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Napolitano G, Lynge E, Lillholm M, Vejborg I, van Gils CH, Nielsen M, Karssemeijer N. Change in mammographic density across birth cohorts of Dutch breast cancer screening participants. Int J Cancer 2019; 145:2954-2962. [PMID: 30762225 PMCID: PMC6850337 DOI: 10.1002/ijc.32210] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 01/15/2019] [Accepted: 01/31/2019] [Indexed: 12/02/2022]
Abstract
High mammographic density is a well‐known risk factor for breast cancer. This study aimed to search for a possible birth cohort effect on mammographic density, which might contribute to explain the increasing breast cancer incidence. We separately analyzed left and right breast density of Dutch women from a 13‐year period (2003–2016) in the breast cancer screening programme. First, we analyzed age‐specific changes in average percent dense volume (PDV) across birth cohorts. A linear regression analysis (PDV vs. year of birth) indicated a small but statistically significant increase in women of: 1) age 50 and born from 1952 to 1966 (left, slope = 0.04, p = 0.003; right, slope = 0.09, p < 0.0001); 2) age 55 and born from 1948 to 1961 (right, slope = 0.04, p = 0.01); and 3) age 70 and born from 1933 to 1946 (right, slope = 0.05, p = 0.002). A decrease of total breast volume seemed to explain the increase in PDV. Second, we compared proportion of women with dense breast in women born in 1946–1953 and 1959–1966, and observed a statistical significant increase of proportion of highly dense breast in later born women, in the 51 to 55 age‐groups for the left breast (around a 20% increase in each age‐group), and in the 50 to 56 age‐groups for the right breast (increase ranging from 27% to 48%). The study indicated a slight increase in mammography density across birth cohorts, most pronounced for women in their early 50s, and more marked for the right than for the left breast. What's new? Women with dense breast tissue are at increased risk of breast cancer. Here, changes in mammographic density were investigated across birth cohorts in women enrolled in a breast cancer screening program in the Netherlands. The findings reveal an increase in the average fraction of dense tissue in the breast across cohorts. In particular, greater breast density was observed in a higher proportion of women in later‐born than earlier‐born birth cohorts. The increase was most significant among women in their early 50s and may be linked to a reported shift toward older age at menopause among women in Europe.
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Affiliation(s)
- George Napolitano
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Elsebeth Lynge
- Nykøbing Falster Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lillholm
- Department of Computer Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ilse Vejborg
- Department of Radiology, University Hospital Copenhagen, Copenhagen, Denmark
| | - Carla H van Gils
- Department of Epidemiology, Julius Center for Health, Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Mads Nielsen
- Department of Computer Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nico Karssemeijer
- Department of Radiology and Nuclear Medicine, Radboud University, Medical Center, Nijmegen, The Netherlands
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Bokhof B, Khil L, Urbschat I, Gnas L, Hecht G, Heidinger O, Heindel W, Kieschke J, Weigel S, Hense H. Zeitliche Entwicklung der Programmsensitivität des deutschen Mammographie-Screening-Programms in Nordrhein-Westfalen und Niedersachsen. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2018; 61:1517-1527. [DOI: 10.1007/s00103-018-2843-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Ripping TM, Ten Haaf K, Verbeek ALM, van Ravesteyn NT, Broeders MJM. Quantifying Overdiagnosis in Cancer Screening: A Systematic Review to Evaluate the Methodology. J Natl Cancer Inst 2017; 109:3845953. [PMID: 29117353 DOI: 10.1093/jnci/djx060] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 03/10/2017] [Indexed: 12/21/2022] Open
Abstract
Background Overdiagnosis is the main harm of cancer screening programs but is difficult to quantify. This review aims to evaluate existing approaches to estimate the magnitude of overdiagnosis in cancer screening in order to gain insight into the strengths and limitations of these approaches and to provide researchers with guidance to obtain reliable estimates of overdiagnosis in cancer screening. Methods A systematic review was done of primary research studies in PubMed that were published before January 1, 2016, and quantified overdiagnosis in breast cancer screening. The studies meeting inclusion criteria were then categorized by their methods to adjust for lead time and to obtain an unscreened reference population. For each approach, we provide an overview of the data required, assumptions made, limitations, and strengths. Results A total of 442 studies were identified in the initial search. Forty studies met the inclusion criteria for the qualitative review. We grouped the approaches to adjust for lead time in two main categories: the lead time approach and the excess incidence approach. The lead time approach was further subdivided into the mean lead time approach, lead time distribution approach, and natural history modeling. The excess incidence approach was subdivided into the cumulative incidence approach and early vs late-stage cancer approach. The approaches used to obtain an unscreened reference population were grouped into the following categories: control group of a randomized controlled trial, nonattenders, control region, extrapolation of a prescreening trend, uninvited groups, adjustment for the effect of screening, and natural history modeling. Conclusions Each approach to adjust for lead time and obtain an unscreened reference population has its own strengths and limitations, which should be taken into consideration when estimating overdiagnosis.
