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®). She joined AJMC® in 2013 and is the primary staff editor for 

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®'s premier annual oncology meeting, Patient-Centered Oncology Care®. For more than a decade, Mary has covered ASCO, ASH, ACC and other leading scientific meetings for 

Mary has a BA in communications and philosophy from Loyola University New Orleans. You can connect with Mary on 

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The breast cancer section is a comprehensive resource for clinical news and expert insights on breast cancer. Read more at AJMC.

Breast Cancer | Managed Care News & Insights | AJMC

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Compendium

Breast Cancer

Age and insurance status were associated with disproportionate access to antibody-drug conjugate (ADC) treatment among patients with metastatic 

 from Komodo Health, a health care intelligence company, and the Tigerlily Foundation, a national breast cancer advocacy organization.

The incidence of metastatic breast cancer cases reported in the US increased from 5.8 per 100,000 women in 2001 to 7.9 per 100,000 women in 2021.

 Furthermore, from 2021 to 2023, ADC treatment rates increased 3.7-fold. During this same period, the median time to treatment also decreased from 331 to 109 days. However, demographic data showed that older women had disproportionately lower rates of treatment (2557 per 100,000) and the longest delays (median, 242 days).

Contrary to historical cancer care patterns, Black women saw higher rates of treatment when compared with those of White and Asian women, which researchers likely attribute to the higher prevalence of triple-negative breast cancer.

The analysis, powered by Komodo’s Health Care Map, included a refined subset of 17,005 patients from an initial cohort of 431,276 patients. Treatment rates adjusted by insurance coverage saw a significant difference in commercially insured patients, second to that of Medicaid beneficiaries. Medicare beneficiaries had the lowest rate of treatment.

“While we've overcome some racial barriers, which I think is extremely positive, I think that this is an example of where we can target older patients a little bit better,” said Tabby Khan, MD, senior director of analytics at Komodo Health, in an interview with 

“We have to continue to counsel these patients and also providers on why this may be a really good option for women in that age group.”

Komodo Health layered its platform Marmot on top of its health care map, which has data of over 330 million patients, to quantify disparities on a vast scale.

“I think this was a great example of using this AI platform to really blend all of those things, and in recognition of Breast Cancer Awareness Month,” Khan said.

Listen above or on one of these podcast services:

1. Freckelton E. Komodo health analysis uncovers dual reality in metastatic breast cancer care: rapid targeted cancer therapy adoption amid glaring age-related disparities. Komodo Health. October 20, 2025. Accessed October 29, 2025. 

https://www.komodohealth.com/press/dual-reality-metastatic-breast-cancer-care-rapid-targeted-cancer-therapy-adoption-amid-glaring-age-related-disparities/

2. Metastatic female breast cancer incidence. Centers for Disease Control and Prevention. November 12, 2024. Accessed October 29, 2025. 

https://www.cdc.gov/united-states-cancer-statistics/publications/metastatic-breast-cancer.html.

3. Komodo Health; Tigerlily Foundation. ADC treatment patterns in metastatic breast cancer: research brief. New York, NY: Komodo Health; 2025. Accessed October 25, 2025. 

https://knowledge.komodohealth.com/hubfs/2025/PDFs/Komodo_And_Tigerlily_ADC_Treatment_Patterns_In_Metastatic_Breast_Cancer.pdf

A new analysis from Komodo Health pinpointed significant disparities by age and insurance in antibody-drug conjugate (ADC) treatment rates for metastatic breast cancer. 

Age-Related Disparities in ADC Treatment Rates in Breast Cancer: Tabby Khan, MD

Studies focused on applying deep-learning artificial intelligence (AI) models to mammography screenings have shown promising results in improving radiologist reading times and reducing false negatives 

 spoke with Robert Nishikawa, PhD, a professor in the Department of Radiology at the University of Pittsburgh, in light of Breast Cancer Awareness Month. Nishikawa’s career and research focus on breast imaging technology, development, implementation, and assessment.

Nishikawa discussed the practical implications and evolution of AI models used in mammography screenings to aid radiologists’ readings and advance 

 screenings for patients.

Recent developments in deep-learning AI models applied to mammography screening improved double-radiologist readings in the Netherlands while detecting a significant number of malignancies. However, when forced to match the high specificity of double-radiologist readings, its sensitivity was far less.



Contrary to European practices of double-radiologist readings, the US only requires a single reader with the assistance of computer-aided detection.

