Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction

Giuseppe Marano; Patrizia Boracchi; Elia M. Biganzoli

doi:10.1007/978-3-319-24462-4_16

Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction

Giuseppe Marano, Patrizia Boracchi, Elia M. Biganzoli

Fondazione IRCCS Istituto Nazionale dei Tumori

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Methods for fitting survival regression models with a penalized smoothed hazard function have been recently discussed, even though they could be cumbersome. A simpler alternative which does not require specific software packages could be fitting a penalized piecewise exponential model. In this work the implementation of such strategy in Win- BUGS is illustrated, and preliminary results are reported concerning the application of Bayesian P-splines techniques. The technique is applied to a pre-specified model in which the number and positions of knots were fixed on the basis of clinical knowledge, thus defining a non-standard smoothing problem.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	183-198
Number of pages	16
Volume	8623
ISBN (Print)	9783319244617
DOIs	https://doi.org/10.1007/978-3-319-24462-4_16
Publication status	Published - 2015
Event	11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2014 - Cambridge, United Kingdom Duration: Jun 26 2014 → Jun 28 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8623
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2014
Country	United Kingdom
City	Cambridge
Period	6/26/14 → 6/28/14

Keywords

Bayesian P-splines
Hazard Smoothing
Piecewise Exponential Model
Survival analysis

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

Access to Document

10.1007/978-3-319-24462-4_16

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Cite this

Marano, G., Boracchi, P., & Biganzoli, E. M. (2015). Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8623, pp. 183-198). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8623). Springer Verlag. https://doi.org/10.1007/978-3-319-24462-4_16

Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction. / Marano, Giuseppe; Boracchi, Patrizia; Biganzoli, Elia M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8623 Springer Verlag, 2015. p. 183-198 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8623).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Marano, G, Boracchi, P & Biganzoli, EM 2015, Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8623, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8623, Springer Verlag, pp. 183-198, 11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2014, Cambridge, United Kingdom, 6/26/14. https://doi.org/10.1007/978-3-319-24462-4_16

Marano G, Boracchi P, Biganzoli EM. Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8623. Springer Verlag. 2015. p. 183-198. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-24462-4_16

Marano, Giuseppe ; Boracchi, Patrizia ; Biganzoli, Elia M. / Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8623 Springer Verlag, 2015. pp. 183-198 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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