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  • 标题:Responsiveness and minimal important differences for patient reported outcomes
  • 本地全文:下载
  • 作者:Dennis A Revicki ; David Cella ; Ron D Hays
  • 期刊名称:Health and Quality of Life Outcomes
  • 印刷版ISSN:1477-7525
  • 电子版ISSN:1477-7525
  • 出版年度:2006
  • 卷号:4
  • 期号:1
  • 页码:70
  • DOI:10.1186/1477-7525-4-70
  • 语种:English
  • 出版社:BioMed Central
  • 摘要:Patient reported outcomes provide the patient's perspective on the effectiveness of treatment. The draft Food and Drug Administration guidance on patient reported outcomes for labeling and promotional claims raises a number of method and measurement issues that require further clarification, including methods of determining responsiveness and minimal important differences. For clinical trials, instruments need to be based on a clear conceptual framework, have evidence supporting content validity and acceptable psychometric qualities. The measures must also have evidence documenting responsiveness and interpretation guidelines (i.e., minimal important difference) to be most useful as effectiveness endpoints in clinical trials. The recommended approach is to estimate the minimal important difference based on several anchor-based methods, with relevant clinical or patient-based indicators, and to examine various distribution-based estimates (i.e., effect size, standardized response mean, standard error of measurement) as supportive information, and then to triangulate on a single value or small range of values for the MID. Confidence in a specific MID value evolves over time and is confirmed by additional research evidence, including clinical trial experience. The MID may vary by population and context, and no one MID will be valid for all study applications involving a PRO instrument. Responsiveness and MID must be demonstrated and documented for the particular study population, and these measurement characteristics are needed for PRO labeling and promotional claims.
  • 关键词:Minimally Important Difference ; Standardize Response Mean ; Clinical Trial Experience ; Effectiveness Endpoint ; Minimally Important Difference Estimate
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