A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis

Abstract

Objectives: To compare meta-analysis of summary study level data with the equivalent individual patient data (IPD) analysis when interest lies in identification of binary patient characteristics related to treatment efficacy.

Design: A simulation study comparing meta-regression with IPD analyses of randomized controlled trials.

Methods: Twenty-seven different meta-analysis situations were simulated with 1000 repetitions in each case. The following parameters were varied: (1) the treatment effect magnitude for different patient risk groups; (2) sample sizes of individual studies; and (3) number of studies. The meta-regression and IPD results were then compared for each situation.

Results: The statistical power of meta-regression was dramatically and consistently lower than that of IPD analysis, with little agreement between the parameter estimates obtained from the two methods. Only in meta-analyses of large numbers of large trials, did meta-regression detect differential treatment effects between risk groups with any consistency.

Conclusions: Meta-analysis of summary data may be adequate when estimating a single pooled treatment effect or investigating study level characteristics. However, when interest lies in investigating whether patient characteristics are related to treatment, IPD analysis will generally be necessary to discover any such relationships. In these situations practitioners should try to obtain individual-level data.