ArticleJAMA network open2021
Assessment of a Risk-Based Approach for Triaging Mammography Examinations During Periods of Reduced Capacity.
Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 13 citations in OpenAlex.
- Comparative Evaluation of Machine Learning and Specialist Physicians in Breast Care Triaging: A Real-World Observational Study.European journal of breast health · 2025Article
- Evaluating breast cancer screening performance without registries using medico-administrative data.Scientific reports · 2025Article
- Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study.Radiology · 2023Observational
- Prioritizing Screening Mammograms for Immediate Interpretation and Diagnostic Evaluation on the Basis of Risk for Recall.Journal of the American College of Radiology : JACR · 2023Article
- Nimble Approach: fast, adapting, calculating and ethically mindful approach to managing colorectal cancer screening programmes during a pandemic.BMJ open gastroenterology · 2022Article
- Prioritizing breast imaging services during the COVID pandemic: A survey of breast imaging facilities within the Breast Cancer Surveillance Consortium.Preventive medicine · 2021Article
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14 authors at 12 institutions in 1 country.
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Abstract
Importance: Breast cancer screening, surveillance, and diagnostic imaging services were profoundly limited during the initial phase of the coronavirus disease 2019 (COVID-19) pandemic. Objective: To develop a risk-based strategy for triaging mammograms during periods of decreased capacity. Design, Setting, and Participants: This population-based cohort study used data collected prospectively from mammography examinations performed in 2014 to 2019 at 92 radiology facilities in the Breast Cancer Surveillance Consortium. Participants included individuals undergoing mammography. Data were analyzed from August 10 to November 3, 2020. Exposures: Clinical indication for screening, breast symptoms, personal history of breast cancer, age, time since last mammogram/screening interval, family history of breast cancer, breast density, and history of high-risk breast lesion. Main Outcomes and Measures: Combinations of clinical indication, clinical history, and breast cancer risk factors that subdivided mammograms into risk groups according to their cancer detection rate were identified using classification and regression trees. Results: The cohort included 898 415 individuals contributing 1 878 924 mammograms (mean [SD] age at mammogram, 58.6 [11.2] years) interpreted by 448 radiologists, with 1 722 820 mammograms in individuals without a personal history of breast cancer and 156 104 mammograms in individuals with a history of breast cancer. Most individuals were aged 50 to 69 years at imaging (1 113 174 mammograms [59.2%]), and 204 305 (11.2%) were Black, 206 087 (11.3%) were Asian or Pacific Islander, 126 677 (7.0%) were Hispanic or Latina, and 40 021 (2.2%) were another race/ethnicity or mixed race/ethnicity. Cancer detection rates varied widely based on clinical indication, breast symptoms, personal history of breast cancer, and age. The 12% of mammograms with very high (89.6 [95% CI, 82.3-97.5] to 122.3 [95% CI, 108.1-138.0] cancers detected per 1000 mammograms) or high (36.1 [95% CI, 33.1-39.3] to 47.5 [95% CI, 42.4-53.3] cancers detected per 1000 mammograms) cancer detection rates accounted for 55% of all detected cancers and included mammograms to evaluate an abnormal mammogram or breast lump in individuals of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with a breast cancer history or without a history but aged 60 years or older, and for short-interval follow-up in individuals aged 60 years or older without a breast cancer history. The 44.2% of mammograms with very low cancer detection rates accounted for 13.1% of detected cancers and included annual screening mammograms in individuals aged 50 to 69 years (3.8 [95% CI, 3.5-4.1] cancers detected per 1000 mammograms) and all screening mammograms in individuals younger than 50 years regardless of screening interval (2.8 [95% CI, 2.6-3.1] cancers detected per 1000 mammograms). Conclusions and Relevance: In this population-based cohort study, clinical indication and individual risk factors were associated with cancer detection and may be useful for prioritizing mammography in times and settings of decreased capacity.
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