Author + information
- Received February 2, 2018
- Revision received February 22, 2018
- Accepted February 22, 2018
- Published online April 23, 2018.
- Francesca Maria Notarangelo, MDa,
- Giuseppe Maglietta, MScb,c,
- Paola Bevilacqua, MSca,
- Marco Cereda, PhDd,
- Piera Angelica Merlini, MDe,
- Giovanni Quinto Villani, MDf,
- Paolo Moruzzi, MDg,
- Giampiero Patrizi, MDh,
- Guidantonio Malagoli Tagliazucchi, PhDa,b,
- Antonio Crocamo, MDa,
- Angela Guidorossi, MDa,
- Filippo Pigazzani, MD, PhDa,
- Elisa Nicosia, MSca,
- Giorgia Paoli, MDa,
- Marco Bianchessi, PhDd,
- Mario Angelo Comelli, MSci,
- Caterina Caminiti, MScb and
- Diego Ardissino, MDa,∗ ()
- aDivision of Cardiology, Azienda Ospedaliero–Universitaria di Parma, Parma, Italy
- bDivision of Research and Innovation, Azienda Ospedaliero–Universitaria di Parma, Parma, Italy
- cDepartment of Statistics, Computer Science, Applications, Università di Firenze, Florence, Italy
- dST Microelectronics S.R.L., Agrate Brianza, Monza Brianza, Italy
- eDivision of Cardiology, Azienda Ospedaliera, Ospedale Niguarda Cà Granda, Milano, Italy
- fDivision of Cardiology, Azienda Territoriale di Piacenza, Piacenza, Italy
- gDivision of Cardiology, Azienda Territoriale di Parma, Fidenza, Italy
- hDivision of Cardiology, Azienda Territoriale di Modena, Carpi, Italy
- iDepartment of Brain and Behavioural Science, Università di Pavia, Pavia, Italy
- ↵∗Address for correspondence:
Dr. Diego Ardissino, Unità Operativa di Cardiologia, Azienda Ospedaliero–Universitaria di Parma, Via Gramsci 14, 43126 Parma, Italy.
Background Although clopidogrel is still frequently used in patients with acute coronary syndromes (ACS), its efficacy is hampered by interpatient response variability caused by genetic polymorphisms associated with clopidogrel’s metabolism.
Objectives The goal of this study was to evaluate whether selecting antiplatelet therapy (clopidogrel, prasugrel, or ticagrelor) on the basis of a patient’s genetic and clinical characteristics leads to better clinical outcomes compared with the standard of care, which bases the selection on clinical characteristics alone.
Methods Patients hospitalized for ACS were randomly assigned to standard of care or the pharmacogenomic arm, which included the genotyping of ABCB1, CYP2C19*2, and CYP2C19*17 using an ST Q3 system that provides data within 70 min at each patient’s bedside. The patients were followed up for 12 ± 1 month for the primary composite endpoint of cardiovascular death and the first occurrence of nonfatal myocardial infarction, nonfatal stroke, and major bleeding defined according to Bleeding Academic Research Consortium type 3 to 5 criteria.
Results After enrolling 888 patients, the study was prematurely stopped. Clopidogrel was used more frequently in the standard-of-care arm (50.7% vs. 43.3%), ticagrelor in the pharmacogenomic arm (42.6% vs. 32.7%; p = 0.02), and prasugrel was equally used in both arms. The primary endpoint occurred in 71 patients (15.9%) in the pharmacogenomic arm and in 114 (25.9%) in the standard-of-care arm (hazard ratio: 0.58; 95% confidence interval: 0.43 to 0.78; p < 0.001).
Conclusions A personalized approach to selecting antiplatelet therapy for patients with ACS may reduce ischemic and bleeding events. (Pharmacogenetics of Clopidogrel in Patients With Acute Coronary Syndromes [PHARMCLO]; NCT03347435)
Dual antiplatelet therapy with aspirin and a P2Y12 receptor antagonist is the mainstay of treatment of acute coronary syndromes (ACS). Prasugrel and ticagrelor have proved to be superior to clopidogrel in preventing ischemic events but lead to an increased risk of bleeding complications. International guidelines (1–4) strongly suggest using front-line treatment with prasugrel or ticagrelor, and only using clopidogrel if these other drugs are unavailable or contraindicated. However, the use of more potent antiplatelet drugs involves a fundamental trade-off between decreasing the risk of ischemia and increasing the risk of bleeding. For this reason, clopidogrel is frequently chosen in the real world (5–8), but when balancing ischemic/bleeding risks, only the clinical characteristics of individual patients are taken into account.
