Cost of breast cancer screening in the USA: Comparison of current practice, advocated guidelines, and a personalized risk-based approach.

Authors

null

Kimberly Badal

University of California, San Francisco, San Francisco, CA

Kimberly Badal , James Staib , Jeffrey Tice , Mi-Ok Kim , Martin Eklund , Stacey DaCosta Byfield , Kierstin Catlett , Leslie Wilson , Liz Maffey , Rashna Soonavala , Allison Stover-Fiscalini , Laura Esserman

Organizations

University of California, San Francisco, San Francisco, CA, OptumLabs at UnitedHealth Group, Minnetonka, MN, UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, Karolinska Institutet, Stockholm, Sweden, Optum Labs, Minnetonka, MN, Optum Center for Research and Innovation, Minnetonka, MN, University of California San Francisco, San Francisco, CA, University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, CA

Research Funding

No funding received
None.

Background: Several clinical trials are comparing the safety and efficacy of risk-based and age-based breast cancer screening. This study aimed to estimate the aggregate yearly cost of screening in the USA for 2019 to 2021 and to project cost of four strategies: annual, biennial, hybrid, and the WISDOM (Women Informed to Screen Depending on Measures of risk) clinical trial’s risk-based strategy. An assessment of screening costs under different strategies can inform policy decisions. Methods: Total cost was estimated for each strategy by summing screening and recall cost for eligible women from a national payer perspective. Data from the FDA Mammography Quality Standards Act and Program was used to estimate the number of screening mammograms in 2019 to 2021. Data from the Optum Labs Data Warehouse (OLDW) was used to estimate utilization of 2D and 3D mammograms, MRI and mammogram costs, recall costs and rates. OLDW contains longitudinal de-identified administrative, medical, and pharmacy claims for over 200 million commercial and Medicare Advantage (MA) enrollees and patients. Study subjects were continuously enrolled for approximately three years to capture all encounters. Medicare Advantage claims were used to approximate public payer costs and rates. We assumed 100% adherence to all strategies. The risk-based strategy used a cost of $270 for genetic testing and risk assessment. Probabilistic sensitivity analysis was used to estimate uncertainty in the estimated aggregate cost. One-way deterministic sensitivity analysis was used to determine the impact of each input on the aggregate cost. Results: Median mammogram costs ranged from $139-$360, MRI costs ranged from $545-$2,439, while recall rates ranged from 9.2%-20.9%. The annual cost of screening 50% of eligible women in 2019 was $11.5B ($10.37-13.94B) and cost $77,824 per breast cancer detected. The estimated yearly aggregate cost of screening 100% of eligible women was: $26.71B ($24.61-32.82B) for annual; $18.09B ($16.03-21.16B) for hybrid; $7.57B ($6.97-9.29B) for biennial; and $9.60B ($8.88-11.70B) for risk-based strategies. The estimated average cost per woman screened until 74 years was: $22,315 for annual; $16,552 for hybrid; $4,133 for biennial; and $6,878 for risk-based. The yearly aggregate cost of screening was most sensitive to variations in commercial 3D mammography cost. Conclusions: Biennial and risk-based screening can reduce cost substantially. Risk-based screening reduced cost even with the cost of population genetic testing included while maintaining intensive screening for the highest-risk women. The resources saved can be used to improve screening for women at high-risk of fast-growing disease who are often identified between screens and for improving overall adherence.

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Abstract Details

Meeting

2023 ASCO Annual Meeting

Session Type

Publication Only

Session Title

Publication Only: Health Services Research and Quality Improvement

Track

Quality Care/Health Services Research

Sub Track

Value/Cost of Care

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr e18917)

DOI

10.1200/JCO.2023.41.16_suppl.e18917

Abstract #

e18917

Abstract Disclosures

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