Related Experiment Video
Updated: Jul 8, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Mortality from leading cancers in districts of England from 2002 to 2019: a population-based, spatiotemporal study
Theo Rashid1, James E Bennett1, David C Muller1
1Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK.
Background:
Cancers are the leading cause of death in England. We aimed to estimate trends in mortality from leading cancers from 2002 to 2019 for the 314 districts in England.
Methods:
We did a high-resolution spatiotemporal analysis of vital registration data from the UK Office for National Statistics using data on all deaths from the ten leading cancers in England from 2002 to 2019. We used a Bayesian hierarchical model to obtain robust estimates of age-specific and cause-specific death rates. We used life table methods to calculate the primary outcome, the unconditional probability of dying between birth and age 80 years by sex, cancer cause of death, local district, and year. We reported Spearman rank correlations between the probability of dying from a cancer and district-level poverty in 2019.
Findings:
In 2019, the probability of dying from a cancer before age 80 years ranged from 0·10 (95% credible interval [CrI] 0·10-0·11) to 0·17 (0·16-0·18) for women and from 0·12 (0·12-0·13) to 0·22 (0·21-0·23) for men. Variation in the probability of dying was largest for lung cancer among women, being 3·7 times (95% CrI 3·2-4·4) higher in the district with the highest probability than in the district with the lowest probability; and for stomach cancer for men, being 3·2 times (2·6-4·1) higher in the district with the highest probability than in the one with the lowest probability. The variation in the probability of dying was smallest across districts for lymphoma and multiple myeloma (95% CrI 1·2 times [1·1-1·4] higher in the district with the highest probability than the lowest probability for women and 1·2 times [1·0-1·4] for men), and leukaemia (1·1 times [1·0-1·4] for women and 1·2 times [1·0-1·5] for men). The Spearman rank correlation between probability of dying from a cancer and district poverty was 0·74 (95% CrI 0·72-0·76) for women and 0·79 (0·78-0·81) for men. From 2002 to 2019, the overall probability of dying from a cancer declined in all districts: the reductions ranged from 6·6% (95% CrI 0·3-13·1) to 30·1% (25·6-34·5) for women and from 12·8% (7·1-18·8) to 36·7% (32·2-41·2) for men. However, there were increases in mortality for liver cancer among men, lung cancer and corpus uteri cancer among women, and pancreatic cancer in both sexes in some or all districts with posterior probability greater than 0·80.
Interpretation:
Cancers with modifiable risk factors and potential for screening for precancerous lesions had heterogeneous trends and the greatest geographical inequality. To reduce these inequalities, factors affecting both incidence and survival need to be addressed at the local level.
Funding:
Wellcome Trust, Imperial College London, UK Medical Research Council, and the National Institute of Health Research.
Related Concept Videos
Cancer Survival Analysis
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Statistical Methods for Analyzing Epidemiological Data
Kaplan-Meier Approach
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Comparing the Survival Analysis of Two or More Groups

