NCCN Guidelines® Insights: Breast Cancer Screening and Diagnosis, Version 1.2023

Featured Updates to the NCCN Guidelines

Authors:
Therese B. Bevers The University of Texas MD Anderson Cancer Center

Search for other papers by Therese B. Bevers in
Current site
Google Scholar
PubMed
Close
 MD
,
Bethany L. Niell Moffitt Cancer Center

Search for other papers by Bethany L. Niell in
Current site
Google Scholar
PubMed
Close
 MD, PhD
,
Jennifer L. Baker UCLA Jonsson Comprehensive Cancer Center

Search for other papers by Jennifer L. Baker in
Current site
Google Scholar
PubMed
Close
 MD
,
Debbie L. Bennett Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine

Search for other papers by Debbie L. Bennett in
Current site
Google Scholar
PubMed
Close
 MD
,
Ermelinda Bonaccio Roswell Park Comprehensive Cancer Center

Search for other papers by Ermelinda Bonaccio in
Current site
Google Scholar
PubMed
Close
 MD
,
Melissa S. Camp The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins

Search for other papers by Melissa S. Camp in
Current site
Google Scholar
PubMed
Close
 MD
,
Sona Chikarmane Dana-Farber/Brigham and Women’s Cancer Center

Search for other papers by Sona Chikarmane in
Current site
Google Scholar
PubMed
Close
 MD
,
Emily F. Conant Abramson Cancer Center at the University of Pennsylvania

Search for other papers by Emily F. Conant in
Current site
Google Scholar
PubMed
Close
 MD
,
Mohammad Eghtedari UC San Diego Moores Cancer Center

Search for other papers by Mohammad Eghtedari in
Current site
Google Scholar
PubMed
Close
 MD, PhD
,
Meghan R. Flanagan Fred Hutchinson Cancer Center

Search for other papers by Meghan R. Flanagan in
Current site
Google Scholar
PubMed
Close
 MD, MPH
,
Jeffrey Hawley The Ohio State University Comprehensive Cancer Center - James Cancer Hospital and Solove Research Institute

Search for other papers by Jeffrey Hawley in
Current site
Google Scholar
PubMed
Close
 MD
,
Mark Helvie University of Michigan Rogel Cancer Center

Search for other papers by Mark Helvie in
Current site
Google Scholar
PubMed
Close
 MD
,
Linda Hodgkiss St. Jude Children’s Research Hospital/The University of Tennessee Health Science Center

Search for other papers by Linda Hodgkiss in
Current site
Google Scholar
PubMed
Close
 MD
,
Tamarya L. Hoyt Vanderbilt-Ingram Cancer Center

Search for other papers by Tamarya L. Hoyt in
Current site
Google Scholar
PubMed
Close
 MD
,
Jennifer Ivanovich Indiana University Melvin and Bren Simon Comprehensive Cancer Center

Search for other papers by Jennifer Ivanovich in
Current site
Google Scholar
PubMed
Close
 MS, CGC
,
Maxine S. Jochelson Memorial Sloan Kettering Cancer Center

Search for other papers by Maxine S. Jochelson in
Current site
Google Scholar
PubMed
Close
 MD
,
Swati Kulkarni Robert H. Lurie Comprehensive Cancer Center of Northwestern University

Search for other papers by Swati Kulkarni in
Current site
Google Scholar
PubMed
Close
 MD
,
Rachael B. Lancaster O’Neal Comprehensive Cancer Center at UAB

Search for other papers by Rachael B. Lancaster in
Current site
Google Scholar
PubMed
Close
 MD
,
Caitlin Mauer UT Southwestern Simmons Comprehensive Cancer Center

Search for other papers by Caitlin Mauer in
Current site
Google Scholar
PubMed
Close
 MA, MS, CGC
,
Jessica Maxwell Fred & Pamela Buffett Cancer Center

Search for other papers by Jessica Maxwell in
Current site
Google Scholar
PubMed
Close
 MD, MS
,
Bhavika K. Patel Mayo Clinic Comprehensive Cancer Center

Search for other papers by Bhavika K. Patel in
Current site
Google Scholar
PubMed
Close
 MD
,
Mark Pearlman University of Michigan Rogel Cancer Center

Search for other papers by Mark Pearlman in
Current site
Google Scholar
PubMed
Close
 MD
,
Liane Philpotts Yale Cancer Center/Smilow Cancer Hospital

Search for other papers by Liane Philpotts in
Current site
Google Scholar
PubMed
Close
 MD
,
Donna Plecha Case Comprehensive Cancer Center/University Hospitals Seidman Cancer Center and Cleveland Clinic Taussig Cancer Institute

Search for other papers by Donna Plecha in
Current site
Google Scholar
PubMed
Close
 MD
,
Jennifer K. Plichta Duke Cancer Institute

Search for other papers by Jennifer K. Plichta in
Current site
Google Scholar
PubMed
Close
 MD, MS
,
Shadi Shakeri UC Davis Comprehensive Cancer Center

Search for other papers by Shadi Shakeri in
Current site
Google Scholar
PubMed
Close
 MD
,
Mary Lou Smith Research Advocacy Network

Search for other papers by Mary Lou Smith in
Current site
Google Scholar
PubMed
Close
 JD, MBA
,
Clarie L. Streibert Fox Chase Cancer Center

Search for other papers by Clarie L. Streibert in
Current site
Google Scholar
PubMed
Close
 MD
,
Roberta M. Strigel University of Wisconsin Carbone Cancer Center

Search for other papers by Roberta M. Strigel in
Current site
Google Scholar
PubMed
Close
 MD, MS
,
Lusine Tumyan City of Hope National Medical Center

Search for other papers by Lusine Tumyan in
Current site
Google Scholar
PubMed
Close
 MD
,
Nicole S. Winkler Huntsman Cancer Institute at the University of Utah

Search for other papers by Nicole S. Winkler in
Current site
Google Scholar
PubMed
Close
 MD
,
Dulcy E. Wolverton University of Colorado Cancer Center

Search for other papers by Dulcy E. Wolverton in
Current site
Google Scholar
PubMed
Close
 MD
,
Mary Anne Bergman National Comprehensive Cancer Network

Search for other papers by Mary Anne Bergman in
Current site
Google Scholar
PubMed
Close
,
Rashmi Kumar National Comprehensive Cancer Network

Search for other papers by Rashmi Kumar in
Current site
Google Scholar
PubMed
Close
 PhD
, and
Katie Stehman National Comprehensive Cancer Network

Search for other papers by Katie Stehman in
Current site
Google Scholar
PubMed
Close
 PA-C, MMS
Full access

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.

Abstract

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.

NCCN Continuing Education

Target Audience: This activity is designed to meet the educational needs of oncologists, nurses, pharmacists, and other healthcare professionals who manage patients with cancer.

