Greene, G., Griffiths, R., Han, J. et al. (10 more authors) (2022) Impact of the SARS-CoV-2 pandemic on female breast, colorectal and non-small cell lung cancer incidence, stage and healthcare pathway to diagnosis during 2020 in Wales, UK, using a national cancer clinical record system. British Journal of Cancer, 127 (3). pp. 558-568. ISSN 0007-0920
Abstract
Background COVID-19 pandemic responses impacted behaviour and health services. We estimated the impact on incidence, stage and healthcare pathway to diagnosis for female breast, colorectal and non-small cell lung cancers at population level in Wales.
Methods Cancer e-record and hospital admission data linkage identified adult cases, stage and healthcare pathway to diagnosis (population ~2.5 million). Using multivariate Poisson regressions, we compared 2019 and 2020 counts and estimated incidence rate ratios (IRR).
Results Cases decreased 15.2% (n = −1011) overall. Female breast annual IRR was 0.81 (95% CI: 0.76–0.86, p < 0.001), colorectal 0.80 (95% CI: 0.79–0.81, p < 0.001) and non-small cell lung 0.91 (95% CI: 0.90–0.92, p < 0.001). Decreases were largest in 50–69 year olds for female breast and 80+ year olds for all cancers. Stage I female breast cancer declined 41.6%, but unknown stage increased 55.8%. Colorectal stages I–IV declined (range 26.6–29.9%), while unknown stage increased 803.6%. Colorectal Q2-2020 GP-urgent suspected cancer diagnoses decreased 50.0%, and 53.9% for non-small cell lung cancer. Annual screen-detected female breast and colorectal cancers fell 47.8% and 13.3%, respectively. Non-smal -cell lung cancer emergency presentation diagnoses increased 9.5% (Q2-2020) and 16.3% (Q3-2020).
Conclusion Significantly fewer cases of three common cancers were diagnosed in 2020. Detrimental impacts on outcomes varied between cancers. Ongoing surveillance with health service optimisation will be needed to mitigate impacts.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s), under exclusive licence to Springer Nature Limited 2022. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1038/s41416-022-01830-6. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Pathology and Data Analytics The University of Leeds > Academic Services (Leeds) > IT |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Jul 2024 12:31 |
Last Modified: | 12 Jul 2024 10:10 |
Status: | Published |
Publisher: | Springer Nature |
Identification Number: | 10.1038/s41416-022-01830-6 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:214136 |