A study of oral metformin for the intravesical treatment of non‐muscle‐invasive bladder cancer
Bibliographic record
Abstract
OBJECTIVES: To evaluate the effect of metformin on non-muscle-invasive bladder cancer (NMIBC) marker lesions. PATIENTS AND METHODS: A phase II, open-label, multicentre, marker lesion trial using oral metformin in patients with primary or recurrent, multiple, low-grade Ta-T1 NMIBC was conducted. After transurethral resection for histological confirmation, leaving one tumour as a marker lesion, 11 patients were treated with oral metformin up to 3000 mg per day for 3 months. Reported outcomes included response of the marker lesion, safety of metformin, quality of life and pharmacological and immunohistochemical examinations of the mechanism of action of metformin. RESULTS: One complete response and one partial response were observed. In the other nine patients, the marker lesion remained, while five of these patients also developed new Ta low-grade lesions. Diarrhoea grade ≤ 2 was the most common adverse event (AE), observed in nine out of 11 patients. No serious AEs related to study treatment occurred. Metformin concentrations in the urine were significantly higher than metformin levels in the blood. Immunohistochemical analysis before and after treatment showed no difference in expression of markers associated with the mechanism of metformin. CONCLUSION: We did not find conclusive evidence for the hypothesis of an antitumour effect of metformin in bladder cancer.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".