Accreditation Statements

In support of improving patient care, National Comprehensive Cancer Network (NCCN) is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.

FL1

Physicians: NCCN designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 CreditTM. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Nurses: NCCN designates this educational activity for a maximum of 1.0 contact hour.

Pharmacists: NCCN designates this knowledge-based continuing education activity for 1.0 contact hour (0.1 CEUs) of continuing education credit. UAN: JA4008196-0000-23-009-H01-P

PAs: NCCN has been authorized by the American Academy of PAs (AAPA) to award AAPA Category 1 CME credit for activities planned in accordance with AAPA CME Criteria. This activity is designated for 1.0 AAPA Category 1 CME credit. Approval is valid until September 10, 2024. PAs should only claim credit commensurate with the extent of their participation.

All clinicians completing this activity will be issued a certificate of participation. To participate in this journal CE activity: (1) review the educational content; (2) take the posttest with a 66% minimum passing score and complete the evaluation at https://education.nccn.org/node/92935; and (3) view/print certificate.

Pharmacists: You must complete the posttest and evaluation within 30 days of the activity. Continuing pharmacy education credit is reported to the CPE Monitor once you have completed the posttest and evaluation and claimed your credits. Before completing these requirements, be sure your NCCN profile has been updated with your NAPB e-profile ID and date of birth. Your credit cannot be reported without this information. If you have any questions, please email education@nccn.org.

Release date: September 10, 2023; Expiration date: September 10, 2024

Learning Objectives:

Upon completion of this activity, participants will be able to:

  • • Integrate into professional practice the updates to the NCCN Guidelines for Breast Cancer Screening and Diagnosis

  • • Describe the rationale behind the decision-making process for developing the NCCN Guidelines for Breast Cancer Screening and Diagnosis

Disclosure of Relevant Financial Relationships

None of the planners for this educational activity have relevant financial relationship(s) to disclose with ineligible companies whose primary business is producing, marketing, selling, reselling, or distributing healthcare products used by or on patients.

Individuals Who Provided Content Development and/or Authorship Assistance:

The faculty listed below have no relevant financial relationship(s) with ineligible companies to disclose.

Maxine S. Jochelson, MD, Panel Member

Jennifer K. Plichta, MD, MS, Panel Member

Mary Anne Bergman, Guidelines Coordinator, NCCN

Rashmi Kumar, PhD, Senior Director, Clinical Information Operations, NCCN

Katie Stehman, PA-C, MMS, Oncology Scientist/Medical Writer, NCCN

The faculty listed below have the following relevant financial relationship(s) with ineligible companies to disclose. All of the relevant financial relationships listed for these individuals have been mitigated.

Therese B. Bevers, MD, Panel Chair, has disclosed receiving grant/research support from Namida Lab, Inc., Preferred Medicine, and Toray Industries, Inc.

Bethany L. Niell, MD, PhD, Panel Vice Chair, has disclosed receiving grant/research support from Hologic, Inc.

Emily F. Conant, MD, Panel Member, has disclosed receiving grant/research support from iCAD Inc. and OM1, Inc.; and serving as a scientific advisor for iCAD Inc.

Roberta M. Strigel, MD, MS, Panel Member, has disclosed receiving grant/research support from General Electric.

To view all of the conflicts of interest for the NCCN Guidelines panel, go to NCCN.org/guidelines/guidelines-panels-and-disclosure/disclosure-panels

This activity is supported by educational grants from AstraZeneca; Exact Sciences; Novartis; and Taiho Oncology, Inc. This activity is supported by an independent educational grant from Daiichi Sankyo. This activity is supported by independent medical education grants from Illumina, Inc. and Regeneron Pharmaceuticals, Inc.

Overview

The average lifetime risk of breast cancer for a female in the United States has been estimated at 12.3% (or 1 in 8 females).1 For 2023, the American Cancer Society estimates that 300,590 cases of invasive breast cancer (299,540 in females and 2,800 in males) and 55,720 cases of female carcinoma in situ will be diagnosed in the United States.2 About 43,700 breast cancer–related deaths are estimated for 2023.2 Although breast cancer incidence rates increased by 0.5% each year from 2010 through 2019, mortality rates declined, falling an average of 1.3% each year from 2011 to 2020.3 This decrease has been attributed to a combination of screening and treatment advances.4

Breast screening is performed in individuals without any signs or symptoms of breast cancer so that disease can be detected as early as possible. Earlier disease detection may decrease the overall treatment needed and reduce morbidity and mortality rates. Diagnostic breast imaging and evaluation differ from breast screening in that they are used to evaluate an existing problem (eg, palpable mass, discharge from the nipple, mammographic finding). NCCN screening recommendations are largely intended for cisgender females due to the preponderance of data in this population. For breast cancer screening of transgender individuals, the NCCN panel endorses the consensus-based guidelines developed by the American College of Radiology (ACR) Appropriateness Criteria.5 Transgender individuals should consult with their primary care provider to determine when and/or whether screening would be appropriate.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Breast Cancer Screening and Diagnosis provide clinicians with a practical, consistent framework for screening and evaluating a spectrum of clinical breast presentations. These NCCN Guidelines Insights summarize the panel’s decision-making and discussion surrounding the most recent updates to the guideline’s screening recommendations. Recommendations on diagnosis and a complete list of the recent updates for 2023 are currently available in the complete version of these guidelines, available at NCCN.org.

Individuals are stratified into 2 basic categories of risk for the purpose of screening recommendations: average risk and increased risk of developing breast cancer. Risk assessment is outlined in the NCCN Guidelines for Breast Cancer Risk Reduction (available at NCCN.org). The increased risk category consists of 6 groups: (1) individuals who have a lifetime risk ≥20% as defined by models that are largely dependent on family history (eg, BRCAPRO,6 Tyrer-Cuzick,7 BOADICEA/CanRisk8); (2) those who received prior thoracic radiation therapy (RT) between the ages of 10 and 30 years (eg, mantle irradiation); (3) those aged ≥35 years with a 5-year risk of invasive breast cancer ≥1.7% (per Gail model); (4) those who have a lifetime risk ≥20% based on history of atypical ductal hyperplasia (ADH); (5) those who have a lifetime risk ≥20% based on history of lobular carcinoma in situ (LCIS) or atypical lobular hyperplasia (ALH); and (6) those with a known genetic predisposition or a pedigree suggestive of a genetic predisposition.

The components of a breast screening evaluation are dependent on age and other factors such as medical and family history, and can include breast awareness (ie, familiarity with one’s own breasts); regular clinical encounters, which include breast cancer risk assessment and clinical breast examination (CBE); breast imaging with screening mammography; and, in selected cases, breast MRI with and without contrast or breast ultrasound.

