The Use of Glyburide Compared With Other Sulfonylureas and the Risk of Cancer in Patients With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To determine whether the use of glyburide is associated with an increased risk of cancer compared with the use of other second-generation sulfonylureas among patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: The U.K. Clinical Practice Research Datalink was used to conduct a cohort study among 52,600 patients newly prescribed glyburide or other second-generation sulfonylureas between 1 January 1988 and 31 July 2013. A time-dependent Cox proportional hazards model was used to estimate adjusted hazard ratios (HRs) and 95% CIs of any cancer associated with the use of glyburide compared with the use of second-generation sulfonylureas. Secondary analyses were conducted to determine whether the association varied with cumulative duration of use and cumulative dose (expressed as defined daily dose [DDD]). RESULTS: During 280,288 person-years of follow-up, 4,105 patients were given a new diagnosis of cancer (incidence rate 14.6 per 1,000 person-years). Overall, when compared with the use of other second-generation sulfonylureas, the use of glyburide was associated with a nonsignificant increased risk of any cancer (HR 1.09 [95% CI 0.98-1.22]). In secondary analyses, duration- and dose-response relationships were observed, with longer cumulative durations and cumulative doses associated with an increased risk of any cancer (>36 months: HR 1.21 [95% CI: 1.03-1.42]; >1,096 DDDs: HR 1.27 [95% CI 1.06-1.51]). CONCLUSIONS: In this population-based cohort study, longer cumulative durations and higher cumulative doses of glyburide were associated with an increased risk of cancer.
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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".