Bayer has announced the publication of a novel health economic model in the Journal of Medical Economics, funded by Bayer, analyzing cost effectiveness and infrastructural capacity of supplemental imaging modalities for women with dense breasts at average or intermediate risk of breast cancer.
The results of the model demonstrated all investigated supplemental imaging modalities — contrast-enhanced breast magnetic resonance imaging (MRI) in abbreviated (Ab-MRI) or full (Fp-MRI) protocol, contrast-enhanced mammography (CEM) and ultrasound (U/S) — improved clinical outcomes (i.e., fewer breast cancer deaths, false negative results and undetected cancers) with the exception of the number of false positives, compared to routine screening alone with either x-ray mammography (XM) or digital breast tomosynthesis (DBT).
Though U/S seemed more advantageous from a purely economic perspective, MRI and CEM offered the best clinical outcomes. The model provided a unique perspective of comparing all available imaging modalities (primary and supplemental), exploring their risk benefit ratio and cost effectiveness.
“The findings of this economic model are aligned with ongoing efforts in U.S. Congress to improve access to supplementary breast cancer screening,” said Dr. Elizabeth Morris, Chair, Department of Radiology, University of California, Davis, and study co-author. “Reintroduced earlier this year, the Find It Early Act seeks to ensure coverage of supplemental screening with no cost-sharing for certain individuals at greater risk, including those with dense breasts. The results of this study provide important evidence that reinforces the value of this Act. The analysis also helps build much-needed consensus around the preferred supplemental screening modalities that, in combination with improved access, will help contribute to the impact of life-saving breast cancer screening.”
“At Bayer, we are committed to increasing awareness of the importance of supplemental breast imaging for patients at higher risk of breast cancer, as early detection is essential to improving outcomes,” said Wagdy Youssef, Vice President and Head of Medical Affairs, Bayer Radiology, Americas. “The results of this study point to the clinical value and economic viability of contrast-enhanced modalities for supplemental breast cancer screening for women with dense breasts. We are proud to support this important study and hopeful the results will help build awareness and access around the cost-effectiveness of supplemental screening modalities.”
The publication of this study comes on the heels of changes in the U.S. landscape for supplemental breast cancer screening. On March 9, 2023, the FDA updated its mammography regulation, which starting in September 2024, requires mammography facilities to notify patients about the density of their breasts as part of their mammography report. On May 3, 2023, the American College of Radiology (ACR) updated its breast cancer screening guidelines for women at higher than average risk. For women with dense breasts, the ACR recommends supplemental screening, with breast MRI in addition to x-ray mammography, and for those who qualify for but cannot undergo breast MRI, CEM or U/S could be considered.
Methodology “Utilized in the Health Economic Model Publication”
The cost-effectiveness of the breast cancer screening modalities was analyzed for a simulated sample of 1,000 asymptomatic women with dense breasts at average or immediate risk of breast cancer. Clinical and economic outcomes for supplemental imaging modalities, including full and abbreviated protocol MRI, contrast-enhanced mammography (CEM) and ultrasound as add on to x-ray mammography (XM) or digital breast tomosynthesis (DBT), were compared to XM or DBT alone, in a decision tree linked to a Markov chain validated by comparison with a microsimulation analysis. Sensitivity and specificity values for XM and DBT and supplemental screening modalities were taken from the literature. In addition, a Delphi panel of experts supplemented information from the literature for the model scenario analysis.
