Abstract 4016: Does Prasugrel Provide a Clinically Important Treatment Benefit Compared with Clopidogrel? A Bayesian Analysis of TRITON-TIMI 38

Abstract

Background: In contrast to the conventional frequentist analysis, the Bayesian method is ideally suited to provide a quantitative estimate of a given magnitude of treatment benefit or harm. Objective: A reappraisal, with emphasis on both statistical significance and clinical importance, of the recently reported TRITON-TIMI 38 trial that compared prasugrel with clopidogrel in ACS patients scheduled for PCI. Methods: Posterior probabilities (Pr) that the relative difference (d) in benefit and risk is greater than the putative threshold value for clinical importance (d>0% to 20%) were derived from a Bayesian analysis using an uninformative or “agnostic” prior (log mean RR, = 0, SD = 2) and empirical evidence from TRITON-TIMI 38. Results (Table ) : Although the Pr(d>0%) and Pr(d>10%) difference in the primary endpoint are 100% and 97.5%, respectively, the Pr(d>20%), the “minimum clinically important difference” that the study was powered to detect, is only 40%. Similar patterns are observed with all-cause death/MI/CVA. The Pr(d>10%) harm (for either TIMI major or TIMI major plus minor bleeding) exceeds 90%, and Pr (d>20%) harm exceeds 65%. The Pr(d>20%) harm exceeds the Pr(d>20%) benefit. Combining ischemic endpoints and TIMI major bleeding into net clinical benefit, the Pr(d>10%) benefit is <80% and Pr(d>20%) benefit is <5%. If TIMI major plus minor bleeding is included, the probability of net clinical benefit with prasugrel therapy is reduced even further (<5% for d>10% and <1% for d>20%). Conclusions: The probability of clinically important benefit associated with prasugrel treatment in TRITON-TIMI 38 is far less than that implied by conventional statistical significance. Bayesian analysis provides a useful tool in quantifying clinically meaningful difference. Ultimately, the clarity of the balance between “clinically important”, not just “statistically significant”, benefit or harm should influence guideline recommendations and treatment decisions. Bayesian Analysis of TRITON-TIMI 38 Trial