Long-Term Use of Long-Acting Insulin Analogs and Breast Cancer Incidence in Women With Type 2 Diabetes
Bibliographic record
Abstract
Purpose The association between long-acting insulin analogs and increased breast cancer risk is uncertain, particularly with the short follow-up in previous studies. We assessed this risk long term in women with type 2 diabetes. Methods A population-based cohort of women 40 years or older, all of whom were treated with long-acting (glargine, detemir) or neutral protamine Hagedorn (NPH) insulin between 2002 and 2012, was formed using the United Kingdom's Clinical Practice Research Datalink. Women were followed until February 2015 or breast cancer diagnosis. Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) and 95% CIs of incident breast cancer, comparing long-acting insulin analogs with NPH overall, as well as by duration and cumulative dose. Results The cohort included 22,395 women who received insulin treatment, with 321 incident breast cancer events occurring during up to 12 years of follow-up (incidence rate 3.3 per 1,000 person-years). Compared with NPH insulin, insulin glargine was associated with an increased risk of breast cancer (HR, 1.44; 95% CI, 1.11 to 1.85), mainly increasing 5 years after glargine initiation (HR, 2.23; 95% CI, 1.32 to 3.77) and after > 30 prescriptions (HR, 2.29; 95% CI, 1.26 to 4.16). The risk was particularly elevated among prior insulin users (HR, 1.53; 95% CI, 1.10 to 2.12) but not for new users, which included fewer patients and for which one cannot rule out an HR of 1.81. The risk associated with insulin detemir was not significantly elevated (HR, 1.17; 95% CI, 0.77 to 1.77). Conclusion Long-term use of insulin glargine is associated with an increased risk of breast cancer in women with type 2 diabetes. The risk associated with insulin detemir remains uncertain because there are fewer users of this insulin.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".