White Ian R, Quartagno Matteo, Babiker Abdel G, Turner Rebecca M, Parmar Mahesh Kb, Walker A Sarah
MRC Clinical Trials Unit at UCL, London, UK.
Nuffield Department of Clinical Medicine, Oxford, UK.
BMJ Med. 2025 Jun 15;4(1):e000845. doi: 10.1136/bmjmed-2023-000845. eCollection 2025.
Non-inferiority trials aim to show that major disease related outcomes with a new intervention are not importantly worse than with standard care. These trials are useful when the new intervention has some advantages over standard care (eg, toxicity, convenience, or cost). The ability to show non-inferiority, however, is sensitive to the control risk, the outcome frequency under standard care. Two control risk problems are described that can make non-inferiority trials underpowered or uninterpretable, and two ways of tackling these problems are outlined. Firstly, the choice of effect measure used to express the non-inferiority margin is critical: the effect measure must be based on understanding both the clinical setting and the implications for sample size. Which effect measures can lead to smaller or larger sample sizes is shown. Secondly, investigators need to consider, and potentially plan for, the possibility that the observed control risk might differ from the anticipated risk at the design stage of the trial. How the non-inferiority margin can be adapted in the trial analysis in a statistically principled manner is shown.
非劣效性试验旨在表明，新干预措施的主要疾病相关结局并不比标准治疗差很多。当新干预措施相对于标准治疗具有某些优势（如毒性、便利性或成本）时，这些试验很有用。然而，显示非劣效性的能力对对照风险（即标准治疗下的结局频率）很敏感。描述了两个可能导致非劣效性试验效能不足或无法解释的对照风险问题，并概述了处理这些问题的两种方法。首先，用于表达非劣效性界值的效应量选择至关重要：效应量必须基于对临床背景和样本量影响的理解。展示了哪些效应量会导致较小或较大的样本量。其次，研究人员需要考虑，并可能在试验设计阶段就为观察到的对照风险可能与预期风险不同的可能性制定计划。展示了如何在试验分析中以统计学原则的方式调整非劣效性界值。