Clinical Encounters

The rationale for recommending clinical encounters is to maximize the earliest detection of breast cancers and ensure ongoing risk assessment. In the 2023 update, the panel notes that this is particularly true in regions where mammographic screening may not be easily accessible (see BSCR-1, BSCR-1A, and BSCR-24, pages 902–906). Although randomized trials comparing incremental CBE versus mammographic screening have not been performed, a study based in Mumbai, India, comparing CBE and cancer awareness information versus no screening revealed that the addition of CBE and cancer awareness information led to an earlier age at breast cancer diagnosis, a significant reduction in breast cancers diagnosed at stages III or IV, a nonsignificant reduction in mortality of 15% in the overall study population (ages 35–64 years), and a significant relative reduction in mortality of nearly 30% in individuals aged >50 years.9

F1
F2
F3
F4
F5

Breast Imaging

Tomosynthesis

For the 2023 guidelines update, the panel modified the screening algorithm to make a stronger recommendation for all annual screening mammograms to be performed with tomosynthesis, regardless of risk category (see BSCR-14, pages 902–906). Previously, tomosynthesis was recommended, if available, in a separate bullet point from annual screening mammography.

Tomosynthesis has been shown to decrease false-positive callback rates and improve cancer detection compared with 2D mammography in several studies,1019 including for those with dense breasts.2024 Tomosynthesis allows acquisition of multiple low-dose x-ray images across a limited arc and a digital detector. These data are reconstructed using computer algorithms to generate thin sections displayed in a quasi-3D format. The combined use of 2D mammography and tomosynthesis results in double the radiation exposure compared with mammography alone. However, this increase in radiation dose falls below the dose limits of radiation set by the FDA for standard mammography. The radiation dose can be minimized by newer tomosynthesis techniques that create a synthetic 2D image from the tomosynthesis acquisition, which may obviate the need for a conventional digital image.11,25,26 A meta-analysis comparing the use of synthetic 2D mammography versus standard 2D digital mammography with tomosynthesis revealed comparable diagnostic accuracy, with 85% versus 84% sensitivity and 93% versus 91% specificity, respectively.27

Supplemental Imaging

For many individuals considered at increased risk of breast cancer, annual breast MRIs with and without contrast are recommended in addition to annual screening mammograms with tomosynthesis. In the 2023 guideline update, the panel noted that many experts recommended alternating the mammogram and MRI every 6 months (see BSCR-24, pages 904–906). While the panel recognizes that there are limited data to support this approach, the presumption is that this may lead to earlier identification of interval cancers.28 Mention was also made in the 2023 guideline update that abbreviated MRI has a higher cancer detection rate than mammogram with tomosynthesis and likely has similar sensitivity compared with full diagnostic protocol breast MRI.29 Meta-analyses comparing abbreviated versus full diagnostic protocol MRI revealed similar sensitivity and specificity between the 2 modalities.30,31

For individuals who qualify for but cannot undergo MRI, the previous recommendation was to consider contrast-enhanced mammography (CEM) or whole breast ultrasound. In the 2023 guidelines update, although CEM is still recommended in this circumstance, the panel chose to replace whole breast ultrasound with molecular breast imaging (MBI) as another alternative to MRI. Whole breast ultrasound is now only recommended if contrast-enhanced imaging or functional imaging is not available/accessible (see BSCR-24, pages 904–906). There is emerging evidence that CEM and MBI may improve detection of early breast cancers among females with mammographically dense breasts.3235 CEM carries a risk of iodinated contrast reactions, although a systematic review revealed a pooled rate of adverse events of only 0.82%.36 CEM also has a higher breast radiation exposure per examination than standard mammography, although the radiation dose remains below the dose limits set by the FDA for standard mammography.32,36,37 Additionally, MBI has a whole-body effective radiation dose that is substantially higher than that of mammography.32

Breast Density

The presence of increased dense breast tissue decreases the sensitivity of mammography due to the obscuration or “masking” of cancers by overlying dense breast tissue. In addition, dense breast tissue as measured by mammography is increasingly recognized as an important risk factor for breast cancer.3841 Approximately half of all females of screening age have “dense” breast tissue referred to as “heterogeneously dense” or “extremely dense” by ACR Breast Imaging Reporting and Data System (BI-RADS) nomenclature.42 Of note, the presence of dense tissue is not abnormal and can change over time. Although many individual states have passed legislation mandating patient notification of breast density,43 not all states require insurance coverage for supplemental screening. Recently, the FDA issued a final rule, effective nationally by September 10, 2024, to update the Mammography Quality Standards Act by requiring a breast density assessment be reported to patients and health care providers (HCPs), with additional language notifying patients that in the setting of dense breast tissue, supplemental imaging studies beyond mammography may help detect cancer and recommending that individuals discuss their risk of breast cancer and review their personal preferences with their HCPs.44

Based on evolving requirements for reporting of breast density and increasing individual state insurance coverage for supplemental screening, in the 2023 guidelines update the panel added a statement to the algorithm recommending consideration of supplemental screening for individuals aged ≥40 years who have heterogeneously dense or extremely dense breast tissue and are otherwise considered at average risk of developing breast cancer (see BSCR-1, page 902). The risks and benefits of such screening should be discussed with individual patients.45 Different supplemental imaging modalities may be considered based on risk and patient values/preference.46 The ACR has published guidelines for supplemental screening based on breast density.47

Screening Recommendations for Specific Increased Risk Groups

Individuals With a Lifetime Risk ≥20% per ModelsLargely Dependent on Family History

A lifetime risk of breast cancer of ≥20% as assessed by models based largely on family history (eg, BRCAPRO,6 Tyrer-Cuzick,7 BOADICEA/CanRisk8) is a risk threshold used in the guidelines to identify an individual as a potential candidate for risk reduction strategies, as well as to direct screening strategies. A comparison of predictive risk models for risk assessment is outlined in the NCCN Guidelines for Breast Cancer Risk Reduction (available at NCCN.org).

Screening recommendations for individuals with a lifetime risk ≥20% as defined by models that are largely dependent on family history include breast awareness, consideration of risk reduction strategies in accordance with the NCCN Guidelines for Breast Cancer Risk Reduction, and a clinical encounter every 6 to 12 months beginning at the age identified as being at increased risk, but not prior to age 21 years. A referral to a genetic counselor or other health professional with expertise and experience in cancer genetics should be considered, if not already done. A referral to a breast specialist as appropriate should also be considered. Although the panel still recommends starting annual screening mammograms with tomosynthesis beginning 10 years prior to when the youngest family member was diagnosed with breast cancer, but not prior to age 30 years, or beginning at age 40 years (whichever comes first), in the 2023 guideline update, the panel added a footnote that beginning annual screening mammograms with tomosynthesis at age 25 years can be considered on a case-by-case basis, depending on the family history (see BSCR-2, page 904). Multiple panel members recognize that they treat an increasing number of individuals with breast cancer between the ages of 25 and 30 years and that they prefer not to delay screening mammography until age 30 years for individuals with family members diagnosed with breast cancer within this earlier age range. Although there is the option to begin annual breast MRI with and without contrast at age 25 years (to begin 10 years prior to when the youngest family member was diagnosed with breast cancer, but not prior to age 25 years, or beginning at age 40 years [whichever comes first]), it was noted that MRI may not be available in smaller or more rural community practices.