Whereas European studies supplement the second radiologist’s readings with deep-learning AI models, practical application is not as feasible for studies in the US, Nishikawa said. However, when used, it allowed radiologists to read screenings faster at a higher sensitivity and specificity, he said.

To further develop the accuracy of deep-learning AI models, Nishikawa suggested using them in clinical settings to gauge their effectiveness in the US. As the AI models cannot replace single-radiologist readings, Nishikawa emphasized it’s up to the radiologist to decide whether they want to use it or not. Within that, he explained that radiologists must maintain a certain level of trust when interacting with AI, as current algorithms are “very accurate.”

Clinical applications of AI models may also optimize survivorship care, as screenings are one of the primary points in follow-up care. In cases where there is a low likelihood of malignancy, AI can be used to expedite such cases, thus relieving radiologists’ workload so they can focus on more complex cases.

1. McCrear S. AI-assisted mammogram readings reduce radiologist workload and maintain performance. 

. August 20, 2025. Accessed October 22, 2025. 

https://www.ajmc.com/view/ai-assisted-mammogram-readings-reduce-radiologist-workload-maintain-performance

2. Taylor-Phillips S, Stinton C. Double reading in breast cancer screening: considerations for policy-making. 

. 2020;93(1106):20190610. doi:10.1259/bjr.20190610

3. McCrear S, Adriana Olivo N. The future of survivorship care: precision tools for women after breast cancer. 

. September 10, 2025. Accessed October 22, 2025. 

https://www.ajmc.com/view/the-future-of-survivorship-care-precision-tools-for-women-after-breast-cancer

4. Screening for breast cancer. CDC. September 16, 2024. Accessed October 22, 2025. 

https://www.cdc.gov/breast-cancer/screening/index.html

AI-powered mammography is enhancing breast cancer screening and early detection through cutting-edge radiology insights.

The Evolution of AI Models in Mammography With Robert Nishikawa, PhD

 is the second most common cancer among women and the second leading cause of 

Nevertheless, the National Institute of Cancer (NCI) is committed to advancing breast cancer research to improve prevention, detection, and treatment as 

) highlights these efforts in recognition of Breast Cancer Research Awareness Day on August 18.

a plethora of research dating back decades, more recently, there are a couple of significant advancements related to breast cancer screenings, therapies and treatment, NCI-supported research programs and clinical trials, and discoveries about breast cancer itself, many of which have potential for major impacts in breast cancer treatment and positive patient outcomes.

First, let’s dive into breast cancer screenings and prevention. Mammography is the primary screening tool for effective breast cancer screening for individuals with average risk. Magnetic resonance imaging, or MRIs, and ultrasound can also be used but are less frequently used for women with above-average risk.

Mammograms are an X-ray tool that can detect lesions, calcifications, and other abnormal masses or changes in breast tissue. Over the last 50 years, there have been significant innovations to mammographs, but the most recent innovation is the implementation of artificial intelligence, or AI, which can be associated with improved early detection.² With over 2 million new cases reported in 2020, the need for more effective early diagnosis advancements is crucial for reducing the mortality rate, enhancing treatment effectiveness, and improving patient outcomes.

SimonMed, one of the largest outpatient medical imaging providers in the US, introduced its new AI-enhanced mammogram service, Mammogram+. SimonMed partnered with iCAD, a company responsible for Profound AI, which is an AI-powered mammography detection software. iCAD reported that with their software’s overall diagnostic accuracy in hard-to-find cancers improved by 22% and showed an 18% improvement in reducing false positives when reading 2D and 3D mammographs and digital breast tomosynthesis screenings.

And this is not the only instance in which AI has been used to enhance mammographs. Digital breast tomosynthesis, or DBT—which is used to obtain multiple projections to produce a 3-dimensional and sectional image of the breast—helps overcome obstructions like tissue overlap, or, more specifically, dense breast tissue that can make detecting some breast lesions more difficult. 

DBT utilizes full-field digital mammography, which is common amongst most practices. However, DBT, unlike full-field digital mammographs, or FFDs, uses a series of low-dose 2D x-ray images from multiple different angles around the breast, which are then computed to produce a 3D volumetric image of the breast.

