Biomarker driven population enrichment for adaptive oncology trials with time to event endpoints

Abstract

The development of molecularly targeted therapies for certain types of cancers has led to the consideration of population enrichment designs that explicitly factor in the possibility that the experimental compound might differentially benefit different biomarker subgroups. In such designs, enrollment would initially be open to a broad patient population with the option to restrict future enrollment, following an interim analysis, to only those biomarker subgroups that appeared to be benefiting from the experimental therapy. While this strategy could greatly improve the chances of success for the trial, it poses several statistical and logistical design challenges. Because late-stage oncology trials are typically event driven, one faces a complex trade-off between power, sample size, number of events, and study duration. This trade-off is further compounded by the importance of maintaining statistical independence of the data before and after the interim analysis and of optimizing the timing of the interim analysis. This paper presents statistical methodology that ensures strong control of type 1 error for such population enrichment designs, based on generalizations of the conditional error rate approach. The special difficulties encountered with time-to-event endpoints are addressed by our methods. The crucial role of simulation for guiding the choice of design parameters is emphasized. Although motivated by oncology, the methods are applicable as well to population enrichment designs in other therapeutic areas.

Group Sequential and Confirmatory Adaptive Designs in Clinical Trials

“…Suggestions have also been made to construct valid adaptive test statistics including as much information as possible and allowing interim decision making on all collected data for multi-arm and population enrichment designs (Friede et al 2011;Jenkins et al 2011;Mehta et al 2014;Irle and Schäfer 2014;Carreras et al 2015). We describe these very important applications of adaptive designs in more detail in Part III of this book.…”

“…Recently, some proposals were made to overcome the problem that Type I error rate control cannot be guaranteed anymore with the naïve use of the closed adaptive test. Essentially, proposals are either based on a modification of the combination testing principle or the CRP approach (Jenkins et al 2011;Magirr et al 2014a;Mehta et al 2014;Irle and Schäfer 2014;Stallard et al 2014;Carreras et al 2015) or requiring additional assumptions regarding the joint distribution of the primary and the short-term endpoints (Di Scala and Glimm 2011;Stallard 2010). There is intensive ongoing research in this area.…”

Clinical trial designs incorporating predictive biomarkers

“…A more general testing framework for adaptive enrichment was described by Mehta and Gao [44]; specifically, a group sequential design may be modified to alter the number, spacing, and information times of subsequent interim analyses, with potential restriction of enrollment to a sensitive subgroup. A similar approach was described by Mehta et al [45] with specific focus on the challenges associated with time-to-event endpoints used in a sequential enrichment strategy, namely the complex tradeoff between power, sample size, number of events, timing of interim analyses, and study duration. A review of adaptive enrichment methods can be found in an article by Wang and Hung [46].…”

Use of big data in drug development for precision medicine

“…For example, integrating information regarding predictive biomarker-based enrichment of potential drug responders to clinical trials is expected to improve statistical power, while reducing sample size [28]. This approach has been further expanded to a variety of specific scenarios such as two-stage patient enrichment to cope with biomarker misclassification [29] and enrichment for time to event endpoint [30]. Nevertheless, running a clinical trial for each one of drug-target pairs is unrealistic given the vast number of such pairs.…”