Randomized Trial of Surveillance with Abbreviated MRI in Breast Cancer Survivors – Does it impact patient anxiety and cancer detection rate?
Bibliographic record
Abstract
Abstract Purpose: Abbreviated breast MRI substantially reduces the image acquisition and reading times and has been reported to have similar diagnostic accuracy as a full diagnostic protocol but has not been evaluated prospectively with respect to impact on patient anxiety in breast cancer survivors and cancer outcomes.Methods: This prospective controlled trial of parallel design was performed at an academic center on women with a personal history of breast cancer who were randomized into two groups: surveillance with MG or MG plus A-MRI. Primary outcome was anxiety compared between the two and measured by four validated questionnaires at three different time-points during the study. Other parameters including the CDR, abnormal interpretation rate (AIR), and positive predictive value for biopsy (PPV3) were compared between modalities of MG and A-MRI. Tissue diagnoses or 1 year of follow-up were used to establish the reference standard. Linear mixed models were used to analyze anxiety and Fisher’s exact test to compare imaging outcomes.Results: 198 patients were allocated to either MG alone (94) or A-MRI plus MG (104). Anxiety scores in all questionnaires were similarly elevated in both groups (50.99+/-4.6 with MG vs 51.73+/-2.56 with MRI,p>0.05) and did not change over time. MRI detected 5 invasive cancers and 1 DCIS, and MG detected 1 DCIS. MRI had higher incremental CDR(48/1000(5/104) vs MG 5/1000(1/198,p=0.01)) and higher AIR 25%(26/104) vs MG 4.5%(9/198,p<0.00001), with no difference in PPV3:MRI 28.6%(6/21)vs MG 16.7%(1/6,p=0.557).Conclusion:Compared to mammography alone, A-MRI had significantly higher incremental cancer detection in breast cancer survivors. Despite a higher rate of recalls and biopsies, A-MRI had no adverse impact on anxiety.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".