Predicting Survival in cost-effectiveness analyses based on clinical trials
This paper deals with the question how to model health effects after the cessation of a randomised controlled trial (RCT). Using clinical trial data on severe congestive heart failure patients we illustrate how survival beyond the cessation of a RCT can be predicted based on parametric survival models. In the analysis we compare the predicted survival and the resulting incremental cost-effectiveness ratio (ICER) of different survival models with the actual survival/ICER. Our main finding is that the results are highly sensitive to the choice of survival model and that extensive sensitivity analysis in the CE analysis is required. We also show that adding the true survival after the end of the clinical study will underestimate the true variability.
|Date of creation:||08 May 2001|
|Contact details of provider:|| Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden|
Phone: +46-(0)8-736 90 00
Fax: +46-(0)8-31 01 57
Web page: http://www.hhs.se/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:hhs:hastef:0442. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Helena Lundin)
If references are entirely missing, you can add them using this form.