Incretin-based Drugs and the Incidence of Colorectal Cancer in Patients with Type 2 Diabetes
Bibliographic record
Abstract
BACKGROUND: Evidence on the safety of the incretin-based drugs (glucagon-like peptide-1 [GLP-1] analogues and dipeptidyl peptidase-4 [DPP-4] inhibitors) with respect to colorectal cancer is contradictory. The objective of this study was to determine whether use of incretin-based drugs is associated with risk of incident colorectal cancer in patients with type 2 diabetes. METHODS: Using data from the UK Clinical Practice Research Datalink, we identified a cohort of 112,040 patients newly treated with antidiabetic drugs between 1 January 2007 and 31 March 2015. We modeled use of GLP-1 analogues and DPP-4 inhibitors as time-varying variables and compared them with use of sulfonylureas. We lagged exposures by 1 year for latency and to reduce reverse causality and detection bias. We used time-dependent Cox proportional hazards models to estimate hazard ratios with 95% confidence intervals of incident colorectal cancer associated with the use of GLP-1 analogues and DPP-4 inhibitors overall, by cumulative duration of use and by time since initiation. RESULTS: During 388,619 person-years of follow-up, there were 733 incident colorectal cancer events (incidence rate: 1.9 per 1,000 person-years). Use of GLP-1 analogues was not associated with colorectal cancer incidence (hazard ratio: 1.0; 95% confidence interval = 0.7, 1.6), nor was use of DPP-4 inhibitors (hazard ratio: 1.2; 95% confidence interval = 1.0, 1.5). There was no evidence of a duration-response relation for either drug. CONCLUSIONS: The results of this large population-based study indicate that use of incretin-based drugs is not associated with colorectal cancer incidence among patients with type 2 diabetes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".