Methods for Employing Information About Uncertainty of Ascertainment of Events in Clinical Trials.

BACKGROUND: Uncertain ascertainment of events in clinical trials has been noted for decades. To correct possible bias, Clinical Endpoint Committees (CECs) have been employed as a critical element of trials to ensure consistent and high-quality endpoint evaluation, especially for cardiovascular endpoints. However, the efficiency and usefulness of adjudication have been debated.
METHODS: The multiple imputation (MI) method was proposed to incorporate endpoint event uncertainty. In a simulation conducted to explain this methodology, the dichotomous outcome was imputed each time with subject-specific event probabilities. As the final step, the desired analysis was conducted based on all imputed data. This proposed method was further applied to real trial data from PARADIGM-HF.
RESULTS: Compared with the conventional Cox model with adjudicated events only, the Cox MI method had higher power, even with a small number of uncertain events. It yielded more robust inferences regarding treatment effects and required a smaller sample size to achieve the same power.
CONCLUSIONS: Instead of using dichotomous endpoint data, the MI method enables incorporation of event uncertainty and eliminates the need for categorizing endpoint events. In future trials, assigning a probability of event occurrence for each event may be preferable to a CEC assigning a dichotomous outcome. Considerable resources could be saved if endpoint events can be identified more simply and in a manner that maintains study power.