title: Parametric cure models of relative and cause-specific survival for grouped survival times.
abstract: With parametric cure models, we can express survival parameters (e.g. cured fraction, location and scale parameters) as functions of covariates. These models can measure survival from a specific disease process, either by examining deaths due to the cause under study (cause-specific survival), or by comparing all deaths to those in a matched control population (relative survival). We present a binomial maximum likelihood algorithm to be used for actuarial data, where follow-up times are grouped into specific intervals. Our algorithm provides simultaneous maximum likelihood estimates for all the parameters of a cure model and can be used for cause-specific or relative survival analysis with a variety of survival distributions. Current software does not provide the flexibility of this unified approach.
authors.affiliation: Veterans Administration Hospital and University of Louisville School of Medicine, KY 40292, USA. jwgamel@louisville.edu
authors.forename: J W
authors.initials: JW
authors.lastname: Gamel
authors.forename: E A
authors.initials: EA
authors.lastname: Weller
authors.forename: M N
authors.initials: MN
authors.lastname: Wesley
authors.forename: E J
authors.initials: EJ
authors.lastname: Feuer
mesh_terms: D000206:Actuarial Analysis / Q000379:methods*; D000465:Algorithms; D006689:Hodgkin Disease / Q000401:mortality*; D006801:Humans; D016013:Likelihood Functions; D008545:Melanoma / Q000401:mortality*; D008954:Models, Biological; D012878:Skin Neoplasms / Q000401:mortality*; D016019:Survival Analysis