Abstract

Objectives

This study aimed to empirically compare commonly used statistical models for estimating treatment effects using EuroQol 5-Dimension (EQ-5D) data from randomized clinical trials (RCTs).

Methods

We identified eligible RCTs through Vivli using National Clinical Trial numbers. Trials reporting EQ-5D at baseline and at least 2 follow-ups were included. Treatment effects on EQ-5D utilities or EQ Visual Analog Scale (VAS) were estimated as change from baseline both at the final visit and averaged across visits. We compared 4 commonly used models: linear mixed-effects model (LMM), generalized estimating equations (GEE), mixed-effects Tobit model, and mixed-effects Beta model, in terms of model diagnostics on distributional assumptions, agreements in statistical significance (P .05), and clinical relevance using the minimally important difference.

Results

Thirteen RCTs (n = 120-1841) were included. Baseline mean EQ-5D utilities ranged from 0.596 to 0.772, and EQ VAS scores from 44.5 to 75.5.

Conclusions

Our analyses showed high agreement in statistical significance and clinical relevance across models. Considering model diagnostics, robustness, and practical usability, the LMM might be a reasonable and pragmatic option.