Department of Health Management and Policy, UCLA School of Public Health, Los Angeles, CA, USA.
Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, CA, USA.
Pharmacoeconomics. 2020 Nov;38(11):1153-1164. doi: 10.1007/s40273-020-00937-z.
This tutorial presents practical guidance on transforming various types of information published in journals, or available online from government and other sources, into transition probabilities for use in state-transition models, including cost-effectiveness models. Much, but not all, of the guidance has been previously published in peer-reviewed journals. Our purpose is to collect it in one location to serve as a stand-alone resource for decision modelers who draw most or all of their information from the published literature. Our focus is on the technical aspects of manipulating data to derive transition probabilities. We explain how to derive model transition probabilities from the following types of statistics: relative risks, odds, odds ratios, and rates. We then review the well-known approach for converting probabilities to match the model's cycle length when there are two health-state transitions and how to handle the case of three or more health-state transitions, for which the two-state approach is not appropriate. Other topics discussed include transition probabilities for population subgroups, issues to keep in mind when using data from different sources in the derivation process, and sensitivity analyses, including the use of sensitivity analysis to allocate analyst effort in refining transition probabilities and ways to handle sources of uncertainty that are not routinely formalized in models. The paper concludes with recommendations to help modelers make the best use of the published literature.
本教程提供了实用的指导，介绍如何将期刊上发表的或从政府和其他来源在线获取的各种类型的信息转化为用于状态转移模型（包括成本效益模型）的转移概率。虽然大部分（但不是全部）指导先前已在同行评议期刊上发表过，但我们将其收集在一个位置，为主要或全部从已发表文献中提取信息的决策模型制作者提供一个独立的资源。我们的重点是处理数据以推导出转移概率的技术方面。我们解释了如何从以下类型的统计数据中推导出模型转移概率：相对风险、胜算、优势比和比率。然后，我们回顾了在有两个健康状态转移时将概率转换为匹配模型周期长度的方法，以及在有三个或更多健康状态转移时的处理方法，对于这种情况，两状态方法不适用。讨论的其他主题包括人群亚组的转移概率、在推导过程中使用来自不同来源的数据时需要注意的问题以及敏感性分析，包括使用敏感性分析来分配分析师在改进转移概率方面的工作以及处理模型中未常规形式化的不确定性来源的方法。本文最后提出了一些建议，以帮助模型制作者充分利用已发表的文献。
