The aim of the present article is to introduce and discuss the problem of optimal modelling of the prognostic information provided by putative prognostic variables, possibly measured on a quantitative scale. A number of methodological aspects will be treated, with particular reference to the role of spline functions and artificial neural networks, which will be discussed in the context of the analysis of survival data. The problem of the evaluation and the choice of the optimal statistical models will be examined, with particular attention to the critical aspects related to the definition of prognostic indexes on the basis of the results of the selected models. Clinical examples in breast cancer on the evaluation of the prognostic impact of several tumor markers are provided. This paper is addressed to all researchers who are interested in the evaluation of the prognostic role of tumor markers, therefore we will stress the necessity of integrating the methodologies of biological, clinical and statistical research in the assessment of prognosis.

Flexible modelling in survival analysis. Structuring biological complexity from the information provided by tumor markers / E. Biganzoli, P. Boracchi, M. G. Daidone, M. Gion, E. Marubini. - In: THE INTERNATIONAL JOURNAL OF BIOLOGICAL MARKERS. - ISSN 0393-6155. - 13:3(1998), pp. 107-23-123.

Flexible modelling in survival analysis. Structuring biological complexity from the information provided by tumor markers

E. Biganzoli
Primo
;
P. Boracchi
Secondo
;
1998

Abstract

The aim of the present article is to introduce and discuss the problem of optimal modelling of the prognostic information provided by putative prognostic variables, possibly measured on a quantitative scale. A number of methodological aspects will be treated, with particular reference to the role of spline functions and artificial neural networks, which will be discussed in the context of the analysis of survival data. The problem of the evaluation and the choice of the optimal statistical models will be examined, with particular attention to the critical aspects related to the definition of prognostic indexes on the basis of the results of the selected models. Clinical examples in breast cancer on the evaluation of the prognostic impact of several tumor markers are provided. This paper is addressed to all researchers who are interested in the evaluation of the prognostic role of tumor markers, therefore we will stress the necessity of integrating the methodologies of biological, clinical and statistical research in the assessment of prognosis.
Artificial neural networks; Spline functions; Survival analysis; Tumor markers
Settore MED/01 - Statistica Medica
Article (author)
File in questo prodotto:
Non ci sono file associati a questo prodotto.
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: https://hdl.handle.net/2434/190144
Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 21
  • ???jsp.display-item.citation.isi??? ND
social impact