Bibliographic record
Abstract
High insulin levels have been associated with increased risk of breast cancer and poorer survival after a breast cancer diagnosis. Waist-to-hip ratio (WHR) is a marker for insulin resistance and hyperinsulinemia. In this study, the authors tested the hypothesis that elevated WHR is directly related to breast cancer mortality. For identification of modifiable factors affecting survival, data were collected on 603 patients with incident breast cancer who visited the Vancouver Cancer Centre of the British Columbia Cancer Agency (Vancouver, British Columbia, Canada) in 1991-1992, including body measurements and information on demographic, medical, reproductive, and dietary factors. These patients were followed for up to 10 years. Cox proportional hazards regression models were used to relate the variables to breast cancer mortality (n = 112). After adjustment for age, body mass index, family history, estrogen receptor (ER) status, tumor stage at diagnosis, and systemic treatment (chemotherapy or tamoxifen), WHR was directly related to breast cancer mortality in postmenopausal women (for highest quartile vs. lowest, relative risk = 3.3, 95% confidence interval: 1.1, 10.4) but not in premenopausal women (relative risk = 1.2, 95% confidence interval: 0.4, 3.4). Stratification according to ER status showed that the increased mortality was restricted to ER-positive postmenopausal women. Elevated WHR was confirmed as a predictor of breast cancer mortality, with menopausal status and ER status at diagnosis found to be important modifiers of that relation.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".