Does Sitagliptin Affect the Rate of Osteoporotic Fractures in Type 2 Diabetes? Population-Based Cohort Study
Bibliographic record
Abstract
CONTEXT: Type 2 diabetes and osteoporosis are both common, chronic, and increase with age, whereas type 2 diabetes is also a risk factor for major osteoporotic fractures (MOFs). However, different treatments for type 2 diabetes can affect fracture risk differently, with metaanalyses showing some agents increase risk (eg, thiazolidinediones) and some reduce risk (eg, sitagliptin). OBJECTIVE: To determine the independent association between new use of sitagliptin and MOF in a large population-based cohort study. DESIGN, SETTING, AND SUBJECTS: A sitagliptin new user study design employing a nationally representative Unites States claims database of 72 738 insured patients with type 2 diabetes. We used 90-day time-varying sitagliptin exposure windows and controlled confounding by using multivariable analyses that adjusted for clinical data, comorbidities, and time-updated propensity scores. MAIN OUTCOMES: We compared the incidence of MOF (hip, clinical spine, proximal humerus, distal radius) in new users of sitagliptin vs nonusers over a median 2.2 years follow-up. RESULTS: At baseline, the median age was 52 years, 54% were men, and median A1c was 7.5%. There were 8894 new users of sitagliptin and 63 834 nonusers with a total 181 139 person-years of follow-up. There were 741 MOF (79 hip fractures), with 53 fractures (4.8 per 1000 person-years) among new users of sitagliptin vs 688 fractures (4.0 per 1000 person-years) among nonusers (P = .3 for difference). In multivariable analyses, sitagliptin was not associated with fracture (adjusted hazard ratio 1.1, 95% confidence interval 0.8-1.4; P = .7), although insulin (P < .001), sulfonylureas (P < .008), and thiazolidinedione (P = .019) were each independently associated with increased fracture risk. CONCLUSIONS: Even in a young population with type 2 diabetes, osteoporotic fractures were not uncommon. New use of sitagliptin was not associated with fracture, but other commonly used second-line agents for type 2 diabetes were associated with increased risk. These data should be considered when making treatment decisions for those with type 2 diabetes at particularly high risk of fractures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".