Use of Dipeptidyl Peptidase-4 Inhibitors and New-onset Rheumatoid Arthritis in Patients with Type 2 Diabetes
Bibliographic record
Abstract
BACKGROUND: Case reports have suggested a link between dipeptidyl peptidase-4 (DPP-4) inhibitors, antidiabetic drugs used as second- to third-line treatments, and incidence of rheumatoid arthritis. Because the DPP-4 enzyme is involved in several immunologic processes and possibly in the pathophysiology of rheumatoid arthritis, further research is warranted. This population-based study aimed to determine whether use of DPP-4 inhibitors is associated with incidence of rheumatoid arthritis. METHODS: Using the United Kingdom Clinical Practice Research Datalink, we conducted a cohort study among 144,603 patients with type 2 diabetes initiating antidiabetic drugs between 2007 and 2016. We estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for incident rheumatoid arthritis using time-dependent Cox proportional hazards models, comparing use of DPP-4 inhibitors with use of other antidiabetic drugs. We imposed a 6-month exposure lag period for latency and diagnostic delays. Secondary analyses included assessment of the duration-response relation and comparison with other second-line antidiabetic drugs, among others. RESULTS: During 567,169 person-years of follow-up, 464 patients were newly diagnosed with rheumatoid arthritis (crude incidence rate: 82 per 100,000/year). Compared with use of other antidiabetic drugs, use of DPP-4 inhibitors was not associated with an increased risk of rheumatoid arthritis (82 vs. 79 per 100,000/year; HR = 1.0; 95% CI = 0.8, 1.3), with no evidence of duration-response relation. The results did not change after using second-line antidiabetic drugs as the comparator group. CONCLUSIONS: In this large population-based study, use of DPP-4 inhibitors was not associated with an increased risk of incident rheumatoid arthritis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".