Flexible analytical methods for adding a treatment arm mid-study to an ongoing clinical trial

Abstract

It is not uncommon to have experimental drugs under different stages of development for a given disease area. Methods are proposed for use when another treatment arm is to be added mid-study to an ongoing clinical trial. Monte Carlo simulation was used to compare potential analytical approaches for pairwise comparisons through a difference in means in independent normal populations including (1) a linear model adjusting for the design change (stage effect), (2) pooling data across the stages, or (3) the use of an adaptive combination test. In the presence of intra-stage correlation (or a non-ignorable fixed stage effect), simply pooling the data will result in a loss of power and will inflate the type I error rate. The linear model approach is more powerful, but the adaptive methods allow for flexibility (re-estimating sample size). The flexibility to add a treatment arm to an ongoing trial may result in cost savings as treatments that become ready for testing can be added to ongoing studies.