Effect of Rosiglitazone, Metformin, and Glyburide on Bone Biomarkers in Patients with Type 2 Diabetes
Bibliographic record
Abstract
CONTEXT: An increase in bone fractures has been observed in women taking thiazolidinediones. OBJECTIVE: The objective of the study was to examine whether changes in circulating bone biomarkers provide insight into the underlying mechanisms responsible for the increase in bone fractures in female participants randomized to rosiglitazone in A Diabetes Outcome Progression Trial (ADOPT). RESEARCH DESIGN AND METHODS: Paired stored baseline and 12-month serum samples were available from 1605 participants (689 women, 916 men) in ADOPT, a long-term clinical trial comparing the effects of rosiglitazone, glyburide, and metformin on glycemic control in patients with type 2 diabetes. RESULTS: This subset was well matched to the total ADOPT study population. In women a marker of osteoclast activity, C-terminal telopeptide (for type 1 collagen), increased by 6.1% with rosiglitazone compared with reductions of 1.3% (P = 0.03 vs. rosiglitazone) and 3.3% (P = 0.002 vs. rosiglitazone) with metformin and glyburide, respectively. In men, C-terminal telopeptide was unchanged on rosiglitazone (-1.0%) and fell on metformin (-12.7%; P < 0.001) and glyburide (-4.3%, P = NS). Markers of osteoblast activity, procollagen type 1 N-propeptide (P1NP) and bone alkaline phosphatase, were reduced for women and men in almost all treatment groups, with the greatest changes in the metformin group (P1NP in females, -14.4%; P1NP in males, -19.3%), intermediate for rosiglitazone (P1NP in females, -4.4%; P1NP in males, -14.4%), and smallest for glyburide (P1NP in males, +0.2%; bone alkaline phosphatase in females, -11.6%). CONCLUSIONS: Commonly measured bone biomarkers suggest that changes in bone resorption may be partly responsible for the increased risk of fracture in women taking thiazolidinediones.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".