Treatment of palmoplantar psoriasis with infliximab: a randomized, double‐blind placebo‐controlled study
Bibliographic record
Abstract
BACKGROUND: Palmoplantar psoriasis is a difficult to treat variant of plaque psoriasis. OBJECTIVE: To study the safety and efficacy of infliximab in non-pustular palmoplantar psoriasis. METHODS: Patients with non-pustular palmoplantar psoriasis affecting at least 10% of their palms and soles and with a modified palmoplantar psoriasis area and severity index (m-PPPASI) of at least eight were recruited. Patients were randomized (1:1) to receive infliximab 5 mg/kg or placebo at weeks 0, 2 and 6. Patients initially randomized to placebo received infliximab at weeks 14, 16 and 20 whereas patients randomized to infliximab received additional infliximab infusions every 8 weeks until week 22. RESULTS: Twenty four (24) patients were randomized in this study. At week 14, 33.3% and 66.7% of patients treated with infliximab achieved m-PPPASI 75 and m-PPPASI 50 respectively compared to 8.3% for both m-PPPASI 75 (P = 0.317) and m-PPPASI 50 (P = 0.009) for patients randomized to placebo. A reduction of 50.3% in the mean surface area of palms and soles affected with psoriasis was seen at week 14 in patients randomized to infliximab as compared to an increase of 14.9% in patients randomized to placebo (P = 0.009). CONCLUSIONS: This pilot study did not reach its primary endpoint of m-PPPASI 75 at week 14. However, infliximab was observed to be more efficacious than placebo in improving PPSA and with respect to the percentage of patients reaching m-PPPASI 50 at week 14. Larger and longer term studies are needed for severe patients to better assess the efficacy of infliximab in palmoplantar psoriasis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".