A Tutorial on Time-Dependent Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example.
A Tutorial on Time-Dependent Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example.
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DOI：
10.1177/0272989x221121747
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发表时间：
2023-01
影响因子：
3.6
通讯作者：
Jalal, Hawre
中科院分区：
文献类型：
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作者：
Alarid-Escudero, Fernando;Krijkamp, Eline;Enns, Eva A.;Yang, Alan;Hunink, M. G. Myriam;Pechlivanoglou, Petros;Jalal, Hawre
关键词：
在介绍性教程中，我们演示了在R中构建队列状态转换模型（cSTM），其中状态转换概率随时间变化恒定。然而，在实践中，许多cSTM需要过渡，奖励或两者都随时间而变化（时间依赖性）。本教程以先前发布的多策略成本效益分析为例，说明如何添加两种类型的时间依赖性。第一个是模拟时间依赖性，其允许转移概率作为自模拟开始以来测量的时间的函数而变化（例如，随着年龄的增长，死亡的可能性也在变化）。第二个是状态驻留时间依赖性，允许通过使用隧道状态跟踪在任何特定健康状态下花费的时间来记录历史。我们使用这些随时间变化的cSTM进行成本效益和概率敏感性分析。我们还从cSTM生成的输出中获得了各种感兴趣的流行病学结果，例如生存概率和疾病患病率，这些结果通常用于模型校准和验证。我们首先给出数学符号，然后是执行计算的R代码。完整的R代码在一个公共代码库中提供，以便更广泛地实现。
In an introductory tutorial, we illustrated building cohort state-transition models (cSTMs) in R, where the state transitions probabilities were constant over time. However, in practice, many cSTMs require transitions, rewards, or both to vary over time (time-dependent). This tutorial illustrates adding two types of time-dependency using a previously published cost-effectiveness analysis of multiple strategies as an example. The first is simulation-time dependence, which allows for the transition probabilities to vary as a function of time as measured since the start of the simulation (e.g., varying probability of death as the cohort ages). The second is state-residence time dependence, allowing for history by tracking the time spent in any particular health state using tunnel states. We use these time-dependent cSTMs to conduct cost-effectiveness and probabilistic sensitivity analyses. We also obtain various epidemiological outcomes of interest from the outputs generated from the cSTM, such as survival probability and disease prevalence, often used for model calibration and validation. We present the mathematical notation first, followed by the R code to execute the calculations. The full R code is provided in a public code repository for broader implementation.
DOI：
10.1007/s41669-018-0075-2
发表时间：
2018-12
期刊：
PharmacoEconomics - open
影响因子：
--
作者：
Djatche LM;Varga S;Lieberthal RD
通讯作者：
Lieberthal RD