Individual insulin use and the risk of breast cancer: An international clinical epidemiology study.
Bibliographic record
Abstract
1578 Background: The association between individual insulin use and cancer risk has been previously considered with studies reporting higher breast cancer incidence for insulin glargine. Objective: To assess the relative risk of breast cancer associated with individual insulin use (glargine, human insulin, insulin analogs aspart and lispro). Methods: Systematic case-control study of incident breast cancer occurring in women with diabetes from across the United Kingdom, Canada and France. Participants and Settings: 775 case-patients with diabetes and primary invasive or in situ carcinoma of the breast (diagnosed between 1 January, 2008 and 30 June, 2009) selected from 39,958 incident breast cancer patients from 92 large oncology clinics; and 3,050 control-patients with diabetes selected from 580 general practices and matched on country, age, date, type of diabetes (1 or 2), and management by diabetologist or general practitioner. Data on exposure: Data was collected from physicians and patients. Statistical analysis: The main risk model was a multivariable conditional logistic regression including individual insulin use, 8 years preceding the index date, and controlling for past use of any insulin, oral antidiabetic drug use, reproductive factors, lifestyle, education, hormone replacement therapies and contraceptive use, body mass index, comorbidities, diabetes duration, and annual number of physician visits. Results: Adjusted odds ratios of breast cancer were: 1.04 [95% Confidence Interval: 0.76-1.44] for glargine; 1.23 [0.79-1.92] for lispro; 0.95 [0.64-1.40] for aspart; 0.81 [0.55-1.20] for human insulin. Similar results were observed in new insulin users. No effect of dose or duration of use was observed for glargine on the risk of breast cancer. Conclusions: This first international case-controlled study found no difference in the risk of developing breast cancer among patients according to individual insulin use.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".