Predicting survival in cost-effectiveness analyses based on clinical trials.
This study deals with the question of how to model health effects after the cessation of a randomized controlled trial (RCT). By using clinical trial data on severe congestive heart failure patients, we illustrate how survival beyond the cessation of an RCT can be predicted based on parametric survival models. In the analysis, we compare predicted survival and the resulting incremental cost-effectiveness ratio (ICER) of different survival models with actual survival/ICER. Our main finding is that the results are sensitive to the choice of survival model and that an extensive sensitivity analysis in the CE analysis is required.
Gerdtham
Ulf G
UG
Department of Community Medicine, Malmö University Hospital, Sweden.
Zethraeus
Niklas
N
D000806:Angiotensin-Converting Enzyme Inhibitors / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000191:economics / Q000592:standards; D016001:Confidence Intervals; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D004656:Enalapril / Q000627:therapeutic use; D006333:Heart Failure / Q000188:drug therapy / Q000401:mortality; D006801:Humans; D016013:Likelihood Functions; D016019:Survival Analysis; D013548:Sweden; D013995:Time
D000806:Angiotensin-Converting Enzyme Inhibitors; D004656:Enalapril