The effect of Paget disease on axillary lymph node metastases and survival in invasive ductal carcinoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to examine the effect of Paget disease (PD) on axillary lymph node metastases and survival in patients who had concomitant invasive ductal carcinoma (PD-IDC). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was used to identify women who were diagnosed with PD-IDC from 2000 to 2011, comparing baseline demographic and tumor characteristics with those who were diagnosed with IDC alone during the same period. Multivariable logistic regression was used to examine the association of PD-IDC with axillary lymph node metastasis, and breast cancer-specific survival and overall survival were compared between the PD-IDC and IDC groups using the Kaplan-Meier method and Cox proportional hazards regression. RESULTS: The study cohort included 1102 patients with PD-IDC and 302,242 controls with IDC alone. PD-IDC tumors were more likely to be centrally located (26.9% vs 5.5%; P < .001), high grade (63.5% vs 40.3%; P < .001), >2 cm in greatest dimension (47.1% vs 35.7%; P < .001), and estrogen/progesterone receptor-negative (45.2% vs 22.1%; P < .001). In adjusted analyses, patients with PD-IDC had higher odds of axillary lymph node metastasis (odds ratio, 1.83; P < .001). The unadjusted 10-year breast cancer-specific and overall survival rates were lower for the PD-IDC group compared with the IDC-alone group, although, after adjusting for disease stage, tumor characteristics, and local therapy, no significant differences in mortality risk were observed between the 2 groups (hazard ratio, 0.91; P = .24). CONCLUSIONS: PD-IDC is associated with an increased risk of axillary lymph node metastasis, but not with inferior survival, compared with IDC alone after adjustment for other disease factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it