Typical analyses of clinical trials involve intervention comparisons for each efficacy and safety outcome. Outcome-specific effects are tabulated and potentially combined in benefit:risk analyses with the belief that such analyses inform the totality of effects on patients. However such approaches do not incorporate associations between outcomes of interest, suffer from competing risk challenges, and since efficacy and safety analyses are conducted on different analysis populations, the population to which these benefit:risk analyses apply, is unclear.
This deficit can be remedied with more thoughtful benefit:risk evaluation with a pragmatic focus. Critical components of this vision include: (i) using outcomes to analyze patients rather than patients to analyze outcomes, (ii) incorporating patient values, and (iii) evaluating personalized effects. Crucial to this approach entails improved understanding of how to analyze one patient before analyzing many. Newly developed approaches to the design and analyses of trials such as partial credit and the desirability of outcome ranking (DOOR), are being implemented to more optimally inform patient treatment.