Bibliographic record
Abstract
BACKGROUND: The period of time during which a patient is exposed to a drug does not necessarily correspond to the period during which the drug produces the adverse effect under consideration. We propose the term Pharmacologically pertinent period of effect (PPPE) to address this time window. We explored the PPPE in light of the rofecoxib saga. METHODS: We identified the observational database studies of rofecoxib at doses 25 and 50 mg daily and thromboembolic events. We also obtained the Kaplan-Meier curves of Vioxx Gastrointestinal Outcomes Research trial (VIGOR) and Adenomatous Polyp Prevention on Vioxx (APPROVE) trials. RESULTS: We found seven observational studies with nine analyses. All the studies only looked at current exposure. At the dose of 25 mg, only three of nine analyses were barely statistically significant. At the dose of 50 mg, the risk ratios were much higher. The visual inspection of the Kaplan-Meier curves shows that in the APPROVE trial (25 mg), the placebo and rofecoxib curves start separating to become statistically significantly different only after 36 months. In contrast the VIGOR (50 mg), curves start separating very early and the divergence increases after 8 months. DISCUSSION: The 50 mg observational studies, looking at current exposure, correctively identified the almost immediate increase in risk evident in the VIGOR Kaplan-Meier curves. The absence of an immediate increase in risk shown by the APPROVE trial was also correctively identified by most observational 25 mg studies. To our knowledge no observational study was done on the long-term cardiac toxicity of the 25-mg dose. It would thus appear that the two doses of rofecoxib have different PPPEs.
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".