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Overdiagnosis and overtreatment associated with breast cancer mammography screening: A simulation study with calibration to population-based data

Affiliations

• ¹ Unité d'évaluation médicale, pavillon Taillefer, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France; Université Joseph Fourier Grenoble 1, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique Mathématiques et Applications Grenoble, Unité Mixte de Recherche 5525, 38041 Grenoble, France. Electronic address: aseigneurin@chu-grenoble.fr.
• ² Unité d'évaluation médicale, pavillon Taillefer, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France; Université Joseph Fourier Grenoble 1, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique Mathématiques et Applications Grenoble, Unité Mixte de Recherche 5525, 38041 Grenoble, France.
• ³ Université Joseph Fourier Grenoble 1, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique Mathématiques et Applications Grenoble, Unité Mixte de Recherche 5525, 38041 Grenoble, France.
• ⁴ Office De Lutte contre le Cancer, 38240 Meylan, France.
• ⁵ Registre du Cancer de l'Isère, Pavillon E, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France.

• PMID: 27240167
• DOI: 10.1016/j.breast.2016.04.013

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Arnaud Seigneurin et al. Breast. 2016 Aug.

• ¹ Unité d'évaluation médicale, pavillon Taillefer, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France; Université Joseph Fourier Grenoble 1, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique Mathématiques et Applications Grenoble, Unité Mixte de Recherche 5525, 38041 Grenoble, France. Electronic address: aseigneurin@chu-grenoble.fr.
• ² Unité d'évaluation médicale, pavillon Taillefer, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France; Université Joseph Fourier Grenoble 1, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique Mathématiques et Applications Grenoble, Unité Mixte de Recherche 5525, 38041 Grenoble, France.
• ³ Université Joseph Fourier Grenoble 1, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique Mathématiques et Applications Grenoble, Unité Mixte de Recherche 5525, 38041 Grenoble, France.
• ⁴ Office De Lutte contre le Cancer, 38240 Meylan, France.
• ⁵ Registre du Cancer de l'Isère, Pavillon E, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France.

• PMID: 27240167
• DOI: 10.1016/j.breast.2016.04.013

Item in Clipboard

Objectives: The magnitude of overdiagnosis of breast cancer associated with mammography screening remains controversial because of methodological issues. The objective of this study was to quantify overdiagnosis and overtreatment associated with a population-based screening programme, taking into account lead time and uncertainty concerning baseline incidence of breast cancers.

Material and methods: A simulation model was developed to replicate incidence and detection rates of breast cancer observed in the Isère Département, France. The parameters of the model were estimated using an approximate Bayesian computation method.

Results: For women aged 50-74 years during the 2007-2010 period, overdiagnosis of non-progressive breast cancers accounted for 17.0% (95% credibility interval (CI): 2.5%-35.5%) of all in situ cancers diagnosed, 5.5% (95% CI: 0.8%-9.8%) of all invasive cancers diagnosed, and 20.3% (95% CI: 3.0%-38.9%) of in situ and 13.0% (95% CI: 2.2%-23.3%) of invasive screen detected breast cancers. The estimates of overdiagnosis due to competitive causes of death were 1.0% (95% CI: 0.2%-%1.7) and 1.1% (95% CI: 0.6%-1.7%) for all in situ and invasive cancers diagnosed, respectively, and 1.3% (95% CI: 0.2%-2.0%) and 2.6% (95% CI: 1.4%-4.0%) of all in situ and invasive screen detected breast cancers, respectively. Among 1000 screen-detected cancers in 2010, 155 (95% CI: 27-284), 134 (95% CI: 10-242) and 140 (95% CI: 25-254) women underwent breast conserving surgery, lymph node dissection and radiation therapy for overdiagnosed cancers, respectively.

Conclusion: Our estimates of overdiagnosis should be balanced against the reduction of breast cancer mortality to assess the value of breast cancer screening programme.

Keywords: Breast cancer; Cancer screening; Epidemiology; Modelling.

Copyright © 2016 Elsevier Ltd. All rights reserved.

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