New use of rosiglitazone decreased following publication of a meta‐analysis suggesting harm
Bibliographic record
Abstract
AIMS: It is uncertain whether meta-analyses lead to changes in prescribing practices. We studied trends in the prescribing of glucose-lowering therapy before and after the publication of a meta-analysis suggesting harm from rosiglitazone. METHODS: We examined the prescription records of all residents of Ontario, Canada, aged > or = 66 years. For each week between January and December 2007, we identified new users of five categories of glucose-lowering medications: rosiglitazone, pioglitazone, metformin, glibenclamide (glyburide) and insulin. The effect of the meta-analysis was assessed using interventional autoregressive integrated moving-average models. RESULTS: Following the release of the meta-analysis, there was a sudden decline in new users of rosiglitazone (P = 0.01), mirrored by a nearly identical but transient increase in new users of pioglitazone (P < 0.001). There was also a net decline in new users of thiazolidinediones as a class (P < 0.001). The number of new users of other glucose-lowering medications did not change. CONCLUSIONS: A highly-publicized meta-analysis regarding rosiglitazone's potential harms led to an abrupt decline in new users of the drug, as well as a transient surge in new use of pioglitazone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".