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Abstract：
Conducting sensitivity analyses is an integral part of the systematic review process to explore the robustness of results derived from the primary analysis. When the primary analysis results can be sensitive to assumptions concerning a model\'s parameters (e.g., missingness mechanism to be missing at random), sensitivity analyses become necessary. However, what can be concluded from sensitivity analyses is not always clear. For instance, in a pairwise meta-analysis (PMA) and network meta-analysis (NMA), conducting sensitivity analyses usually boils down to examining how \'similar\' the estimated treatment effects are from different re-analyses to the primary analysis or placing undue emphasis on the statistical significance. To establish objective decision rules regarding the robustness of the primary analysis results, we propose an intuitive index, which uses the whole distribution of the estimated treatment effects under the primary and alternative re-analyses. This novel index is compared to an objective threshold to infer the presence or lack of robustness. In the case of missing outcome data, we additionally propose a graph that contrasts the primary analysis results to those of alternative scenarios about the missingness mechanism in the compared arms. When robustness is questioned according to the proposed index, the suggested graph can demystify the scenarios responsible for producing inconsistent results to the primary analysis. The proposed decision framework is immediately applicable to a broad set of sensitivity analyses in PMA and NMA. We illustrate our framework in the context of missing outcome data in both PMA and NMA using published systematic reviews.
摘要：
进行敏感性分析是系统审查过程的组成部分，以探索从主要分析得出的结果的稳健性。当主要分析结果可能对有关模型参数的假设敏感时(例如，随机缺失的机制)，敏感性分析是必要的。然而,从敏感性分析中可以得出的结论并不总是很清楚的。例如,在成对荟萃分析(PMA)和网络荟萃分析(NMA)中，进行敏感性分析通常归结为检查“相似”的估计治疗效果是如何从不同的重新分析到主要分析或过分强调统计显著性。为了建立有关主要分析结果稳健性的客观决策规则，我们提出了一个直观的索引，它使用主要和替代再分析下估计治疗效果的整体分布。将该新颖指数与客观阈值进行比较以推断鲁棒性的存在或缺乏。在缺少结果数据的情况下，我们还提出了一个图表，将主要分析结果与比较臂中错误机制的替代方案的结果进行对比。当根据建议的指标对稳健性提出质疑时，建议的图可以将负责产生与主要分析不一致的结果的场景揭开神秘面纱。拟议的决策框架立即适用于PMA和NMA中的广泛敏感性分析。我们使用已发表的系统评价，在PMA和NMA缺少结果数据的情况下说明了我们的框架。
