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

BACKGROUND: Whilst 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. MET...

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Autores principales: Conroy, Megan C., Reeves, Gillian K., Allen, Naomi E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326925/
https://www.ncbi.nlm.nih.gov/pubmed/37415095
http://dx.doi.org/10.1186/s12889-023-16202-9
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author Conroy, Megan C.
Reeves, Gillian K.
Allen, Naomi E.
author_facet Conroy, Megan C.
Reeves, Gillian K.
Allen, Naomi E.
author_sort Conroy, Megan C.
collection PubMed
description BACKGROUND: Whilst 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. METHODS: We 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. RESULTS: Of 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. CONCLUSIONS: Individuals 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16202-9.
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spelling pubmed-103269252023-07-08 Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study Conroy, Megan C. Reeves, Gillian K. Allen, Naomi E. BMC Public Health Research BACKGROUND: Whilst 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. METHODS: We 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. RESULTS: Of 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. CONCLUSIONS: Individuals 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16202-9. BioMed Central 2023-07-06 /pmc/articles/PMC10326925/ /pubmed/37415095 http://dx.doi.org/10.1186/s12889-023-16202-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Conroy, Megan C.
Reeves, Gillian K.
Allen, Naomi E.
Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study
title Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study
title_full Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study
title_fullStr Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study
title_full_unstemmed Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study
title_short Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study
title_sort multi-morbidity and its association with common cancer diagnoses: a uk biobank prospective study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326925/
https://www.ncbi.nlm.nih.gov/pubmed/37415095
http://dx.doi.org/10.1186/s12889-023-16202-9
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