Individuals Who Received Thoracic RT Between Ages 10 and 30 Years

Results from several studies have demonstrated that females who received thoracic RT in their second or third decade of life have a substantially increased risk of developing breast cancer by age 40 years.4853 For example, in the Late Effects Study Group trial, the overall risk of breast cancer associated with prior thoracic RT at a young age was found to be 56.7-fold (55.5-fold for female patients) greater than the risk of breast cancer in the general population.49,52 The relative risk of female breast cancer according to follow-up interval was 0 at 5–9 years; 71.3 at 10–14 years; 90.8 at 15–19 years; 50.9 at 20–24 years; 41.2 at 25–29 years; and 24.5 at >29 years.52 Results from a case-control study of females treated with thoracic RT at a young age for Hodgkin lymphoma indicated that the estimated cumulative absolute risk of breast cancer at age 55 years was 29.0% (95% CI, 20.2%–40.1%) for a female treated at age 25 years with at least 40 Gy of radiation and no alkylating agents.54 Unfortunately, findings from a survey of breast screening practices in this population of patients suggest that a sizable segment of this group is not undergoing regular mammographic screening.55

Screening recommendations for individuals that received thoracic RT between ages 10 and 30 years and are currently aged <25 years include an annual clinical encounter beginning 8 years after RT and breast awareness. For those currently aged ≥25 years, breast awareness is recommended, and clinical encounters are recommended every 6 to 12 months beginning 8 years after RT. In addition, individuals in this risk group should be counseled on risk-reduction strategies in accordance with the NCCN Guidelines for Breast Cancer Risk Reduction (available at NCCN.org). Although the panel still recommends starting annual screening mammograms with tomosynthesis 8 years after RT for individuals who have undergone thoracic RT between the ages of 10 and 30 years, the recommendation was previously to delay this until age 30 years, whereas in the 2023 guideline update, the panel updated its recommendation to delay only until age 25 years (see BSCR-3, page 905). As previously mentioned, multiple panel members acknowledged the increasing number of individuals being diagnosed with breast cancer between the ages of 25 and 30 years, and that although annual MRI with and without contrast is recommended 8 years after RT but not prior to age 25 years, MRI may not be available in smaller or more rural community practices. Also, in a prospective study comparing MRI with mammography in females who had received chest RT for Hodgkin lymphoma, MRI missed 6 breast malignancies that were detected by mammogram, all with suspicious calcifications.56 These points all impacted the decision to allow for mammographic screening beginning at this earlier age range, along with MRI. Although there is a concern that the cumulative radiation exposure from mammography in a young individual may itself pose a risk for cancer, it is felt that the additional radiation in this population is negligible compared with overall radiation exposure.

Individuals Aged ≥35 Years With 5-Year Risk of Invasive Breast Cancer ≥1.7% per Modified Gail Model

Although most screening guidelines are based on lifetime risk of breast cancer, the NCCN Guidelines do include the increased risk category of 5-year risk of invasive breast cancer ≥1.7% per the modified Gail model in individuals aged ≥35 years.5761 The modified Gail model assesses the risk of invasive breast cancer as a function of age, menarche, age at first live birth or nulliparity, number of first-degree relatives with breast cancer, number of previous benign breast biopsies, atypical hyperplasia in a previous breast biopsy, and race. The model calculates 5-year and lifetime projected probabilities of developing invasive breast cancer and can be used to identify individuals at increased risk.

Screening recommendations for individuals aged ≥35 years with 5-year risk of invasive breast cancer ≥1.7% per the modified Gail model include breast awareness, a clinical encounter every 6 to 12 months, and annual mammography with tomosynthesis, to begin at the age identified as being at increased risk by the Gail model. In addition, according to the panel, individuals in this group should be counseled on risk-reduction strategies in accordance with the NCCN Guidelines for Breast Cancer Risk Reduction (available at NCCN.org).

Mirroring the recommendation for individuals in the average risk category aged >40 years, in the 2023 guideline update, the panel added the recommendation to consider supplemental screening for individuals in this risk category who have heterogeneously dense or extremely dense breast tissue as well, as this is the only increased risk category where annual MRI is not explicitly recommended as a supplement to annual screening mammography with tomosynthesis (see BSCR-4, page 906).

Individuals With ADH or Lobular Neoplasia and ≥20% Residual Lifetime Risk

Screening recommendations for individuals with ADH or lobular neoplasia (LCIS/ALH) and ≥20% residual lifetime risk of breast cancer include a clinical encounter every 6 to 12 months to begin at diagnosis of ADH or lobular neoplasia, breast awareness, counseling on risk-reduction strategies in accordance with the NCCN Guidelines for Breast Cancer Risk Reduction (available at NCCN.org), and annual screening mammogram with tomosynthesis to begin at diagnosis of ADH or lobular neoplasia but not prior to age 30 years. It is also recommended to consider annual breast MRI with and without contrast. Consideration was made for changing this recommendation from annual breast MRI to a broader recommendation for contrast or physiologic imaging (CEM, MRI, or MBI). A study examining cancer detection rates with mammography alone versus mammography in addition to MRI in a large cohort of females with LCIS was discussed, in which MRI did not lead to increased cancer detection rates.62 A more recent, similar study was also discussed, which also revealed a lack of improvement in cancer detection rates with screening MRI in females with LCIS as well as ADH and ALH and also revealed a significantly higher biopsy rate with the use of mammogram and MRI combined.63 Despite the discussion surrounding these 2 studies, the panel ultimately decided to keep its recommendation to consider annual breast MRI with and without contrast given concern for missing an invasive lobular carcinoma with mammography alone and given that there are more published studies in this population investigating MRI compared with CEM or MBI (see BSCR-4, page 906). Although there are emerging data for CEM in this population,34,6467 most studies have included a mixed population of increased risk groups rather than ADH or lobular neoplasia specifically. Like other increased risk groups, CEM or MBI can be considered for those who qualify for but cannot undergo MRI.

