临床试验
医学
治疗效果
替代医学
边距(机器学习)
重症监护医学
医学物理学
计算机科学
内科学
病理
机器学习
传统医学
作者
Conor Tweed,Matteo Quartagno,Michelle Clements,Rebecca Turner,Andrew Nunn,David Dunn,Ian R. White,Andrew Copas
标识
DOI:10.1136/bmj-2023-078000
摘要
Non-inferiority trials compare the efficacy of a new treatment with an existing one where the new treatment is expected to have broadly similar efficacy to the existing treatment, but where other benefits might make the new treatment desirable. These trials might aim to demonstrate that a new treatment is either an alternative to, or a replacement for, the current treatment. In this article, how treatment comparisons can be based only on efficacy, or on both efficacy and other benefits, is explained, and guidance on how to choose the correct objective for a trial is given. This choice should influence the design of the trial (eg, choosing the non-inferiority margin and secondary outcomes), analysis, and reporting of the trial. Most non-inferiority trials aim to show only that a new treatment is an alternative to the standard of care. Being more transparent about the trial objective, however, could mean that more trials are conducted with an emphasis on the risk-benefit trade-off for a new treatment and generate more clinically meaningful trial results with a greater effect on practice.
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