Atypical ductal hyperplasia on core needle biopsy: Development of a predictive model stratifying carcinoma upgrade risk on excision
Bibliographic record
Abstract
BACKGROUND: Although the rate of carcinoma upgrade for atypical ductal hyperplasia (ADH) diagnosed on core needle biopsy (CNB) is variable, current standard treatment consists of surgical excision (SE) for all ADH CNB diagnoses. Our objective was to identify features of ADH on CNB that may stratify carcinoma upgrade risk on SE. METHODS: We retrospectively analyzed cases diagnosed as ADH on CNB. An independent slide review and detailed analysis of radiological and clinical data was performed. Statistical analyses were used to identify predictors for upgrade. Using variables predictive of upgrade, a model to stratify the probability of upgrade of ADH diagnosed on CNB was constructed. RESULTS: We identified 124 ADH cases with subsequent SE. Of these, 62 cases (50%) were upgraded to carcinoma. Features predictive of upgrade were as follows: diagnosis of "At least ADH", percentage of cores involved by ADH, radiologic lesion size, presence of ipsilateral carcinoma, and patient age. A 4-tiered predictive model using percentage of cores involved by ADH, histologic extent of ADH, radiologic lesion size, and patient age was constructed. This predictive model has a fair accuracy, with an area under the ROC curve of 0.76. CONCLUSION: We have identified several predictors of carcinoma upgrade for ADH diagnosed on CNB. Our predictive model may be used to stratify the risk of carcinoma upgrade on SE.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".