Summary

The goal of breast screening is to detect breast cancer as early as possible, prior to the onset of signs or symptoms of disease, to allow for earlier, less aggressive treatments, thus reducing the mortality and morbidity associated with the disease. These NCCN Guidelines Insights highlight important recent updates to screening recommendations in the NCCN Guidelines for Breast Cancer Screening and Diagnosis, including but not limited to an increased emphasis on tomosynthesis and updated supplemental imaging recommendations.

References

  • 1.

    American Cancer Society. Breast cancer facts and figures: 2009–2010. Accessed July 1, 2023. Available at: https://www.cancer.org/research/cancer-facts-statistics/breast-cancer-facts-figures.html

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA Cancer J Clin 2023;73:1748.

  • 3.

    Giaquinto AN, Sung H, Miller KD, et al. Breast cancer statistics, 2022. CA Cancer J Clin 2022;72:524541.

  • 4.

    Humphrey LL, Helfand M, Chan BK, et al. Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med 2002;137:347360.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Brown A, Lourenco AP, Niell BL, et al. ACR Appropriateness Criteria transgender breast cancer screening. J Am Coll Radiol 2021;18(Suppl 11):S502515.

  • 6.

    Parmigiani G, Berry D, Aguilar O. Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 1998;62:145158.

  • 7.

    Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 2004;23:11111130.

  • 8.

    Antoniou AC, Cunningham AP, Peto J, et al. The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions. Br J Cancer 2008;98:14571466.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Mittra I, Mishra GA, Dikshit RP, et al. Effect of screening by clinical breast examination on breast cancer incidence and mortality after 20 years: prospective, cluster randomised controlled trial in Mumbai. BMJ 2021;372:n256.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Ciatto S, Houssami N, Bernardi D, et al. Integration of 3D digital mammography with tomosynthesis for population breast-cancer screening (STORM): a prospective comparison study. Lancet Oncol 2013;14:583589.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Skaane P, Bandos AI, Gullien R, et al. Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program. Radiology 2013;267:4756.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Rafferty EA, Park JM, Philpotts LE, et al. Assessing radiologist performance using combined digital mammography and breast tomosynthesis compared with digital mammography alone: results of a multicenter, multireader trial. Radiology 2013;266:104113.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Friedewald SM, Rafferty EA, Rose SL, et al. Breast cancer screening using tomosynthesis in combination with digital mammography. JAMA 2014;311:24992507.

  • 14.

    Lourenco AP, Barry-Brooks M, Baird GL, et al. Changes in recall type and patient treatment following implementation of screening digital breast tomosynthesis. Radiology 2015;274:337342.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Rose SL, Tidwell AL, Ice MF, et al. A reader study comparing prospective tomosynthesis interpretations with retrospective readings of the corresponding FFDM examinations. Acad Radiol 2014;21:12041210.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Destounis S, Arieno A, Morgan R. Initial experience with combination digital breast tomosynthesis plus full field digital mammography or full field digital mammography alone in the screening environment. J Clin Imaging Sci 2014;4:9.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Lång K, Andersson I, Rosso A, et al. Performance of one-view breast tomosynthesis as a stand-alone breast cancer screening modality: results from the Malmö Breast Tomosynthesis Screening Trial, a population-based study. Eur Radiol 2016;26:184190.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Marinovich ML, Hunter KE, Macaskill P, et al. Breast cancer screening using tomosynthesis or mammography: a meta-analysis of cancer detection and recall. J Natl Cancer Inst 2018;110:942949.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Heindel W, Weigel S, Gerss J, et al. Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial. Lancet Oncol 2022;23:601611.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Moshina N, Aase HS, Danielsen AS, et al. Comparing screening outcomes for digital breast tomosynthesis and digital mammography by automated breast density in a randomized controlled trial: results from the to-be trial. Radiology 2020;297:522531.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Conant EF, Barlow WE, Herschorn SD, et al. Association of digital breast tomosynthesis vs digital mammography with cancer detection and recall rates by age and breast density. JAMA Oncol 2019;5:635642.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Margolies L, Cohen A, Sonnenblick E, et al. Digital breast tomosynthesis changes management in patients seen at a tertiary care breast center. ISRN Radiol 2014;2014:658929.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Gilbert FJ, Tucker L, Gillan MG, et al. Accuracy of digital breast tomosynthesis for depicting breast cancer subgroups in a UK retrospective reading study (TOMMY trial). Radiology 2015;277:697706.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Pattacini P, Nitrosi A, Giorgi Rossi P, et al. A randomized trial comparing breast cancer incidence and interval cancers after tomosynthesis plus mammography versus mammography alone. Radiology 2022;303:256266.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Zuckerman SP, Conant EF, Keller BM, et al. Implementation of synthesized two-dimensional mammography in a population-based digital breast tomosynthesis screening program. Radiology 2016;281:730736.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Skaane P, Bandos AI, Eben EB, et al. Two-view digital breast tomosynthesis screening with synthetically reconstructed projection images: comparison with digital breast tomosynthesis with full-field digital mammographic images. Radiology 2014;271:655663.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Abdullah P, Alabousi M, Ramadan S, et al. Synthetic 2D mammography versus standard 2D digital mammography: a diagnostic test accuracy systematic review and meta-analysis. AJR Am J Roentgenol 2021;217:314325.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    MD Anderson Cancer Center. Breast cancer screening. Accessed April 10, 2023. Available at: https://www.mdanderson.org/content/dam/mdanderson/documents/for-physicians/algorithms/screening/screening-breast-web-algorithm.pdf

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Comstock CE, Gatsonis C, Newstead GM, et al. Comparison of abbreviated breast MRI vs digital breast tomosynthesis for breast cancer detection among women with dense breasts undergoing screening. JAMA 2020;323:746756.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Baxter GC, Selamoglu A, Mackay JW, et al. A meta-analysis comparing the diagnostic performance of abbreviated MRI and a full diagnostic protocol in breast cancer. Clin Radiol 2021;76:154.e123132.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Geach R, Jones LI, Harding SA, et al. The potential utility of abbreviated breast MRI (FAST MRI) as a tool for breast cancer screening: a systematic review and meta-analysis. Clin Radiol 2021;76:154.e1122.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Hruska CB. Molecular breast imaging for screening in dense breasts: state of the art and future directions. AJR Am J Roentgenol 2017;208:275283.

  • 33.

    Shermis RB, Wilson KD, Doyle MT, et al. Supplemental breast cancer screening with molecular breast imaging for women with dense breast tissue. AJR Am J Roentgenol 2016;207:450457.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Jochelson M. Contrast-enhanced digital mammography. Radiol Clin North Am 2014;52:609616.

  • 35.

    Covington MF, Parent EE, Dibble EH, et al. Advances and future directions in molecular breast imaging. J Nucl Med 2022;63:1721.

  • 36.

