Cargando…
One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data
BACKGROUND: The existing literature does not provide a prediction model for mortality of all colorectal cancer patients using contemporary national hospital data. We developed and validated such a model to predict colorectal cancer death within 90, 180 and 365 days after diagnosis. METHODS: Cohort s...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652941/ https://www.ncbi.nlm.nih.gov/pubmed/32830202 http://dx.doi.org/10.1038/s41416-020-01034-w |
_version_ | 1783607800993153024 |
---|---|
author | Cowling, Thomas E. Bellot, Alexis Boyle, Jemma Walker, Kate Kuryba, Angela Galbraith, Sarah Aggarwal, Ajay Braun, Michael Sharples, Linda D. van der Meulen, Jan |
author_facet | Cowling, Thomas E. Bellot, Alexis Boyle, Jemma Walker, Kate Kuryba, Angela Galbraith, Sarah Aggarwal, Ajay Braun, Michael Sharples, Linda D. van der Meulen, Jan |
author_sort | Cowling, Thomas E. |
collection | PubMed |
description | BACKGROUND: The existing literature does not provide a prediction model for mortality of all colorectal cancer patients using contemporary national hospital data. We developed and validated such a model to predict colorectal cancer death within 90, 180 and 365 days after diagnosis. METHODS: Cohort study using linked national cancer and death records. The development population included 27,480 patients diagnosed in England in 2015. The test populations were diagnosed in England in 2016 (n = 26,411) and Wales in 2015–2016 (n = 3814). Predictors were age, gender, socioeconomic status, referral source, performance status, tumour site, TNM stage and treatment intent. Cox regression models were assessed using Brier scores, c-indices and calibration plots. RESULTS: In the development population, 7.4, 11.7 and 17.9% of patients died from colorectal cancer within 90, 180 and 365 days after diagnosis. T4 versus T1 tumour stage had the largest adjusted association with the outcome (HR 4.67; 95% CI: 3.59–6.09). C-indices were 0.873–0.890 (England) and 0.856–0.873 (Wales) in the test populations, indicating excellent separation of predicted risks by outcome status. Models were generally well calibrated. CONCLUSIONS: The model was valid for predicting short-term colorectal cancer mortality. It can provide personalised information to support clinical practice and research. |
format | Online Article Text |
id | pubmed-7652941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76529412021-08-24 One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data Cowling, Thomas E. Bellot, Alexis Boyle, Jemma Walker, Kate Kuryba, Angela Galbraith, Sarah Aggarwal, Ajay Braun, Michael Sharples, Linda D. van der Meulen, Jan Br J Cancer Article BACKGROUND: The existing literature does not provide a prediction model for mortality of all colorectal cancer patients using contemporary national hospital data. We developed and validated such a model to predict colorectal cancer death within 90, 180 and 365 days after diagnosis. METHODS: Cohort study using linked national cancer and death records. The development population included 27,480 patients diagnosed in England in 2015. The test populations were diagnosed in England in 2016 (n = 26,411) and Wales in 2015–2016 (n = 3814). Predictors were age, gender, socioeconomic status, referral source, performance status, tumour site, TNM stage and treatment intent. Cox regression models were assessed using Brier scores, c-indices and calibration plots. RESULTS: In the development population, 7.4, 11.7 and 17.9% of patients died from colorectal cancer within 90, 180 and 365 days after diagnosis. T4 versus T1 tumour stage had the largest adjusted association with the outcome (HR 4.67; 95% CI: 3.59–6.09). C-indices were 0.873–0.890 (England) and 0.856–0.873 (Wales) in the test populations, indicating excellent separation of predicted risks by outcome status. Models were generally well calibrated. CONCLUSIONS: The model was valid for predicting short-term colorectal cancer mortality. It can provide personalised information to support clinical practice and research. Nature Publishing Group UK 2020-08-24 2020-11-10 /pmc/articles/PMC7652941/ /pubmed/32830202 http://dx.doi.org/10.1038/s41416-020-01034-w Text en © The Author(s), under exclusive licence to Cancer Research UK 2020 https://creativecommons.org/licenses/by/4.0/Note This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution 4.0 International (CC BY 4.0). |
spellingShingle | Article Cowling, Thomas E. Bellot, Alexis Boyle, Jemma Walker, Kate Kuryba, Angela Galbraith, Sarah Aggarwal, Ajay Braun, Michael Sharples, Linda D. van der Meulen, Jan One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
title | One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
title_full | One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
title_fullStr | One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
title_full_unstemmed | One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
title_short | One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
title_sort | one-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652941/ https://www.ncbi.nlm.nih.gov/pubmed/32830202 http://dx.doi.org/10.1038/s41416-020-01034-w |
work_keys_str_mv | AT cowlingthomase oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT bellotalexis oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT boylejemma oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT walkerkate oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT kurybaangela oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT galbraithsarah oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT aggarwalajay oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT braunmichael oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT sharpleslindad oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata AT vandermeulenjan oneyearmortalityofcolorectalcancerpatientsdevelopmentandvalidationofapredictionmodelusinglinkednationalelectronicdata |