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Breast Cancer Screening: Global Practices and Future Directions
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Breast Cancer Screening: Global Practices and Future Directions

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Causes, Screening and Diagnosis".

Deadline for manuscript submissions: 26 November 2026 | Viewed by 5113

Special Issue Editor

Dr. Rudolf Morant

E-Mail Website
Guest Editor
Cancer League of Eastern Switzerland, Flurhofstrasse 7, 9000 St. Gallen, Switzerland
Interests: mammography screening; organized screening programmes; tomosynthesis; 2-D mammography; artificial intelligence; personalized screening

Special Issue Information

Dear Colleagues,

Breast cancer is the most common female cancer and, in most countries, it represents the most common cause of death from female cancer. Organized breast cancer screening is performed worldwide but does not cover all geographical areas. It is carried out according to different protocols in different medical settings, with varying participation rates. Organized breast cancer screening has proven efficient in various settings in diagnosing breast cancer at earlier stages, leading to improved survival through the use of less aggressive treatments. It has also been shown to be cost-efficient in certain medical settings. 

Breast cancer mortality has dramatically decreased over recent decades, partially due to increased awareness and earlier detection thanks to successful screening efforts but also due to improved treatment methods and improved, structured treatment protocols in breast cancer centers, involving tumor boards and the cooperation of many specialists, including, surgeons, plastic surgeons, radiation therapists, medical oncologists, geneticists, breast cancer nurses, and psychological and social support.

Most screening programs rely on digital mammography and contact all women in a determined age bracket, often between 50 and 75 years, to invite them to participate.

Through this Special Issue dedicated to breast cancer screening, we will provide an overview of the extent and types of current screening programs in Europe and beyond.

The future of screening involves risk-adapted screening, the integration and use of other technologies, such as tomosynthesis, and the use of ultrasound and magnetic resonance in certain situations. The optimal integration of artificial intelligence into organized screening programs represents a very timely and important topic. Personalized screening according to individual risk should also be discussed. To achieve this, as well as clinical risk factors, risk scores based on the analysis of mammography using artificial intelligence and genetic analyses should be addressed. 

These new possibilities, as well as current efforts and ongoing studies, will be explored in this Special Issue, which will be introduced by an Editorial summarizing the most relevant findings and offering perspectives on the future of organized breast cancer screening.

I look forward to receiving your contributions.

Dr. Rudolf Morant
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mammography screening
  • organized screening programs
  • tomosynthesis
  • 2D mammography
  • artificial intelligence
  • personalized screening

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Published Papers (3 papers)

