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解读和评估网状荟萃分析结果的可信度:临床医生的入门指南。

Interpreting and assessing confidence in network meta-analysis results: an introduction for clinicians.

机构信息

Program in Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Canada.

Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, 555 University Ave, #2211, Toronto, ON, M5G 1X8, Canada.

出版信息

J Anesth. 2022 Aug;36(4):524-531. doi: 10.1007/s00540-022-03072-5. Epub 2022 Jun 1.


DOI:10.1007/s00540-022-03072-5
PMID:35641661
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9338903/
Abstract

PURPOSE: We aimed to provide clinicians with introductory guidance for interpreting and assessing confidence in on Network meta-analysis (NMA) results. METHODS: We reviewed current literature on NMA and summarized key points. RESULTS: Network meta-analysis (NMA) is a statistical method for comparing the efficacy of three or more interventions simultaneously in a single analysis by synthesizing both direct and indirect evidence across a network of randomized clinical trials. It has become increasingly popular in healthcare, since direct evidence (head-to-head randomized clinical trials) are not always available. NMA methods are categorized as either Bayesian or frequentist, and while the two mostly provide similar results, the two approaches are theoretically different and require different interpretations of the results. CONCLUSIONS: We recommend a careful approach to interpreting NMA results and the validity of an NMA depends on its underlying statistical assumptions and the quality of the evidence used in the NMA.

摘要

目的:为临床医生提供解读和评估网状meta 分析(NMA)结果可信度的入门指导。

方法:我们回顾了当前关于 NMA 的文献,并总结了要点。

结果:网状meta 分析(NMA)是一种统计方法,可通过综合多个随机临床试验网络中的直接和间接证据,在单次分析中同时比较三种或更多干预措施的疗效。由于直接证据(头对头随机临床试验)并不总是可用,因此它在医疗保健中越来越受欢迎。NMA 方法分为贝叶斯或频率派,虽然两者主要提供相似的结果,但两种方法在理论上有所不同,需要对结果进行不同的解释。

结论:我们建议谨慎解读 NMA 结果,并且 NMA 的有效性取决于其基础统计假设和 NMA 中使用的证据质量。

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本文引用的文献

[1]
Steroid treatment in patients with acute respiratory distress syndrome: a systematic review and network meta-analysis.

J Anesth. 2022-2

[2]
Effects of individualized positive end-expiratory pressure combined with recruitment maneuver on intraoperative ventilation during abdominal surgery: a systematic review and network meta-analysis of randomized controlled trials.

J Anesth. 2022-4

[3]
Predictive P-score for treatment ranking in Bayesian network meta-analysis.

BMC Med Res Methodol. 2021-10-17

[4]
Effects of intrathecal opioids on cesarean section: a systematic review and Bayesian network meta-analysis of randomized controlled trials.

J Anesth. 2021-12

[5]
Understanding Network Meta-analysis (NMA) Conclusions Requires Scrutiny of Methods and Results: Introduction to NMA and the Geometry of Evidence.

Arthroscopy. 2021-7

[6]
Big Data in Studying Acute Pain and Regional Anesthesia.

J Clin Med. 2021-4-1

[7]
Comparison of PECS II and erector spinae plane block for postoperative analgesia following modified radical mastectomy: Bayesian network meta-analysis using a control group.

J Anesth. 2021-10

[8]
Assessing the confidence in network meta-analysis results.

Am J Emerg Med. 2021-3

[9]
When does the use of individual patient data in network meta-analysis make a difference? A simulation study.

BMC Med Res Methodol. 2021-1-13

[10]
Determining Associations and Estimating Effects with Regression Models in Clinical Anesthesia.

Anesthesiology. 2020-9

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