Chambers James D, Naci Huseyin, Wouters Olivier J, Pyo Junhee, Gunjal Shalak, Kennedy Ian R, Hoey Mark G, Winn Aaron, Neumann Peter J
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street, #63, Boston, Massachusetts, 02111, United States of America.
LSE Health and Social Care, Cowdray House, London School of Economics and Political Science Houghton Street, London, WC2A 2AE, United Kingdom.
PLoS One. 2015 Apr 29;10(4):e0121715. doi: 10.1371/journal.pone.0121715. eCollection 2015.
To assess the methodological quality of published network meta-analysis.
Systematic review.
We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological approach, and reporting of findings. We compared studies published in journals with lower impact factors with those published in journals with higher impact factors, studies published prior to January 1st, 2013 with those published after that date, and studies supported financially by industry with those supported by non-profit institutions or that received no support.
The systematic literature search identified 854 citations. Three hundred and eighteen studies met our inclusion criteria. The number of network meta-analyses has grown rapidly, with 48% of studies published since January 2013. The majority of network meta-analyses were supported by a non-profit institution or received no support (68%). We found considerable inconsistencies among reviewed studies. Eighty percent reported search terms, 61% a network diagram, 65% sufficient data to replicate the analysis, and 90% the characteristics of included trials. Seventy percent performed a risk of bias assessment of included trials, 40% an assessment of model fit, and 56% a sensitivity analysis. Among studies with a closed loop, 69% examined the consistency of direct and indirect evidence. Sixty-four percent of studies presented the full matrix of head-to-head treatment comparisons. For Bayesian studies, 41% reported the probability that each treatment was best, 31% reported treatment ranking, and 16% included the model code or referenced publicly-available code. Network meta-analyses published in higher impact factors journals and those that did not receive industry support performed better across the assessment criteria. We found few differences between older and newer studies.
There is substantial variation in the network meta-analysis literature. Consensus among guidelines is needed improve the methodological quality, transparency, and consistency of study conduct and reporting.
评估已发表的网状Meta分析的方法学质量。
系统评价。
我们在医学文献中检索药物的网状Meta分析。我们评估了一般研究特征、研究透明度和可重复性、方法学方法以及结果报告。我们比较了发表在影响因子较低期刊上的研究与发表在影响因子较高期刊上的研究,2013年1月1日前发表的研究与该日期后发表的研究,以及由行业资助的研究与由非营利机构资助或未获得资助的研究。
系统文献检索共识别出854条引文。318项研究符合我们的纳入标准。网状Meta分析的数量增长迅速,自2013年1月以来发表的研究占48%。大多数网状Meta分析由非营利机构资助或未获得资助(68%)。我们发现所审查的研究之间存在相当大的不一致性。80%的研究报告了检索词,61%的研究报告了网络图,65%的研究有足够的数据来重复分析,90%的研究报告了纳入试验的特征。70%的研究对纳入试验进行了偏倚风险评估,40%的研究进行了模型拟合评估,56%的研究进行了敏感性分析。在有闭环的研究中,69%的研究检验了直接和间接证据的一致性。64%的研究展示了两两治疗比较的完整矩阵。对于贝叶斯研究,41%的研究报告了每种治疗为最佳的概率,31%的研究报告了治疗排名,16%的研究包含模型代码或引用了公开可用的代码。发表在影响因子较高期刊上的网状Meta分析以及未获得行业支持的研究在各项评估标准上表现更好。我们发现新旧研究之间差异不大。
网状Meta分析文献存在很大差异。需要指南之间达成共识以提高研究实施和报告的方法学质量、透明度和一致性。