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

被引:785
|
作者
Nikolakopoulou, Adriani [1 ]
Higgins, Julian P. T. [2 ]
Papakonstantinou, Theodoros [1 ]
Chaimani, Anna [3 ,4 ]
Del Giovane, Cinzia [5 ]
Egger, Matthias [1 ]
Salanti, Georgia [1 ]
机构
[1] Univ Bern, Inst Social & Prevent Med, Bern, Switzerland
[2] Univ Bristol, Bristol Med Sch, Populat Hlth Sci, Bristol, Avon, England
[3] Univ Paris, Res Ctr Epidemiol & Stat, INSERM, Sorbonne Paris Cite,INRA,CRESS,UMR1153, Paris, France
[4] Cochrane France, Paris, France
[5] Univ Bern, Inst Primary Hlth Care BIHAM, Bern, Switzerland
基金
瑞士国家科学基金会;
关键词
DECISION-MAKING; PUBLICATION BIAS; HEALTH-CARE; PHARMACEUTICAL-INDUSTRY; SYSTEMATIC REVIEWS; CLINICAL-RESEARCH; TASK-FORCE; QUALITY; INCONSISTENCY; GRADE;
D O I
10.1371/journal.pmed.1003082
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页数:19
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