An Experimental Design for Confirmatory Clinical Trials Testing the Clinical Utility of an Individualization Rule for 2 Treatments.

Abstract

There is a need for efficient and scientifically sound clinical trials that examine the clinical utility of individualized treatment rules (ITRs) that individualize 2 or more medical treatments. These are trials assessing the effectiveness of the medical decision process taking place in the individualization of the treatments, not the effectiveness of the particular treatments involved. We developed a new experimental design for confirming the superiority of an ITR for 2 treatments over decision processes that ignore patient covariates. The design is built on a new published idea, the ITR's individualization potential (IP), which compares the average effect on clinical response (AER) of the ITR with that of treatment without individualization (TWI). The AER of a decision approach compares the expected potential response of a patient treated with the treatment recommended by the approach versus the expected response should the patient be treated with the alternative therapy instead. The IP concept implies a novel way of constructing the control group of our design and testing the ITR's utility. The experimental design provides estimates of the AERs of both the ITR and TWI, which we use to test the individualization potential's statistical significance. In personalized medicine, one of the 2 treatments is often recommended to a subpopulation of lower-frequency patients more difficult to recruit. Thus, as another innovation, our formulation implies convenient sample size calculations that minimize the number of these patients in the total sample size, contrary to traditional methods of powering clinical trials that usually oversample them. Our design usually needs smaller sample sizes than popular designs and has a more appropriate control group. We illustrate calculating sample sizes for a hypothetical ophthalmology clinical trial.