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J Clin Epidemiol. 2015 Dec;68(12):1388-96. doi: 10.1016/j.jclinepi.2015.03.015. Epub 2015 Mar 28.

Minimal important change (MIC) based on a predictive modeling approach was more precise than MIC based on ROC analysis.

Author information

1
Department of General Practice and Elderly Care Medicine, EMGO Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands. Electronic address: b.terluin@vumc.nl.
2
Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands.

Abstract

OBJECTIVES:

To present a new method to estimate a "minimal important change" (MIC) of health-related quality of life (HRQOL) scales, based on predictive modeling, and to compare its performance with the MIC based on receiver operating characteristic (ROC) analysis. To illustrate how the new method deals with variables that modify the MIC across subgroups.

STUDY DESIGN AND SETTING:

The new method uses logistic regression analysis and identifies the change score associated with a likelihood ratio of 1 as the MIC. Simulation studies were conducted to investigate under which distributional circumstances both methods produce concordant or discordant results and whether the methods differ in accuracy and precision.

RESULTS:

The "predictive MIC" and the ROC-based MIC were identical when the variances of the change scores in the improved and not-improved groups were equal and the distributions were normal or oppositely skewed. The predictive MIC turned out to be more precise than the ROC-based MIC. The predictive MIC allowed for the testing and estimation of modifying factors such as baseline severity.

CONCLUSION:

In many situations, the newly described MIC based on predictive modeling yields the same value as the ROC-based MIC but with significantly greater precision. This advantage translates to increased statistical power in MIC studies.

KEYWORDS:

Change scores; Health-related quality of life; Likelihood ratio; Minimal important change; Predictive modeling; ROC method

PMID:
25913670
DOI:
10.1016/j.jclinepi.2015.03.015
[Indexed for MEDLINE]

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