Title | Network meta-analysis of randomized clinical trials: reporting the proper summaries. |
Publication Type | Journal Article |
Year of Publication | 2014 |
Authors | Zhang, Jing, Bradley P. Carlin, James D. Neaton, Guoxing G. Soon, Lei Nie, Robert Kane, Beth A. Virnig, and Haitao Chu |
Journal | Clin Trials |
Volume | 11 |
Issue | 2 |
Pagination | 246-62 |
Date Published | 2014 Apr |
ISSN | 1740-7753 |
Keywords | Bayes Theorem, Humans, Meta-Analysis as Topic, Odds Ratio, Randomized Controlled Trials as Topic |
Abstract | BACKGROUND: In the absence of sufficient data directly comparing multiple treatments, indirect comparisons using network meta-analyses (NMAs) can provide useful information. Under current contrast-based (CB) methods for binary outcomes, the patient-centered measures including the treatment-specific event rates and risk differences (RDs) are not provided, which may create some unnecessary obstacles for patients to comprehensively trade-off efficacy and safety measures.PURPOSE: We aim to develop NMA to accurately estimate the treatment-specific event rates.METHODS: A Bayesian hierarchical model is developed to illustrate how treatment-specific event rates, RDs, and risk ratios (RRs) can be estimated. We first compare our approach to alternative methods using two hypothetical NMAs assuming a fixed RR or RD, and then use two published NMAs to illustrate the improved reporting.RESULTS: In the hypothetical NMAs, our approach outperforms current CB NMA methods in terms of bias. In the two published NMAs, noticeable differences are observed in the magnitude of relative treatment effects and several pairwise statistical significance tests from previous report.LIMITATIONS: First, to facilitate the estimation, each study is assumed to hypothetically compare all treatments, with unstudied arms being missing at random. It is plausible that investigators may have selected treatment arms on purpose based on the results of previous trials, which may lead to 'nonignorable missingness' and potentially bias our estimates. Second, we have not considered methods to identify and account for potential inconsistency between direct and indirect comparisons.CONCLUSIONS: The proposed NMA method can accurately estimate treatment-specific event rates, RDs, and RRs and is recommended. |
DOI | 10.1177/1740774513498322 |
Alternate Journal | Clin Trials |
Original Publication | Network meta-analysis of randomized clinical trials: reporting the proper summaries. |
PubMed ID | 24096635 |
PubMed Central ID | PMC3972291 |
Grant List | P30 CA077598 / CA / NCI NIH HHS / United States R01 CA157458 / CA / NCI NIH HHS / United States 1P01CA142538 / CA / NCI NIH HHS / United States R24 HD041041 / HD / NICHD NIH HHS / United States AI103012 / AI / NIAID NIH HHS / United States P01 CA142538 / CA / NCI NIH HHS / United States R21 AI103012 / AI / NIAID NIH HHS / United States 1R01-CA157458-01A1 / CA / NCI NIH HHS / United States |
Network meta-analysis of randomized clinical trials: reporting the proper summaries.
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