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Abstract B101: Cost comparison of high-risk targeted breast MRI vs. mammography in screening underserved women

2011· article· en· W1974404744 on OpenAlexaboutno aff
Lamisha Banks, Anne Ford, Victoria L. Seewaldt

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2011
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMammographyBreast cancerBreast cancer screeningBiopsyBreast MRIBreast ultrasoundPopulationBreast biopsyRadiologyObstetricsDigital mammographyBreast imagingGynecologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Our current recommendations for mammographic and MRI screening are based on studies in European, European-Canadian and European-American women. To our knowledge, there has been no large-scale analysis of the effectiveness of mammographic screening in African-American and Latino women. We have little information on the relative benefits of general mammography screening versus high-risk targeted breast Magnetic Resonance Imaging (MRI) screening in underserved women. Mammography has the advantage of being relatively inexpensive and well accepted. In contrast, MRI is expensive and has the potential to increase the number of benign biopsy. Methods: We compared the ability of mammography screening in a general risk underserved population (standard-of-care) with targeted breast MRI screening in high-risk underserved women to a) detect breast cancer, b) cost of screening/breast diagnosis, c) number of benign biopsies, and d) compliance. From 6/15/2004 to 5/7/2011, 1) 299 general risk women underserved women were underwent digital mammographic screening and 2) 299 high-risk women underwent combined mammogram and breast MRI screening. Women were recruited by our Breast Navigation team from sites throughout central North Carolina and underwent screening accompanied by a member of our Navigation team. Women found to have an abnormal mammogram were evaluated by ultrasound, ultrasound guided biopsy, and/or stereotactic biopsy. Women with an abnormal breast MRI were evaluated with ultrasound, ultrasound guided biopsy, and/or MRI guided biopsy. All follow-up services were provided for free. Results: The average age of women was 50 years for women undergoing mammographic screening and 47 years for women undergoing MRI. The racial composition of general-risk women undergoing mammographic screening was 40% African American, 25% Caucasian, 25% Hispanic, and 1% other vs. 33% African American, 62% Caucasian, 3% Hispanic, and 2% other for high-risk women undergoing breast MRI. Mammographic screening detected 1 breast cancer vs. 9 for MRI. The cost per diagnosis was $37,375.00 vs. $21,561.22. The number of benign breast biopsies/total biopsies was 7/8 (88%) for mammographic screening vs. 31/40 (78%) for MRI. Compliance with follow-up studies was 75% for mammographic screening vs. 90% for MRI. Conclusions: Breast MRI screening in high-risk underserved women is highly feasible and with Navigation, there is a high rate of compliance with follow up studies. The cost per breast cancer diagnosis is significantly lower for targeted breast MRI screening of high-risk women than for mammographic screening of general risk women. Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):B101.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.086
GPT teacher head0.342
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2011
Admission routes1
Has abstractyes

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