Disruption of the expected positive correlation between breast tumor size and lymph node status in <i>BRCA1</i>‐related breast carcinoma
Bibliographic record
Abstract
BACKGROUND: A positive correlation between breast tumor size and the number of axillary lymph nodes containing tumor is well established. It has been reported that patients with BRCA1-related breast carcinoma are more likely than patients with nonhereditary breast carcinoma to have negative lymph node status. Therefore, the authors questioned whether the known positive correlation between tumor size and lymph node status also was present in women with BRCA1-related breast carcinomas. METHODS: The relation between the greatest dimension of the resected breast tumor (size) and the presence of positive axillary lymph nodes (expressed as a percentage of all lymph nodes examined) was evaluated in 1555 women with invasive breast carcinoma who were ascertained at 10 centers in North America between 1975 and 1997. There were 276 BRCA1 mutation carriers, 136 BRCA2 carriers, and 1143 women without a known mutation (208 BRCA1/BRCA2 noncarriers and 935 untested women). Patients were stratified according to tumor size, and odds ratios were estimated for the presence of positive lymph nodes with increasing tumor size. RESULTS: A highly significant positive correlation between tumor size and the frequency of positive axillary lymph nodes was seen for BRCA1/BRCA2 noncarriers, for BRCA2 carriers, and for untested women (overall P < 0.0001 for each). In contrast, there was no clear correlation between tumor size and positive lymph node status in BRCA1 carriers (overall P = 0.20). CONCLUSIONS: The relation between tumor size and lymph node status in patients with breast carcinoma appears to be different in BRCA1 carriers compared with BRCA2 carriers and noncarriers. These findings have important implications for estimating the route of metastatic spread and for evaluating the effectiveness of early diagnosis in patients with BRCA1-related breast carcinoma.
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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 | 0.000 | 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 | 0.000 | 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".