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Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)

BACKGROUND: The management of locally advanced pancreatic cancer (LAPC) patients remains controversial. Better discrimination for overall survival (OS) at diagnosis is needed. We address this issue by developing and validating a prognostic nomogram and a score for OS in LAPC (PROLAP). METHODS: Analy...

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Autores principales: Vernerey, Dewi, Huguet, Florence, Vienot, Angélique, Goldstein, David, Paget-Bailly, Sophie, Van Laethem, Jean-Luc, Glimelius, Bengt, Artru, Pascal, Moore, Malcolm J, André, Thierry, Mineur, Laurent, Chibaudel, Benoist, Benetkiewicz, Magdalena, Louvet, Christophe, Hammel, Pascal, Bonnetain, Franck
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4973163/
https://www.ncbi.nlm.nih.gov/pubmed/27404456
http://dx.doi.org/10.1038/bjc.2016.212
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author Vernerey, Dewi
Huguet, Florence
Vienot, Angélique
Goldstein, David
Paget-Bailly, Sophie
Van Laethem, Jean-Luc
Glimelius, Bengt
Artru, Pascal
Moore, Malcolm J
André, Thierry
Mineur, Laurent
Chibaudel, Benoist
Benetkiewicz, Magdalena
Louvet, Christophe
Hammel, Pascal
Bonnetain, Franck
author_facet Vernerey, Dewi
Huguet, Florence
Vienot, Angélique
Goldstein, David
Paget-Bailly, Sophie
Van Laethem, Jean-Luc
Glimelius, Bengt
Artru, Pascal
Moore, Malcolm J
André, Thierry
Mineur, Laurent
Chibaudel, Benoist
Benetkiewicz, Magdalena
Louvet, Christophe
Hammel, Pascal
Bonnetain, Franck
author_sort Vernerey, Dewi
collection PubMed
description BACKGROUND: The management of locally advanced pancreatic cancer (LAPC) patients remains controversial. Better discrimination for overall survival (OS) at diagnosis is needed. We address this issue by developing and validating a prognostic nomogram and a score for OS in LAPC (PROLAP). METHODS: Analyses were derived from 442 LAPC patients enrolled in the LAP07 trial. The prognostic ability of 30 baseline parameters was evaluated using univariate and multivariate Cox regression analyses. Performance assessment and internal validation of the final model were done with Harrell's C-index, calibration plot and bootstrap sample procedures. On the basis of the final model, a prognostic nomogram and a score were developed, and externally validated in 106 consecutive LAPC patients treated in Besançon Hospital, France. RESULTS: Age, pain, tumour size, albumin and CA 19-9 were independent prognostic factors for OS. The final model had good calibration, acceptable discrimination (C-index=0.60) and robust internal validity. The PROLAP score has the potential to delineate three different prognosis groups with median OS of 15.4, 11.7 and 8.5 months (log-rank P<0.0001). The score ability to discriminate OS was externally confirmed in 63 (59%) patients with complete clinical data derived from a data set of 106 consecutive LAPC patients; median OS of 18.3, 14.1 and 7.6 months for the three groups (log-rank P<0.0001). CONCLUSIONS: The PROLAP nomogram and score can accurately predict OS before initiation of induction chemotherapy in LAPC-untreated patients. They may help to optimise clinical trials design and might offer the opportunity to define risk-adapted strategies for LAPC management in the future.
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spelling pubmed-49731632017-07-26 Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP) Vernerey, Dewi Huguet, Florence Vienot, Angélique Goldstein, David Paget-Bailly, Sophie Van Laethem, Jean-Luc Glimelius, Bengt Artru, Pascal Moore, Malcolm J André, Thierry Mineur, Laurent Chibaudel, Benoist Benetkiewicz, Magdalena Louvet, Christophe Hammel, Pascal Bonnetain, Franck Br J Cancer Clinical Study BACKGROUND: The management of locally advanced pancreatic cancer (LAPC) patients remains controversial. Better discrimination for overall survival (OS) at diagnosis is needed. We address this issue by developing and validating a prognostic nomogram and a score for OS in LAPC (PROLAP). METHODS: Analyses were derived from 442 LAPC patients enrolled in the LAP07 trial. The prognostic ability of 30 baseline parameters was evaluated using univariate and multivariate Cox regression analyses. Performance assessment and internal validation of the final model were done with Harrell's C-index, calibration plot and bootstrap sample procedures. On the basis of the final model, a prognostic nomogram and a score were developed, and externally validated in 106 consecutive LAPC patients treated in Besançon Hospital, France. RESULTS: Age, pain, tumour size, albumin and CA 19-9 were independent prognostic factors for OS. The final model had good calibration, acceptable discrimination (C-index=0.60) and robust internal validity. The PROLAP score has the potential to delineate three different prognosis groups with median OS of 15.4, 11.7 and 8.5 months (log-rank P<0.0001). The score ability to discriminate OS was externally confirmed in 63 (59%) patients with complete clinical data derived from a data set of 106 consecutive LAPC patients; median OS of 18.3, 14.1 and 7.6 months for the three groups (log-rank P<0.0001). CONCLUSIONS: The PROLAP nomogram and score can accurately predict OS before initiation of induction chemotherapy in LAPC-untreated patients. They may help to optimise clinical trials design and might offer the opportunity to define risk-adapted strategies for LAPC management in the future. Nature Publishing Group 2016-07-26 2016-07-12 /pmc/articles/PMC4973163/ /pubmed/27404456 http://dx.doi.org/10.1038/bjc.2016.212 Text en Copyright © 2016 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Clinical Study
Vernerey, Dewi
Huguet, Florence
Vienot, Angélique
Goldstein, David
Paget-Bailly, Sophie
Van Laethem, Jean-Luc
Glimelius, Bengt
Artru, Pascal
Moore, Malcolm J
André, Thierry
Mineur, Laurent
Chibaudel, Benoist
Benetkiewicz, Magdalena
Louvet, Christophe
Hammel, Pascal
Bonnetain, Franck
Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)
title Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)
title_full Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)
title_fullStr Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)
title_full_unstemmed Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)
title_short Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)
title_sort prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (prolap)
topic Clinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4973163/
https://www.ncbi.nlm.nih.gov/pubmed/27404456
http://dx.doi.org/10.1038/bjc.2016.212
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