Statistical Efficiency in Adaptive Trials from Incorporating Early Endpoint Data

This talk will focus on the statistical efficiencies gained in adaptive clinical trials that include intermediate endpoint values in the estimation of the final endpoint. The early data augments the complete subjects to increase the effective sample size of the analysis population – this sample size improvement is quantifiable. The increased effective sample size leads to improved precision and MSE of the treatment response estimates at the final endpoint time. This precision benefit increases power over a design that only uses completers. Additionally, incorporating longitudinal data in the analysis models produces interim estimates nearer to the estimates available after complete data is available on the subjects enrolled at the interim. Leveraging early endpoint data, and its relationship to the final endpoint, leads to more accurate predictive probabilities, which results in better decision making at interim analyses.

Longitudinal Data

Adaptive Designs

Bayesian

Statistical Efficiency

Simulations