Adalimumab for moderate to severe chronic plaque psoriasis: efficacy and safety of retreatment and disease recurrence following withdrawal from therapy
Bibliographic record
Abstract
BACKGROUND: Adalimumab is effective for moderate to severe chronic plaque psoriasis; however, data regarding retreatment following withdrawal and subsequent relapse are limited. OBJECTIVES: To evaluate the efficacy and safety of adalimumab if interrupted and then resumed in patients with moderate to severe psoriasis. METHODS: Patients in a long-term adalimumab open-label extension study (NCT00195676) who achieved a Physician's Global Assessment (PGA) score of 'Mild' (2), 'Minimal' (1) or 'Clear' (0) were withdrawn from adalimumab and monitored for relapse to PGA of 'Moderate' (3) or worse. The subgroup of interest had stable psoriasis control, defined as PGA of 0/1 for ≥12 weeks on every other week (eow) dosing before withdrawal. Relapsing patients were retreated with adalimumab (80 mg at week 0 and 40 mg eow starting at week 1). PGA, Psoriasis Area and Severity Index responses, fatigue, pharmacokinetics and immunogenicity were assessed. RESULTS: In total, 525 patients were withdrawn from adalimumab; the subgroup with stable psoriasis control comprised 285 patients. Of these, 178 relapsed (median=141 days) before treatment reinitiation and 107 did not relapse. Patients without relapse by 40 weeks off therapy reinitiated adalimumab. Rates of PGA 0/1 after 16 weeks of adalimumab retreatment were 89% for patients without relapse and 69% for patients who relapsed. Relapsers experienced significantly less fatigue after retreatment. Nine patients (3%) had serious adverse events (two were infections). No rebound or allergic reactions occurred. CONCLUSIONS: Adalimumab-treated patients who discontinued therapy and subsequently relapsed had a good likelihood of regaining clinical efficacy following adalimumab reinitiation.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| 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".