TY - JOUR
T1 - Minimal important changes in standard deviation units are highly variable and no universally applicable value can be determined
AU - Tsujimoto, Yasushi
AU - Fujii, Tomoko
AU - Tsutsumi, Yusuke
AU - Kataoka, Yuki
AU - Tajika, Aran
AU - Okada, Yohei
AU - Carrasco-Labra, Alonso
AU - Devji, Tahira
AU - Wang, Yuting
AU - Guyatt, Gordon H.
AU - Furukawa, Toshi A.
N1 - Funding Information:
Funding: The Minimal Important Difference Inventory project was funded in part by the Canadian Institutes of Health Research (CIHR), Knowledge Synthesis grant number DC0190SR. The present study was also funded by Kyoto University School of Public Health Crossover Award.
Funding Information:
Declaration of Competing Interest: Dr Furukawa reports grants and personal fees from Mitsubishi-Tanabe, personal fees from MSD, grants and personal fees from Shionogi, and personal fees from SONY outside the submitted work. In addition, Dr Furukawa has a patent (2020-548587) concerning smartphone Cognitive Behavior Therapy applications pending and intellectual properties for Kokoro-app licensed to Mitsubishi-Tanabe. The other authors have no conflicts of interest to declare. Funding: The Minimal Important Difference Inventory project was funded in part by the Canadian Institutes of Health Research (CIHR), Knowledge Synthesis grant number DC0190SR. The present study was also funded by Kyoto University School of Public Health Crossover Award.
Publisher Copyright:
© 2022
PY - 2022/5
Y1 - 2022/5
N2 - Objectives: This study aims to describe the distribution of anchor-based minimal important change (MIC) estimates in standard deviation (SD) units and examine if the robustness of such estimates depends on the specific SD used or on the methodological credibility of the anchor-based estimates. Design and Setting: We included all anchor-based MIC estimates from studies published in MEDLINE and relevant literature databases upto October 2018. Each MIC was converted to SD units using baseline, endpoint, and change from baseline SDs. We performed a descriptive analysis of MICs in SD units and checked how the distribution would change if MICs with low methodological credibility were excluded from the analysis. Results: We included 1,009 MIC estimates from 182 studies. The medians and interquartile ranges of MICs in SD units were 0.43 (0.25 to 0.69), 0.42 (0.22 to 0.70), and 0.51 (0.28 to 0.78) for baseline, endpoint, and change SD units, respectively. Some MICs were extremely large or small. The distribution did not change significantly after excluding MICs estimated by less credible methods. Conclusions: The size of the universally applicable MIC in SD units could not be determined. Anchor-based MICs in SD units were widely distributed, with more than half in the range of 0.2 to 0.8.
AB - Objectives: This study aims to describe the distribution of anchor-based minimal important change (MIC) estimates in standard deviation (SD) units and examine if the robustness of such estimates depends on the specific SD used or on the methodological credibility of the anchor-based estimates. Design and Setting: We included all anchor-based MIC estimates from studies published in MEDLINE and relevant literature databases upto October 2018. Each MIC was converted to SD units using baseline, endpoint, and change from baseline SDs. We performed a descriptive analysis of MICs in SD units and checked how the distribution would change if MICs with low methodological credibility were excluded from the analysis. Results: We included 1,009 MIC estimates from 182 studies. The medians and interquartile ranges of MICs in SD units were 0.43 (0.25 to 0.69), 0.42 (0.22 to 0.70), and 0.51 (0.28 to 0.78) for baseline, endpoint, and change SD units, respectively. Some MICs were extremely large or small. The distribution did not change significantly after excluding MICs estimated by less credible methods. Conclusions: The size of the universally applicable MIC in SD units could not be determined. Anchor-based MICs in SD units were widely distributed, with more than half in the range of 0.2 to 0.8.
KW - anchor-based method
KW - distribution-based method
KW - effect size
KW - Minimal important change
KW - patient-reported outcome
UR - http://www.scopus.com/inward/record.url?scp=85124708111&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2022.01.017
DO - 10.1016/j.jclinepi.2022.01.017
M3 - Article
C2 - 35091045
AN - SCOPUS:85124708111
SN - 0895-4356
VL - 145
SP - 92
EP - 100
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
ER -