title: Overdiagnosis and overtreatment associated with breast cancer mammography screening: A simulation study with calibration to population-based data.
abstract: OBJECTIVE
  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.
  
  
  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.
  
  
  CONCLUSIONS
  Our estimates of overdiagnosis should be balanced against the reduction of breast cancer mortality to assess the value of breast cancer screening programme.
authors.affiliation: 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.
authors.forename: Arnaud
authors.initials: A
authors.lastname: Seigneurin
authors.affiliation: 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.
authors.forename: José
authors.initials: J
authors.lastname: Labarère
authors.affiliation: 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.
authors.forename: Olivier
authors.initials: O
authors.lastname: François
authors.affiliation: Office De Lutte contre le Cancer, 38240 Meylan, France.
authors.forename: Catherine
authors.initials: C
authors.lastname: Exbrayat
authors.affiliation: 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.
authors.forename: Maylis
authors.initials: M
authors.lastname: Dupouy
authors.affiliation: 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.
authors.forename: Marc
authors.initials: M
authors.lastname: Filippi
authors.affiliation: Registre du Cancer de l'Isère, Pavillon E, Centre Hospitalier Universitaire de Grenoble, Cs 10217, 38043 Grenoble Cedex 9, France.
authors.forename: Marc
authors.initials: M
authors.lastname: Colonna
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D000071960:Breast Carcinoma In Situ / Q000000981:diagnostic imaging* / Q000453:epidemiology* / Q000401:mortality / Q000628:therapy; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology* / Q000401:mortality / Q000628:therapy; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging* / Q000453:epidemiology* / Q000401:mortality / Q000628:therapy; D003198:Computer Simulation; D055088:Early Detection of Cancer; D005189:False Positive Reactions; D005260:Female; D005602:France / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D008197:Lymph Node Excision / Q000706:statistics & numerical data; D008327:Mammography / Q000009:adverse effects*; D015412:Mastectomy, Segmental / Q000706:statistics & numerical data; D000069342:Medical Overuse / Q000706:statistics & numerical data*; D008875:Middle Aged; D015233:Models, Statistical; D011878:Radiotherapy / Q000706:statistics & numerical data; D019564:Unnecessary Procedures / Q000706:statistics & numerical data
keywords: Breast cancer; Cancer screening; Epidemiology; Modelling