title: Survival extrapolation using the poly-Weibull model.
abstract: Recent studies of (cost-) effectiveness in cardiothoracic transplantation have required estimation of mean survival over the lifetime of the recipients. In order to calculate mean survival, the complete survivor curve is required but is often not fully observed, so that survival extrapolation is necessary. After transplantation, the hazard function is bathtub-shaped, reflecting latent competing risks which operate additively in overlapping time periods. The poly-Weibull distribution is a flexible parametric model that may be used to extrapolate survival and has a natural competing risks interpretation. In addition, treatment effects and subgroups can be modelled separately for each component of risk. We describe the model and develop inference procedures using freely available software. The methods are applied to two problems from cardiothoracic transplantation.
authors.affiliation: Agricultural University of Athens, Athens, Greece nikos.demiris@gmail.com.
authors.forename: Nikolaos
authors.initials: N
authors.lastname: Demiris
authors.affiliation: Medical Research Council Biostatistics Unit, Cambridge, UK.
authors.forename: David
authors.initials: D
authors.lastname: Lunn
authors.affiliation: Medical Research Council Biostatistics Unit, Cambridge, UK.
authors.forename: Linda D
authors.initials: LD
authors.lastname: Sharples
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D056808:Biostatistics; D050377:Cold Ischemia; D003362:Cost-Benefit Analysis; D006801:Humans; D016013:Likelihood Functions; D016040:Lung Transplantation / Q000191:economics / Q000401:mortality / Q000706:statistics & numerical data; D015233:Models, Statistical; D009926:Organ Preservation / Q000191:economics / Q000295:instrumentation / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012984:Software; D016019:Survival Analysis