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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.
Afiliação
  • Cowling TE; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK. thomas.cowling@lshtm.ac.uk.
  • Bellot A; Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK. thomas.cowling@lshtm.ac.uk.
  • Boyle J; Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK.
  • Walker K; Alan Turing Institute, London, UK.
  • Kuryba A; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK.
  • Galbraith S; Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
  • Aggarwal A; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK.
  • Braun M; Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
  • Sharples LD; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK.
  • van der Meulen J; Department of Palliative Care, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Br J Cancer ; 123(10): 1474-1480, 2020 11.
Article em En | MEDLINE | ID: mdl-32830202
ABSTRACT

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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Registros Eletrônicos de Saúde Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Br J Cancer Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Registros Eletrônicos de Saúde Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Br J Cancer Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Reino Unido