Implementing a Pharmacogenomic-driven Algorithm to Guide Antiplatelet Therapy among Caribbean Hispanics: A Nonrandomized Prospective Cohort Study.

BackgroundAfter percutaneous coronary intervention (PCI), clopidogrel resistant patients are at an increased risk of major adverse cardiovascular and cerebrovascular events (MACCEs). We aimed to assess whether genotype-guided selection of oral antiplatelet drugs using a clinical decision support (CDS) algorithm reduces the occurrence of these ischemic events and improves outcomes among Caribbean Hispanic patients from Puerto Rico, who are underrepresented in clinical pharmacogenomic (PGx)-guided implementation studies. MethodsIndividual platelet function testing (PRU) measures, CYP2C19*2 and PON1 rs662 genotypes, clinical and demographic data from 8 medical facilities were included. Patients were separated into standard of care (SoC) and genotype-guided groups (150 each). Risk scores were calculated based on a previously developed CDS risk prediction algorithm designed to make actionable treatment recommendations for each patient. Alternative therapy with ticagrelor was recommended for patients with a high risk score [≥]2. Statistical associations between patient time free of MACCEs and predictor variables (i.e., treatment groups, risk scores) were tested in this population using Kaplan-Meier survival analyses and Cox proportional-hazards regression models. ResultsMedian age of participants is 67 years; BMI: 27.8; 48% women; 14% smokers; 59% with type-2 diabetes mellitus (T2DM). Among patients with high-risk scores who were free from MACCE events 6 months after coronary stenting, genotype-driven guidance of antiplatelet therapy showed superiority over SoC in terms of reducing the incidence rate of atherothrombotic events. ConclusionsThe clinical utility of our PGx-driven CDS algorithm to reduce the incidence rate of MACCEs among post-PCI Caribbean Hispanic patients on clopidogrel was externally demonstrated. Clinical Trial Registration Unique IdentifierNCT03419325