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

After 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.

Individual 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.

Median 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.

The 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.

NCT03419325.