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作者信息

Lynggaard Helle, Keene Oliver N, Mütze Tobias, Rehal Sunita

机构信息

Novo Nordisk A/S, Bagsvaerd, Denmark.

KeeneONStatistics, Maidenhead, UK.

出版信息

Pharm Stat. 2024 Nov-Dec;23(6):1156-1165. doi: 10.1002/pst.2433. Epub 2024 Aug 8.

Abstract

Most published applications of the estimand framework have focused on superiority trials. However, non-inferiority trials present specific challenges compared to superiority trials. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use notes in their addendum on estimands and sensitivity analysis in clinical trials that there may be special considerations to the implementation of estimands in clinical trials with a non-inferiority objective yet provides little guidance. This paper discusses considerations that trial teams should make when defining estimands for a clinical trial with a non-inferiority objective. We discuss how the pre-addendum way of establishing non-inferiority can be embraced by the estimand framework including a discussion of the role of the Per Protocol analysis set. We examine what clinical questions of interest can be formulated in the context of non-inferiority trials and outline why we do not think it is sensible to describe an estimand as 'conservative'. The impact of the estimand framework on key considerations in non-inferiority trials such as whether trials should have more than one primary estimand, the choice of non-inferiority margin, assay sensitivity, switching from non-inferiority to superiority and estimation are discussed. We conclude by providing a list of recommendations, and important considerations for defining estimands for trials with a non-inferiority objective.

摘要

大多数已发表的估计量框架应用都集中在优效性试验上。然而,与优效性试验相比,非劣效性试验存在一些特殊挑战。人用药品技术要求国际协调理事会在其关于临床试验中估计量和敏感性分析的附录中指出,在以非劣效性为目标的临床试验中实施估计量时可能需要特殊考虑,但几乎没有提供指导。本文讨论了试验团队在为非劣效性临床试验定义估计量时应考虑的因素。我们讨论了估计量框架如何采用确立非劣效性的附录前方法,包括对符合方案分析集作用的讨论。我们研究了在非劣效性试验背景下可以提出哪些感兴趣的临床问题,并概述了为什么我们认为将估计量描述为“保守的”是不明智的。讨论了估计量框架对非劣效性试验中关键考虑因素的影响,如试验是否应具有多个主要估计量、非劣效性界值的选择、分析敏感性、从非劣效性转换为优效性以及估计。我们通过提供一份建议清单以及为非劣效性目标试验定义估计量的重要考虑因素来得出结论。

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