Apremilast, an oral phosphodiesterase 4 inhibitor, improves patient‐reported outcomes in the treatment of moderate to severe psoriasis: results of two phase <scp>III</scp> randomized, controlled trials
Bibliographic record
Abstract
BACKGROUND: Apremilast, an oral phosphodiesterase 4 inhibitor, has an acceptable safety profile and is effective for treatment of plaque psoriasis and psoriatic arthritis. OBJECTIVES: To evaluate the impact of apremilast on health-related quality of life (HRQOL), general functioning and mental health using patient-reported outcome (PRO) assessments among patients with moderate to severe plaque psoriasis in the ESTEEM 1 and 2 trials. METHODS: A total of 1255 patients were randomized (2 : 1) to apremilast 30 mg BID or placebo for 16 weeks; all received apremilast through Week 32. PRO assessments included the Dermatology Life Quality Index (DLQI), 36-Item Short-Form Health Survey version 2 mental/physical component summary scores (SF-36v2 MCS/PCS), Patient Health Questionnaire-8 (PHQ-8), EuroQol-5D (EQ-5D) and Work Limitations Questionnaire-25 (WLQ-25). Post hoc analyses examined relationships between Psoriasis Area and Severity Index (PASI) scores and PHQ-8 in the apremilast-treated population at Week 16. RESULTS: Treatment with apremilast improved all HRQOL PROs at Week 16 (vs. placebo), except the SF-36v2 PCS, and improvements were sustained through Week 32. Mean DLQI and SF-36v2 MCS improvements exceeded minimal clinically important differences. Changes at Week 16 in PHQ-8 and PASI were weakly correlated, and only 35.8% of patients who achieved a ≥75% reduction from baseline in PASI score (PASI-75) with apremilast treatment also achieved PHQ-8 scores of 0-4. CONCLUSIONS: Apremilast led to improvements in HRQOL PROs vs. placebo in patients with moderate to severe plaque 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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".