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Estimates of overdiagnosis from two trials of mammographic screening for breast cancer
Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Medical Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology UHL.
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2005 (English)In: Breast Cancer Research, ISSN 1465-542X, Vol. 7, no 6, 258-265 p.Article in journal (Refereed) Published
Abstract [en]

Randomised controlled trials have shown that the policy of mammographic screening confers a substantial and significant reduction in breast cancer mortality. This has often been accompanied, however, by an increase in breast cancer incidence, particularly during the early years of a screening programme, which has led to concerns about overdiagnosis, that is to say, the diagnosis of disease that, if left undetected and therefore untreated, would not become symptomatic. We used incidence data from two randomised controlled trials of mammographic screening, the Swedish Two-county Trial and the Gothenburg Trial, to establish the timing and magnitude of any excess incidence of invasive disease and ductal carcinoma in situ (DCIS) in the study groups, to ascertain whether the excess incidence of DCIS reported early in a screening trial is balanced by a later deficit in invasive disease and provide explicit estimates of the rate of 'real' and non-progressive 'overdiagnosed' tumours from the study groups of the trials. We used a multistate model for overdiagnosis and used Markov Chain Monte Carlo methods to estimate the parameters. After taking into account the effect of lead time, we estimated that less than 5% of cases diagnosed at prevalence screen and less than 1 % of cases diagnosed at incidence screens are being overdiagnosed. Overall, we estimate overdiagnosis to be around 1 % of all cases diagnosed in screened populations. These estimates are, however, subject to considerable uncertainty. Our results suggest that overdiagnosis in mammography screening is a minor phenomenon, but further studies with very large numbers are required for more precise estimation. © 2005 BioMed Central Ltd.

Place, publisher, year, edition, pages
2005. Vol. 7, no 6, 258-265 p.
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-30243DOI: 10.1186/bcr1354Local ID: 15748OAI: diva2:251065
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2011-01-12

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Faculty of Health SciencesMedical RadiologyDepartment of Radiology UHL
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Breast Cancer Research
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