Sequential designs for phase III clinical trials incorporating treatment selection

Abstract

Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power.

A Comparison of Methods for Treatment Selection in Seamless Phase II/III Clinical Trials Incorporating Information on Short-Term Endpoints

“…At the end of the second stage, the confirmatory stage, the selected treatment(s) is (are) compared to the control within a formal testing framework, again possibly involving a sequence of interim analyses, based on all data from the selected treatment(s) and the control. Several authors have developed methodology for conducting phase II/III studies that protects the overall type I error rate of the trial (see, e.g., Bauer and Kieser, 1999;Stallard and Todd, 2003;Kelly et al, 2005;Posch et al, 2005;Bretz et al, 2006;Koenig et al, 2008). Reviews of the different approaches are given by Chow et al (2005), Friede and Stallard (2008), Bretz et al (2009), and Stallard and Todd (2011).…”

“…Indeed, there are a number of therapeutic areas where phase II/III seamless adaptive designs have already been implemented. Schmoll et al (2010) describe a pharmaceutical trial in oncology that was designed using the methodology of Stallard and Todd (2003) and Todd and Stallard (2005). Barnes et al (2010) discuss the use of a phase II/III design in chronic obstructive pulmonary disease.…”

Sequential Methods for Clinical Trials

“…Data from both stages feature in the final analysis, and the overall type I error is controlled. Stallard & Todd [52,53] take a similar approach, considering general responses rather than just the binary case, incorporating extra looks into the second pairwise comparison stage, and allowing the selection to be based on a surrogate (See Surrogate Endpoints) rather than the primary response.…”

Optimizing randomized trial designs to distinguish which subpopulations benefit from treatment

“…Methods have been proposed to deal with the multiple testing problem that arises from design adaptations in which the study population, study treatment or study endpoint may be changed (e.g., Thall et al, 1988;Schaid et al, 1990;Bauer & Köhne, 1994;Follmann et al, 1994;Follmann, 1997;Russek-Cohen & Simon, 1997;Kieser et al, 1999;Hommel, 2001;Stallard & Todd, 2003;Sampson & Sill, 2005;Bischoff & Miller, 2005;Jennison & Turnbull, 2006Wang et al, 2007Wang et al, , 2009. In many cases, these methods lead to sharp bounds on familywise Type I error.…”