In cancer research, study of the hazard function provides useful information on the disease dynamic, in addition to the identification of prognostic factors. The widely utilized Cox proportional hazard model uses a stepwise nonparametric estimator for the baseline hazard function. Therefore the use of parametric models and/or other approaches to estimate the hazard function is often invoked. A recent work by C. Cox and colleagues [1] has stimulated the use of a complex and flexible parametric model based on the General Gamma distribution, supported by the development of optimization software. Use of the General Gamma to study the shape of the hazard function is investigated. As a benchmark, the flexible approach based on piecewise exponential model and a nonparametric kernel estimate are considered. An example based on breast cancer survival is used to illustrate the main findings.

Flexible Parametric Modelling of the Hazard Function in Breast Cancer Studies / I. Ardoino, F. Ambrogi, C. Bajdik, P.J. Lisboa, E.M. Biganzoli, P. Boracchi - In: Proceedings of the 2010 IEEE World Congress on Computational Intelligence (IEEE WCCI 2010) / [a cura di] J. Aranda, S. Xambò. - [s.l] : IEEE, 2010. - ISBN 9781424481262. - pp. 2018-2022 (( convegno IEEE World Congress on Computational Intelligence (IEEE WCCI) tenutosi a Barcelona nel 2010 [10.1109/IJCNN.2010.5596297].

Flexible Parametric Modelling of the Hazard Function in Breast Cancer Studies

I. Ardoino;F. Ambrogi;E.M. Biganzoli;P. Boracchi
2010

Abstract

In cancer research, study of the hazard function provides useful information on the disease dynamic, in addition to the identification of prognostic factors. The widely utilized Cox proportional hazard model uses a stepwise nonparametric estimator for the baseline hazard function. Therefore the use of parametric models and/or other approaches to estimate the hazard function is often invoked. A recent work by C. Cox and colleagues [1] has stimulated the use of a complex and flexible parametric model based on the General Gamma distribution, supported by the development of optimization software. Use of the General Gamma to study the shape of the hazard function is investigated. As a benchmark, the flexible approach based on piecewise exponential model and a nonparametric kernel estimate are considered. An example based on breast cancer survival is used to illustrate the main findings.
Settore MED/01 - Statistica Medica
IEEE
IJCNN
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
N-0386.pdf

non disponibili

Tipologia: Publisher's version/PDF
Dimensione 1.22 MB
Formato Adobe PDF
1.22 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/166094
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact