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基于模型的敏感性分析在利益和危害结局的荟萃分析中结局报告偏倚的分析。

Model-based sensitivity analysis for outcome reporting bias in the meta analysis of benefit and harm outcomes.

机构信息

1 Department of Statistics, University of Warwick, Coventry, UK.

2 Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.

出版信息

Stat Methods Med Res. 2019 Mar;28(3):889-903. doi: 10.1177/0962280217738546. Epub 2017 Nov 14.

Abstract

Outcome reporting bias occurs when outcomes in research studies are selectively reported, the selection being influenced by the study results. For benefit outcomes, we have shown how risk assessments using the Outcome Reporting Bias in Trials risk classification scale can be used to calculate bias-adjusted treatment effect estimates. This paper presents a new and simpler version of the benefits method, and shows how it can be extended to cover the partial reporting and non-reporting of harm outcomes. Our motivating example is a Cochrane systematic review of 12 studies of Topiramate add-on therapy for drug-resistant partial epilepsy. Bias adjustments for partially reported or unreported outcomes suggest that the review has overestimated the benefits and underestimated the harms of the test treatment.

摘要

当研究中的结果被选择性地报告时,就会出现结果报告偏倚,这种选择受到研究结果的影响。对于获益结局,我们已经展示了如何使用试验中的结果报告偏倚风险分类量表进行风险评估,以计算偏倚调整后的治疗效果估计。本文提出了一种新的、更简单的获益方法,并展示了如何将其扩展到涵盖危害结局的部分报告和未报告情况。我们的实例是对托吡酯添加治疗耐药性部分性癫痫的 12 项研究进行的 Cochrane 系统评价。对部分报告或未报告结局的偏倚调整表明,该综述高估了试验治疗的获益,低估了其危害。

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