Sequential monitoring of clinical trials with correlated responses

This paper demonstrates how the alpha-spending method of Lan & DeMets (1983) can be applied to the generalised estimating equations regression model for correlated data proposed by Liang & Zeger (1986). Under large-sample conditions, the sequential regression parameters are shown to have an independent increments structure, conditional on the amount of Type I error allocated at each interim analysis. We propose and evaluate surrogates for the information fraction, which determines this allocation of Type I error. Data from the Early Treatment Diabetic Retinopathy Study are used to illustrate the proposed methods for ordered polytomous outcomes.