Association of diabetes mellitus and metformin use with oncological outcomes of patients with non‐muscle‐invasive bladder cancer
Bibliographic record
Abstract
OBJECTIVE: To assess the association between diabetes mellitus (DM) and metformin use with prognosis and outcomes of non-muscle-invasive bladder cancer (NMIBC) PATIENTS AND METHODS: We retrospectively evaluated 1117 patients with NMIBC treated at four institutions between 1996 and 2007. Cox regression models were used to analyse the association of DM and metformin use with disease recurrence, disease progression, cancer-specific mortality and any-cause mortality. RESULTS: Of the 1117 patients, 125 (11.1%) had DM and 43 (3.8%) used metformin. Within a median (interquartile range) follow-up of 64 (22-106) months, 469 (42.0%) patients experienced disease recurrence, 103 (9.2%) experienced disease progression, 50 (4.5%) died from bladder cancer and 249 (22.3%) died from other causes. In multivariable Cox regression analyses, patients with DM who did not take metformin had a greater risk of disease recurrence (hazard ratio [HR]: 1.45, 95% confidence interval [CI] 1.09-1.94, P = 0.01) and progression (HR: 2.38, 95% CI 1.40-4.06, P = 0.001) but not any-cause mortality than patients without DM. DM with metformin use was independently associated with a lower risk of disease recurrence (HR: 0.50, 95% CI 0.27-0.94, P = 0.03). CONCLUSION: Patients with DM and NMIBC who do not take metformin seem to be at an increased risk of disease recurrence and progression; metformin use seems to exert a protective effect with regard to disease recurrence. The mechanisms behind the impact of DM on patients with NMIBC and the potential protective effect of metformin need further elucidation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".