{"title":"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。","authors":"Jitendra Ganju","doi":"10.1002/pst.70015","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"24 3","pages":"e70015"},"PeriodicalIF":1.3000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why \\\"Minimal Clinically Important Difference\\\" for Interpreting the Magnitude of the Treatment Effect Is Not Useful.\",\"authors\":\"Jitendra Ganju\",\"doi\":\"10.1002/pst.70015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":19934,\"journal\":{\"name\":\"Pharmaceutical Statistics\",\"volume\":\"24 3\",\"pages\":\"e70015\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmaceutical Statistics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/pst.70015\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceutical Statistics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/pst.70015","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
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.
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.