Abstract

Multiplicity is a common issue in clinical drug development and there exists many proposals for the handling of multiple testing in clinical trials. However, the literature on testing procedures for claiming success on at least k out of m tests and the operating characteristics of these procedures is still sparse. Such testing is very relevant in biosimilar drug development, for example, where products have gained regulatory approval in the past, even though not all hypotheses could be rejected. Obviously, simple adjustments for multiplicity like the Bonferroni-adjustment or the Holm-procedure are valid as well for this testing problem, but can be conservative. In this article, we propose simple testing procedures for claiming success on at least k out of m tests which are more powerful than standard procedures while still providing strong control of the family-wise error rate. We illustrate their applicability in practice using an example from biosimilar drug development. In the supplementary materials, we provide proofs of the properties of our testing procedures and demonstrate the superiority of the proposed methodologies using simulations.

摘要

多重性是临床药物开发中的常见问题，并且存在许多关于在临床试验中处理多重检测的建议。然而，在测试程序为声称在至少成功文献ķ出米测试和这些程序的工作特性仍然是稀疏的。此类测试与生物仿制药的开发非常相关，例如，尽管并非所有假设都可以被拒绝，但过去产品已获得监管部门的批准。显然，对多重性的简单调整（如Bonferroni调整或Holm程序）也适用于此测试问题，但可以保守。在这篇文章中，我们提出了至少声称成功简单的测试程序ķ出来的m个测试比标准过程更强大，同时仍然可以很好地控制系列错误率。我们以生物仿制药开发为例，说明它们在实践中的适用性。在补充材料中，我们提供了测试程序特性的证明，并通过仿真证明了所提出方法的优越性。