Citations 2
NCCN Guidelines® Insights: Breast Cancer Screening and Diagnosis, Version 1.2023
Bevers, Therese B. , Niell, Bethany L. , Bonaccio, Ermelinda, Camp, Melissa , Chikarmane, Sona A. , Eghtedari, Mohammad , Flanagan, Meghan R. , Hawley, Jeffrey , Helvie, Mark A. , Hodgkiss, Linda, Hoyt, Tamarya L., Ivanovich, Jennifer , Kulkarni, Swati , Lancaster, Rachael, Mauer, Caitlin , Pearlman, Mark D. , Philpotts, Liane E. , Plichta, Jennifer K. , Shakeri, Shadi Aminololama, Smith, Mary Lou , Streibert, Clarie L., Strigel, Roberta M. , Tumyan, Lusine , Winkler, Nicole , Wolverton, Dulcy , Bergman, Mary Anne, Stehman, Katie, Plichta, Jennifer K , Baker, Jennifer L. , Bennett, Debbie Lee , Conant, Emily F. , Jochelson, Maxine S. , Maxwell, Jessica, Patel, Bhavika , Plecha, Donna , Kumar, Rashmi
Journal of the National Comprehensive Cancer Network | September 6, 2023 | Volume: 21 | Issue: 9 | Pages: 900-909
The NCCN Guidelines for Breast Cancer Screening and Diagnosis provide health care providers with a practical, consistent framework for screening and evaluating a spectrum of clinical presentations and breast lesions. The NCCN Breast Cancer Screening and Diagnosis Panel is composed of a multidisciplinary team of experts in the field, including representation from medical oncology, gynecologic oncology, surgical oncology, internal medicine, family practice, preventive medicine, pathology, diagnostic and interventional radiology, as well as patient advocacy. The NCCN Breast Cancer Screening and Diagnosis Panel meets at least annually to review emerging data and comments from reviewers within their institutions to guide updates to existing recommendations. These NCCN Guidelines Insights summarize the panel’s decision-making and discussion surrounding the most recent updates to the guideline’s screening recommendations.
Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures
Stone, Jennifer , Thompson, Deborah J. , dos‐Santos‐Silva, Isabel , Lindström, Sara , Hazra, Aditi , Li, Jingmei , Eriksson, Louise , Jensen, Matt , Cunningham, Julie M. , Purrington, Kristen S. , Brown, Judith, Leyland, Jean, Warren, Ruth , Luben, Robert , Smith, Paula , Jud, Sebastian M. , Heusinger, Katharina, Beckmann, Matthias W. , Douglas, Julie A. , Shah, Kaanan P., Chan, Heang‐Ping , Helvie, Mark A. , Kolonel, Laurence N. , Woolcott, Christy , Haiman, Christopher A. , Giles, Graham G. , Baglietto, Laura , Krishnan, Kavitha , Southey, Melissa C. , Apicella, Carmel, Andrulis, Irene L. , Knight, Julia A. , Ursin, Giske , Alnæs, Grethe I.G., Kristensen, Vessela N. , Børresen‐Dale, Anne‐Lise , Bolla, Manjeet K. , Wang, Qin , Michailidou, Kyriaki , Simard, Jacques , Dunning, Alison M. , Easton, Douglas F. , Fasching, Peter A. , Vachon, Celine M. , Durocher, Francine , Cunningham, Julie, Scott, Christopher G. , Tamimi, Rulla M. , Kraft, Peter , Czene, Kamila , Hall, Per N , Olson, Janet E. , Couch, Fergus J. , Khaw, Kay‐Tee , Wareham, Nicholas J. , Marchand, Loı̈c Le , Maskarinec, Gertraud , Gram, Inger Torhild , Dennis, Joe , Pharoah, Paul D.P. , Pankratz, V. Shane , Hopper, John L. , Vachon, Celine M. , Luben, Robert N , Giles, Graham G , Southey, Melissa C , Dunning, Alison M , Li, Jingmei , Michailidou, Kyriaki , Simard, Jacques , Stone, Jennifer , Baglietto, Laura , Purrington, Kristen S , Chan, Heang-Ping
Cancer Research | April 10, 2015 | Volume: 75 | Issue: 12 | Pages: 2457-2467
Abstract Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.