Randomized trial of surveillance with abbreviated MRI in women with a personal history of breast cancer– impact on patient anxiety and cancer detection
Bibliographic record
Abstract
BACKGROUND: Abbreviated breast MRI (A-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 psychological distress in women with a prior history of breast cancer (PHBC). This study aimed to determine if surveillance mammography (MG) plus A-MRI reduced psychological distress and if A-MRI improved cancer detection rates (CDR) as compared to MG alone. METHODS: This prospective controlled trial of parallel design was performed at a tertiary cancer center on asymptomatic women with PHBC who were randomized into two groups: routine surveillance with MG or intervention of MG plus A-MRI in a 1:1 ratio. Primary outcome was anxiety measured by four validated questionnaires at three different time-points during the study. Other parameters including CDR and positive predictive value for biopsy (PPV3) were compared between imaging 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 measures and Fisher's exact test to compare imaging outcomes. RESULTS: One hundred ninety-eight patients were allocated to either MG alone (94) or MG plus A-MRI (104). No significant group difference emerged for improvement in trait anxiety, worry and perceived health status (all Time-by-surveillance group interaction ps > .05). There was some advantage of A-MRI in reducing state anxiety at Time 2 (p < .05). Anxiety scores in all questionnaires were similarly elevated in both groups (50.99 ± 4.6 with MG alone vs 51.73 ± 2.56 with MG plus A-MRI, p > 0.05) and did not change over time. A-MRI detected 5 invasive cancers and 1 ductal carcinoma in situ (DCIS), and MG detected 1 DCIS. A-MRI had higher incremental CDR (48/1000(5/104) vs MG 5/1000(1/198, p = 0.01)) and higher biopsy rates (19.2% (20/104) vs MG 2.1% (2/94), p < 0.00001) with no difference in PPV3 (A-MRI 28.6% (6/21) vs MG 16.7% (1/6, p > .05). CONCLUSION: There was no significant impact of A-MRI to patient anxiety or perceived health status. Compared to MG alone, A-MRI had significantly higher incremental cancer detection in PHBC. Despite a higher rate of biopsies, A-MRI had no demonstrable impact on anxiety, worry, and perceived health status. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT02244593 ). Prospectively registered on Sept. 14, 2014.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".