Bayesian estimation of cost-effectiveness from censored data.
We describe a Bayesian methodology for estimating the cost-effectiveness of a new treatment compared to a standard in a clinical trial, when censoring of survival, the effectiveness variable, induces censoring of total cost. The statistical model assumes that survival follows a Weibull distribution and that total health care cost follows a gamma distribution whose mean has a linear regression on survival time. We summarize the posterior distributions of key parameters by importance sampling. We illustrate the method with an analysis of data from a randomized clinical trial of a treatment for cardiovascular disease.
Heitjan
Daniel F
DF
Department of Biostatistics & Epidemiology, University of Pennsylvania School of Medicine, 622 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, U.S.A. dheitjan@cceb.upenn.edu
Kim
Clara Yuri
CY
Li
Huiling
H
D001499:Bayes Theorem; D002318:Cardiovascular Diseases / Q000191:economics / Q000628:therapy; D002986:Clinical Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis / Q000379:methods* / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D017048:Health Care Costs / Q000706:statistics & numerical data; D006801:Humans; D016013:Likelihood Functions; D017059:Models, Econometric; D016032:Randomized Controlled Trials as Topic; D012044:Regression Analysis; D016019:Survival Analysis; D016896:Treatment Outcome