Parametric cure models of relative and cause-specific survival for grouped survival times

Comput Methods Programs Biomed. 2000 Feb;61(2):99-110. doi: 10.1016/s0169-2607(99)00022-x.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Actuarial Analysis / methods*
  • Algorithms*
  • Hodgkin Disease / mortality*
  • Humans
  • Likelihood Functions*
  • Melanoma / mortality*
  • Models, Biological
  • Skin Neoplasms / mortality*
  • Survival Analysis*