Personalizing the Decision for Prolonged DAPT
What are the factors to help decide on prolonged dual antiplatelet therapy (DAPT) that balance an individual patient’s potential benefits and harms?
The investigators used population-based electronic health records (EHRs) (CALIBER, England, 2000-2010) of patients evaluated 1 year after acute myocardial infarction (MI), and developed (n = 12,694 patients) and validated (n = 5,613) prognostic models for cardiovascular events (cardiovascular death, MI, or stroke) and three different bleeding endpoints. The authors applied trial effect estimates to determine potential benefits and harms of DAPT and the net clinical benefit of individuals. Associations between endpoints and prognostic factors were evaluated using proportional hazard models with Weibull baseline hazards.
Prognostic models for cardiovascular events (c-index, 0.75; 95% confidence interval [CI], 0.74-0.77) and bleeding (c-index, 0.72; 95% CI, 0.67-0.77) were well calibrated: 3-year risk of cardiovascular events was 16.5% overall (5.2% in the lowest- and 46.7% in the highest-risk individuals), while for major bleeding, it was 1.7% (0.3% in the lowest- and 5.4% in the highest-risk patients). For every 10,000 patients treated per year, the authors estimated 249 (95% CI, 228-269) cardiovascular events prevented and 134 (95% CI, 87-181) major bleeding events caused in the highest-risk patients, and 28 (95% CI, 19-37) cardiovascular events prevented and 9 (95% CI, 0-20) major bleeding events caused in the lowest-risk patients. There was a net clinical benefit of prolonged DAPT in 63-99% of patients, depending on how benefits and harms were weighted.
The authors concluded that prognostic models for cardiovascular events and bleeding using population-based EHRs may help to personalize decisions for prolonged DAPT 1 year following acute MI.
This study developed and validated prognostic models providing personalized estimates of risks of major cardiovascular and bleeding events in patients 12 months after an acute MI. There are marked changes in the year following acute MI in the prevalence of major prognostic factors, including heart failure, renal disease, and smoking, with consequent changes in net benefits. Optimal decision making requires thorough evaluation of patients at the time of decision making including up-to-date medical history and biomarkers. Additional studies are needed to validate this model in more recent cohorts with use of newer P2Y12 inhibitors, and focusing its impact on hard clinical outcomes and costs.
Keywords: Acute Coronary Syndrome, Electronic Health Records, Heart Failure, Hemorrhage, Myocardial Infarction, Platelet Aggregation Inhibitors, Primary Prevention, Prognosis, Stroke, Survivors, Vascular Diseases
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