Meta-analysis on continuous outcomes in minimal important difference units: an application with appropriate variance calculations.

Abstract

OBJECTIVE To compare results from meta-analyses for mean differences in minimal important difference (MID) units (MDMID), when MID is treated as a random variable vs. a constant. STUDY DESIGN AND SETTING Meta-analyses of published data. We calculated the variance of MDMID as a random variable using the delta method and as a constant. We assessed performance under different assumptions. We compare meta-analysis results from data originally used to present the MDMID and data from osteoarthritis studies using different domain instruments. RESULTS Depending on the data set and depending on the values of rho and coefficient of variation of the MID (CoVMID), estimates of treatment effect and P-values between an approach considering the MID as a constant vs. as a random variable may differ appreciably. Using our data sets, we provide examples of the potential magnitude. When rho = 0.5 and CoVMID = 0.8, considering MID as a constant overestimated the treatment effect by 33-110% and decreased the P-value for heterogeneity from above 0.95 to below 0.08. When rho = 0.8 and CoVMID = 0.5, the magnitude of the effects was similar. CONCLUSIONS Considering MID as a random variable avoids unrealistic assumptions and provides more appropriate treatment effect estimates.

DOI: 10.1016/j.jclinepi.2016.07.012

Cite this paper

@article{Shrier2016MetaanalysisOC, title={Meta-analysis on continuous outcomes in minimal important difference units: an application with appropriate variance calculations.}, author={Ian Shrier and Torben Grube Christensen and Carsten Bogh Juhl and Joseph Beyene}, journal={Journal of clinical epidemiology}, year={2016}, volume={80}, pages={57-67} }