About Breast Density
Breast density is a term used to describe the amount of fibroglandular tissue versus fat in the breast. In dense breasts, there is more fibroglandular tissue — the lobules, ducts, and connective tissue — and less fat. In general, women whose breasts have more than 50% fibroglandular tissue are said to have high-density or dense breasts.2,3 Nearly half of all women in U.S. aged 40+ who get mammograms have dense breasts.1 Women with dense breasts have a higher risk of breast cancer compared to women with less dense breast tissue, and the risk is higher with increasing breast density.1,3 Screening mammograms may miss about one in five breast cancers in women and may miss one-third of breast cancers in women with dense breasts.4,5
About Breast Cancer Screening
Breast cancer is the most frequent cancer globally with 2.3 million reported cases in 2020.6 Women with dense breasts face up to a three to five -fold higher risk of developing breast cancer than those with non-dense breasts.7 Breast malignancies are also more likely to be missed by routine screening modalities such as x-ray mammography (XM) and digital breast tomosynthesis (DBT) alone in women with dense breasts.8-11
For more information and resources on dense breasts, visit: RadiologyResources.Bayer.com/Dense-Breast-Resources
About Bayer
Bayer is a global enterprise with core competencies in the life science fields of health care and nutrition. Its products and services are designed to help people and the planet thrive by supporting efforts to master the major challenges presented by a growing and aging global population. Bayer is committed to driving sustainable development and generating a positive impact with its businesses. At the same time, the Group aims to increase its earning power and create value through innovation and growth. The Bayer brand stands for trust, reliability and quality throughout the world. In fiscal 2022, the Group employed around 101,000 people and had sales of 50.7 billion euros. R&D expenses before special items amounted to 6.2 billion euros. For more information, go to www.bayer.com.
Forward-Looking Statements
This release may contain forward-looking statements based on current assumptions and forecasts made by Bayer management. Various known and unknown risks, uncertainties and other factors could lead to material differences between the actual future results, financial situation, development or performance of the company and the estimates given here. These factors include those discussed in Bayer’s public reports which are available on the Bayer website atwww.bayer.com. The company assumes no liability whatsoever to update these forward-looking statements or to confirm them to future events or developments.
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References
1 National Cancer Institute. Dense Breasts: Answers to Commonly Asked Questions. Updated March 29, 2023. Accessed on November 21, 2023 from:https://www.cancer.gov/types/breast/breast-changes/dense-breasts#:~:text=Nearly%20half%20of%20all%20women,other%20factors%20can%20influence%20it.
2 American Cancer Society. Breast Density and Your Mammogram Report. Updated March 28, 2023. Accessed on November 21, 2023 from: https://www.cancer.org/cancer/types/breast-cancer/screening-tests-and-early-detection/mammograms/breast-density-and-your-mammogram-report.html.
3 ACP Internist. Making Sense of Breast Density. June 2020. Accessed on November 21, 2023 from: https://acpinternist.org/archives/2020/06/making-more-sense-of-breast-density.htm
4 National Cancer Institute. Mammograms. Updated February 21, 2023. Accessed on November 21, 2023 from: https://www.cancer.gov/types/breast/mammograms-fact-sheet.
5 George Washington University Cancer Center. Are Your Breasts Dense? Accessed on November 21, 2023 from: https://cancercenter.gwu.edu/specialties/breast-cancer/are-your-breasts-dense.
6 World Health Organization. Breast cancer fact sheet. March 26, 2021. Accessed on November 21, 2023 from: https://www.who.int/news-room/fact-sheets/detail/breast-cancer.
7 Eriksson L, Czene K, Rosenberg LU, et al. Mammographic density and survival in interval breast cancers. Breast Cancer Res. 2013;15(3):R48. doi: 10.1186/bcr3440.
8 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(13):1081–1087. doi: 10.1093/jnci/92.13.1081.
9 Hadadi I, Rae W, Clarke J, et al. Diagnostic performance of adjunctive imaging modalities compared to mammography alone in women with Non-Dense and dense breasts: a systematic review and Meta-Analysis. Clin Breast Cancer. 2021;21(4):278–291. doi: 10.1016/j.clbc.2021.03.006.
10 Boyd NF, Guo H, Martin LJ, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356(3):227–236. doi: 10.1056/NEJMoa062790.
11 Wanders JO, Holland K, Veldhuis WB, et al. Volumetric breast density affects performance of digital screening mammography. Breast Cancer Res Treat. 2017;162(1):95–103. doi: 10.1007/s10549-016-4090-7.
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