Flexible parametric modelling of the hazard function in breast cancer studies

I. Ardoino, E. M. Biganzoli, C. Bajdik, P. J. Lisboa, P. Boracchi, F. Ambrogi

Research output: Contribution to journalArticlepeer-review


In cancer research, study of the hazard function provides useful insights into disease dynamics, as it describes the way in which the (conditional) probability of death changes with time. The widely utilized Cox proportional hazard model uses a stepwise nonparametric estimator for the baseline hazard function, and therefore has a limited utility. The use of parametric models and/or other approaches that enables direct estimation of the hazard function is often invoked. A recent work by Cox et al. [6] has stimulated the use of the flexible parametric model based on the Generalized Gamma (GG) distribution, supported by the development of optimization software. The GG distribution allows estimation of different hazard shapes in a single framework. We use the GG model to investigate the shape of the hazard function in early breast cancer patients. The flexible approach based on a piecewise exponential model and the nonparametric additive hazards model are also considered.

Original languageEnglish
Pages (from-to)1409-1421
Number of pages13
JournalJournal of Applied Statistics
Issue number7
Publication statusPublished - Jul 2012


  • accelerated failure time
  • additive model
  • gamma distribution
  • hazard function
  • piecewise exponential model
  • spline

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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