Long‐term optimization of outcomes with flexible adalimumab dosing in patients with moderate to severe plaque psoriasis
Bibliographic record
Abstract
BACKGROUND: The recently updated dosing recommendation for adalimumab for moderate to severe plaque psoriasis states that patients with inadequate response to adalimumab every other week (EOW) after 16 weeks may benefit from an increase in dosing frequency to 40 mg every week (EW). OBJECTIVE: To determine the long-term efficacy of adalimumab in patients with psoriasis with flexibility to escalate and de-escalate between EOW and EW dosing. METHODS: Data from an open-label study in patients with psoriasis who had received adalimumab in phase 2/3 studies and their extensions were included. Patients initially received 40 mg adalimumab EOW for 24 weeks. From weeks 24-252, patients whose Psoriasis Area and Severity Index response was <50% (PASI 50) could have their dose-escalated to 40 mg EW and were re-evaluated at 6 and 12 weeks and then every 12 weeks thereafter. Patients who had their dose-escalated and achieved a PASI 75 response were de-escalated to EOW and could re-escalate to EW if response fell below PASI 50 again; no further de-escalation was allowed. Changes in PASI scores were reported at the last visit before dose escalation or de-escalation. RESULTS: By week 24, 64.1% of patients in the overall population (n = 1256) achieved ≥PASI 75 response, 40.3% ≥PASI 90 response and 21.7% PASI 100 response. Patients who had a <PASI 50 during weeks 24-252 (349/1256, 27.8%) had their dose-escalated to EW; 182 (52.1%) remained on EW dosing and 167 (47.9%) achieved a PASI 75 response and were de-escalated to EOW; 83 patients were later re-escalated to EW dosing owing to a
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".