Violations of the independent increment assumption when using generalized estimating equation in longitudinal group sequential trials

In phase 3 clinical trials, ethical and financial concerns motivate sequential analyses in which the data are analyzed prior to completion of the entire planned study. Existing group sequential software accounts for the effects of these interim analyses on the sampling density by assuming that the contribution of subsequent increments is independent of the contribution from previous data. This independent increment assumption is satisfied in many common circumstances, including when using the efficient estimator. However, certain circumstances may dictate using an inefficient estimator, and the independent increment assumption may then be violated. Consequences of assuming independent increments in a setting where the assumption does not hold have not been previously explored. One important setting in which independent increments may not hold is the setting of longitudinal clinical trials. This paper considers dependent increments that arise because of heteroscedastic and correlated data in the context of longitudinal clinical trials that use a generalized estimating equation (GEE) approach. Both heteroscedasticity over time and correlation of observations within subjects may lead to departures from the independent increment assumption when using GEE. We characterize situations leading to greater departures in this paper. Despite violations of the independent increment assumption, simulation results suggest that operating characteristics of sequential designs are largely maintained for typically observed patterns of accrual, correlation, and heteroscedasticity even when using analyses that use standard software that depends on an independent increment structure. More extreme scenarios may require greater care to avoid departures from the nominal type I error rate and power. Copyright © 2014 John Wiley & Sons, Ltd.