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CINeMA:一种评估网络荟萃分析结果可信度的方法。

CINeMA: An approach for assessing confidence in the results of a network meta-analysis.

机构信息

Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.

Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

出版信息

PLoS Med. 2020 Apr 3;17(4):e1003082. doi: 10.1371/journal.pmed.1003082. eCollection 2020 Apr.

Abstract

BACKGROUND

The evaluation of the credibility of results from a meta-analysis has become an important part of the evidence synthesis process. We present a methodological framework to evaluate confidence in the results from network meta-analyses, Confidence in Network Meta-Analysis (CINeMA), when multiple interventions are compared.

METHODOLOGY

CINeMA considers 6 domains: (i) within-study bias, (ii) reporting bias, (iii) indirectness, (iv) imprecision, (v) heterogeneity, and (vi) incoherence. Key to judgments about within-study bias and indirectness is the percentage contribution matrix, which shows how much information each study contributes to the results from network meta-analysis. The contribution matrix can easily be computed using a freely available web application. In evaluating imprecision, heterogeneity, and incoherence, we consider the impact of these components of variability in forming clinical decisions.

CONCLUSIONS

Via 3 examples, we show that CINeMA improves transparency and avoids the selective use of evidence when forming judgments, thus limiting subjectivity in the process. CINeMA is easy to apply even in large and complicated networks.

摘要

背景

荟萃分析结果的可信度评估已成为证据综合过程的重要组成部分。我们提出了一种方法学框架,用于评估当比较多种干预措施时,来自网络荟萃分析的结果的置信度,即网络荟萃分析可信度(CINeMA)。

方法

CINeMA 考虑了 6 个领域:(i)研究内偏差,(ii)报告偏差,(iii)间接性,(iv)不精确性,(v)异质性,和(vi)不一致性。判断研究内偏差和间接性的关键是百分比贡献矩阵,它显示了每个研究对网络荟萃分析结果的贡献程度。使用免费提供的网络应用程序可以轻松计算贡献矩阵。在评估不精确性、异质性和不一致性时,我们考虑了这些变异性成分对制定临床决策的影响。

结论

通过 3 个示例,我们表明 CINeMA 提高了透明度,并避免了在形成判断时选择性地使用证据,从而限制了该过程中的主观性。即使在大型和复杂的网络中,CINeMA 也易于应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ad7/7122720/67d8abd4259e/pmed.1003082.g001.jpg

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