Literature DB >> 25612892

Overdiagnosis by mammographic screening for breast cancer studied in birth cohorts in The Netherlands.

T M Ripping1, A L M Verbeek1,2, J Fracheboud3, H J de Koning3, N T van Ravesteyn3, M J M Broeders1,2.   

Abstract

A drawback of early detection of breast cancer through mammographic screening is the diagnosis of breast cancers that would never have become clinically detected. This phenomenon, called overdiagnosis, is ideally quantified from the breast cancer incidence of screened and unscreened cohorts of women with follow-up until death. Such cohorts do not exist, requiring other methods to estimate overdiagnosis. We are the first to quantify overdiagnosis from invasive breast cancer and ductal carcinoma in situ (DCIS) in birth cohorts using an age-period-cohort -model (APC-model) including variables for the initial and subsequent screening rounds and a 5-year period after leaving screening. Data on the female population and breast cancer incidence were obtained from Statistics Netherlands, "Stichting Medische registratie" and the Dutch Cancer Registry for women aged 0-99 years. Data on screening participation was obtained from the five regional screening organizations. Overdiagnosis was calculated from the excess breast cancer incidence in the screened group divided by the breast cancer incidence in presence of screening for women aged 20-99 years (population perspective) and for women in the screened-age range (individual perspective). Overdiagnosis of invasive breast cancer was 11% from the population perspective and 17% from the invited women perspective in birth cohorts screened from age 49 to 74. For invasive breast cancer and DCIS together, overdiagnosis was 14% from population perspective and 22% from invited women perspective. A major strength of an APC-model including the different phases of screening is that it allows to estimate overdiagnosis in birth cohorts, thereby preventing overestimation.
© 2015 UICC.

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Year:  2015        PMID: 25612892     DOI: 10.1002/ijc.29452

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  8 in total

1.  Double versus single reading of mammograms in a breast cancer screening programme: a cost-consequence analysis.

Authors:  Margarita C Posso; Teresa Puig; Ma Jesus Quintana; Judit Solà-Roca; Xavier Bonfill
Journal:  Eur Radiol       Date:  2016-01-08       Impact factor: 5.315

2.  Effectiveness of and overdiagnosis from mammography screening in the Netherlands: population based study.

Authors:  Philippe Autier; Magali Boniol; Alice Koechlin; Cécile Pizot; Mathieu Boniol
Journal:  BMJ       Date:  2017-12-05

3.  The method of detection of ductal carcinoma in situ has no therapeutic implications: results of a population-based cohort study.

Authors:  Lotte E Elshof; Michael Schaapveld; Emiel J Rutgers; Marjanka K Schmidt; Linda de Munck; Flora E van Leeuwen; Jelle Wesseling
Journal:  Breast Cancer Res       Date:  2017-03-09       Impact factor: 6.466

4.  Subsequent risk of ipsilateral and contralateral invasive breast cancer after treatment for ductal carcinoma in situ: incidence and the effect of radiotherapy in a population-based cohort of 10,090 women.

Authors:  Lotte E Elshof; Michael Schaapveld; Marjanka K Schmidt; Emiel J Rutgers; Flora E van Leeuwen; Jelle Wesseling
Journal:  Breast Cancer Res Treat       Date:  2016-09-08       Impact factor: 4.872

Review 5.  Prevalence of incidental breast cancer and precursor lesions in autopsy studies: a systematic review and meta-analysis.

Authors:  Elizabeth T Thomas; Chris Del Mar; Paul Glasziou; Gordon Wright; Alexandra Barratt; Katy J L Bell
Journal:  BMC Cancer       Date:  2017-12-02       Impact factor: 4.430

6.  Use of Mastectomy for Overdiagnosed Breast Cancer in the United States: Analysis of the SEER 9 Cancer Registries.

Authors:  C Harding; F Pompei; D Burmistrov; R Wilson
Journal:  J Cancer Epidemiol       Date:  2019-01-22

7.  Prognostic value of histopathological DCIS features in a large-scale international interrater reliability study.

Authors:  Emma J Groen; Jan Hudecek; Lennart Mulder; Maartje van Seijen; Mathilde M Almekinders; Stoyan Alexov; Anikó Kovács; Ales Ryska; Zsuzsanna Varga; Francisco-Javier Andreu Navarro; Simonetta Bianchi; Willem Vreuls; Eva Balslev; Max V Boot; Janina Kulka; Ewa Chmielik; Ellis Barbé; Mathilda J de Rooij; Winand Vos; Andrea Farkas; Natalja E Leeuwis-Fedorovich; Peter Regitnig; Pieter J Westenend; Loes F S Kooreman; Cecily Quinn; Giuseppe Floris; Gábor Cserni; Paul J van Diest; Esther H Lips; Michael Schaapveld; Jelle Wesseling
Journal:  Breast Cancer Res Treat       Date:  2020-07-30       Impact factor: 4.872

8.  Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort.

Authors:  Inge M M Lakeman; Mar Rodríguez-Girondo; Andrew Lee; Rikje Ruiter; Bruno H Stricker; Sara R A Wijnant; Maryam Kavousi; Antonis C Antoniou; Marjanka K Schmidt; André G Uitterlinden; Jeroen van Rooij; Peter Devilee
Journal:  Genet Med       Date:  2020-07-06       Impact factor: 8.864

  8 in total

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