安慰剂效应何时会对网络荟萃分析结果产生影响?

IF 9 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Adriani Nikolakopoulou, Anna Chaimani, Toshi A Furukawa, Theodoros Papakonstantinou, Gerta Rücker, Guido Schwarzer
{"title":"安慰剂效应何时会对网络荟萃分析结果产生影响?","authors":"Adriani Nikolakopoulou, Anna Chaimani, Toshi A Furukawa, Theodoros Papakonstantinou, Gerta Rücker, Guido Schwarzer","doi":"10.1136/bmjebm-2022-112197","DOIUrl":null,"url":null,"abstract":"<p><p>The placebo effect is the 'effect of the simulation of treatment that occurs due to a participant's belief or expectation that a treatment is effective'. Although the effect might be of little importance for some conditions, it can have a great role in others, mostly when the evaluated symptoms are subjective. Several characteristics that include informed consent, number of arms in a study, the occurrence of adverse events and quality of blinding may influence response to placebo and possibly bias the results of randomised controlled trials. Such a bias is inherited in systematic reviews of evidence and their quantitative components, pairwise meta-analysis (when two treatments are compared) and network meta-analysis (when more than two treatments are compared). In this paper, we aim to provide red flags as to when a placebo effect is likely to bias pairwise and network meta-analysis treatment effects. The classic paradigm has been that placebo-controlled randomised trials are focused on estimating the treatment effect. However, the magnitude of placebo effect itself may also in some instances be of interest and has also lately received attention. We use component network meta-analysis to estimate placebo effects. We apply these methods to a published network meta-analysis, examining the relative effectiveness of four psychotherapies and four control treatments for depression in 123 studies.</p>","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":null,"pages":null},"PeriodicalIF":9.0000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10982636/pdf/","citationCount":"0","resultStr":"{\"title\":\"When does the placebo effect have an impact on network meta-analysis results?\",\"authors\":\"Adriani Nikolakopoulou, Anna Chaimani, Toshi A Furukawa, Theodoros Papakonstantinou, Gerta Rücker, Guido Schwarzer\",\"doi\":\"10.1136/bmjebm-2022-112197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The placebo effect is the 'effect of the simulation of treatment that occurs due to a participant's belief or expectation that a treatment is effective'. Although the effect might be of little importance for some conditions, it can have a great role in others, mostly when the evaluated symptoms are subjective. Several characteristics that include informed consent, number of arms in a study, the occurrence of adverse events and quality of blinding may influence response to placebo and possibly bias the results of randomised controlled trials. Such a bias is inherited in systematic reviews of evidence and their quantitative components, pairwise meta-analysis (when two treatments are compared) and network meta-analysis (when more than two treatments are compared). In this paper, we aim to provide red flags as to when a placebo effect is likely to bias pairwise and network meta-analysis treatment effects. The classic paradigm has been that placebo-controlled randomised trials are focused on estimating the treatment effect. However, the magnitude of placebo effect itself may also in some instances be of interest and has also lately received attention. We use component network meta-analysis to estimate placebo effects. We apply these methods to a published network meta-analysis, examining the relative effectiveness of four psychotherapies and four control treatments for depression in 123 studies.</p>\",\"PeriodicalId\":9059,\"journal\":{\"name\":\"BMJ Evidence-Based Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":9.0000,\"publicationDate\":\"2024-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10982636/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Evidence-Based Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjebm-2022-112197\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Evidence-Based Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/bmjebm-2022-112197","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

摘要

安慰剂效应是 "由于参与者相信或期望治疗有效而产生的模拟治疗效果"。虽然安慰剂效应对某些病症可能并不重要,但对另一些病症却有很大作用,主要是当评估的症状是主观症状时。包括知情同意、研究臂数、不良事件发生率和盲法质量在内的一些特征可能会影响对安慰剂的反应,并可能使随机对照试验的结果产生偏差。这种偏差在系统性证据回顾及其定量分析、配对荟萃分析(比较两种治疗方法)和网络荟萃分析(比较两种以上治疗方法)中都会出现。在本文中,我们旨在为安慰剂效应何时可能使配对荟萃分析和网络荟萃分析的治疗效果出现偏差提供警示。传统范式认为,安慰剂对照随机试验的重点是估计治疗效果。然而,在某些情况下,安慰剂效应本身的大小也会引起人们的兴趣,这一点最近也受到了关注。我们使用成分网络荟萃分析来估计安慰剂效应。我们将这些方法应用到已发表的网络荟萃分析中,考察了 123 项研究中四种心理疗法和四种对照疗法对抑郁症的相对疗效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When does the placebo effect have an impact on network meta-analysis results?

The placebo effect is the 'effect of the simulation of treatment that occurs due to a participant's belief or expectation that a treatment is effective'. Although the effect might be of little importance for some conditions, it can have a great role in others, mostly when the evaluated symptoms are subjective. Several characteristics that include informed consent, number of arms in a study, the occurrence of adverse events and quality of blinding may influence response to placebo and possibly bias the results of randomised controlled trials. Such a bias is inherited in systematic reviews of evidence and their quantitative components, pairwise meta-analysis (when two treatments are compared) and network meta-analysis (when more than two treatments are compared). In this paper, we aim to provide red flags as to when a placebo effect is likely to bias pairwise and network meta-analysis treatment effects. The classic paradigm has been that placebo-controlled randomised trials are focused on estimating the treatment effect. However, the magnitude of placebo effect itself may also in some instances be of interest and has also lately received attention. We use component network meta-analysis to estimate placebo effects. We apply these methods to a published network meta-analysis, examining the relative effectiveness of four psychotherapies and four control treatments for depression in 123 studies.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
BMJ Evidence-Based Medicine
BMJ Evidence-Based Medicine MEDICINE, GENERAL & INTERNAL-
CiteScore
8.90
自引率
3.40%
发文量
48
期刊介绍: BMJ Evidence-Based Medicine (BMJ EBM) publishes original evidence-based research, insights and opinions on what matters for health care. We focus on the tools, methods, and concepts that are basic and central to practising evidence-based medicine and deliver relevant, trustworthy and impactful evidence. BMJ EBM is a Plan S compliant Transformative Journal and adheres to the highest possible industry standards for editorial policies and publication ethics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信