The digital reconstruction significantly improves visualization of lesion edges and reduces diagnostic errors, thus lowering the occurrence of false negatives. A recent study published in the National Library of Medicine has introduced AI deep learning technology with DBT to help improve digital reconstruction and analysis. AI deep learning, when used with DBT and radiologists, has led to substantial increases in patient survival due to improved speed and accuracy in detecting and diagnosing lesions.

 seen success using deep learning with DBT, there are still a few hurdles to overcome. One of the main challenges of applying deep learning and other AI models to DBT is the interpretability and lack of transparency in decision-making, which in turn makes it harder for doctors to detect and correct interpretive errors, resulting in misdiagnoses like false negatives.However, that’s not the end-all be-all. Currently, strategies to improve the interpretability of deep learning models by introducing things like innovative neural network architectures and visualization techniques that can help doctors to better understand the decision-making process of the AI model, in addition to a multiview feature fusion, which combines information from multiple angles and image types, help create a complete and more reliable image to further help doctors come to a concrete conclusion.

Nevertheless, enhanced mammograms have the potential to advance early detection. The 5-year survival rate of patients with stage I breast cancer is 100% when compared with patients with stage IV disease, whose survival rate then drops to 25%.

 These data just go to show how crucial early detection and diagnosis are in improving outcomes and overall survival.

Research Addressing Breast Cancer Disparities

Although breast cancer is the second leading cause of cancer-related deaths among women in the US, Black women have a 40% higher mortality rate from breast cancer than White women as of 2024, according to the HHS Office of Minority Health. 

 Recent studies attribute high misdiagnosis rates and even higher prevalence of aggressive cancers to disproportionate access to screenings—which in turn delays diagnosis—and genetic differences that predispose Black and African American women to more aggressive cancers like triple-negative breast cancer.

While we’re still relatively fresh off the topic of breast cancer screenings, in recent news, Pennsylvania passed a law eliminating costs for supplemental screenings for women with an established risk of breast cancer, genetic predispositions, or heterogeneously dense breast tissue, among other criteria. However, if we narrow in on women with dense breast tissue—which Black women are more likely to have—they still were ineligible to receive supplemental screenings under this law based on the breast density and breast cancer risk standardized guidelines.

 Women with dense breast tissue have a risk of breast cancer 5 times that of women with non-dense breast tissue, and they also have higher rates of false-negative mammograms.

Now, under this law, the measurement tools used were the Breast Imaging and Reporting Data System, or BI-RADS, which set the parameters for breast tissue density, and the Breast Cancer Risk Assessment, or BCRAT, which calculates lifetime risk of breast cancer. A recent clinical trial measuring outcomes for supplemental screenings by race, under this Pennsylvania law, reported fewer cases of extremely dense breast tissue in Black women when compared with White women and even fewer with a BCRAT greater than 20%. Now, under this state-level legislation, a woman must have either heterogeneously dense or extremely dense breast tissue and a BCRAT score greater than 20%. However, with these stipulations, Black women had a sensitivity of 0%, meaning there were 0 false-negative mammograms in Black women that were correctly identified as eligible for supplemental screenings out of the 39,397 Black women in this study. However, when researchers adjusted for women missing BCRAT scores, Black women’s sensitivity rose to 53%.

Another stipulation of the law recognized genetic risk, and while it was not investigated in the clinical trial, there are other studies that have. I briefly mentioned before that Black women are prone to more aggressive breast cancers like triple-negative breast cancer or inflammatory breast cancer.

observed improved survival outcomes in Black women with triple-negative breast cancer and increased levels of regulatory T cells and overall T cell populations. These findings encouraged researchers to suggest more specific studies as to why Black women have a higher abundance of certain immune cell populations and how this can be used to advance breast cancer therapies.

Now if we zoom in a little further beyond the cell and look at our DNA, another study published in 

 found genetic variants at 12 loci associated with breast cancer risk, and among the 18,034 cases evaluated in this genome-wide association study, researchers found that 15.4% of cases with triple-negative breast cancer carried 6 out of the 12 risk alleles.

All in all, while there is ongoing research to identify differences in breast cancer in Black women compared with other races and ethnicities, there is still more to be learned about genetic differences impacting how breast cancer presents in women by race and ethnicity and adjusting policies to account for these differences.

There is a plethora of treatments for breast cancer, including surgery, radiation, hormone therapy, chemotherapy, targeted therapy, and immunotherapy. More recently, researchers from Hebrew University made an advance in targeted therapy for breast cancer and developed a new “drug-like” molecule with the ability to degrade the RNA-binding protein, Hu antigen R, or HuR, which plays a crucial role in preserving oncogene cell proliferation, survival, and metastasis, critical processes that all promote oncogenic mRNA stabilization. The molecule MG-HuR2 reduced HuR levels by up to 80%, disrupting expression of downstream oncogenes and significantly inhibiting cell proliferation, survival, and 3D tumor spheroid growth. The study authors believe this discovery will pave the way for future studies aimed at RNA-binding protein degradation in cancers.

