Upgrade rate of percutaneously diagnosed pure flat epithelial atypia: systematic review and meta-analysis of 1,924 lesions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Management remains controversial due to the risk of upgrade for malignancy from flat epithelial atypia (FEA). Data about the frequency and malignancy upgrade rates are scant. Namely, observational follow-up is advised by many studies in cases of pure FEA on core biopsy and in the absence of an additional surgical excision. For cases of pure FEA, the American College of Surgeons no longer recommends surgical excision but rather recommends observation with clinical and imaging follow-up. OBJECTIVES: The aim of this study is to perform a systematic review and meta-analysis to calculate the pooled upgrade of pure FEA following core needle biopsies. METHODS: A search of MEDLINE and Embase databases were conducted in December 2020. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A fixed- or random-effects model was utilized. Heterogeneity among studies was estimated by utilizing the I2 statistic and considered high if the I2 was greater than 50%. The random-effects model with the DerSimonian and Laird method was utilized to calculate the pooled upgrade rate and its 95% confidence interval. RESULTS: A total of 1924 pure FEA were analyzed among 59 included studies. The overall pooled upgrade rate to malignancy was 8.8%. The pooled upgrade rate for mammography only was 8.9%. The pooled upgrade rate for ultrasound was 14%. The pooled upgrade rate for mammography and ultrasound combined was 8.8%. The pooled upgrade rate for MRI-only cases was 27.3%. CONCLUSIONS: Although the guidelines for the management of pure FEA are variable, our data support that pure FEA diagnosed at core needle biopsy should undergo surgical excision since the upgrade rate >2%.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.026 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it