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Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms

Despite consistent evidence that comorbidities and functional status (FS) are strong prognostic factors for colorectal cancer (CRC) patients, these important characteristics are not considered in prognostic nomograms. We assessed to what extent incorporating these characteristics into prognostic mod...

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Autores principales: Boakye, Daniel, Jansen, Lina, Schneider, Martin, Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826360/
https://www.ncbi.nlm.nih.gov/pubmed/31561507
http://dx.doi.org/10.3390/cancers11101435
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author Boakye, Daniel
Jansen, Lina
Schneider, Martin
Chang-Claude, Jenny
Hoffmeister, Michael
Brenner, Hermann
author_facet Boakye, Daniel
Jansen, Lina
Schneider, Martin
Chang-Claude, Jenny
Hoffmeister, Michael
Brenner, Hermann
author_sort Boakye, Daniel
collection PubMed
description Despite consistent evidence that comorbidities and functional status (FS) are strong prognostic factors for colorectal cancer (CRC) patients, these important characteristics are not considered in prognostic nomograms. We assessed to what extent incorporating these characteristics into prognostic models enhances prediction of CRC prognosis. CRC patients diagnosed in 2003–2014 who were recruited into a population-based study in Germany and followed over a median time of 4.7 years were randomized into training (n = 1608) and validation sets (n = 1071). In the training set, Cox models with predefined variables (age, sex, stage, tumor location, comorbidity scores, and FS) were used to construct nomograms for relevant survival outcomes. The performance of the nomograms, compared to models without comorbidity and FS, was evaluated in the validation set using concordance index (C-index). The C-indexes of the nomograms for overall and disease-free survival in the validation set were 0.768 and 0.737, which were substantially higher than those of models including tumor stage only (0.707 and 0.701) or models including stage, age, sex, and tumor location (0.749 and 0.718). The nomograms enabled significant risk stratification within all stages including stage IV. Our study suggests that incorporating comorbidities and FS into prognostic nomograms could substantially enhance prediction of CRC prognosis.
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spelling pubmed-68263602019-11-18 Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms Boakye, Daniel Jansen, Lina Schneider, Martin Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Cancers (Basel) Article Despite consistent evidence that comorbidities and functional status (FS) are strong prognostic factors for colorectal cancer (CRC) patients, these important characteristics are not considered in prognostic nomograms. We assessed to what extent incorporating these characteristics into prognostic models enhances prediction of CRC prognosis. CRC patients diagnosed in 2003–2014 who were recruited into a population-based study in Germany and followed over a median time of 4.7 years were randomized into training (n = 1608) and validation sets (n = 1071). In the training set, Cox models with predefined variables (age, sex, stage, tumor location, comorbidity scores, and FS) were used to construct nomograms for relevant survival outcomes. The performance of the nomograms, compared to models without comorbidity and FS, was evaluated in the validation set using concordance index (C-index). The C-indexes of the nomograms for overall and disease-free survival in the validation set were 0.768 and 0.737, which were substantially higher than those of models including tumor stage only (0.707 and 0.701) or models including stage, age, sex, and tumor location (0.749 and 0.718). The nomograms enabled significant risk stratification within all stages including stage IV. Our study suggests that incorporating comorbidities and FS into prognostic nomograms could substantially enhance prediction of CRC prognosis. MDPI 2019-09-26 /pmc/articles/PMC6826360/ /pubmed/31561507 http://dx.doi.org/10.3390/cancers11101435 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Boakye, Daniel
Jansen, Lina
Schneider, Martin
Chang-Claude, Jenny
Hoffmeister, Michael
Brenner, Hermann
Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms
title Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms
title_full Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms
title_fullStr Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms
title_full_unstemmed Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms
title_short Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms
title_sort personalizing the prediction of colorectal cancer prognosis by incorporating comorbidities and functional status into prognostic nomograms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826360/
https://www.ncbi.nlm.nih.gov/pubmed/31561507
http://dx.doi.org/10.3390/cancers11101435
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