Pioglitazone use in Australia and the United Kingdom following drug safety advisories on bladder cancer risk: An interrupted time series study
Bibliographic record
Abstract
PURPOSE: National regulators in Australia and the United Kingdom issued safety advisories on the association between pioglitazone use and bladder cancer in July 2011. The Australian advisory noted that males were at higher risk of bladder cancer than females, while the UK advisory highlighted a new recommendation, suggest careful consideration in the elderly due to increasing risk with age. This study examined whether these differences in the advisories had different age- and sex-based impacts in each country. METHODS: Interrupted time series analysis was used to compare pioglitazone use (prescriptions/100000 population) in Australia and the United Kingdom for the 24 months before and 11 months after the July 2011 safety advisories (study period July 2009-June 2012). Separate models were used to compare use by sex and age group (≥65 years vs. <65 years) in each country. RESULTS: Pioglitazone use fell in Australia (17%) and the United Kingdom (24%) following the safety advisories. Use of pioglitazone fell more for males (18%) than females (16%) in Australia, and more for females (25%) than males (23%) in the United Kingdom; however, neither difference was statistically significant (Australia p = 0.445, United Kingdom p = 0.462). Pioglitazone use fell to a similar extent among older people than younger people in the United Kingdom (23% vs. 26%, p = 0.354), and did not differ between age groups in Australia (both 18%, p = 0.772). CONCLUSIONS: The results indicate that differences in the Australian and UK safety advisories resulted in substantial reductions in pioglitazone use at the population level in both countries, however, differences by sub-groups were not observed.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".