Evidence map›Paper›PMID 38096890›Full record

ArticleThe Lancet. Oncology2024

Mortality from leading cancers in districts of England from 2002 to 2019: a population-based, spatiotemporal study.

Theo Rashid, James E Bennett, David C Muller, Amanda J Cross, Jonathan Pearson-Stuttard, Perviz Asaria, Hima Iyathooray Daby, Daniela Fecht, Bethan Davies, Majid Ezzati

Open access · hybridAbstract read
In one paragraph

Article in The Lancet. Oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
9.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Theo RashidDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK.
James E BennettDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK.
David C MullerDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK.
Amanda J CrossDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Department of Surgery and Cancer, Imperial College London, London, UK.
Jonathan Pearson-StuttardDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; Health Analytics, Lane Clark and Peacock, London, UK.
Perviz AsariaDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; Department of Cardiology, Imperial College NHS Trust, London, UK.
Hima Iyathooray DabyDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Daniela FechtDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Bethan DaviesDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Majid EzzatiDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK; Regional Institute for Population Studies, University of Ghana, Accra, Ghana. Electronic address: majid.ezzati@imperial.ac.uk.
Imperial College London · GBMRC Centre for Environment and HealthImperial College Healthcare NHS Trust · GBUniversity of Ghana · GH

Funding

Cancer Research UK 25004Cancer Research UK PRCRPG-NOV22/100001Medical Research Council MR/L01341X/1Medical Research Council MR/S019669/1Medical Research Council MR/T03226X/1Medical Research Council MR/V034057/1Wellcome Trust 209376
6 · The paper itself

Abstract

backgroundCancers 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.

methodsWe 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.

findingsIn 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.

interpretationCancers 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.

fundingWellcome Trust, Imperial College London, UK Medical Research Council, and the National Institute of Health Research.

Indexed as

Liver NeoplasmsLung NeoplasmsAged, 80 and overBayes TheoremCause of DeathFemaleHumansInfantMaleMortalityRisk Factors

Identifiers

PMID38096890
PMCPMC7615518
OpenAlexW4389539845

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.