| Title: | Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study |
| Journal: | BMC Public Health |
| Published: | 6 Jul 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37415095/ |
| DOI: | https://doi.org/10.1186/s12889-023-16202-9 |
| URL: | https://bmcpublichealth.biomedcentral.com/counter/pdf/10.1186/s12889-023-16202-9 |
Publication 10305
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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.</p>
3 Authors
- Megan C. Conroy
- Gillian K. Reeves
- Naomi E. Allen
1 Application
| Application ID | Title |
|---|---|
| 41115 | Investigating lifestyle factors on cancer outcomes |
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