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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Main Authors: Boakye, Daniel (Author) , Jansen, Lina (Author) , Schneider, Martin (Author) , Chang-Claude, Jenny (Author) , Hoffmeister, Michael (Author) , Brenner, Hermann (Author)
Format: Article (Journal)
Language:English
Published: 26 September 2019
In: Cancers
Year: 2019, Volume: 11, Issue: 10
ISSN:2072-6694
DOI:10.3390/cancers11101435
Online Access:Verlag, Volltext: https://doi.org/10.3390/cancers11101435
Verlag: https://www.mdpi.com/2072-6694/11/10/1435
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Author Notes:Daniel Boakye, Lina Jansen, Martin Schneider, Jenny Chang-Claude, Michael Hoffmeister and Hermann Brenner
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Summary: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.
Item Description:Gesehen am 30.10.2019
Physical Description:Online Resource
ISSN:2072-6694
DOI:10.3390/cancers11101435