    Zanardo M, Cozzi A, Trimboli RM, et al. Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review. Insights Imaging 2019;10:76.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Gennaro G, Cozzi A, Schiaffino S, et al. Radiation dose of contrast- enhanced mammography: a two-center prospective comparison. Cancers (Basel) 2022;14:1774.

  • 38.

    Nelson HD, Zakher B, Cantor A, et al. Risk factors for breast cancer for women aged 40 to 49 years: a systematic review and meta-analysis. Ann Intern Med 2012;156:635648.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Mandelson MT, Oestreicher N, Porter PL, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst 2000;92:10811087.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Chiu SY, Duffy S, Yen AM, et al. Effect of baseline breast density on breast cancer incidence, stage, mortality, and screening parameters: 25-year follow-up of a Swedish mammographic screening. Cancer Epidemiol Biomarkers Prev 2010;19:12191228.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41.

    Vachon CM, Sellers TA, Scott CG, et al. Longitudinal breast density and risk of breast cancer. Cancer Res 2010;70(8 Suppl):Abstract 4828.

  • 42.

    Sprague BL, Gangnon RE, Burt V, et al. Prevalence of mammographically dense breasts in the United States. J Natl Cancer Inst 2014;106:dju255.

  • 43.

    Richman I, Asch SM, Bendavid E, et al. Breast density notification legislation and breast cancer stage at diagnosis: early evidence from the SEER registry. J Gen Intern Med 2017;32:603609.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44.

    US Food and Drug Administration. Mammography Quality Standards Act. Accessed April 1, 2023. Available at: https://www.federalregister.gov/documents/2023/03/10/2023-04550/mammography-quality-standards-act

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45.

    Berg WA, Harvey JA Breast density and supplemental screening. Accessed April 1, 2023. Available at: https://www.sbi-online.org/white-papers/breast-density-and-supplemental-screening

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46.

    Berg WA, Blume JD, Cormack JB, et al. Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. JAMA 2008;299:21512163.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47.

    Weinstein SP, Slanetz PJ, Lewin AA, et al. ACR Appropriateness Criteria supplemental breast cancer screening based on breast density. J Am Coll Radiol 2021;18(Suppl 11):S456473.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48.

    Bhatia S, Robison LL, Oberlin O, et al. Breast cancer and other second neoplasms after childhood Hodgkin’s disease. N Engl J Med 1996;334:745751.

  • 49.

    Bhatia S, Yasui Y, Robison LL, et al. High risk of subsequent neoplasms continues with extended follow-up of childhood Hodgkin’s disease: report from the Late Effects Study Group. J Clin Oncol 2003;21:43864394.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 50.

    Hancock SL, Tucker MA, Hoppe RT. Breast cancer after treatment of Hodgkin’s disease. J Natl Cancer Inst 1993;85:2531.

  • 51.

    Metayer C, Lynch CF, Clarke EA, et al. Second cancers among long-term survivors of Hodgkin’s disease diagnosed in childhood and adolescence. J Clin Oncol 2000;18:24352443.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52.

    van Leeuwen FE, Klokman WJ, Stovall M, et al. Roles of radiation dose, chemotherapy, and hormonal factors in breast cancer following Hodgkin’s disease. J Natl Cancer Inst 2003;95:971980.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 53.

    Yahalom J, Petrek JA, Biddinger PW, et al. Breast cancer in patients irradiated for Hodgkin’s disease: a clinical and pathologic analysis of 45 events in 37 patients. J Clin Oncol 1992;10:16741681.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 54.

    Travis LB, Hill D, Dores GM, et al. Cumulative absolute breast cancer risk for young women treated for Hodgkin lymphoma. J Natl Cancer Inst 2005;97:14281437.

  • 55.

    Oeffinger KC, Ford JS, Moskowitz CS, et al. Breast cancer surveillance practices among women previously treated with chest radiation for a childhood cancer. JAMA 2009;301:404414.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 56.

    Ng AK, Garber JE, Diller LR, et al. Prospective study of the efficacy of breast magnetic resonance imaging and mammographic screening in survivors of Hodgkin lymphoma. J Clin Oncol 2013;31:22822288.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 57.

    Costantino JP, Gail MH, Pee D, et al. Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 1999;91:15411548.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 58.

    Gail MH, Brinton LA, Byar DP, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 1989;81:18791886.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 59.

    Gail MH, Costantino JP. Validating and improving models for projecting the absolute risk of breast cancer. J Natl Cancer Inst 2001;93:334335.

  • 60.

    Rockhill B, Spiegelman D, Byrne C, et al. Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 2001;93:358366.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 61.

    Spiegelman D, Colditz GA, Hunter D, et al. Validation of the Gail et al. model for predicting individual breast cancer risk. J Natl Cancer Inst 1994;86:600607.

  • 62.

    King TA, Pilewskie M, Muhsen S, et al. Lobular carcinoma in situ: a 29-year longitudinal experience evaluating clinicopathologic features and breast cancer risk. J Clin Oncol 2015;33:39453952.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 63.

    Laws A, Katlin F, Hans M, et al. Screening MRI does not increase cancer detection or result in an earlier stage at diagnosis for patients with high-risk breast lesions: a propensity score analysis. Ann Surg Oncol 2023;30:6877.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 64.

    Hogan MP, Amir T, Sevilimedu V, et al. Contrast-enhanced digital mammography screening for intermediate-risk women with a history of lobular neoplasia. AJR Am J Roentgenol 2021;216:14861491.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 65.

    Neeter LMFH, Robbe MMQ, van Nijnatten TJ, et al. Comparing the diagnostic performance of contrast-enhanced mammography and breast MRI: a systematic review and meta-analysis. J Cancer 2023;14:174182.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 66.

    Sung JS, Lebron L, Keating D, et al. Performance of dual-energy contrast-enhanced digital mammography for screening women at increased risk of breast cancer. Radiology 2019;293:8188.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 67.

    Jochelson MS, Pinker K, Dershaw DD, et al. Comparison of screening CEDM and MRI for women at increased risk for breast cancer: a pilot study. Eur J Radiol 2017;97:3743.

    • PubMed
    • Search Google Scholar
    • Export Citation

NCCN CATEGORIES OF EVIDENCE AND CONSENSUS

Category 1: Based upon high-level evidence, there is uniform NCCN consensus that the intervention is appropriate.

Category 2A: Based upon lower-level evidence, there is uniform NCCN consensus that the intervention is appropriate.

Category 2B: Based upon lower-level evidence, there is NCCN consensus that the intervention is appropriate.

Category 3: Based upon any level of evidence, there is major NCCN disagreement that the intervention is appropriate.

All recommendations are category 2A unless otherwise noted.

Clinical trials: NCCN believes that the best management of any patient with cancer is in a clinical trial. Participation in clinical trials is especially encouraged.

