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用于量化替代预后模型净收益的框架。

A framework for quantifying net benefits of alternative prognostic models.

机构信息

Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

出版信息

Stat Med. 2012 Jan 30;31(2):114-30. doi: 10.1002/sim.4362. Epub 2011 Sep 9.

DOI:10.1002/sim.4362
PMID:21905066
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3496857/
Abstract

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks.

摘要

传统上,新的预后模型是通过判别和风险重新分类的措施来评估的,但这些措施并没有充分考虑临床和健康经济背景。我们提出了一个通过量化支持治疗决策的公共卫生影响(净效益)来比较预后模型的框架,假设了一组预定的临床治疗指南。与传统措施的变化相比,净效益的变化更具有临床可解释性,并且可以用于对用于筛查和分配风险降低干预措施的预后模型进行全面的健康经济评估。我们通过量化生命年中的净效益来扩展该领域的先前工作,从而将预后性能与健康经济措施联系起来;通过充分考虑随时间发生的事件;并考虑在多研究环境中的估计和交叉验证。该方法在使用个体参与者数据荟萃分析进行心血管疾病风险预测的背景下进行了说明。我们根据包含五个既定风险因素的风险预测模型而不是仅包含年龄、性别和地区的模型来估计基于他汀类药物治疗分配的无心血管疾病的生命年数。我们探讨了与多研究设计相关的方法学问题,并表明基于所提出的方法的成本效益比较对一系列建模假设具有稳健性,包括调整竞争风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/02146f8c635e/sim0031-0114-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/9ea72225b7f1/sim0031-0114-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/acbbfc1fd776/sim0031-0114-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/b9a6516d5990/sim0031-0114-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/95a708f15387/sim0031-0114-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/02146f8c635e/sim0031-0114-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/9ea72225b7f1/sim0031-0114-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/acbbfc1fd776/sim0031-0114-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/b9a6516d5990/sim0031-0114-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/95a708f15387/sim0031-0114-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7099/3496857/02146f8c635e/sim0031-0114-f5.jpg

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