Clopidogrel leads to substantial variability in patient responses, and this limits its effectiveness (9). In addition to clinical factors, the reasons for this variability include genotypes: loss-of-function or gain-of-function polymorphisms in the cytochrome P450 2C19 gene are frequently observed and are not only responsible for increasing/reducing enzymatic activity, but also for inducing high/low on-treatment platelet reactivity after clopidogrel exposure, both of which affect its effectiveness in preventing ischemic and bleeding events (10–13). Genetic variants of the genes regulating clopidogrel absorption, such as ABCB1, have also been shown to affect clopidogrel bioavailability, on-treatment platelet reactivity, and clinical outcomes (14).
It can therefore be hypothesized that knowing a patient’s genetic profile of clopidogrel metabolism may lead to more personalized, and therefore more efficient, antiplatelet therapy. The present study was designed to test the hypothesis that selecting antiplatelet therapy on the basis of a combination of genetic information and a patient’s clinical characteristics would lead to better clinical outcomes compared with the standard of care based on clinical characteristics alone.
Unselected patients of European ancestry who were hospitalized because of ST-segment elevation or non–ST-segment elevation ACS were considered eligible for enrollment. The diagnosis of ACS was based on the presence of ≥2 of the following criteria: 1) ischemic symptoms at rest lasting >20 min; 2) electrocardiographic changes with ST-segment elevation or depression of at least 1 mm in 2 contiguous leads; and 3) the typical rise and fall of cardiac biomarker troponin I or T levels above the 99th percentile of the upper reference limit.
The major exclusion criteria were as follows: 1) an inability to provide informed consent or follow study procedures; 2) any contraindication to the use of P2Y12 receptor antagonists; 3) a life expectancy of <1 year; 4) thrombolytic therapy within the previous 24 h; 5) enrollment in another randomized trial or observational registry; and 6) prior knowledge of the patients’ ABCB1, CYP2C19*2, or CYP2C19*17 genotype.
The study protocol was approved by the ethics committee of the coordinating center and afterward by the ethics committee of each participating center. All patients provided written informed consent before participating in the trial.
Immediately after the diagnosis of ACS, the patients were randomly assigned to the strategy of selecting a P2Y12 receptor antagonist on the basis of their clinical characteristics plus the genotyping results, or on the basis of their clinical characteristics alone. An automatic telephone randomization system was used to assign the patients to treatment in a 1:1 ratio based on a centralized list. The randomization list was stratified according to diagnosis (ST-segment elevation vs. all the rest) and center by using the SAS PLAN procedure (SAS Institute, Inc., Cary, North Carolina). The investigators had to digitize the patient’s date of birth, diagnosis, and site number by means of an interactive voice system to obtain the assigned allocation. The data were confirmed by e-mail, and the printout was included in the patient’s case report form.
The patients assigned to the strategy that included genotyping underwent genetic testing for ABCB1 3435 (7q21.1; rs1045642), CYP2C19*2 (10q24.1-q24.3; rs4244285), and CYP2C19*17 (10q24.1-q24.3; rs12248560). Blood samples were taken from all of the patients randomized to the pharmacogenomic arm for deoxyribonucleic acid extraction. The genotyping was conducted by using the ST Q3 system, a compact platform enabling the laboratory analysis of deoxyribonucleic acid by means of real-time polymerase chain reaction. The ST Q3 is designed as a low-entry-cost, portable system for foolproof use by unskilled personnel as a point-of-care instrument. The reaction takes place in a disposable lab-on-chip, which is pre-functionalized with all of the required reagents. The user only has to add the sample by means of a simple loading system, after which the disposable device self-seals and provides the results in approximately 70 min (15) (Online Appendix A).
Study procedure and follow-up
The patients randomized to the arm that included genotyping received 1 of the P2Y12 receptor antagonists (clopidogrel, prasugrel, or ticagrelor) on the basis of an algorithm that considered the results of genetic testing in addition to clinical variables. Patients already taking P2Y12 antagonists could be enrolled, but if switching was necessary to implement the protocol, it was not counted as switching. Switching was counted only if it occurred after the selection of the definite P2Y12 receptor antagonist.
It is important to underline that the genetic algorithm was designed to consider the 3 genes simultaneously, but the ultimate decision concerning antiplatelet therapy also took into account the patient’s clinical characteristics and was left to the discretion of the prescribers (Online Appendix A, Online Figure 1).
The clinical variables used to individualize the choice of P2Y12 receptor antagonist were age, weight, ischemic risk, bleeding risk, diabetes, history of stroke/transient ischemic attack or intracranial bleeding, history of bleeding, active bleeding, anemia, and chronic kidney disease.