Now, while this degrader has not yet made it to clinical trials, as the study was just published in early July of 2025, in 2023, however, the FDA approved an oral hormonal therapy, a selective estrogen receptor degrader, or a SERD, which is more effective than other hormone therapies in postmenopausal women and men with various subtype of breast cancer. These include estrogen receptor positive, or ER+, human epithelial growth receptor 2 negative, or HER2-negative, estrogen receptor alpha-1, or ESR1, mutated advanced or metastatic breast cancer. The brand name of the drug is Orserdu, produced by Stemline Therapeutics, Inc., and in the clinical trials, participants with the ESR1 mutation saw zero progression of their cancer for a little less than 4 months while receiving treatment when compared with patients on another hormone therapy, fulvestrant, an injectable SERD, who only saw their cancer progression stall for 2 months while receiving treatment.

Another oral SERD, imlunestrant, was also shown to be more effective than traditional hormone therapies at slowing the growth of ESR1-mutant tumors in women with advanced ER-positive, HER2-negative breast cancer. And when combined with the cell growth blocker abemaciclib, the SERD was better in treating those with mutated and unmutated ESR1 tumors.

In regard to immunotherapy, which helps the body’s immune system fight the cancer more efficiently and effectively, there have also been recent advancements in immunotherapy drugs, or immune checkpoint inhibitors. Evidence has shown that these inhibitors may improve how long someone with advanced breast cancer can live. This type of treatment is more common for individuals with advanced or more aggressive subtypes of breast cancer.

The reported findings of a clinical trial on the outcomes of the immunotherapy drug pembrolizumab, published earlier this year in the 

, showed improved outcomes in patients with early-stage triple-negative breast cancer who were treated before and after surgery, leading to FDA approval. 

The progressive nature of hormone, targeted, and immune therapies alludes to promising advancements in breast cancer treatments that have the potential to improve outcomes amongst patients with various subtypes of breast cancer.

The NCI is also conducting clinical trials that assess and evaluate breast cancer screening, treatment, and prevention from multiple angles, with the goal of advancing knowledge and improving patient outcomes.

1. Breast cancer statistics. Centers for Disease Control and Prevention. June 10, 2025. Accessed July 31, 2025. 

https://www.cdc.gov/breast-cancer/statistics/index.html

2. Advances in breast cancer research. NCI. April 8, 2025. Accessed July 31, 2025. 

https://www.cancer.gov/types/breast/research#research-in-breast-cancer-treatment

3. Nicosia L, Gnocchi G, Gorini I, Venturini M, Fontana F, Pesapane F, et al., History of mammography: analysis of breast imaging diagnostic achievements over the last century. 

 2023;11(11):1596. doi:10.3390/healthcare11111596

4. Wang R, Chen F, Chen H, Lin C, Shuai J, Wu Y, et.al., Deep learning in digital breast tomosynthesis: current status, challenges, and future trends.

 (2020). 2025;6(6):e70247. doi:10.1002/mco2.70247

5. Cancer and Black/African Americans. Office of Minority Health. February 13, 2025. Accessed August 6, 2025. 

https://minorityhealth.hhs.gov/cancer-and-blackafrican-americans#footnote1

6. Omilian AR, Mendicino L, George A, et al., Quantitative analysis of T cell subsets in a population of Black women with invasive breast cancer. 

2025;11(1):64.doi:10.1038/s41523-025-00780-5

7. Mahmoud MA, Ehsan S, Ginzberg SP, Domchek SM, Nathanson KL, Conant EF, et.al., Racial differences in screening eligibility by breast density after state-level insurance expansion. 

. 2025;8(8):e2525216. doi:10.1001/jamanetworkopen.2025.25216

8. Jia, G, Ping, J, Guo, X, et al., Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction. 

. 2020;56:819-826. doi:10.1038/s41588-024-01736-4

9. Kassabri L, Benhamou RI. Druglike molecular degraders of the oncogenic RNA-binding protein HuR. 

. Published online July 16, 2025. doi:10.1021/jacsau.5c00551

10. Center for Drug Evaluation and Research. FDA approves elacestrant for ER-positive. U.S. Food and Drug Administration. Accessed August 8, 2025. 

Breast cancer is the second most common cancer among women and the second leading cause of cancer-related deaths among women in the US. In light of Breast Cancer Research Awareness Day, The American Journal of Managed Care® breaks down the most recent advancements in breast cancer prevention, screening, and therapies. 

Breast Cancer

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