Journal of biopharmaceutical statistics
-
Substantial heterogeneity in treatment effects across subgroups can cause significant findings in the overall population to be driven predominantly by those of a certain subgroup, thus raising concern on whether the treatment should be prescribed for the least benefitted subgroup. Because of its low power, a nonsignificant interaction test can lead to incorrectly prescribing treatment for the overall population. This article investigates the power of the interaction test and its implications. Also, it investigates the probability of prescribing the treatment to a nonbenefitted subgroup on the basis of a nonsignificant interaction test and other recently proposed criteria.
-
Here, we developed a new dose-finding method that partitions a cohort of patients based on the number of dose combinations within a prespecified acceptable toxicity range in two-agent combination Phase I trials. In the proposed method, patients in the same cohort are partitioned according to several dose combinations, although most of the existing methods allocate patients in the same cohort according to a single-dose combination. We compared the operating characteristics of the proposed and existing methods through simulation studies.
-
Single-arm studies are typically used in phase II of clinical trials, whose main objective is to determine whether a new treatment warrants further testing in a randomized phase III trial. The introduction of randomization in phase II, to avoid the limits of studies based on historical controls, is a critical issue widely debated in the recent literature. We use a Bayesian approach to compare single-arm and randomized studies, based on a binary response variable, in terms of their abilities of reaching the correct decision about the new treatment, both when it performs better than the standard one and when it is less effective. We evaluate how the historical control rate, the total sample size, and the elicitation of the prior distributions affect the decision about which study performs better.
-
Whether confirmatory or exploratory in nature, the investigation of subgroups poses statistical and interpretational challenges, yet these investigations can have important consequences for product licensing, labeling, reimbursement, and prescribing decisions. This article provides a high-level, nontechnical summary of key statistical issues in the analysis of subgroups, with a focus on the regulatory context in which drug development and licensing decisions are made. References to specific aspects of regulatory processes are based on the system in Europe, though it is hoped that the principles outlined can be generally applied to other regulatory regions. ⋯ Investigations into subgroups are unavoidable, yet subgroup analyses suffer from fundamental complications and limitations of which those planning and interpreting clinical trials must be aware. Some areas for further methodological work and an improved methodological framework for the conduct of exploratory subgroup analyses are discussed. Above all, the need for an integrated scientific approach is highlighted.