Predictors of Outcome in Mammary Adenoid Cystic Carcinoma
Bibliographic record
Abstract
Mammary adenoid cystic carcinoma (ACC) is a rare subtype of breast cancer with a favorable prognosis. Here we report on predictors of outcome based on a detailed morphologic review and analysis of 108 mammary ACC. Sixty-four tumors (59.2%) were pure conventional ACC, 23 (21.3%) were pure basaloid ACC. Follow-up was available for 87 patients (median: 51 mo). Eighteen patients (20.7%) developed recurrence: 7 (8%) had local recurrence and 14 (16%) had distant metastasis. Two patients died of disease, 1 died of an unrelated cause, 14 were alive with disease (including 8 in palliative care), and 70 (80.5%) were alive with no evidence of disease. Of 90 patients with known lymph node (LN) status 9 (10%) had nodal involvement (all with basaloid ACC). Distant metastases in patients with predominantly basaloid ACC compared with pure conventional ACC were more common (40% vs. 7.7%) and occurred earlier (22 vs. 84 mo). The following factors were found to be predictive of recurrence-free survival: positive margin, Nottingham grade, neovascularization, basaloid component, perineural invasion, lymphovascular invasion, >30% solid growth, necrosis and LN involvement; the first 3 remained statistically significant on multivariate analysis. Factors predictive of distant disease-free survival were neovascularization, Nottingham grade, lymphovascular invasion, solid component >50%, LN involvement, basaloid component >50%, tumor necrosis, perineural invasion, and final margin. Only neovascularization remained statistically significant on multivariate analysis. Basaloid ACC is an aggressive variant of mammary ACC with more frequent nodal involvement and higher incidence of distant spread. LN staging should be performed for all mammary basaloid ACC.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".