Reasons Women at Elevated Risk of Breast Cancer Refuse Breast MR Imaging Screening: ACRIN 6666
Bibliographic record
Abstract
PURPOSE: To determine reasons for nonparticipation in a trial of supplemental screening with magnetic resonance (MR) imaging after mammography and ultrasonography (US). MATERIALS AND METHODS: Women(n = 2809) at elevated risk of breast cancer were enrolled in the American College of Radiology Imaging Network 6666 US Screening Protocol at 21 institutions. Fourteen institutions met technical and experience requirements for this institutional review board-approved, HIPAA-compliant substudy of supplemental screening with MR imaging. Those women who had completed 0-, 12-, and 24-month screenings with mammography combined with US were considered for a single contrast material-enhanced MR examination within 8 weeks after completing the 24-month mammography-US screening. A total of 1593 women had complete MR substudy registration data: 378 of them were ineligible for the study, and 1215 had analyzable data. Reasons for nonparticipation were determined. Demographic data were compared between study participants and nonparticipants. RESULTS: Of 1215 women with analyzable data, 703 (57.9%), with a mean age of 54.8 years, were enrolled in the MR substudy and 512 (42.1%) declined participation. Women with a 25% or greater lifetime risk of breast cancer were more likely to participate (odds ratio, 1.53; 95% confidence interval: 1.10, 2.12). Of 512 nonparticipants, 130 (25.4%) refused owing to claustrophobia; 93 (18.2%), owing to time constraints; 62 (12.1%), owing to financial concerns; 47 (9.2%), because their physician would not provide a referral and/or did not believe MR imaging was indicated; 40 (7.8%), because they were not interested; 39 (7.6%), because they were medically intolerant to MR imaging; 29 (5.7%), because they did not want to undergo intravenous injection; 27 (5.3%), owing to additional biopsy or other procedures that might be required subsequently; 21 (4.1%), owing to MR imaging scheduling constraints; 11 (2.2%), because of the travel required; seven (1.4%), owing to gadolinium-related risks or allergies; and six (1.2%), for unknown reasons. CONCLUSION: Of 1215 women with elevated breast cancer risk who could, according to protocol guidelines, undergo breast MR imaging, only 57.9% agreed to participate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".