|
| | | | |
| | | |
| Stat |
Members: 3657
Articles: 2'599'751
Articles rated: 2609
14 October 2024 |
|
| | | | |
|
Article overview
| |
|
|
Blended Survival Curves: A New Approach to Extrapolation for Time-to-Event Outcomes from Clinical Trial in Health Technology Assessment | | Zhaojing Che
; Nathan Green
; Gianluca Baio
; | | Date: |
1 Jun 2022 | | Abstract: | Background Survival extrapolation is essential in the cost-effectiveness
analysis to quantify the lifetime survival benefit associated with a new
intervention, due to the restricted duration of randomized controlled trials
(RCTs). Current approaches of extrapolation often assume that the treatment
effect observed in the trial can continue indefinitely, which is unrealistic
and may have a huge impact on decisions for resource allocation. Objective We
introduce a novel methodology as a possible solution to alleviate the problem
of performing survival extrapolation with heavily censored data from clinical
trials. Method The main idea is to mix a flexible model (e.g., Cox
semi-parametric) to fit as well as possible the observed data and a parametric
model encoding assumptions on the expected behaviour of underlying long-term
survival. The two are "blended" into a single survival curve that is identical
with the Cox model over the range of observed times and gradually approaching
the parametric model over the extrapolation period based on a weight function.
The weight function regulates the way two survival curves are blended,
determining how the internal and external sources contribute to the estimated
survival over time. Results A 4-year follow-up RCT of rituximab in combination
with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone
for the first-line treatment of chronic lymphocytic leukemia is used to
illustrate the method. Conclusion Long-term extrapolation from immature trial
data may lead to significantly different estimates with various modelling
assumptions. The blending approach provides sufficient flexibility, allowing a
wide range of plausible scenarios to be considered as well as the inclusion of
genuine external information, based e.g. on hard data or expert opinion. Both
internal and external validity can be carefully examined. | | Source: | arXiv, 2206.00154 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
|
| |
|
|
|
REGISTER