Upgrade Rate of Flat Epithelial Atypia Diagnosed at Stereotactic Core Needle Biopsy of Microcalcifications: Is Excisional Biopsy Indicated?
Bibliographic record
Abstract
OBJECTIVE: Whether the optimal management of pure flat epithelial atypia (FEA) found on core needle biopsy (CNB) specimens is surgical excision or imaging follow-up remains controversial. This study aimed to determine the upgrade rate to ductal carcinoma in situ (DCIS), invasive carcinoma or a high-risk lesion (atypical ductal hyperplasia, atypical lobular hyperplasia, or lobular carcinoma in situ), and it explored the relationship between a family history of breast cancer and the risk of upgrade. METHODS: Cases with pure FEA found on stereotactic CNB of microcalcifications between March 2011 to December 2017 were followed by excisional biopsy or periodic imaging. The proportion of cases upgraded to a high-risk lesion and the odds of upgrade as related to a family history of breast cancer were determined with 95% confidence intervals (CIs). RESULTS: We identified 622 cases of pure FEA; 101 (16.2%) underwent surgical excision and 269 (43.2%) had imaging follow-up of ≥ 24 months. There were no upgrades to DCIS or invasive cancer in any of these 370 individuals (0%), and 4.6% (17/370; 95% CI: 2.9%-7.2%) were upgraded to a high-risk lesion. There was a nonstatistically significant trend between family history and upgrade to high-risk lesion (odds ratio 1.72 [95% CI: 0.65%-4.57%]). CONCLUSION: In our study, the upgrade rate of pure FEA to malignancy was 0%. We suggest that regular imaging follow-up is an appropriate alternative to surgery. Because of potential differences in biopsy techniques and pathologist interpretation of the primary biopsy, individual institutions should audit their own results prior to altering their management of FEA.
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 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 | 0.001 |
| 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) | 0.000 | 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".