Department of Health Management and Health Economics, University of Oslo, Oslo, Norway.
Clinical Trial Unit, Oslo University Hospital, Oslo, Norway.
Med Decis Making. 2024 Oct;44(7):719-741. doi: 10.1177/0272989X241279459. Epub 2024 Sep 20.
The net value of reducing decision uncertainty by collecting additional data is quantified by the expected net benefit of sampling (ENBS). This tutorial presents a general-purpose algorithm for computing the ENBS for collecting survival data along with a step-by-step implementation in R.The algorithm is based on recently published methods for simulating survival data and computing expected value of sample information that do not rely on the survival data to follow any particular parametric distribution and that can take into account any arbitrary censoring process.We demonstrate in a case study based on a previous cancer technology appraisal that ENBS calculations are useful not only for designing new studies but also for optimizing reimbursement decisions for new health technologies based on immature evidence from ongoing trials.
通过收集额外数据来减少决策不确定性的净价值是通过抽样的预期净收益（ENBS）来量化的。本教程介绍了一种用于计算生存数据采集的 ENBS 的通用算法，并在 R 中逐步实现了该算法。该算法基于最近发表的用于模拟生存数据和计算样本信息期望价值的方法，这些方法不依赖于生存数据遵循任何特定的参数分布，并且可以考虑到任何任意的删失过程。我们在一个基于先前癌症技术评估的案例研究中证明，ENBS 计算不仅对于设计新研究有用，而且对于基于正在进行的试验中的不成熟证据对新的卫生技术进行报销决策优化也有用。
