the higher rate of HPR in Black compared to non-Black participants.21–23 Prior translational studies involving healthy volunteers have reported higher platelet reactivity in Black individuals compared to non-Black, attributed to differences in protease-activated receptor 4 (PAR4) reactivity. This finding is potentially linked to increased expression of phosphatidylcholine transfer protein messenger RNA, which correlates with enhanced PAR4-dependent aggregation and calcium mobilization.22,23 Conversely, alterations in the DLK1-DIO3 miRNA cluster are more frequent in White individuals and are associated with decreased PAR4 reactivity.23 Notably, PAR4 forms hetero-oligomers with the P2Y12 receptor, regulating arrestin-2 recruitment and AKT signaling in platelets. Additionally, PAR4 interacts with both P2Y12 and PAR1, a G-protein-coupled receptor primarily activated by thrombin, positioning PAR4 at the center of two critical pathways for platelet activation. Consequently, any alterations in PAR4 reactivity can potentially influence P2Y12 receptor signaling and overall platelet reactivity.21,24 Notably, we recognize that race is a social construct rather than a biological one.25 However, cardiovascular disease disproportionately affects individuals who self-identify as Black.26 Identifying factors such as social determinants of health or genetic influences that contribute to differences in the prevalence of cardiovascular disease, and disparities in outcomes following PCI, as observed in the current study, will be crucial in guiding interventions aimed at reducing health disparities.
In the PCI cohort, we found that Black participants had a significantly higher risk of MACE within 1 year after PCI, even after adjusting for clinical variables and CYP2C19 LOF allele. This difference was primarily driven by MI. Comorbidities such as CKD, prior heart failure, and prior stroke/TIA partially mediated the relationship between Black race and MACE, independent of CYP2C19 LOF allele status. Previously, a pooled analysis of randomized controlled trials reported a higher rate of MACE and MI in Black participants compared to non-Black participants at 1 year after PCI, likely due to a significantly higher burden of comorbidities. However, this analysis included a diverse range of studies and did not evaluate the impact of antiplatelet regimens or CYP2C19 polymorphisms.9 The Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients’ Health Status (TRIUMPH) study examined 1-year outcomes in clopidogrel-treated participants (n=2,062; 20.8% Black) with available CYP2C19 genotyping.6 In the TRIUMPH registry, platelet reactivity was not assessed, and Black participants treated with PCI were underrepresented compared to White participants (77.4% vs. 87.1%).6 In contrast, the outcome data from our study focuses exclusively on participants undergoing PCI and indicates that the increased risk of MACE among clopidogrel-treated Black participants is primarily driven by an elevated risk of MI, potentially attributed to a higher prevalence of HPR and increased reactivity of the P2Y12 receptor signaling pathway. Notably, the association between HPR and subsequent MI is supported by several studies, underscoring the biological plausibility of these findings.20 Of note, our analysis revealed a higher baseline cardiovascular risk among Black participants, including a greater proportion with chronic kidney disease, diabetes, heart failure, and prior stroke/TIA, which partially mediated the overall risk of MACE. Therefore, although our data suggest a potential association between race and both platelet reactivity and MACE, we cannot definitively determine whether these findings are attributable to race itself or to underlying factors such as comorbidities and genetic influences that may be more prevalent in certain racial groups.
Ultimately, within 1-year post-PCI, there was no difference in the rate of clinically significant bleeding between Black and non-Black participants. Prior studies have suggested an association between East Asian race and increased bleeding risk in clopidogrel-treated participants, known as the East Asian paradox, characterized by a lower rate of ischemic events and a higher rate of bleeding events.12,27 Our data suggest that, compared to non-Black races, clopidogrel-tread Black participants exhibit a higher risk of ischemic events without differences in bleeding outcomes. The marginal representation of Asian participants in our study underscore the need for further research to explore potential explanations for these findings.
Limitations
The results of this study should be interpreted considering several limitations. First, the study consists of two independent cohorts, meaning the assessment of platelet reactivity and the outcomes did not occur in the same patients. Second, although all studies were conducted prospectively, the present analysis is retrospective and subject to bias related to the selection criteria of the individual studies. Third, most participants reported as White or Black/African American, limiting the assessment of platelet reactivity and outcomes in other minority groups. Fourth, in the PD cohort, CYP2C19 genotyping data is missing for approximately one-third of the population. Consequently, adjustment for this variable across the entire population was not possible. Ultimately, in the PCI cohort, key variables such as socioeconomic determinants, year of index procedure, and adherence to other guideline-directed medical therapy were not collected, preventing model adjustments for these factors and assessment of their contribution to the observed disparity in outcomes.
