Dataset Information

Borrowing of strength from indirect evidence in 40 network meta-analyses.

ABSTRACT: OBJECTIVES:Network meta-analysis (NMA) is increasingly being used to synthesize direct and indirect evidence and help decision makers simultaneously compare multiple treatments. We empirically evaluate the incremental gain in precision achieved by incorporating indirect evidence in NMAs. STUDY DESIGN AND SETTING:We performed both network and pairwise meta-analyses on 40 published data sets of multiple-treatment comparisons. Their results were compared using the recently proposed borrowing of strength (BoS) statistic, which quantifies the percentage reduction in the uncertainty of the effect estimate when adding indirect evidence to an NMA. RESULTS:We analyzed 915 possible treatment comparisons, from which 484 (53%) had no direct evidence (BoS = 100%). In 181 comparisons with only one study contributing direct evidence, NMAs resulted in reduced precision (BoS < 0) and no appreciable improvements in precision (0 < BoS < 30%) for 104 (57.5%) and 23 (12.7%) comparisons, respectively. In 250 comparisons with at least two studies contributing direct evidence, NMAs provided increased precision with BoS ? 30% for 166 (66.4%) comparisons. CONCLUSION:Although NMAs have the potential to provide more precise results than those only based on direct evidence, the incremental gain may reliably occur only when at least two head-to-head studies are available and treatments are well connected. Researchers should routinely report and compare the results from both network and pairwise meta-analyses.

SUBMITTER: Lin L

PROVIDER: S-EPMC6338506 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Borrowing of strength from indirect evidence in 40 network meta-analyses.

Lin Lifeng L Xing Aiwen A Kofler Michael J MJ Murad Mohammad Hassan MH

Journal of clinical epidemiology 20181017

<h4>Objectives</h4>Network meta-analysis (NMA) is increasingly being used to synthesize direct and indirect evidence and help decision makers simultaneously compare multiple treatments. We empirically evaluate the incremental gain in precision achieved by incorporating indirect evidence in NMAs.<h4>Study design and setting</h4>We performed both network and pairwise meta-analyses on 40 published data sets of multiple-treatment comparisons. Their results were compared using the recently proposed b ...[more]

PMID: 30342086

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Project description:Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes.The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations.Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis.Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

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Project description:BackgroundBrexanolone injection, the first therapy approved by the US FDA for the treatment of postpartum depression (PPD) in adults, has been shown to produce a significantly greater decrease in the Hamilton Rating Scale for Depression (HAM-D) total score than placebo in randomised controlled trials (RCTs) of women with PPD.ObjectivesGiven the rapid effect of brexanolone injection (within 60 h) sustained throughout the length of the trials (30 days), we sought to compare its efficacy data against selective serotonin reuptake inhibitors (SSRIs), the class of antidepressants most commonly prescribed for PPD, using HAM-D and Edinburgh Postnatal Depression Scale (EPDS) outcomes from currently available RCTs.MethodsWe extracted data from 26 studies identified in a systematic literature review of pharmacological and pharmacological/nonpharmacological combination therapies in PPD. Six studies were suitable to form evidence networks through which to perform indirect treatment comparisons (ITCs) of HAM-D and EPDS outcomes between brexanolone and SSRIs. Having assessed the comparability and suitability of the available evidence for analysis, we discovered significant heterogeneity in the study designs, most notably in the placebo arms of the trials. We therefore conducted matching-adjusted indirect comparisons (MAICs) between brexanolone and the placebo arms of comparator studies, subsequently using the MAIC results of brexanolone versus placebo, and results for SSRIs versus placebo, to form ITCs of brexanolone versus SSRIs at three separate time points-day 3, week 4 and last observation. ITCs were calculated as the differences in change from baseline (CFB) in HAM-D and, separately, CFB in EPDS, between treatments, and reported with 95% confidence intervals (CIs).ResultsFor all time points, MAICs showed larger differences in CFB for brexanolone compared with SSRIs. Differences (95% CIs) between brexanolone and SSRIs were 12.79 (8.04-17.53) [day 3], 5.87 (- 1.62 to 13.37) [week 4] and 0.97 (- 6.35 to 8.30) [last observation] for the HAM-D. For the EPDS, the differences in CFB were 7.98 (5.32-10.64) [day 3], 6.35 (3.13-9.57) [week 4] and 4.05 (0.79-7.31) [last observation]. Other analytical approaches are also presented to demonstrate the similarity of results, using a network meta-analysis approach, and the importance of using the MAIC method to control for the important heterogeneity between placebo arms.ConclusionsAcknowledging the limitations of ITCs and this evidence base, when compared with SSRIs, these analyses suggest that brexanolone demonstrated larger differences in CFB for both patient- and clinician-reported PPD outcomes and at all investigated time points after adjusting for differences between placebos in the included studies.

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Borrowing of strength from indirect evidence in 40 network meta-analyses.

Publications

Borrowing of strength from indirect evidence in 40 network meta-analyses.

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