Evaluating Dosage Optimality for Tofacitinib, an Oral Janus Kinase Inhibitor, in Plaque Psoriasis, and the Influence of Body Weight
Bibliographic record
Abstract
Tofacitinib is an oral Janus kinase inhibitor. An integrated analysis was conducted to evaluate dosage optimality for tofacitinib in patients with moderate-to-severe plaque psoriasis and the impact of body weight on optimality in this patient population. Data were pooled from one phase IIb trial (2, 5, and 15 mg twice daily (b.i.d.)) and four phase III trials (5 and 10 mg b.i.d.). A longitudinal exposure-response model for Psoriasis Area and Severity Index (PASI) improvement (percent change from baseline) was established. Body weight influenced potency; heavier subjects require higher doses to achieve comparable benefit to lighter subjects. Disease severity, sex, and prior biologic usage were also predictive of response. The 10 and 5 mg doses were predicted to achieve 81% and 65%, respectively, of the maximum effect based on a 75% improvement in PASI. The greater efficacy of 10 mg over 5 mg was clinically meaningful.
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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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".