论文标题
使用成本效益分析示例R中关于R中的同类状态过渡模型的介绍性教程
An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example
论文作者
论文摘要
决策模型可以结合来自不同来源的信息，以模拟在不确定性存在下替代策略的长期后果。队列国家转变模型（CSTM）是医学决策中常用的决策模型，以模拟随着时间的推移，各种健康状态之间假设队列的过渡。该教程侧重于与时间无关的CSTM，在这种情况下，随着时间的流逝，健康状态之间的过渡概率保持恒定。我们在R r（一种开源数学和统计编程语言）中实现与时间无关的CSTM。我们使用先前发表的决策模型来说明与时间无关的CSTM，计算成本和有效性结果，对多种策略（包括概率灵敏度分析）进行成本效益分析。我们在R中提供开源代码，以促进更广泛的采用。在第二个更高级的教程中，我们说明了时间依赖的CSTM。
Decision models can combine information from different sources to simulate the long-term consequences of alternative strategies in the presence of uncertainty. A cohort state-transition model (cSTM) is a decision model commonly used in medical decision-making to simulate the transitions of a hypothetical cohort among various health states over time. This tutorial focuses on time-independent cSTM, where transition probabilities among health states remain constant over time. We implement time-independent cSTM in R, an open-source mathematical and statistical programming language. We illustrate time-independent cSTMs using a previously published decision model, calculate costs and effectiveness outcomes, conduct a cost-effectiveness analysis of multiple strategies, including a probabilistic sensitivity analysis. We provide open-source code in R to facilitate wider adoption. In a second, more advanced tutorial, we illustrate time-dependent cSTMs.
