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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-09-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/11/10/1435 |
| _version_ | 1797713729918337024 |
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| author | Daniel Boakye Lina Jansen Martin Schneider Jenny Chang-Claude Michael Hoffmeister Hermann Brenner |
| author_facet | Daniel Boakye Lina Jansen Martin Schneider Jenny Chang-Claude Michael Hoffmeister Hermann Brenner |
| author_sort | Daniel Boakye |
| collection | DOAJ |
| 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 (<i>n</i> = 1608) and validation sets (<i>n</i> = 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. |
| first_indexed | 2024-03-12T07:41:08Z |
| format | Article |
| id | doaj.art-fcf52324465f4b1ab3d83f31258d454b |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-12T07:41:08Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-fcf52324465f4b1ab3d83f31258d454b2023-09-02T21:19:01ZengMDPI AGCancers2072-66942019-09-011110143510.3390/cancers11101435cancers11101435Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic NomogramsDaniel Boakye0Lina Jansen1Martin Schneider2Jenny Chang-Claude3Michael Hoffmeister4Hermann Brenner5Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDepartment of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, 69120 Heidelberg, GermanyUnit of Genetic Epidemiology, Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDespite 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 (<i>n</i> = 1608) and validation sets (<i>n</i> = 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.https://www.mdpi.com/2072-6694/11/10/1435comorbidityfunctional statusnomogrampersonalized medicineprognosiscolorectal neoplasm |
| spellingShingle | Daniel Boakye Lina Jansen Martin Schneider Jenny Chang-Claude Michael Hoffmeister Hermann Brenner Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms Cancers comorbidity functional status nomogram personalized medicine prognosis colorectal neoplasm |
| 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 | comorbidity functional status nomogram personalized medicine prognosis colorectal neoplasm |
| url | https://www.mdpi.com/2072-6694/11/10/1435 |
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