One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data

Br J Cancer. 2020 Nov;123(10):1474-1480. doi: 10.1038/s41416-020-01034-w. Epub 2020 Aug 24.

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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Colorectal Neoplasms / diagnosis
  • Colorectal Neoplasms / epidemiology
  • Colorectal Neoplasms / mortality*
  • Colorectal Neoplasms / pathology
  • Electronic Health Records / statistics & numerical data*
  • England / epidemiology
  • Female
  • Follow-Up Studies
  • Humans
  • Male
  • Medical Record Linkage / methods
  • Middle Aged
  • Mortality
  • Prognosis
  • Proportional Hazards Models
  • Risk Assessment
  • Socioeconomic Factors
  • Survival Analysis
  • Wales / epidemiology
  • Young Adult