A case-control study to evaluate the impact of the breast screening programme on breast cancer incidence in England.


Journal

Cancer medicine
ISSN: 2045-7634
Titre abrégé: Cancer Med
Pays: United States
ID NLM: 101595310

Informations de publication

Date de publication:
01 2023
Historique:
revised: 14 06 2022
received: 25 04 2022
accepted: 19 06 2022
pubmed: 20 7 2022
medline: 1 2 2023
entrez: 19 7 2022
Statut: ppublish

Résumé

There is uncertainty about overdiagnosis in mammography screening. We aimed to estimate the effect of screening on breast cancer incidence and overdiagnosis in the NHS Breast Screening Programme in England. The study included 57,493 cases and 105,653 controls, with cases defined as women diagnosed at ages 47-89 with primary breast cancer, invasive or ductal carcinoma in situ, in 2010 or 2011. Where possible, two controls were selected per case, matched on date of birth and screening area. Conditional logistic regression was used to estimate the effect of screening on breast cancer risk, with adjustment for potential self-selection bias. Results were combined with national incidence data to estimate absolute rates of overdiagnosis. Overdiagnosis was calculated as the cumulative excess of cancers diagnosed in the age group 50-77 in a woman attending three-yearly screening between ages 50 and 70 compared with a woman attending no screens. The estimated number of cases overdiagnosed in women attending all screens in the programme was 679.3 per 100,000 without adjustment for self-selection bias and 261.2 per 100,000 with adjustment. These corresponded to an estimated 9.5% of screen-detected cancers overdiagnosed without adjustment and 3.7% with adjustment for self-selection. The NHS Breast Screening Programme in England confers at worst modest levels of overdiagnosis.

Sections du résumé

BACKGROUND
There is uncertainty about overdiagnosis in mammography screening.
METHODS
We aimed to estimate the effect of screening on breast cancer incidence and overdiagnosis in the NHS Breast Screening Programme in England. The study included 57,493 cases and 105,653 controls, with cases defined as women diagnosed at ages 47-89 with primary breast cancer, invasive or ductal carcinoma in situ, in 2010 or 2011. Where possible, two controls were selected per case, matched on date of birth and screening area. Conditional logistic regression was used to estimate the effect of screening on breast cancer risk, with adjustment for potential self-selection bias. Results were combined with national incidence data to estimate absolute rates of overdiagnosis. Overdiagnosis was calculated as the cumulative excess of cancers diagnosed in the age group 50-77 in a woman attending three-yearly screening between ages 50 and 70 compared with a woman attending no screens.
RESULTS
The estimated number of cases overdiagnosed in women attending all screens in the programme was 679.3 per 100,000 without adjustment for self-selection bias and 261.2 per 100,000 with adjustment. These corresponded to an estimated 9.5% of screen-detected cancers overdiagnosed without adjustment and 3.7% with adjustment for self-selection.
CONCLUSIONS
The NHS Breast Screening Programme in England confers at worst modest levels of overdiagnosis.

Identifiants

pubmed: 35851849
doi: 10.1002/cam4.5004
pmc: PMC9883434
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1878-1887

Informations de copyright

© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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Auteurs

Oleg Blyuss (O)

Centre for Prevention, Detection, and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Amanda Dibden (A)

Centre for Prevention, Detection, and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Nathalie J Massat (NJ)

Centre for Prevention, Detection, and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Dharmishta Parmar (D)

Centre for Prevention, Detection, and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Jack Cuzick (J)

Centre for Prevention, Detection, and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Stephen W Duffy (SW)

Centre for Prevention, Detection, and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Peter Sasieni (P)

School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.

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Classifications MeSH