Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force

Amy Trentham-Dietz ¹, Christina Hunter Chapman ², Jinani Jayasekera ³

¹Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison.
²Department of Radiation Oncology and Center for Innovations in Quality, Safety, and Effectiveness, Baylor College of Medicine, Houston, Texas.
³Health Equity and Decision Sciences (HEADS) Research Laboratory, Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland.
⁴University of Washington School of Medicine, Seattle.
⁵Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
⁶Department of Medicine, Stanford University School of Medicine, Stanford, California.
⁷Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison.
⁸Stanford University, Stanford, California.
⁹Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.
¹⁰Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
¹¹Erasmus MC-University Medical Center, Rotterdam, the Netherlands.
¹²University of Texas MD Anderson Cancer Center, Houston.
¹³Department of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison.
¹⁴Departments of Medicine and Epidemiology and Population Health, Stanford University, Stanford, California.
¹⁵Departments of Medicine and Epidemiology and Biostatistics, University of California San Francisco.
¹⁶Kaiser Permanente Washington Health Research Institute, Seattle, Washington.
¹⁷Department of Surgery, University of Vermont, Burlington.
¹⁸Dartmouth Institute for Health Policy and Clinical Practice and Departments of Medicine and Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, New Hampshire.
¹⁹Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
²⁰Departments of Biomedical Data Science and Radiology, Stanford University, Stanford, California.
²¹Albert Einstein College of Medicine, Bronx, New York.
²²Department of Public Health Sciences, University of California Davis.
²³Departments of Oncology and Medicine, Georgetown University Medical Center, and Georgetown Lombardi Comprehensive Institute for Cancer and Aging Research at Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC.

⁰Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison.

Jama +

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April 30, 2024

View abstract on PubMed

Summary

Biennial mammography screening starting at age 40 significantly reduces breast cancer deaths and increases life-years gained. Tailored screening for high-risk women can maintain benefits and reduce disparities.

Area Of Science

Oncology
Radiology
Public Health

Background

Breast cancer screening effectiveness is influenced by incidence changes and treatment advances.
Optimal mammography screening strategies require updated outcome estimations.

Purpose Of The Study

To estimate the lifetime outcomes of various mammography screening strategies in US women.
To compare digital mammography and digital breast tomosynthesis (DBT) screening intervals and ages.

Main Methods

Utilized 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models with national data.
Evaluated 36 screening strategies (ages 40-79, annual/biennial intervals) using digital mammography or DBT.
Assessed outcomes for all women and specifically for Black women, assuming 100% adherence.

Main Results

Biennial DBT screening from age 40 to 74 averted 8.2 deaths per 1000 women vs. no screening, reducing mortality by 30%.
Digital mammography yielded similar benefits but more false positives; annual screening increased benefits but also harms.
Screening continuation until age 79 showed similar or superior benefit-to-harm ratios. Higher-risk women experienced greater benefits.

Conclusions

Biennial mammography screening, particularly starting at age 40, effectively reduces breast cancer mortality and increases life-years.
Intensified screening for high-risk individuals can maintain benefit-to-harm ratios and decrease mortality disparities.
Targeted annual screening for Black women from age 40 followed by biennial screening can mitigate mortality gaps.

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