Glucagon like peptide‐1 receptor agonists and the risk of skin cancer among patients with type 2 diabetes: Population‐based cohort study
Bibliographic record
Abstract
AIMS: The objective of this study was to determine whether the use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) is associated with an increased risk of melanoma and nonmelanoma skin cancer, separately, compared with the use of sulfonylureas among patients with type 2 diabetes. METHODS: Using the United Kingdom Clinical Practice Research Datalink (2007-2019), we assembled two new-user active comparator cohorts. In the first cohort assessing melanoma as the outcome, 11,786 new users of GLP-1 RAs were compared with 208,519 new users of sulfonylureas. In the second cohort assessing nonmelanoma skin cancer as the outcome, 11,774 new users of GLP-1 RAs were compared with 207,788 new users of sulfonylureas. Cox proportional hazards models weighted using propensity score fine stratification were fit to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of melanoma and nonmelanoma skin cancer, respectively. RESULTS: Compared with sulfonylureas, GLP-1 RAs were not associated with an increased risk of either melanoma (42.6 vs. 43.9 per 100,000 person-years, respectively; HR 0.96, 95% CI 0.53-1.75) or nonmelanoma skin cancer (243.9 vs. 229.9 per 100,000 person-years, respectively; HR 1.03, 95% CI 0.80-1.33). There was no evidence of an association between cumulative duration of use with either melanoma or nonmelanoma skin cancer. Consistent results were observed in secondary and sensitivity analyses. CONCLUSIONS: In this population-based cohort study, GLP-1 RAs were not associated with an increased risk of melanoma or nonmelanoma skin cancer, compared with sulfonylureas.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".