PLEASE NOTE

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) are a statement of evidence and consensus of the authors regarding their views of currently accepted approaches to treatment. The NCCN Guidelines Insights highlight important changes in the NCCN Guidelines recommendations from previous versions. Colored markings in the algorithm show changes and the discussion aims to further the understanding of these changes by summarizing salient portions of the panel’s discussion, including the literature reviewed.

The NCCN Guidelines Insights do not represent the full NCCN Guidelines; further, the National Comprehensive Cancer Network® (NCCN®) makes no representations or warranties of any kind regarding their content, use, or application of the NCCN Guidelines and NCCN Guidelines Insights and disclaims any responsibility for their application or use in any way.

The complete and most recent version of these NCCN Guidelines is available free of charge at NCCN.org.

© 2023 National Comprehensive Cancer Network® (NCCN®), All rights reserved. The NCCN Guidelines and the illustrations herein may not be reproduced in any form without the express written permission of NCCN.

  • Collapse
  • Expand
  • 1.

    American Cancer Society. Breast cancer facts and figures: 2009–2010. Accessed July 1, 2023. Available at: https://www.cancer.org/research/cancer-facts-statistics/breast-cancer-facts-figures.html

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA Cancer J Clin 2023;73:1748.

  • 3.

    Giaquinto AN, Sung H, Miller KD, et al. Breast cancer statistics, 2022. CA Cancer J Clin 2022;72:524541.

  • 4.

    Humphrey LL, Helfand M, Chan BK, et al. Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med 2002;137:347360.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Brown A, Lourenco AP, Niell BL, et al. ACR Appropriateness Criteria transgender breast cancer screening. J Am Coll Radiol 2021;18(Suppl 11):S502515.

  • 6.

    Parmigiani G, Berry D, Aguilar O. Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 1998;62:145158.

  • 7.

    Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 2004;23:11111130.

  • 8.

    Antoniou AC, Cunningham AP, Peto J, et al. The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions. Br J Cancer 2008;98:14571466.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Mittra I, Mishra GA, Dikshit RP, et al. Effect of screening by clinical breast examination on breast cancer incidence and mortality after 20 years: prospective, cluster randomised controlled trial in Mumbai. BMJ 2021;372:n256.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Ciatto S, Houssami N, Bernardi D, et al. Integration of 3D digital mammography with tomosynthesis for population breast-cancer screening (STORM): a prospective comparison study. Lancet Oncol 2013;14:583589.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Skaane P, Bandos AI, Gullien R, et al. Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program. Radiology 2013;267:4756.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Rafferty EA, Park JM, Philpotts LE, et al. Assessing radiologist performance using combined digital mammography and breast tomosynthesis compared with digital mammography alone: results of a multicenter, multireader trial. Radiology 2013;266:104113.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Friedewald SM, Rafferty EA, Rose SL, et al. Breast cancer screening using tomosynthesis in combination with digital mammography. JAMA 2014;311:24992507.

  • 14.

    Lourenco AP, Barry-Brooks M, Baird GL, et al. Changes in recall type and patient treatment following implementation of screening digital breast tomosynthesis. Radiology 2015;274:337342.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Rose SL, Tidwell AL, Ice MF, et al. A reader study comparing prospective tomosynthesis interpretations with retrospective readings of the corresponding FFDM examinations. Acad Radiol 2014;21:12041210.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Destounis S, Arieno A, Morgan R. Initial experience with combination digital breast tomosynthesis plus full field digital mammography or full field digital mammography alone in the screening environment. J Clin Imaging Sci 2014;4:9.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Lång K, Andersson I, Rosso A, et al. Performance of one-view breast tomosynthesis as a stand-alone breast cancer screening modality: results from the Malmö Breast Tomosynthesis Screening Trial, a population-based study. Eur Radiol 2016;26:184190.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Marinovich ML, Hunter KE, Macaskill P, et al. Breast cancer screening using tomosynthesis or mammography: a meta-analysis of cancer detection and recall. J Natl Cancer Inst 2018;110:942949.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Heindel W, Weigel S, Gerss J, et al. Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial. Lancet Oncol 2022;23:601611.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Moshina N, Aase HS, Danielsen AS, et al. Comparing screening outcomes for digital breast tomosynthesis and digital mammography by automated breast density in a randomized controlled trial: results from the to-be trial. Radiology 2020;297:522531.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Conant EF, Barlow WE, Herschorn SD, et al. Association of digital breast tomosynthesis vs digital mammography with cancer detection and recall rates by age and breast density. JAMA Oncol 2019;5:635642.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Margolies L, Cohen A, Sonnenblick E, et al. Digital breast tomosynthesis changes management in patients seen at a tertiary care breast center. ISRN Radiol 2014;2014:658929.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Gilbert FJ, Tucker L, Gillan MG, et al. Accuracy of digital breast tomosynthesis for depicting breast cancer subgroups in a UK retrospective reading study (TOMMY trial). Radiology 2015;277:697706.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Pattacini P, Nitrosi A, Giorgi Rossi P, et al. A randomized trial comparing breast cancer incidence and interval cancers after tomosynthesis plus mammography versus mammography alone. Radiology 2022;303:256266.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Zuckerman SP, Conant EF, Keller BM, et al. Implementation of synthesized two-dimensional mammography in a population-based digital breast tomosynthesis screening program. Radiology 2016;281:730736.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Skaane P, Bandos AI, Eben EB, et al. Two-view digital breast tomosynthesis screening with synthetically reconstructed projection images: comparison with digital breast tomosynthesis with full-field digital mammographic images. Radiology 2014;271:655663.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Abdullah P, Alabousi M, Ramadan S, et al. Synthetic 2D mammography versus standard 2D digital mammography: a diagnostic test accuracy systematic review and meta-analysis. AJR Am J Roentgenol 2021;217:314325.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    MD Anderson Cancer Center. Breast cancer screening. Accessed April 10, 2023. Available at: https://www.mdanderson.org/content/dam/mdanderson/documents/for-physicians/algorithms/screening/screening-breast-web-algorithm.pdf

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Comstock CE, Gatsonis C, Newstead GM, et al. Comparison of abbreviated breast MRI vs digital breast tomosynthesis for breast cancer detection among women with dense breasts undergoing screening. JAMA 2020;323:746756.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Baxter GC, Selamoglu A, Mackay JW, et al. A meta-analysis comparing the diagnostic performance of abbreviated MRI and a full diagnostic protocol in breast cancer. Clin Radiol 2021;76:154.e123132.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Geach R, Jones LI, Harding SA, et al. The potential utility of abbreviated breast MRI (FAST MRI) as a tool for breast cancer screening: a systematic review and meta-analysis. Clin Radiol 2021;76:154.e1122.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Hruska CB. Molecular breast imaging for screening in dense breasts: state of the art and future directions. AJR Am J Roentgenol 2017;208:275283.

