Pancreatic Safety of Sitagliptin in the TECOS Study
Bibliographic record
Abstract
OBJECTIVE: We evaluated the incidence of acute pancreatitis and pancreatic cancer in patients with type 2 diabetes and cardiovascular disease who were treated with sitagliptin, a dipeptidyl peptidase-4 inhibitor (DPP-4i). RESEARCH DESIGN AND METHODS: In the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study, a cardiovascular safety study of sitagliptin, all suspected cases of acute pancreatitis and pancreatic cancer were collected prospectively for 14,671 participants during a median follow-up time of 3 years, and were adjudicated blindly. RESULTS: Baseline differences were minimal between participants confirmed to have no pancreatic events, acute pancreatitis, or pancreatic cancer. Among those participants randomized to receive sitagliptin, 23 (0.3%) (vs. 12 randomized to receive placebo [0.2%]) had pancreatitis (hazard ratio 1.93 [95% CI 0.96-3.88], P = 0.065; 0.107 vs. 0.056/100 patient-years), with 25 versus 17 events, respectively. Severe pancreatitis (two fatal) occurred in four individuals allocated to receive sitagliptin. Cases of pancreatic cancer were numerically fewer with sitagliptin (9 [0.1%]) versus placebo (14 [0.2%]) (hazard ratio 0.66 [95% CI 0.28-1.51], P = 0.32; 0.042 vs. 0.066 events/100 patient-years). Meta-analysis with two other DPP-4i cardiovascular outcome studies showed an increased risk for acute pancreatitis (risk ratio 1.78 [95% CI 1.13-2.81], P = 0.01) and no significant effect for pancreatic cancer (risk ratio 0.54 [95% CI 0.28-1.04], P = 0.07). CONCLUSIONS: Pancreatitis and pancreatic cancer were uncommon events with rates that were not statistically significantly different between the sitagliptin and placebo groups, although numerically more sitagliptin participants developed pancreatitis and fewer developed pancreatic cancer. Meta-analysis suggests a small absolute increased risk for pancreatitis with DPP-4i therapy.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".