Given the TRITON-TIMI-38 (Trial to Assess Improvement in Therapeutic Outcomes by Optimizing Platelet Inhibition with Prasugrel—Thrombolysis In Myocardial Infarction-38) trial findings and the exclusion criteria, prasugrel was not prescribed for: 1) patients whose coronary anatomy was unknown; 2) those at high bleeding risk (particularly those with a history of stroke or transient ischemic attack, those >75 years of age, and those with a body weight <60 kg); 3) those receiving fibrinolytic therapy within the previous 24 h; 4) those with active internal bleeding; 5) those with severe liver disease; 6) those taking oral anticoagulant therapy that could not be stopped; or 7) those with known clinically important thrombocytopenia (16).
Given the PLATO (Platelet Inhibition and Patient Outcomes) trial exclusion criteria, ticagrelor was contraindicated in: 1) patients with active pathological bleeding; 2) those with a history of intracranial bleeding; 3) those requiring dialysis; 4) those taking oral anticoagulant therapy that could not be stopped; 5) those with known clinically important thrombocytopenia; 6) those receiving fibrinolytic therapy within the previous 24 h; and 7) those taking concomitant therapy with strong cytochrome P450 3A inhibitors or inducers (17).
In the standard-of-care arm, the decision regarding which P2Y12 receptor antagonist to use was based on clinical characteristics as described earlier and the clinicians’ preference. The patients were followed-up for 12 months by means of outpatient visits or standardized telephone contacts scheduled 1, 6, and 12 ± 1 months after randomization.
The primary endpoint was the composite of cardiovascular death and the first occurrence of nonfatal myocardial infarction, nonfatal stroke, and major bleeding defined according to the Bleeding Academic Research Consortium type 3 to 5 within 12 months of randomization.
The secondary endpoint was the composite of the primary endpoint plus the occurrence of definite or probable stent thrombosis. Secondary non–pre-specified endpoints were the composite of the first occurrence of the ischemic endpoints (cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke) and the composite of the first occurrence of the Bleeding Academic Research Consortium type 3 to 5–defined major bleeding (Online Appendix B).
All of the events were adjudicated by an independent clinical events committee consisting of 3 cardiologists who were unaware of the study group assignments. Two cardiologists reviewed the medical records and, in the case of disagreement, the opinion of the third member was required. Only adjudicated endpoints were considered for the statistical analysis.
The sample size was calculated on the assumption that the cumulative incidence of the primary endpoint in the standard-of-care arm after 12 months would be 25%. Given a relative risk reduction in the pharmacogenomic arm of 20%, 95% power, and a type alpha error of 5%, the calculated sample size was 1,806 patients in each arm.
Descriptive statistics were used to compare the baseline characteristics of the 2 groups to test the randomization process. The primary analysis was based on the intention-to-treat principle. Cox proportional hazards models were used to analyze the data relating to the primary and secondary endpoints. The proportional hazards assumption for the Cox regression model was confirmed by using the Schoenfeld residuals test. An Andersen-Gill intensity model analysis was not pre-specified but was conducted to account for repeated occurrences of all of the components of the primary endpoint during the study period, using a time-dependent model.
The cumulative incidence of the endpoints during the 12 months of follow-up was graphically represented by means of Aalen-Johansen curves, and the significance of the differences between the sub-distribution of the hazards was tested by using the Fine-Gray model. All of the tests were 2-sided at a significance level of 0.05. No interim analysis was performed, and no multiplicity test correction was made. The statistical analyses were made by using the R-package Survival version 2.41-3 and R Statistical software version 3.1.3 (R Foundation for Statistical Computing, Vienna, Austria).
A total of 888 patients were recruited between June 12, 2013, and February 18, 2015. A total of 448 patients were randomized to the pharmacogenomic arm and 440 to the standard-of-care arm. This grouping represents 24.6% of the pre-specified sample size because, on February 18, 2015, the Ethics Committee of Modena (Italy) required that the trial be prematurely stopped and all of the patients followed-up as planned because of the lack of in vitro diagnosis certification for the ST Q3 instrument.
The mean age of the population was 70.9 ± 12.2 years (range 35 to 97 years), with 28.4% of the patients >80 years of age. Virtually all of the patients (98.1%) experienced the typical rise and fall of cardiac markers indicating an acute myocardial infarction, and 96.3% underwent coronary angiography. Seventy-three percent underwent revascularization: 62.2% by means of a percutaneous coronary intervention and 11% by means of coronary artery bypass grafting. All of these characteristics indicate a high-risk study population. The concomitant treatments were those currently used for patients with ACS. The 2 groups were well balanced in terms of the patients’ baseline characteristics (Table 1).
