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Cover of Breast Cancer Screening With Mammography: An Updated Decision Analysis for the U.S. Preventive Services Task Force

Breast Cancer Screening With Mammography: An Updated Decision Analysis for the U.S. Preventive Services Task Force

Technical Report, No. 231s

Investigators: , PhD, MS, , MD, MS, , PhD, MS, , MD, , PhD, MPH, , MS, , MD, , PhD, MS, , PhD, , PhD, , MS, , PhD, , MSc, , MS, , , PhD, MS, , PhD, , PhD, , MD, MSc, , MD, , PhD, , PhD, , ScD, , PhD, , PhD, MS, , PhD, , PhD, , MD, PhD, , PhD, , ScD, , MA, MD, , PhD, , PhD, ScM, and , MD, MPH.

Rockville (MD): Agency for Healthcare Research and Quality (US); .
Report No.: 23-05303-EF-2

Structured Abstract

Importance:

The U.S. Preventive Services Task Force (USPSTF) is updating its 2016 guidelines for screening mammography for breast cancer.

Objective:

To provide the USPSTF with updated model-based estimates of the benefits and harms of breast cancer screening strategies that vary by the ages to begin and end screening, screening modality, and screening interval. Models estimated outcomes for the overall average-risk population of U.S. female persons and for groups of female persons based on Black race, breast density, elevated relative risk of breast cancer, and level of comorbidity.

Design:

Comparative modeling using six microsimulation and analytic models that produce outcomes with and without breast cancer screening in a hypothetical cohort of average-risk U.S. 40-year-old female persons (all races) born in 1980 with no previous breast cancer diagnosis. Analyses were repeated for groups of female persons by Black race, breast density category, elevated risk, and comorbidity level.

Exposures:

Screening from ages 40, 45, or 50 years until ages 74 or 79 years with digital mammography (DM) or digital breast tomosynthesis (DBT) annually or biennially or a hybrid combination of the two intervals. Screening strategies using DBT were evaluated in strata according to breast density categories and, separately, for modestly elevated risk levels of breast cancer (relative risk 1.5 and 2.0). Screening strategies with additional stopping ages (69 and 84) were evaluated for female persons older than 65 years according to four levels of comorbidity (none, low, moderate, severe). Full adherence with all screening was assumed, and all cases received immediate treatment regardless of the method of detection according to current treatment dissemination patterns in the United States.

Main Outcome and Measures:

Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained [LYG], quality-adjusted life-years [QALYs] gained), harms (false-positive recalls, benign biopsies, overdiagnosis with overtreatment), number of screening tests, and the stage distribution of breast cancers for a cohort of 1,000 40-year-old female persons screened. Trade-offs of harm and benefit were evaluated through efficiency frontier plots and by calculating harm-to-benefit and benefit-to-harm ratios. Efficient (and near-efficient) strategies were those that required fewer mammograms (or similar) per LYG and per breast cancer mortality reduction relative to other strategies.

Results:

Modeling identified five efficient screening strategies resulting in the highest breast cancer mortality reduction and LYG. Efficient strategies involved DBT and biennial screening (ages 50–74, 40–79, or 45–79), annual screening (ages 40–79), and a hybrid combination of intervals (annual at ages 40–49 with biennial at ages 50–79). Across all models for a cohort of 1,000 average-risk 40-year-old female persons including all races, estimated median breast cancer mortality reduction across these five DBT efficient screening strategies compared to no screening ranged from 25.4% to 41.7%, LYG ranged from 120.8 to 229.7, deaths averted ranged from 6.7 to 11.5, lifetime number of mammograms ranged from 11,208 to 34,441, median false-positive recalls ranged from 873 to 2,224, and the number of overdiagnosed cases ranged from 12 to 25.

Four models of breast cancer in Black female persons identified three efficient DBT screening strategies, two with biennial (ages 40–79 or 45–79) and one with annual (ages 40–79) screening. Across the four models for a cohort of 1,000 average-risk Black female persons, estimated median breast cancer mortality reduction across these three efficient screening strategies compared to no screening ranged from 31.2% to 39.6%, LYG ranged from 219.4 to 309.0, deaths averted ranged from 11.7 to 15.5, lifetime number of mammograms ranged from 14,755 to 33,577, false-positive recalls ranged from 1,107 to 2,074, and the number of overdiagnosed cases ranged from 20 to 25. Breast cancer mortality disparities for Black female persons persisted if all female persons obtained mammography with the same screening strategy. More intensive screening for Black female persons (e.g., biennial ages 40 or 45 to 79 with female persons overall screened at ages 50–74) could reduce the elevated disparity in breast cancer mortality rates from 42% to 30%.