CONCLUSION
Black participants treated with clopidogrel exhibit higher platelet reactivity compared to non-Black individuals, with Black race identified as an independent risk factor for HPR, irrespective of clinical risk factors and CYP2C19 LOF allele status. Black participants also had a higher rate of MACE compared to non-Black participants, primarily driven by an increased risk of MI, without significant differences in clinically relevant bleeding. Clinical characteristics, rather than CYP2C19 LOF allele status, appear to mediate the relationship between Black race, HPR, and MACE. Further investigations are needed to confirm these findings and determine whether the use of alternative P2Y₁₂ inhibitors could help overcome the disparities observed in this study.
Supplementary Material
STUDY HIGHLIGHTS.
What is the current knowledge on the topic?
Clopidogrel is the most used P2Y12 receptor inhibitor, but it suffer from significant interindividual variability. Data on the pharmacodynamic and clinical effects of clopidogrel in Black patients are lacking, as this population is under represented in both pharmacodynamic and clinical studies.
What question did this study address?
This study assessed the racial differences in platelet reactivity and clinical outcomes among clopidogrel-treated participants with coronary artery disease undergoing percutaneous revascularization.
What does this study add to our knowledge?
Among patients with coronary artery disease undergoing percutaneous revascularization, Black individuals receiving clopidogrel suffer from significantly higher platelet reactivity compared to non-Black individuals. In addition, Black individuals appear to have significantly higher risk of major adverse cardiovascular events, primarily driven by myocardial infarction in a large cohort of patients (N=2,770).
How might this change clinical pharmacology or translational science?
The present study highlight a significant gap in knowledge in race-based platelet response to clopidogrel, laying the foundation for future genetic, pharmacodynamic and clinical studies aiming to find the best antiplatelet regimens in line with the current standards of personalized medicine, in order to improve overall outcomes in the broad population.
FUNDING
This work was supported by the National Institutes of Health National Heart, Lung, and Blood Institute (R01HL149752), National Human Genome Research Institute (U01HG007269), and National Center for Advancing Translational Sciences (UL1TR002489, UL1TR001427). Spartan Bioscience Inc. (Ottawa, ON) provided the genotyping platforms and kits for initial testing at the University of Florida Health Jacksonville site. Werfen (MA, USA) provided the VerifyNow console and a portion of the P2Y12 cartridges used in this study. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
ABREVIATIONS
- AIC
Akaike Information Criterion
- ASCVD
Atherosclerotic Cardiovascular Disease
- CAD
Coronary Artery Disease
- CKD
Chronic Kidney Disease
- CYP2C19
Cytochrome P450 2C19
- DAPT
Dual Antiplatelet Therapy
- DLK1-DIO3
Delta-Like Homolog 1 and Dio3
- EHR
Electronic Health Record
- GUSTO
Global Use of Strategies to Open Occluded Arteries
- HPR
High Platelet Reactivity
- IQR
Interquartile Range
- LOF
Loss of Function
- MACE
Major Adverse Cardiovascular Events
- MI
Myocardial Infarction
- PAR1
Protease-Activated Receptor 1
- PAR4
Protease-Activated Receptor 4
- PCI
Percutaneous Coronary Intervention
- PD
Pharmacodynamic
- PRU
P2Y12 Reaction Units
- TIA
Transient Ischemic Attack
- TRIUMPH
Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients’ Health Status
Footnotes
CONFLICT OF INTEREST
Dr. Franchi declares that he has received payment as an individual for consulting fee or honoraria from AstraZeneca, Bayer and Sanofi; and institutional payments for grants from PLx Pharma and The Scott R. MacKenzie Foundation. Dr. Cavallari declares that she has received research support from Wefren. Dr. Angiolillo declares that he has received consulting fees or honoraria from Abbott, Amgen, Anthos, AstraZeneca, Bayer, Biosensors, Boehringer Ingelheim, Bristol-Myers Squibb, Chiesi, CSL Behring, Daiichi-Sankyo, Eli Lilly, Faraday, Haemonetics, Janssen, Merck, Novartis, Novo Nordisk, PhaseBio, PLx Pharma, Pfizer, and Sanofi; D.J.A. also declares that his institution has received research grants from Amgen, AstraZeneca, Bayer, Biosensors, CeloNova, CSL Behring, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Idorsia, Janssen, Matsutani Chemical Industry Co., Merck, Novartis, and the Scott R. MacKenzie Foundation. Other authors have nothing to declare.
