Underestimation of malignancy in biopsy-proven cases of stromal fibrosis
Bibliographic record
Abstract
OBJECTIVE: To determine the rate of underestimation of malignancy in patients with biopsy-proven stromal fibrosis. METHODS: Following institutional review board approval, we retrospectively reviewed the charts of patients with biopsy-proven stromal fibrosis who underwent percutaneous breast biopsy in the 5-year period between 1 January 2005 and 31 December 2009. The medical records and the histopathology in patients who underwent repeat biopsy and/or surgical excision at the site of stromal fibrosis within 2 years were reviewed. Interval stability for up to 2 years was documented in patients who did not undergo additional biopsy or surgical excision. An upgrade was defined as any patient with biopsy-proven stromal fibrosis or fibroadenoma with evidence of malignancy at the site of biopsy within 2 years. RESULTS: 365 cases of stromal fibrosis were identified, of which 25 (7%) were upgraded to in situ or invasive malignancy on repeat biopsy or surgical excision. 7 were upgraded to ductal carcinoma in situ and 18 were upgraded to invasive cancer. Of the upgraded cases, 8 out of 24 (32%) were considered concordant with a benign diagnosis. The false-negative rate, that is, cases of stromal fibrosis concordant with benignity, but with subsequent upgrade, comprised 2% of all cases. CONCLUSION: In biopsy-proven cases of stromal fibrosis, there is a 7% upgrade to malignancy. We recommend that all instances of stromal fibrosis with radiology-pathology discordance undergo repeat biopsy or surgical excision. Cases that demonstrate radiology-pathology concordance can be safely categorized as a Breast Imaging Reporting and Data System 3 (BI-RADS® 3) lesion with a 6-month follow-up, owing to a false-negative rate for missed cancer of 2%. ADVANCES IN KNOWLEDGE: We now recommend that concordant cases of stromal fibrosis be categorized as BI-RADS 3 with a short-term follow-up, as this results in a missed cancer rate of 2%.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".