Compared with DM, DBT resulted in fewer false-positive recalls, with minimal or modest improvements in mortality for female persons overall and for Black female persons. No DM strategies were efficient or near-efficient in most models for female persons overall or for Black female persons.

When models estimated screening outcomes for female persons with greater breast cancer risk, due to either more dense breast tissue or other risk factors such as a first-degree family history of breast cancer, trade-offs in the benefits and harms of screening improved. Trade-offs were also superior for female persons with a lower comorbidity burden.

Limitations:

To isolate the benefits of screening, all modeled scenarios assumed 100% screening adherence and prompt evaluation of abnormal screening results, which may overestimate the benefit of screening compared to real world implementation. Relative performance of compared strategies might change if adherence or evaluation patterns differ by age, race, or screening frequency. We did not consider imaging modalities besides mammography, individuals at high risk of breast cancer due to genetic susceptibility, or potential risk of breast cancer due to screening-related radiation. Model projections were based on a 1980 U.S. birth cohort with current screening performance and treatment effectiveness assumed for breast cancer diagnosed in the future.

Conclusions:

This collaborative modeling analysis suggests that several mammography screening strategies reduce breast cancer mortality and increase life expectancy in average-risk female persons. Strategies with biennial screening, start ages at 40 or 45, and cessation age at 79 resulted in greater incremental gains in mortality reduction per mammogram compared with most strategies involving annual screening, start age at 50, and/or cessation age at 74. For some groups of female persons with higher risk of breast cancer and breast cancer death, more intensive screening can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Author’s Contributions

Authors Chapman, Jayasekera, Lowry, and Miglioretti contributed equally to this report.

Prepared for: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, 5600 Fishers Lane, Rockville, MD 20857; www.ahrq.gov Prepared by: The Cancer Intervention and Surveillance Modeling Network (CISNET), Breast Cancer Working Group

Suggested citation:

CISNET Breast Cancer Working Group. Breast Cancer Screening With Mammography: An Updated Decision Analysis for the U.S. Preventive Services Task Force. AHRQ Publication No. 23-05303-EF-2. Rockville, MD: Agency for Healthcare Research and Quality; 2024.

Investigators worked with USPSTF members and Agency for Healthcare Research and Quality (AHRQ) staff to develop the scope, analytic framework, and key questions for this review. AHRQ had no role in study selection, quality assessment, or synthesis. AHRQ staff provided project oversight; reviewed the report to ensure that the analysis met methodological standards; and distributed the draft for peer review. Otherwise, AHRQ had no role in the conduct of the study, or collection, management, analysis, and interpretation of the data. The findings and conclusions in this document are those of the authors and do not reflect the official position of AHRQ, the National Cancer Institute, or the U.S. Department of Health and Human Services.

The information in this report is intended to help healthcare decision makers—patients and clinicians, health system leaders, and policymakers, among others—make well-informed decisions and thereby improve the quality of healthcare services. This report is not intended to be a substitute for the application of clinical judgment. Anyone who makes decisions concerning the provision of clinical care should consider this report in the same way as any medical reference and in conjunction with all other pertinent information (i.e., in the context of available resources and circumstances presented by individual patients).

This report may be used, in whole or in part, as the basis for the development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.

Funding

This report is based on research conducted by the CISNET Breast Cancer Working Group under National Cancer Institute grant number U01 CA253911 and contract number HHSA290201500007I, Task Order 2 from AHRQ, U.S. Department of Health and Human Services.

The Breast Cancer Surveillance Consortium and its data collection activities are funded by grants from the National Cancer Institute (P01CA154292, U54CA163303), the Patient-Centered Outcomes Research Institute (PCS-1504-30370), and AHRQ (R01 HS018366-01A1). The collection of cancer and vital status data is supported in part by several state public health departments and cancer registries throughout the United States.

This work was also supported in part by National Cancer Institute grant number P30CA014520 and a Vilas Associates Award to Amy Trentham-Dietz. Jinani Jayasekera was supported by the Division of Intramural Research at the National Institute on Minority Health and Health Disparities of the National Institutes of Health, and the National Institutes of Health Distinguished Scholars Program (Grant Number: N/A).

None of the investigators have any affiliations or financial involvement that conflicts with the material presented in this report.

Bookshelf ID: NBK603560PMID: 38718151

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