Evidence map›Paper›PMID 37415095›Full record

ArticleBMC public health2023

Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study.

Megan C Conroy, Gillian K Reeves, Naomi E Allen

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

5 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Real-world evidence: state-of-the-art and future perspectives.Journal of comparative effectiveness research · 2025
    Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Megan C ConroyNuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK. megan.conroy@ndph.ox.ac.uk.ORCID 0000-0002-3847-6202
Gillian K Reeves *Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.ORCID 0000-0003-3035-4697
Naomi E Allen *Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.ORCID 0000-0003-1938-5038
University of Oxford · GB

Funding

British Heart FoundationCancer Research UK 29017Cancer Research UK 29186Department of HealthMedical Research Council G0700474Medical Research Council G9900923Medical Research Council MC_PC_20058Medical Research Council MR/K02700X/1Wellcome Trust 205339/Z/16/ZWellcome Trust 223600/Z/21/Z
6 · The paper itself

Abstract

backgroundWhilst multi-morbidity is known to be a concern in people with cancer, very little is known about the risk of cancer in multi-morbid patients. This study aims to investigate the risk of being diagnosed with lung, colorectal, breast and prostate cancer associated with multi-morbidity.

methodsWe investigated the association between multi-morbidity and subsequent risk of cancer diagnosis in UK Biobank. Cox models were used to estimate the relative risks of each cancer of interest in multi-morbid participants, using the Cambridge Multimorbidity Score. The extent to which reverse causation, residual confounding and ascertainment bias may have impacted on the findings was robustly investigated.

resultsOf the 436,990 participants included in the study who were cancer-free at baseline, 21.6% (99,965) were multi-morbid (≥ 2 diseases). Over a median follow-up time of 10.9 [IQR 10.0-11.7] years, 9,019 prostate, 7,994 breast, 5,241 colorectal, and 3,591 lung cancers were diagnosed. After exclusion of the first year of follow-up, there was no clear association between multi-morbidity and risk of colorectal, prostate or breast cancer diagnosis. Those with ≥ 4 diseases at recruitment had double the risk of a subsequent lung cancer diagnosis compared to those with no diseases (HR 2.00 [95% CI 1.70-2.35] p for trend < 0.001). These findings were robust to sensitivity analyses aimed at reducing the impact of reverse causation, residual confounding from known cancer risk factors and ascertainment bias.

conclusionsIndividuals with multi-morbidity are at an increased risk of lung cancer diagnosis. While this association did not appear to be due to common sources of bias in observational studies, further research is needed to understand what underlies this association.

Indexed as

Breast NeoplasmsColorectal NeoplasmsLung NeoplasmsBiological Specimen BanksFemaleHumansMaleMultimorbidityProspective StudiesRisk FactorsUnited KingdomCancer riskMulti-morbidityUK Biobank

Identifiers

PMID37415095
PMCPMC10326925
OpenAlexW4383373687

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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.