  • 33.

    Shermis RB, Wilson KD, Doyle MT, et al. Supplemental breast cancer screening with molecular breast imaging for women with dense breast tissue. AJR Am J Roentgenol 2016;207:450457.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Jochelson M. Contrast-enhanced digital mammography. Radiol Clin North Am 2014;52:609616.

  • 35.

    Covington MF, Parent EE, Dibble EH, et al. Advances and future directions in molecular breast imaging. J Nucl Med 2022;63:1721.

  • 36.

    Zanardo M, Cozzi A, Trimboli RM, et al. Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review. Insights Imaging 2019;10:76.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Gennaro G, Cozzi A, Schiaffino S, et al. Radiation dose of contrast- enhanced mammography: a two-center prospective comparison. Cancers (Basel) 2022;14:1774.

  • 38.

    Nelson HD, Zakher B, Cantor A, et al. Risk factors for breast cancer for women aged 40 to 49 years: a systematic review and meta-analysis. Ann Intern Med 2012;156:635648.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Mandelson MT, Oestreicher N, Porter PL, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst 2000;92:10811087.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Chiu SY, Duffy S, Yen AM, et al. Effect of baseline breast density on breast cancer incidence, stage, mortality, and screening parameters: 25-year follow-up of a Swedish mammographic screening. Cancer Epidemiol Biomarkers Prev 2010;19:12191228.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41.

    Vachon CM, Sellers TA, Scott CG, et al. Longitudinal breast density and risk of breast cancer. Cancer Res 2010;70(8 Suppl):Abstract 4828.

  • 42.

    Sprague BL, Gangnon RE, Burt V, et al. Prevalence of mammographically dense breasts in the United States. J Natl Cancer Inst 2014;106:dju255.

  • 43.

    Richman I, Asch SM, Bendavid E, et al. Breast density notification legislation and breast cancer stage at diagnosis: early evidence from the SEER registry. J Gen Intern Med 2017;32:603609.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44.

    US Food and Drug Administration. Mammography Quality Standards Act. Accessed April 1, 2023. Available at: https://www.federalregister.gov/documents/2023/03/10/2023-04550/mammography-quality-standards-act

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45.

    Berg WA, Harvey JA Breast density and supplemental screening. Accessed April 1, 2023. Available at: https://www.sbi-online.org/white-papers/breast-density-and-supplemental-screening

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46.

    Berg WA, Blume JD, Cormack JB, et al. Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. JAMA 2008;299:21512163.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47.

    Weinstein SP, Slanetz PJ, Lewin AA, et al. ACR Appropriateness Criteria supplemental breast cancer screening based on breast density. J Am Coll Radiol 2021;18(Suppl 11):S456473.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48.

    Bhatia S, Robison LL, Oberlin O, et al. Breast cancer and other second neoplasms after childhood Hodgkin’s disease. N Engl J Med 1996;334:745751.

  • 49.

    Bhatia S, Yasui Y, Robison LL, et al. High risk of subsequent neoplasms continues with extended follow-up of childhood Hodgkin’s disease: report from the Late Effects Study Group. J Clin Oncol 2003;21:43864394.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 50.

    Hancock SL, Tucker MA, Hoppe RT. Breast cancer after treatment of Hodgkin’s disease. J Natl Cancer Inst 1993;85:2531.

  • 51.

    Metayer C, Lynch CF, Clarke EA, et al. Second cancers among long-term survivors of Hodgkin’s disease diagnosed in childhood and adolescence. J Clin Oncol 2000;18:24352443.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52.

    van Leeuwen FE, Klokman WJ, Stovall M, et al. Roles of radiation dose, chemotherapy, and hormonal factors in breast cancer following Hodgkin’s disease. J Natl Cancer Inst 2003;95:971980.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 53.

    Yahalom J, Petrek JA, Biddinger PW, et al. Breast cancer in patients irradiated for Hodgkin’s disease: a clinical and pathologic analysis of 45 events in 37 patients. J Clin Oncol 1992;10:16741681.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 54.

    Travis LB, Hill D, Dores GM, et al. Cumulative absolute breast cancer risk for young women treated for Hodgkin lymphoma. J Natl Cancer Inst 2005;97:14281437.

  • 55.

    Oeffinger KC, Ford JS, Moskowitz CS, et al. Breast cancer surveillance practices among women previously treated with chest radiation for a childhood cancer. JAMA 2009;301:404414.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 56.

    Ng AK, Garber JE, Diller LR, et al. Prospective study of the efficacy of breast magnetic resonance imaging and mammographic screening in survivors of Hodgkin lymphoma. J Clin Oncol 2013;31:22822288.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 57.

    Costantino JP, Gail MH, Pee D, et al. Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 1999;91:15411548.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 58.

    Gail MH, Brinton LA, Byar DP, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 1989;81:18791886.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 59.

    Gail MH, Costantino JP. Validating and improving models for projecting the absolute risk of breast cancer. J Natl Cancer Inst 2001;93:334335.

  • 60.

    Rockhill B, Spiegelman D, Byrne C, et al. Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 2001;93:358366.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 61.

    Spiegelman D, Colditz GA, Hunter D, et al. Validation of the Gail et al. model for predicting individual breast cancer risk. J Natl Cancer Inst 1994;86:600607.

  • 62.

    King TA, Pilewskie M, Muhsen S, et al. Lobular carcinoma in situ: a 29-year longitudinal experience evaluating clinicopathologic features and breast cancer risk. J Clin Oncol 2015;33:39453952.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 63.

    Laws A, Katlin F, Hans M, et al. Screening MRI does not increase cancer detection or result in an earlier stage at diagnosis for patients with high-risk breast lesions: a propensity score analysis. Ann Surg Oncol 2023;30:6877.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 64.

    Hogan MP, Amir T, Sevilimedu V, et al. Contrast-enhanced digital mammography screening for intermediate-risk women with a history of lobular neoplasia. AJR Am J Roentgenol 2021;216:14861491.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 65.

    Neeter LMFH, Robbe MMQ, van Nijnatten TJ, et al. Comparing the diagnostic performance of contrast-enhanced mammography and breast MRI: a systematic review and meta-analysis. J Cancer 2023;14:174182.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 66.

    Sung JS, Lebron L, Keating D, et al. Performance of dual-energy contrast-enhanced digital mammography for screening women at increased risk of breast cancer. Radiology 2019;293:8188.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 67.

    Jochelson MS, Pinker K, Dershaw DD, et al. Comparison of screening CEDM and MRI for women at increased risk for breast cancer: a pilot study. Eur J Radiol 2017;97:3743.

    • PubMed
    • Search Google Scholar
    • Export Citation

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 19002 19002 639
PDF Downloads 15687 15687 612
EPUB Downloads 0 0 0