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Research

13 pages, 1044 KB  
Article
Supplemental Breast Ultrasound in Mammography Screening for Women with Critically Dense Breasts
by Sylvia H. Heywang-Köbrunner, Susanne A. Elsner, Eva Haußmann, Astrid Hacker, Paula Grieger, Moritz Hadwiger, Michael Hertlein and Alexander Katalinic
Cancers 2026, 18(10), 1631; https://doi.org/10.3390/cancers18101631 - 19 May 2026
Viewed by 149
Abstract
Background: The sensitivity of mammography screening is compromised in women with dense breast tissue. Supplemental ultrasound (S-US) can enhance cancer detection, but evidence regarding its feasibility, harms, and benefits within Western population-based screening programs remains limited. Methods: This pragmatic, prospective controlled trial was [...] Read more.
Background: The sensitivity of mammography screening is compromised in women with dense breast tissue. Supplemental ultrasound (S-US) can enhance cancer detection, but evidence regarding its feasibility, harms, and benefits within Western population-based screening programs remains limited. Methods: This pragmatic, prospective controlled trial was integrated into the German national mammography screening program across 16 sites. Breast density was assessed using automated AI software. Women with “critically dense” breasts (top 15–20%) were offered handheld supplemental S-US in addition to mammography (MXUS). The control group (MX-only) comprised women with comparable densities who did not receive S-US. Primary outcomes included cancer detection rate (CDR), recall rate, biopsy rate, and short-term follow-up recommendations. Results: From May 2020 to March 2024, 25,341 women underwent MXUS, while 38,529 received MX-only. The CDR was significantly higher in the MXUS group, at 10.7 per 1000 (95% CI: 9.4–12.0) compared to 7.2 per 1000 (95% CI: 6.4–8.1) in the MX-only group, yielding an incremental CDR of 3.5 per 1000 (95% CI: 1.9–5.0). However, MXUS led to higher rates of recall (6.6% vs. 5.4%), biopsies (3.2% vs. 1.5%), and short-term follow-up recommendations (0.9% vs. 0.5%). Conclusions: Implementing quality-assured S-US for women with critically dense breasts substantially increases the detection of invasive cancers, but also raises false positives. While these results support density-adapted screening, the high resource intensity suggests that future strategies should optimize risk stratification to target S-US more selectively. Long-term data are required to confirm clinical benefits. Full article
(This article belongs to the Special Issue Breast Cancer Screening: Global Practices and Future Directions)
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12 pages, 444 KB  
Article
Association of Breast Density with Breast Cancer Risk and Stage at Diagnosis: A Korean Nationwide Cohort Study
by Hongki Gwak, Donghyoun Lee and Seong Hwan Kim
Cancers 2025, 17(24), 3897; https://doi.org/10.3390/cancers17243897 - 5 Dec 2025
Viewed by 925
Abstract
Background/Objectives: Breast density, as defined by the Breast Imaging Reporting and Data System (BI-RADS), reduces mammographic sensitivity and is a risk factor for breast cancer. However, its association with cancer risk and stage at diagnosis remains debated, with limited large-scale evidence. Methods: We [...] Read more.
Background/Objectives: Breast density, as defined by the Breast Imaging Reporting and Data System (BI-RADS), reduces mammographic sensitivity and is a risk factor for breast cancer. However, its association with cancer risk and stage at diagnosis remains debated, with limited large-scale evidence. Methods: We conducted a nationwide retrospective cohort study of 952,755 Korean women who underwent screening mammography between 2013 and 2014, with breast cancer diagnoses identified over a 5-year follow-up period. Breast density was categorized by BI-RADS criteria (A–D). Breast cancer risk was evaluated using logistic regression, with odds ratios representing relative odds of developing breast cancer during the 5-year interval. Stage at diagnosis was classified as localized versus regional/distant disease according to national cancer registry records. Results: During 5 years of follow-up, 11,286 women (1.2%) were diagnosed with breast cancer. Higher breast density was significantly associated with increased breast cancer risk: multivariable-adjusted odds ratios (ORs) were 1.174 (95% CI, 1.093–1.260), 1.268 (95% CI, 1.186–1.356), and 1.287 (95% CI, 1.196–1.385) for BI-RADS B–D, respectively, compared with BI-RADS A (all p < 0.001). However, the risk of advanced stage (regional/distant vs. localized) disease at diagnosis did not significantly differ across breast density categories except for a modest association in BI-RADS B (OR 1.16, 95% CI, 1.01–1.33; p = 0.035). Conclusions: Higher breast density was independently associated with increased breast cancer risk but not with advanced-stage disease at diagnosis. These findings underscore the importance of individualized screening strategies for women with dense breasts. Full article
(This article belongs to the Special Issue Breast Cancer Screening: Global Practices and Future Directions)
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22 pages, 2468 KB  
Article
Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women
by Peh Joo Ho, Christine Kim Yan Loo, Ryan Jak Yang Lim, Meng Huang Goh, Mustapha Abubakar, Thomas U. Ahearn, Irene L. Andrulis, Natalia N. Antonenkova, Kristan J. Aronson, Annelie Augustinsson, Sabine Behrens, Clara Bodelon, Natalia V. Bogdanova, Manjeet K. Bolla, Kristen D. Brantley, Hermann Brenner, Helen Byers, Nicola J. Camp, Jose E. Castelao, Melissa H. Cessna, Jenny Chang-Claude, Stephen J. Chanock, Georgia Chenevix-Trench, Ji-Yeob Choi, Sarah V. Colonna, Kamila Czene, Mary B. Daly, Francoise Derouane, Thilo Dörk, A. Heather Eliassen, Christoph Engel, Mikael Eriksson, D. Gareth Evans, Olivia Fletcher, Lin Fritschi, Manuela Gago-Dominguez, Jeanine M. Genkinger, Willemina R. R. Geurts-Giele, Gord Glendon, Per Hall, Ute Hamann, Cecilia Y. S. Ho, Weang-Kee Ho, Maartje J. Hooning, Reiner Hoppe, Anthony Howell, Keith Humphreys, Hidemi Ito, Motoki Iwasaki, Anna Jakubowska, Helena Jernström, Esther M. John, Nichola Johnson, Daehee Kang, Sung-Won Kim, Cari M. Kitahara, Yon-Dschun Ko, Peter Kraft, Ava Kwong, Diether Lambrechts, Susanna Larsson, Shuai Li, Annika Lindblom, Martha Linet, Jolanta Lissowska, Artitaya Lophatananon, Robert J. MacInnis, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, Keitaro Matsuo, Kyriaki Michailidou, Roger L. Milne, Nur Aishah Mohd Taib, Kenneth R. Muir, Rachel A. Murphy, William G. Newman, Katie M. O'Brien, Nadia Obi, Olufunmilayo I. Olopade, Mihalis I. Panayiotidis, Sue K. Park, Tjoung-Won Park-Simon, Alpa V. Patel, Paolo Peterlongo, Dijana Plaseska-Karanfilska, Katri Pylkäs, Muhammad U. Rashid, Gad Rennert, Juan Rodriguez, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Christopher G. Scott, Shamim Shahi, Xiao-Ou Shu, Katerina Shulman, Jacques Simard, Melissa C. Southey, Jennifer Stone, Jack A. Taylor, Soo-Hwang Teo, Lauren R. Teras, Mary Beth Terry, Diana Torres, Celine M. Vachon, Maxime Van Houdt, Jelle Verhoeven, Clarice R. Weinberg, Alicja Wolk, Taiki Yamaji, Cheng Har Yip, Wei Zheng, Mikael Hartman, Jingmei Li, on behalf of the ABCTB Investigators, kConFab Investigators, MyBrCa Investigators and SGBCC Investigatorsadd Show full author list remove Hide full author list
Cancers 2025, 17(21), 3561; https://doi.org/10.3390/cancers17213561 - 3 Nov 2025
Cited by 2 | Viewed by 3561
Abstract
Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk [...] Read more.
Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations. Full article
(This article belongs to the Special Issue Breast Cancer Screening: Global Practices and Future Directions)
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