Model of outcomes of screening mammography: information to support informed choices
BMJ 2005; 330 doi: https://doi.org/10.1136/bmj.38398.469479.8F (Published 21 April 2005) Cite this as: BMJ 2005;330:936
- Alexandra Barratt, associate professor of epidemiology (alexb{at}health.usyd.edu.au)1,
- Kirsten Howard, research fellow health economics1,
- Les Irwig, professor of epidemiology1,
- Glenn Salkeld, associate professor of health economics1,
- Nehmat Houssami, clinical associate and honorary senior lecturer1
- 1 Screening and Test Evaluation Program, School of Public Health, University of Sydney, NSW 2006, Australia
- Correspondence to: A Barratt
- Accepted 9 February 2005
Abstract
Objective To provide easy to use estimates of the benefits and harms of biennial screening mammography for women aged 40, 50, 60, and 70 years.
Design Markov process model, with data from BreastScreen Australia, the Australian Institute of Health and Welfare, and the Australian Bureau of Statistics.
Main outcome measure Age specific outcomes expressed per 1000 women over 10 years.
Results For every 1000 women screened over 10 years, 167-251 (depending on age) receive an abnormal result; 56-64 of these women undergo at least one biopsy, 9-26 have an invasive cancer detected by screening, and 3-6 have ductal carcinoma in situ (DCIS) detected by screening. More breast cancers (both invasive and DCIS) are diagnosed among screened than unscreened women. For example, among 1000 women aged 50 who have five biennial screens, 33 breast cancers are diagnosed: 28 invasive cancers (18 detected at screening and 10 interval cancers) and five DCIS (all detected at screening). By comparison, among 1000 women aged 50 who decline screening, 20 cancers are diagnosed over 10 years. There are about 0.5, 2, 3, and 2 fewer deaths from breast cancer over 10 years per 1000 women aged 40, 50, 60, and 70, respectively, who choose to be screened compared with women who decline screening at times determined by relevant policy.
Conclusion Benefits and harms of screening mammography are relatively finely balanced. Quantitative estimates such as these can be used to support individual informed choices about screening.
Footnotes
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The formula used to calculate mortality from breast cancer in unscreened women is on bmj.com -
Contributors All authors contributed to the intellectual development of this paper. AB wrote the first draft and coordinated all revisions. KH undertook the modelling. All authors commented on drafts of the paper. All authors are guarantors
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Funding This work was undertaken as part of the screening and test evaluation programme, funded by the National Health and Medical Research Council of Australia (grant No 211205).
Competing interests: None declared
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Competing interests None declared
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Ethical approval Not required.
- Accepted 9 February 2005