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

作者：Shrier Ian^*; Christensen Robin; Juhl Carsten; Beyene Joseph

来源：Journal of Clinical Epidemiology, 2016, 80: 57-67.

DOI：10.1016/j.jclinepi.2016.07.012

• Continuous outcomes
• Meta-analysis
• Minimal important difference
• Standardized mean difference
• Ratio of means
• Variance
• Methods

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 MDivim 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 (CoVmm), 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.

• 出版日期2016-12