1506-P: Breast Cancer as a Risk Factor for New Diabetes
Bibliographic record
Abstract
While diabetes is an important risk factor for breast cancer, less is known regarding whether a breast cancer diagnosis is associated with increased risk of subsequent diabetes. We therefore assessed the effect of a breast cancer diagnosis on incident diabetes, using population-level data from Danish healthcare registries during 2005-2016. Our study population comprised 33,909 women aged >50 years with new-onset breast cancer and 313,998 comparison cohort members matched by age and the breast cancer diagnosis date (index date) from the general population, all with no prior history of cancer or diabetes. Women with breast cancer and their comparison cohort members were followed for up to 12 years, to ascertain a first occurrence of glucose-lowering drug treatment or hospital-diagnosed diabetes. The hazard of breast cancer for subsequent diabetes was computed using Cox proportional hazard models, adjusting for a range of comorbidities and medications. Mean age at baseline was 66.0 in cancer patients and 65.8 in the comparison cohort. The rate of developing diabetes was 15% greater in breast cancer patients than in the comparison cohort during the first year after breast cancer diagnosis/index date (adjusted hazard ratio [aHR] 1.15, 95% confidence interval [CI] 1.01-1.30). During total follow-up (median 5.2 years), the diabetes rate was 23% greater in women with breast cancer (aHR 1.23, 95% CI 1.16-1.30), corresponding to 8.4 new cases of diabetes per 1000 women per year vs. 6.8 among comparison cohort members. Breast cancer patients were more likely to be treated with an insulin-based regimen (4.8%) compared to comparison cohort members (2.1%). Our findings suggest that breast cancer is an important risk factor for diabetes. Breast cancer patients may benefit from targeted screening for diabetes and counseling regarding risk factor modification. Disclosure R. Shah: None. H. Gerstein: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Other Relationship; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Sanofi. S.K. Szépligeti: None. H.T. Sôrensen: None. R.W. Thomsen: None.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".