A Systematic Review of Methods for Handling Missing Variance Data in Meta-Analyses of Interventions in Type 2 Diabetes Mellitus

AimsMeta-analysis is of critical importance to decision makers to assess the comparative efficacy and safety of interventions and is integral to health technology assessment. A major problem for the meta-analysis of continuous outcomes is that associated variance data are not consistently reported in trial publications. The omission of studies from a meta-analysis due to incomplete reporting may introduce bias. The objectives of this study are to summarise and describe the methods used for handling missing variance data in meta-analyses in populations with type 2 diabetes mellitus (T2DM).MethodsElectronic databases, Embase, MEDLINE, and the Cochrane Library (accessed June 2015), were systematically searched to identify meta-analyses of interventions in patients with T2DM. Eligible studies included those which analysed the change in HbA1c from baseline.ResultsSixty-seven publications reporting on meta-analyses of change in HbA1c from baseline in T2DM were identified. Approaches for dealing with missing variance data were reported in 41% of publications and included algebraic calculation, trial-level imputation, and no imputation.ConclusionsMeta-analysis publications typically fail to report standardised approaches for dealing with missing variance data. While no particular imputation method is favoured, authors are discouraged from using a no-imputation approach. Instead, authors are encouraged to explore different approaches using sensitivity analyses and to improve the quality of reporting by documenting the methods used to deal with missing variance data.

研究目的 荟萃分析（Meta-analysis）对于决策者评估干预措施的比较疗效与安全性至关重要，亦是卫生技术评估的核心组成部分。针对连续性结局的荟萃分析所面临的一大核心难题，在于相关方差数据在试验文献中并未得到统一报告。因报告不全而将研究排除出荟萃分析，可能引入偏倚。本研究旨在总结并阐述针对2型糖尿病（T2DM）人群的荟萃分析中缺失方差数据的处理方法。
研究方法 本研究于2015年6月系统性检索了电子数据库，包括荷兰医学文摘（Embase）、医学文献分析与检索系统（MEDLINE）及考克兰图书馆（Cochrane Library），以识别针对2型糖尿病患者干预措施的荟萃分析。纳入研究需分析糖化血红蛋白（HbA1c）较基线的变化值。
研究结果 本研究共检索到67篇针对2型糖尿病患者糖化血红蛋白基线变化的荟萃分析文献。其中仅41%的文献报告了缺失方差数据的处理方法，涵盖代数计算法、试验层面插补法与无插补法三类。
研究结论 现有荟萃分析文献通常未标准化报告缺失方差数据的处理方案。尽管尚无最优插补方法被广泛认可，但研究者应避免采用无插补法。取而代之的是，建议通过敏感性分析探索不同处理路径，并完整记录缺失方差数据的处理方法，以提升报告质量。