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临床试验设计的信息价值:考虑所有相关对照的重要性。

Value of Information for Clinical Trial Design: The Importance of Considering All Relevant Comparators.

作者信息

Heath Anna, Baio Gianluca, Manolopoulou Ioanna, Welton Nicky J

机构信息

Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.

Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.

出版信息

Pharmacoeconomics. 2024 May;42(5):479-486. doi: 10.1007/s40273-024-01372-0. Epub 2024 Apr 7.

DOI:10.1007/s40273-024-01372-0
PMID:38583100
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11039417/
Abstract

Value of Information (VOI) analyses calculate the economic value that could be generated by obtaining further information to reduce uncertainty in a health economic decision model. VOI has been suggested as a tool for research prioritisation and trial design as it can highlight economically valuable avenues for future research. Recent methodological advances have made it increasingly feasible to use VOI in practice for research; however, there are critical differences between the VOI approach and the standard methods used to design research studies such as clinical trials. We aimed to highlight key differences between the research design approach based on VOI and standard clinical trial design methods, in particular the importance of considering the full decision context. We present two hypothetical examples to demonstrate that VOI methods are only accurate when (1) all feasible comparators are included in the decision model when designing research, and (2) all comparators are retained in the decision model once the data have been collected and a final treatment recommendation is made. Omitting comparators from either the design or analysis phase of research when using VOI methods can lead to incorrect trial designs and/or treatment recommendations. Overall, we conclude that incorrectly specifying the health economic model by ignoring potential comparators can lead to misleading VOI results and potentially waste scarce research resources.

摘要

信息价值(VOI)分析计算通过获取更多信息以降低健康经济决策模型中的不确定性而可能产生的经济价值。VOI已被提议作为研究优先级排序和试验设计的工具,因为它可以突出未来研究在经济上有价值的途径。最近的方法学进展使得在实践中使用VOI进行研究变得越来越可行;然而,VOI方法与用于设计研究(如临床试验)的标准方法之间存在关键差异。我们旨在突出基于VOI的研究设计方法与标准临床试验设计方法之间的关键差异,特别是考虑整个决策背景的重要性。我们给出两个假设示例,以证明VOI方法只有在以下情况下才是准确的:(1)在设计研究时,决策模型中包含所有可行的比较方案;(2)一旦收集到数据并做出最终治疗建议,所有比较方案都保留在决策模型中。在使用VOI方法时,从研究的设计或分析阶段省略比较方案可能会导致错误的试验设计和/或治疗建议。总体而言,我们得出结论,通过忽略潜在的比较方案而错误地指定健康经济模型可能会导致误导性的VOI结果,并可能浪费稀缺的研究资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/7125cbd1364a/40273_2024_1372_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/83f79e0d8946/40273_2024_1372_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/8d2f3817f644/40273_2024_1372_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/7125cbd1364a/40273_2024_1372_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/83f79e0d8946/40273_2024_1372_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/8d2f3817f644/40273_2024_1372_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b2/11039547/7125cbd1364a/40273_2024_1372_Fig3_HTML.jpg

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Value of Information Choices that Influence Estimates: A Systematic Review of Prevailing Considerations.信息价值选择对估计值的影响:系统综述流行考虑因素。
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Use of a random effects meta-analysis in the design and analysis of a new clinical trial.在新临床试验的设计和分析中使用随机效应荟萃分析。
Stat Med. 2018 Dec 30;37(30):4665-4679. doi: 10.1002/sim.7948. Epub 2018 Sep 6.
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