REFERENCES
- 1.Angiolillo DJ, Galli M, Collet JP, Kastrati A, O’Donoghue ML. Antiplatelet therapy after percutaneous coronary intervention. EuroIntervention. 2022;17:e1371–e1396. doi: 10.4244/EIJ-D-21-00904 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Galli M, Ortega-Paz L, Franchi F, Rollini F, Angiolillo DJ. Precision medicine in interventional cardiology: implications for antiplatelet therapy in patients undergoing percutaneous coronary intervention. Pharmacogenomics. 2022;23:723–737. doi: 10.2217/pgs-2022-0057 [DOI] [PubMed] [Google Scholar]
- 3.Angiolillo DJ, Capodanno D, Danchin N, Simon T, Bergmeijer TO, Ten Berg JM, Sibbing D, Price MJ. Derivation, Validation, and Prognostic Utility of a Prediction Rule for Nonresponse to Clopidogrel: The ABCD-GENE Score. JACC Cardiovasc Interv. 2020;13:606–617. doi: 10.1016/j.jcin.2020.01.226 [DOI] [PubMed] [Google Scholar]
- 4.Nguyen AB, Cavallari LH, Rossi JS, Stouffer GA, Lee CR. Evaluation of race and ethnicity disparities in outcome studies of CYP2C19 genotype-guided antiplatelet therapy. Front Cardiovasc Med. 2022;9:991646. doi: 10.3389/fcvm.2022.991646 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Tunehag KR, Thomas CD, Franchi F, Rossi JS, Keeley EC, Anderson RD, Beitelshees AL, Duarte JD, Gong Y, Kerensky RA, et al. CYP2C19 Genotype Is Associated With Adverse Cardiovascular Outcomes in Black Patients Treated With Clopidogrel Undergoing Percutaneous Coronary Intervention. J Am Heart Assoc. 2024;13:e033791. doi: 10.1161/JAHA.123.033791 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Cresci S, Depta JP, Lenzini PA, Li AY, Lanfear DE, Province MA, Spertus JA, Bach RG. Cytochrome p450 gene variants, race, and mortality among clopidogrel-treated patients after acute myocardial infarction. Circ Cardiovasc Genet. 2014;7:277–286. doi: 10.1161/CIRCGENETICS.113.000303 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Pendyala LK, Torguson R, Loh JP, Devaney JM, Chen F, Kitabata H, Minha S, Barbash IM, Suddath WO, Satler LF, et al. Racial disparity with on-treatment platelet reactivity in patients undergoing percutaneous coronary intervention. Am Heart J. 2013;166:266–272. doi: 10.1016/j.ahj.2013.04.008 [DOI] [PubMed] [Google Scholar]
- 8.Yang G, Alarcon C, Friedman P, Gong L, Klein T, O’Brien T, Nutescu EA, Tuck M, Meltzer D, Perera MA. The Role of Global and Local Ancestry on Clopidogrel Response in African Americans. Pac Symp Biocomput. 2023;28:221–232. [PMC free article] [PubMed] [Google Scholar]
- 9.Golomb M, Redfors B, Crowley A, Smits PC, Serruys PW, von Birgelen C, Madhavan MV, Ben-Yehuda O, Mehran R, Leon MB, et al. Prognostic Impact of Race in Patients Undergoing PCI: Analysis From 10 Randomized Coronary Stent Trials. JACC Cardiovasc Interv. 2020;13:1586–1595. doi: 10.1016/j.jcin.2020.04.020 [DOI] [PubMed] [Google Scholar]
- 10.Kumar A, Ogunnowo GO, Khot UN, Raphael CE, Ghobrial J, Rampersad P, Puri R, Khatri JJ, Reed GW, Krishnaswamy A, et al. Interaction Between Race and Income on Cardiac Outcomes After Percutaneous Coronary Intervention. J Am Heart Assoc. 2022;11:e026676. doi: 10.1161/JAHA.122.026676 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Cavallari LH, Lee CR, Franchi F, Keeley EC, Rossi JS, Thomas CD, Gong Y, McDonough CW, Starostik P, Al Saeed MJ, et al. Precision Antiplatelet Therapy after Percutaneous Coronary Intervention (Precision PCI) Registry - Informing optimal antiplatelet strategies. Clin Transl Sci. 2024;17:e70004. doi: 10.1111/cts.70004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Angiolillo DJ, Galli M, Alexopoulos D, Aradi D, Bhatt DL, Bonello L, Capodanno D, Cavallari LH, Collet JP, Cuisset T, et al. International Consensus Statement on Platelet Function and Genetic Testing in Percutaneous Coronary Intervention: 2024 Update. JACC Cardiovasc Interv. 2024;17:2639–2663. doi: 10.1016/j.jcin.2024.08.027 [DOI] [PubMed] [Google Scholar]
- 13.Cutlip DE, Windecker S, Mehran R, Boam A, Cohen DJ, van Es GA, Steg PG, Morel MA, Mauri L, Vranckx P, et al. Clinical end points in coronary stent trials: a case for standardized definitions. Circulation. 2007;115:2344–2351. doi: 10.1161/CIRCULATIONAHA.106.685313 [DOI] [PubMed] [Google Scholar]
