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Article

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

1
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
2
Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany
3
Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, 69120 Heidelberg, Germany
4
Unit of Genetic Epidemiology, Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
5
Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf (UKE), 20251 Hamburg, Germany
6
Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
7
German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
Cancers 2019, 11(10), 1435; https://doi.org/10.3390/cancers11101435
Received: 2 August 2019 / Revised: 10 September 2019 / Accepted: 24 September 2019 / Published: 26 September 2019
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. View Full-Text
Keywords: comorbidity; functional status; nomogram; personalized medicine; prognosis; colorectal neoplasm comorbidity; functional status; nomogram; personalized medicine; prognosis; colorectal neoplasm
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MDPI and ACS Style

Boakye, D.; Jansen, L.; Schneider, M.; Chang-Claude, J.; Hoffmeister, M.; Brenner, H. Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms. Cancers 2019, 11, 1435. https://doi.org/10.3390/cancers11101435

AMA Style

Boakye D, Jansen L, Schneider M, Chang-Claude J, Hoffmeister M, Brenner H. Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms. Cancers. 2019; 11(10):1435. https://doi.org/10.3390/cancers11101435

Chicago/Turabian Style

Boakye, Daniel; Jansen, Lina; Schneider, Martin; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann. 2019. "Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms" Cancers 11, no. 10: 1435. https://doi.org/10.3390/cancers11101435

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