Table 2 shows the genotype distributions of the patients in the pharmacogenomic arm. Briefly, genotyping revealed that 47.1% had at least 1 copy of the ABCB1 3435 allele, and 26.4% were homozygous; 29.2% had at least 1 copy of the loss-of-function CYP2C19*2 allele, and 4.3% were homozygous; and 31.3% had at least 1 copy of the gain-of-function CYP2C19*17 allele, and 7.8% were homozygous.
The distribution of the P2Y12 receptor antagonists used during the acute phase and the 12 months of follow-up in the pharmacogenomic arm was clopidogrel in 43.3% of the patients, prasugrel in 7.6%, and ticagrelor in 42.6%. The corresponding figures in the standard-of-care arm were clopidogrel 50.7%, prasugrel 8.4%, and ticagrelor 32.7%. The difference in the distribution of the treatments with the various P2Y12 receptor antagonists between the 2 arms was statistically significant (p = 0.02). After the selection of the P2Y12 receptor antagonist, 6.8% of the patients in the pharmacogenomic arm and 5.6% in the standard-of-care arm changed their P2Y12 receptor antagonist at least once. Upon discharge, 6.5% of the patients in the pharmacogenomic arm and 8.2% of those in the standard-of-care arm were not receiving any P2Y12 receptor antagonist, mainly because of misdiagnosis, normal coronary angiograms, or the concomitant use of oral anticoagulant agents.
One patient in the pharmacogenomic arm was lost to follow-up. The primary endpoint occurred in 71 patients (15.9%) in the pharmacogenomic arm and 114 (25.9%) in the standard-of-care arm (hazard ratio [HR]: 0.58; 95% confidence interval [CI]: 0.43 to 0.78; p < 0.001) (Central Illustration, Table 3). In patients receiving clopidogrel, the primary endpoint occurred in 48 patients in the pharmacogenomic arm (24.7%) and 79 (35.4%) in the standard-of-care arm (hazard ratio: 0.68; 95% confidence interval: 0.47 to 0.97; p = 0.03) (Figure 1).
Definite or probable stent thrombosis was observed in only 8 patients (3 in the pharmacogenomic arm and 5 in the standard-of-care arm), thus precluding an outcome analysis of this secondary endpoint.
Ischemic endpoints occurred in 58 patients (13%) in the pharmacogenomic arm and 94 (21.4%) in the standard-of-care arm (HR: 0.57; 95% CI: 0.41 to 0.8; p < 0.001) (Figure 2). Bleeding endpoints occurred in 19 patients (4.2%) in the pharmacogenomic arm and 30 (6.8%) in the standard-of-care arm (HR: 0.62; 95% CI: 0.35 to 1.1; p = 0.1) (Figure 3).
Repeated ischemic and bleeding endpoints were also less frequent in the patients randomized to the pharmacogenomic arm: 85 versus 136 endpoints (HR: 0.61; 95% CI: 0.4 to 0.8; p < 0.001).
Over the last 10 years, there have been substantial advances in our understanding of the genetic variability associated with patient responses to clopidogrel treatment (10–14). However, although these genetic associations have been widely replicated and the effect sizes are sufficiently large to be predictive in the clinical setting, there are limited examples of the use of pharmacogenetic data concerning clopidogrel metabolism to guide clinical practice (18–23).
This prospective, randomized multicenter study provides evidence that the use of genomic medicine to select P2Y12 receptor antagonists can be successfully incorporated into the clinical care of patients with ACS. This scenario may be considered one of the most challenging clinical settings in which to use pharmacogenetic data to guide clinical practice because of the urgency of the situation and the need to start drug treatment promptly. In our case, this approach was made feasible by the development of a bedside instrument capable of providing genotype results within 70 min of blood sampling.
In patients with ACS, the selection of a P2Y12 receptor antagonist (clopidogrel, ticagrelor, or prasugrel) is based on their individual clinical characteristics to obtain the best trade-off between ischemic events and bleeding complications. The main finding of the present study is that selecting treatment on the basis of genetic data related to clopidogrel metabolism in addition to considerations concerning the patients’ clinical characteristics may lead to a significantly lower rate of ischemic and bleeding events compared with usual practice.
