An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial.

ABSTRACT:

Background

Decisions about new health technologies are increasingly being made while trials are still in an early stage, which may result in substantial uncertainty around key decision drivers such as estimates of life expectancy and time to disease progression. Additional data collection can reduce uncertainty, and its value can be quantified by computing the expected value of sample information (EVSI), which has typically been described in the context of designing a future trial. In this article, we develop new methods for computing the EVSI of extending an existing trial's follow-up, first for an assumed survival model and then extending to capture uncertainty about the true survival model.

Methods

We developed a nested Markov Chain Monte Carlo procedure and a nonparametr

SUBMITTER: Vervaart M 

PROVIDER: S-EPMC9189722 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature