A Comparison of the Risks of In-Breast Recurrence after a Diagnosis of Dcis or Early Invasive Breast Cancer
Bibliographic record
Abstract
BACKGROUND: It is controversial whether ductal carcinoma in situ (dcis) is a preinvasive marker of breast cancer or if it is part of a spectrum of small cancers with malignant potential. Comparing clinical outcomes in women with invasive and noninvasive breast lesions might help to resolve the issue. METHODS: From a database of 2641 patients with breast cancer, we selected women who had been treated with breast-conserving surgery for a cancer that was 2.0 cm or less in size, node-negative, and nonpalpable. No subject received chemotherapy. Cancers were categorized as noninvasive (stage 0, n = 172) or invasive (stage 1, n = 401) based on a review of the pathology records. We compared the actuarial risks of in-breast recurrence after invasive and noninvasive breast lesions before and after adjusting for tamoxifen and radiotherapy. RESULTS: The 18-year cumulative risk of in-breast recurrence was 35.2% for patients with dcis and 12.8% for patients with small invasive cancers (hazard ratio: 2.4; 95% confidence interval: 1.5 to 3.8; p < 0.0003). After adjustment for radiotherapy and tamoxifen treatment, the difference was small and nonsignificant (hazard ratio: 1.4; 95% confidence interval: 0.9 to 2.4; p = 0.22). CONCLUSIONS: For women with small, nonpalpable, node-negative breast cancers, the likelihood of experiencing an in-breast recurrence was associated with radiotherapy and with tamoxifen, but not with the presence of cancer cells invading beyond the basement membrane.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".