SEQUENTIAL SAMPLING IN PROSPECTIVE OBSERVATIONAL STUDIES

Many factors must be taken into account when designing an observa-tional study. Unlike controlled studies, observational studies cannot mitigate the effects of confounding through randomization, and such factors should be incorporated into both the study analysis and the study design. Unfortu-nately, there is often little data available on most of these factors at the design stage, rendering it infeasible to reliably postulate the impact of these fac-tors on the treatment effect estimate and precision of such an effect. In this work we demonstrate how failure to account for adjustment covariates in the design stage of observational studies utilizing group sequential designs has deleterious effects on the study's observed power. We do this by constructing a hypothetical study of Alzheimer's disease biomarkers on cognition, using data from the Alzheimer's Disease Neuroimaging Initiative. We then outline a constrained boundaries procedure that uses data collected at interim anal-yses to better estimate variance and correct stopping boundaries to maintain power and type I error, while allowing for early study termination.