Adipose Tissue Distribution and Survival Among Women with Nonmetastatic Breast Cancer
Bibliographic record
Abstract
OBJECTIVE: Previous studies of breast cancer survival have not considered specific depots of adipose tissue such as subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT). METHODS: This study assessed these relationships among 3,235 women with stage II and III breast cancer diagnosed between 2005 and 2013 at Kaiser Permanente Northern California and between 2000 and 2012 at Dana Farber Cancer Institute. SAT and VAT areas (in centimeters squared) were calculated from routine computed tomography scans within 6 (median: 1.2) months of diagnosis, covariates were collected from electronic health records, and vital status was assessed by death records. Hazard ratios (HRs) and 95% CIs were estimated using Cox regression. RESULTS: increase; HR [95% CI]: 1.02 [0.91-1.14]). An association with VAT was noted among women with stage II cancer (stage II: HR: 1.17 [95% CI: 0.99-1.39]; stage III: HR: 0.90 [95% CI: 0.76-1.07]; P interaction < 0.01). Joint increases in SAT and VAT were associated with mortality above either alone (simultaneous 1-SD increase: HR 1.19 [95% CI: 1.05-1.34]). CONCLUSIONS: SAT may be an underappreciated risk factor for breast cancer-related death.
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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 | 0.001 |
| 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) | 0.001 | 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".