Use of thiazolidinediones and the risk of bladder cancer among people with type 2 diabetes: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Patients with type 2 diabetes have a 40% increased risk of bladder cancer. Thiazolidinediones, especially pioglitazone, may increase the risk. We conducted a systematic review and meta-analysis to evaluate the risk of bladder cancer among adults with type 2 diabetes taking thiazolidinediones. METHODS: We searched key biomedical databases (including MEDLINE, Embase and Scopus) and sources of grey literature from inception through March 2012 for published and unpublished studies, without language restrictions. We included randomized controlled trials (RCTs), cohort studies and case-control studies that reported incident bladder cancer among people with type 2 diabetes who ever (v. never) were exposed to pioglitazone (main outcome), rosiglitazone or any thiazolidinedione. RESULTS: Of the 1787 studies identified, we selected 4 RCTs, 5 cohort studies and 1 case-control study. The total number of patients was 2,657,365, of whom 3643 had newly diagnosed bladder cancer, for an overall incidence of 53.1 per 100,000 person-years. The one RCT that reported on pioglitazone use found no significant association with bladder cancer (risk ratio [RR] 2.36, 95% confidence interval [CI] 0.91-6.13). The cohort studies of thiazolidinediones (pooled RR 1.15, 95% CI 1.04-1.26; I(2) = 0%) and of pioglitazone specifically (pooled RR 1.22, 95% CI 1.07-1.39; I(2) = 0%) showed significant associations with bladder cancer. No significant association with bladder cancer was observed in the two RCTs that evaluated rosiglitazone use (pooled RR 0.87, 95% CI 0.34-2.23; I(2) = 0%). INTERPRETATION: The limited evidence available supports the hypothesis that thiazolidinediones, particularly pioglitazone, are associated with an increased risk of bladder cancer among adults with type 2 diabetes.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".