In one paragraphArticle in Annals of internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
20 authors.
Anna N A TostesonThe Dartmouth Institute for Health Policy and Clinical Practice, Departments of Medicine and Community and Family Medicine, and Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire (A.N.A.T.).ORCID 0000-0001-7718-8943 Natasha K StoutDivision of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland (N.K.S.).ORCID 0000-0002-7946-5649 Yu-Ru SuKaiser Permanente Washington Health Research Institute, Seattle, Washington (Y.-R.S., L.A.).ORCID 0000-0001-6150-960X Nicolien T van RavesteynDepartment of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands (N.T.v.R., H.J.d.K.).
Kathryn P LowryUniversity of Washington School of Medicine, Fred Hutchinson Cancer Center, Seattle, Washington (K.P.L.).ORCID 0000-0002-0840-7855 Linn AbrahamKaiser Permanente Washington Health Research Institute, Seattle, Washington (Y.-R.S., L.A.).ORCID 0000-0002-0840-1947 Oguzhan AlagozDepartment of Industrial and Systems Engineering and Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin (O.A.).ORCID 0000-0002-5133-1382 Roberta DiFlorio-AlexanderDepartment of Radiology, Dartmouth Hitchcock Medical Center, and Geisel School of Medicine at Dartmouth, Dartmouth Cancer Center, Lebanon, New Hampshire (R.D.-A.).ORCID 0000-0003-0589-8158 Harry J de KoningDepartment of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands (N.T.v.R., H.J.d.K.).ORCID 0000-0003-4682-3646 John M HamptonDepartment of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin (J.M.H., A.T.-D.).
Louise HendersonDepartment of Radiology, University of North Carolina, Chapel Hill, North Carolina (L.H.).ORCID 0000-0001-8356-9267 Jeanne S MandelblattLombardi Comprehensive Cancer Center, Georgetown University Medical Center, Department of Oncology and Institute for Cancer and Aging REsearch (I-CARE), Georgetown University, Washington, DC (J.S.M.).ORCID 0000-0002-2490-005X Tracy OnegaDepartment of Population Health Sciences and the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.).ORCID 0000-0002-1633-3040 Clyde B SchechterDepartment of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, New York (C.B.S.).ORCID 0000-0003-0010-2827 Brian L SpragueDepartments of Surgery and Radiology, University of Vermont Cancer Center, University of Vermont Larner College of Medicine, Burlington, Vermont (B.L.S.).ORCID 0000-0001-7948-8317 Sarah SteinDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts (S.S.).
Amy Trentham-DietzDepartment of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin (J.M.H., A.T.-D.).ORCID 0000-0002-5971-4660 Diana L MigliorettiDepartment of Public Health Sciences, University of California Davis School of Medicine, Davis, California, and Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.L.M.).ORCID 0000-0002-5547-1833 Karla KerlikowskeDepartments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California (K.K.).ORCID 0000-0001-8793-8779 Christoph I LeeUniversity of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (C.I.L.).ORCID 0000-0002-8185-7721 Funding
Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Steven D Leach · 1985 to 2026
$91.3MRisk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Diana L Miglioretti · 2011 to 2026
$52.9MIdentifying effective risk-based supplemental ultrasound screening strategies for women with dense breastsR01CA248068 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Diana L Miglioretti, Brian L Sprague · 2020 to 2026
$5.1MNCI NIH HHS P01 CA154292NCI NIH HHS P30 CA023108NCI NIH HHS R01 CA248068
6 · The paper itselfAbstract
backgroundFederally mandated breast density notifications motivate consideration of supplemental breast magnetic resonance imaging (MRI).
objectiveTo evaluate supplemental breast MRI strategies.
designSimulation of women at average to 4 times higher-than-average relative risk (RR) for breast cancer incidence undergoing screening digital breast tomosynthesis (DBT) with or without supplemental MRI. DATA SOURCES: Breast Cancer Surveillance Consortium and literature. TARGET POPULATION: Women aged 40 years or older. TIME HORIZON: Lifetime. PERSPECTIVE: U.S. federal payer.
interventionScreening with DBT with or without breast density-targeted MRI by starting age (40, 45, or 50 years) and interval (annual or biennial). OUTCOME MEASURES: Breast cancer deaths averted, false-positive biopsy recommendations, harm-benefit ratios, and incremental cost-effectiveness ratios (ICERs). RESULTS OF BASE-CASE ANALYSIS: Across all starting ages and intervals, DBT averted 7.4 to 10.5 breast cancer deaths per 1000 average-risk women screened and 23.2 to 33.6 per 1000 women with 4 times higher-than-average risk. Across all RR levels, DBT with supplemental MRI for women with extremely dense breasts (DBT+MRId) averted 0.1 to 0.8 additional breast cancer deaths and resulted in 22 to 186 additional false-positive biopsy recommendations. False-positive biopsies per breast cancer death averted for biennial DBT+MRId for women with 2 times higher-than-average risk were similar to those associated with DBT in average-risk women. For all risk groups, biennial DBT+MRId starting at age 50 years was more effective but less cost-effective than DBT starting at age 45 years. RESULTS OF SENSITIVITY ANALYSIS: The ICERs were sensitive to cancer risk, MRI costs, and false-positive biopsy rates. LIMITATION: Subgroups considered risk and breast density only.
conclusionSupplemental MRI for women aged 40 years or older with extremely dense breasts and higher-than-average risk (RR ≥2.0) had harm-benefit ratios similar to biennial DBT alone and could be cost-effective if MRI costs and false-positive biopsy rates are reduced. PRIMARY FUNDING SOURCE: National Cancer Institute.
Indexed as
Breast NeoplasmsEarly Detection of CancerMagnetic Resonance ImagingMass ScreeningAdultBiopsyBreastBreast DensityCost-Benefit AnalysisCost-Effectiveness AnalysisFalse Positive ReactionsFemaleHumansMammographyMiddle AgedUnited States
Identifiers
PMID41771133
PMCPMC13109907
What OpenQuestion holds
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