A study in a rat initiation-promotion bladder tumour model demonstrated no promoter/progressor potential of dapagliflozin
Bibliographic record
Abstract
Dapagliflozin, a sodium-glucose co-transporter 2 (SGLT2) inhibitor, is indicated to improve glycaemic control in adults of type 2 diabetes. In nonclinical studies, dapagliflozin was neither genotoxic nor carcinogenic. However, in some clinical studies, an increased incidence of bladder cancer was observed in the dapagliflozin group vs. the placebo. Therefore, this study was undertaken to determine if dapagliflozin can act as a promoter in a 2-stage bladder cancer model in rats induced with N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN). Rats given BBN (100 or 400 mg/kg, po) twice weekly for 6 weeks in Phase 1 were assigned in Phase 2 to receive daily dose of vehicle, dapagliflozin (0.5 mg/kg, po) or uracil (positive control, 3% in diet) from weeks 8-34. All bladders were evaluated by histopathology. Verifying the validity of the model, uracil increased the incidence of bladder cancer, while dapagliflozin had no effect on the incidence or invasiveness of transitional cell carcinoma. The exposure of dapagliflozin at 0.5 mg/kg/day in rats was 7 times the clinical exposure at maximal therapeutic dose (10 mg). In conclusion, dapagliflozin does not act as promoter or progressor of bladder cancer in a validated bladder cancer model in rats.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".