Although it is relatively easy to explain why knowledge of a patient’s genetic data may lead to a better clinical outcome, it is more difficult to explain the magnitude of this effect. Given the premature discontinuation of the study after the enrollment of only 25% of the planned number of patients, it is possible that the observed differences between the 2 arms may simply be attributable to chance. Alternatively, it is possible that the effect size in our sample size calculation may have simply been underestimated: a retrospective analysis of the TRITON-TIMI-38 trial by Mega et al. (14) showed that the absolute difference in cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke was 7.3% between the most and least favorable ABCB1 and 2C19*2 genetic profile, with a relative difference of 50%. Another possible explanation may be related to the percentage of patients receiving clopidogrel or ticagrelor in the standard-of-care arm. Because ticagrelor proved to be more effective than clopidogrel in the PLATO trial (17), it is possible that some of the benefit observed in the present study may have been related to the more frequent use of clopidogrel in the standard-of-care arm. Finally, the ascertainment bias associated with the single-blind nature of the study may also partially account for the magnitude of the effect size.
Genotype-guided antiplatelet therapy may be seen as an alternative approach to personalized treatment in ACS. Other strategies based on platelet function tests have been evaluated but all have failed to show any significant clinical benefit (24–26), and it is only recently that the de-escalation of antiplatelet therapy has been shown to be not inferior to prasugrel when based on platelet function test results (27). The major limitation of platelet function tests is the great variability of the results, but this limitation can be overcome by genetic testing (28). Two randomized trials of personalized antiplatelet therapy based on the genotyping of Chinese patients undergoing percutaneous coronary interventions have shown a significant reduction in major adverse cardiovascular events (29,30), and our own randomized findings are in line with this outcome, although given the premature discontinuation of the study, no definite conclusion can be drawn. A number of randomized clinical trials with structured and standardized study protocols based on cytochrome P450 2C19 genotyping are ongoing and will soon provide important results that will allow fine-tuning in this field (31).
The findings of this study show that the implementation of multiple genotyping to guide antiplatelet therapy in patients with ACS is feasible across different institutions. Our data also suggest that a more personalized approach to the selection of antiplatelet therapy may lead to a clinically meaningful reduction in ischemic and bleeding complications. Future studies of genotype-guided antiplatelet therapy are required to confirm these data and clarify the cost efficacy of genotyping in the challenging setting of ACS before implementing it in everyday clinical practice.
COMPETENCY IN MEDICAL KNOWLEDGE: Selection of P2Y12 receptor antagonists on the basis of genotype information pertaining to clopidogrel metabolism in addition to clinical variables may improve clinical outcomes in patients with ACS.
TRANSLATIONAL OUTLOOK: Larger prospective studies are needed to confirm the value of incorporating genetic data in the selection of antiplatelet therapy for patients with ACS and those undergoing percutaneous revascularization.
The authors thank all of the study investigators (Online Appendix C) for their sustained commitment to the PHARMCLO trial.
This scientific project was approved by the Health Authority of Regione Emilia Romagna and was supported by “Programma di Ricerca Regione–Università, Regione Emilia Romagna, bando 2010–2012–Area 2 Ricerca per il Governo clinico” (project identification number and title: PRUa2-2010-010, PHARMCLO (Pharmacogenetics of Clopidogrel in Patients With Acute Coronary Syndromes). The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- acute coronary syndrome(s)
- confidence interval
- hazard ratio
- Received February 2, 2018.
- Revision received February 22, 2018.
- Accepted February 22, 2018.
- 2018 American College of Cardiology Foundation
- American College of Emergency Physicians,
- Society for Cardiovascular Angiography and Interventions,
- O’Gara P.T.,
- Kushner F.G.,
- Ascheim D.D.,
- et al.
- Amsterdam E.A.,
- Wenger N.K.,
- Brindis R.G.,
- et al.
- Ibanes B.,
- James S.,
- Agewall S.,
- et al.
- Roffi M.,
- Patrono C.,
- Collet J.P.,
- et al.
- Fan W.,
- Plent S.,
- Prats J.,
- Deliargyris E.N.
- Sahlén A.,
- Varenhorst C.,
- Lagerqvist B.,
- et al.
- Angiolillo D.J.,
- Rollini F.,
- Storey R.F.,
- et al.
- Gurbel P.A.,
- Bliden K.P.,
- Hiatt B.L.,
- et al.
- Hulot J.S.,
- Bura A.,
- Villard E.,
- et al.
- Marziliano N.,
- Notarangelo M.F.,
- Cereda M.,
- et al.
- Peterson J.F.,
- Field J.R.,
- Unertl K.M.,
- et al.
- Cavallari L.H.,
- Lee C.R.,
- Beitelshees A.L.,
- et al.
- Trenk D.,
- Stone G.W.,
- Gawaz M.,
- et al.
- Sibbing D.,
- Aradi D.,
- Jacobshagen C.,
- et al.
- Angiolillo D.J.
- Shen D.L.,
- Wang B.,
- Bai J.,
- et al.
- Moon J.Y.,
- Franchi F.,
- Rollini F.,
- et al.