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Affiliation(s)
- Theodora M Ripping
- Affiliations of authors: Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands (TMR, ALMV, MJMB); Department of Public Health, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands (KtH, NTvR); Dutch Reference Centre for Screening, Nijmegen, the Netherlands (MJMB)
| | - Kevin Ten Haaf
- Affiliations of authors: Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands (TMR, ALMV, MJMB); Department of Public Health, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands (KtH, NTvR); Dutch Reference Centre for Screening, Nijmegen, the Netherlands (MJMB)
| | - André L M Verbeek
- Affiliations of authors: Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands (TMR, ALMV, MJMB); Department of Public Health, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands (KtH, NTvR); Dutch Reference Centre for Screening, Nijmegen, the Netherlands (MJMB)
| | - Nicolien T van Ravesteyn
- Affiliations of authors: Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands (TMR, ALMV, MJMB); Department of Public Health, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands (KtH, NTvR); Dutch Reference Centre for Screening, Nijmegen, the Netherlands (MJMB)
| | - Mireille J M Broeders
- Affiliations of authors: Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands (TMR, ALMV, MJMB); Department of Public Health, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands (KtH, NTvR); Dutch Reference Centre for Screening, Nijmegen, the Netherlands (MJMB)
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Ripping T, Verbeek A, ten Haaf K, van Ravesteyn N, Broeders M. Extrapolation of pre-screening trends: Impact of assumptions on overdiagnosis estimates by mammographic screening. Cancer Epidemiol 2016; 42:147-53. [DOI: 10.1016/j.canep.2016.04.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Revised: 03/22/2016] [Accepted: 04/25/2016] [Indexed: 10/21/2022]
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Bleyer A. Screening mammography: update and review of publications since our report in the New England Journal of Medicine on the magnitude of the problem in the United States. Acad Radiol 2015; 22:949-60. [PMID: 26100188 DOI: 10.1016/j.acra.2015.03.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Revised: 02/15/2015] [Accepted: 03/08/2015] [Indexed: 12/16/2022]
Abstract
RATIONALE AND OBJECTIVES After a half century of clinical trials, expansive observations, vigorous advocacy and debate, screening mammography could not be in a more controversial condition, especially the potential harm of overdiagnosis. Despite a simple rationale (catch the cancer early and either prevent death or at least decrease the amount of therapy needed for cure), the estimates to date of overdiagnosis rates are conflicting and the interpretations complex. MATERIALS AND METHODS Since the author's 2012 publication in the New England Journal of Medicine (NEJM), the peer-reviewed publications on overdiagnosis caused by screening mammography are reviewed and the NEJM analyses updated with three additional calendar years of results. RESULTS The recent peer-reviewed medical literature on screening mammography induced overdiagnosis of breast cancer has increased exponentially, nearly 10-fold in 10 years. The average estimate of overdiagnosis is about 30%, but the range extends from 0% to 70+%. An update of the NEJM report estimates that in the US, 78,000 women and 30%-31% of those diagnosed with breast cancer at the age of 40 years or older during 2011 were overdiagnosed. CONCLUSIONS Until we have better screening procedures that identify who really has cancer and needs to be treated, the risk of overdiagnosis relative to the benefit of screening merits more effective public and professional education. Radiologists, pathologists, and other professionals involved with screening mammography should recognize that the potential harm of overdiagnosis is downplayed or not discussed with the patient and family, despite agreement that the objective is informed choice.
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Ripping TM, Verbeek ALM, Fracheboud J, de Koning HJ, van Ravesteyn NT, Broeders MJM. Overdiagnosis by mammographic screening for breast cancer studied in birth cohorts in The Netherlands. Int J Cancer 2015; 137:921-9. [PMID: 25612892 DOI: 10.1002/ijc.29452] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2014] [Accepted: 01/13/2015] [Indexed: 11/11/2022]
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.
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Affiliation(s)
- T M Ripping
- Department for Health Evidence, Radboud university medical center, Nijmegen, The Netherlands
| | - A L M Verbeek
- Department for Health Evidence, Radboud university medical center, Nijmegen, The Netherlands.,Dutch Reference Center for Screening, Nijmegen, The Netherlands
| | - J Fracheboud
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands
| | - H J de Koning
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands
| | - N T van Ravesteyn
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands
| | - M J M Broeders
- Department for Health Evidence, Radboud university medical center, Nijmegen, The Netherlands.,Dutch Reference Center for Screening, Nijmegen, The Netherlands
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