title: Overview of parametric survival analysis for health-economic applications.
abstract: Health economic models rely on data from trials to project the risk of events (e.g., death) over time beyond the span of the available data. Parametric survival analysis methods can be applied to identify an appropriate statistical model for the observed data, which can then be extrapolated to derive a complete time-to-event curve. This paper describes the properties of the most commonly used statistical distributions as a basis for these models and describes an objective process of identifying the most suitable parametric distribution in a given dataset. The approach can be applied with both individual-patient data as well as with survival probabilities derived from published Kaplan-Meier curves. Both are illustrated with analyses of overall survival from the Sorafenib Hepatocellular Carcinoma Assessment Randomised Protocol trial.
authors.affiliation: United BioSource Corporation, 185 Dorval Avenue, Suite 500, Dorval, QC, H9S 5J9, Canada. Jack.ishak@unitedbiosource.com
authors.forename: K Jack
authors.initials: KJ
authors.lastname: Ishak
authors.forename: Noemi
authors.initials: N
authors.lastname: Kreif
authors.forename: Agnes
authors.initials: A
authors.lastname: Benedict
authors.forename: Noemi
authors.initials: N
authors.lastname: Muszbek
mesh_terms: D000970:Antineoplastic Agents / Q000191:economics / Q000627:therapeutic use; D006528:Carcinoma, Hepatocellular / Q000188:drug therapy / Q000401:mortality; D006801:Humans; D008113:Liver Neoplasms / Q000188:drug therapy / Q000401:mortality; D018803:Models, Economic; D016032:Randomized Controlled Trials as Topic; D016019:Survival Analysis
chemical_list: D000970:Antineoplastic Agents