为什么用“最小临床重要差异”来解释治疗效果的大小是没有用的。

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Jitendra Ganju
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引用次数: 0

摘要

术语“最小临床重要差异”(MCID)虽然定义为对患者有意义的结果的最小变化,但通常用于解释治疗组之间的差异。正是在这种背景下,讨论了MCID的局限性,其中包括:在其对进行性疾病的定义中忽略了时间的作用;在随机、安慰剂对照、盲法研究中采用开放标签研究衍生的MCID的不适宜性;罕见病试验中MCID的不可靠性;当安慰剂患者也出现MCID时,解释的挑战;未能解释患者群体的差异如何影响MCID(例如,纳入或排除既往治疗的患者);没有认识到真实治疗效果、MCID和功率之间的联系;缺乏对分析方法差异的考虑(例如,缺失数据的程度及其处理方式);以及基于mcid的应答者分析的局限性。因此,建议预先定义一个定制的MCID来解决每个缺陷。如果不能充分解决缺陷,那么建议不参考MCID来解释试验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Why "Minimal Clinically Important Difference" for Interpreting the Magnitude of the Treatment Effect Is Not Useful.

The term "minimal clinically important difference" (MCID), though defined as the smallest change in an outcome that is meaningful to the patient, is often used to interpret differences between treatment groups. It is in this context that the limitations of MCID are discussed, which include: the omission of the role of time in its definition for progressive diseases; the unsuitability of adopting MCID derived from open-label studies for randomized, placebo-controlled, blinded studies; the unreliability of MCID in rare disease trials; challenges in interpretation when placebo patients also achieve MCID; the failure to account for how differences in patient populations affect MCID (e.g., inclusion or exclusion of patients on prior treatment); not recognizing the connection between the true treatment effect, MCID and power; lack of consideration of differences in analysis methods (e.g., the extent of missing data and how it is handled); and the limitations of an MCID-based responder analysis. Therefore, the recommendation made is to prospectively define a customized MCID that addresses each deficit. If the deficits cannot be adequately resolved, then the recommendation is that trial results should be interpreted without reference to MCID.

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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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