Effect of tofacitinib, a Janus kinase inhibitor, on haematological parameters during 12 weeks of psoriasis treatment
Bibliographic record
Abstract
BACKGROUND: The Janus kinase (JAK) inhibitor, tofacitinib, has shown efficacy for the treatment of psoriasis in a phase IIb trial (A3921047; NCT00678210). OBJECTIVES: To report haematology data from the phase IIb trial, given the importance of JAK-dependent signalling in haematopoiesis. METHODS: Patients with moderate-to-severe chronic plaque psoriasis were randomized to receive tofacitinib 2, 5 or 15 mg, or placebo, twice daily over 12 weeks. Blood samples were collected at screening, baseline, weeks 2, 4, 8 and 12 during treatment, and weeks 14 and 16 during off-treatment follow-up. RESULTS: Baseline haematology was similar across patients receiving tofacitinib 2 mg (n = 49), 5 mg (n = 49) or 15 mg (n = 49), or placebo (n = 50). Tofacitinib conferred dose-dependent decreases in haemoglobin, haematocrit and red blood cell counts, while reticulocyte counts initially declined, before recovering by week 8, and exceeding baseline levels after treatment cessation. With regard to white blood cells, tofacitinib had no clear dose-dependent effects on basophils or monocytes, but appeared to be associated with transient or reversible dose-dependent decreases in neutrophil and eosinophil counts and transient increases in lymphocyte counts, which were primarily attributable to increases in B-cell counts. Natural killer cell counts declined with tofacitinib. CONCLUSIONS: Tofacitinib conferred tolerable, dose-dependent changes in haematological parameters during short-term administration in patients with psoriasis. The effects did not appear to be progressive, and were often transient or reversible.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".