- 14.Garcia-Garcia HM, McFadden EP, Farb A, Mehran R, Stone GW, Spertus J, Onuma Y, Morel MA, van Es GA, Zuckerman B, et al. Standardized End Point Definitions for Coronary Intervention Trials: The Academic Research Consortium-2 Consensus Document. Circulation. 2018;137:2635–2650. doi: 10.1161/CIRCULATIONAHA.117.029289 [DOI] [PubMed] [Google Scholar]
- 15.investigators G An international randomized trial comparing four thrombolytic strategies for acute myocardial infarction. N Engl J Med. 1993;329:673–682. doi: 10.1056/NEJM199309023291001 [DOI] [PubMed] [Google Scholar]
- 16.Management Oo, Budget. Revisions to the standards for the classification of federal data on race and ethnicity. Federal Register. 1997;62:58782–58790. [Google Scholar]
- 17.Lange T, Vansteelandt S, Bekaert M. A simple unified approach for estimating natural direct and indirect effects. Am J Epidemiol. 2012;176:190–195. doi: 10.1093/aje/kwr525 [DOI] [PubMed] [Google Scholar]
- 18.Thomas CD, Franchi F, Rossi JS, Keeley EC, Anderson RD, Beitelshees AL, Duarte JD, Ortega-Paz L, Gong Y, Kerensky RA, et al. Effectiveness of Clopidogrel vs Alternative P2Y(12) Inhibitors Based on the ABCD-GENE Score. J Am Coll Cardiol. 2024;83:1370–1381. doi: 10.1016/j.jacc.2024.02.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pereira NL, Cresci S, Angiolillo DJ, Batchelor W, Capers Qt, Cavallari LH, Leifer D, Luzum JA, Roden DM, Stellos K, et al. CYP2C19 Genetic Testing for Oral P2Y12 Inhibitor Therapy: A Scientific Statement From the American Heart Association. Circulation. 2024;150:e129–e150. doi: 10.1161/CIR.0000000000001257 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Brar SS, ten Berg J, Marcucci R, Price MJ, Valgimigli M, Kim HS, Patti G, Breet NJ, DiSciascio G, Cuisset T, et al. Impact of platelet reactivity on clinical outcomes after percutaneous coronary intervention. A collaborative meta-analysis of individual participant data. J Am Coll Cardiol. 2011;58:1945–1954. doi: 10.1016/j.jacc.2011.06.059 [DOI] [PubMed] [Google Scholar]
- 21.Mumaw MM, Nieman MT. Race differences in platelet reactivity: is protease activated receptor 4 a predictor of response to therapy? Arterioscler Thromb Vasc Biol. 2014;34:2524–2526. doi: 10.1161/ATVBAHA.114.304727 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Tourdot BE, Conaway S, Niisuke K, Edelstein LC, Bray PF, Holinstat M. Mechanism of race-dependent platelet activation through the protease-activated receptor-4 and Gq signaling axis. Arterioscler Thromb Vasc Biol. 2014;34:2644–2650. doi: 10.1161/ATVBAHA.114.304249 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Edelstein LC, Simon LM, Montoya RT, Holinstat M, Chen ES, Bergeron A, Kong X, Nagalla S, Mohandas N, Cohen DE, et al. Racial differences in human platelet PAR4 reactivity reflect expression of PCTP and miR-376c. Nat Med. 2013;19:1609–1616. doi: 10.1038/nm.3385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Yang G, Alarcon C, Chanfreau C, Lee NH, Friedman P, Nutescu E, Tuck M, O’Brien T, Gong L, Klein TE, et al. Investigation of Genomic and Transcriptomic Risk Factors of Clopidogrel Response in African Americans. Clin Pharmacol Ther. 2025. doi: 10.1002/cpt.3552 [DOI] [Google Scholar]
- 25.AlSaeed MJ, Thomas CD, Franchi F, Keeley EC, Duarte JD, Gong Y, Rossi JS, Beitelshees AL, Stouffer GA, Lee CR, et al. Evaluating the Effect of Estimating Renal Function With the CKD-EPI 2021 Equation on the ABCD-GENE Score for Clopidogrel Response Prediction. Clin Pharmacol Ther. 2024;116:1227–1230. doi: 10.1002/cpt.3385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, et al. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation. 2024;149:e347–e913. doi: 10.1161/CIR.0000000000001209 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Zhou X, Angiolillo DJ, Ortega-Paz L. P2Y(12) Inhibitor Monotherapy after Percutaneous Coronary Intervention. J Cardiovasc Dev Dis. 2022;9. doi: 10.3390/jcdd9100340 [DOI] [Google Scholar]
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