Comparing the use of aggregate data and various methods of integrating individual patient data to network meta-analysis and its application to first-line ART

Abstract

Background The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. Methods Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) – the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. Results IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. Conclusions Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

Is Network Meta-analysis a Revolutionary Statistical Tool for Improving the Reliability of Clinical Trial Results? A Brief Overview and Emerging Issues Arising

“…multinma R package (95) that includes functions for setting up NMA and multilevel meta-regression (ML-NMR) models (96,97). More specifically a suite of tools is used for performing ML-NMR and NMA with individual patient data (IPD) (98,99), aggregate data (AD), or mixtures of both (100,101). A range of results is thus obtained by performing model fitting estimated in a Bayesian framework using the Stan sampler (102, 103).…”

Bayesian network meta-analysis methods for combining individual participant data and aggregate data from single arm trials and randomised controlled trials

“…More recently, multilevel network meta-regression methods have been proposed which extend the population-adjustment methods beyond the two-study case, and also avoid the issue of aggregation bias by using IPD to inform the covariate distributions in the AD model [ 17 ]. Similarly, methods have been proposed which use IPD to estimate regression coefficients for effect modifiers, and synthesise IPD and AD via either a hierarchical model or by constructing empirical prior distributions [ 18 ].…”