Apremilast monotherapy in DMARD-naive psoriatic arthritis patients: results of the randomized, placebo-controlled PALACE 4 trial
Bibliographic record
Abstract
OBJECTIVES: The PALACE 4 trial evaluated apremilast monotherapy in patients with active PsA who were DMARD-naive. METHODS: Eligible patients were randomized (1:1:1) to placebo, apremilast 20 mg twice a day or apremilast 30 mg twice a day. At week 16 or 24, placebo patients were rerandomized to apremilast. Double-blind apremilast treatment continued to week 52, with extension up to 4 years. The primary endpoint was the proportion of patients achieving ⩾20% improvement in ACR response criteria (ACR20) at week 16; secondary endpoints included the mean change in the HAQ Disability Index (HAQ-DI) score at week 16. RESULTS: A total of 527 patients with mean disease duration of 3.4 years and high disease activity were randomized and received treatment. More apremilast patients achieved ACR20 response at week 16 [placebo, 15.9%; 20 mg, 28.0% (P = 0.0062); 30 mg, 30.7% (P = 0.0010)]. The mean HAQ-DI improvements were -0.17 (20 mg; P = 0.0008) and -0.21 (30 mg; P < 0.0001) vs 0.03 (placebo). Both apremilast doses showed significant ACR50 responses vs placebo at week 16 and improvements in secondary efficacy measures (swollen/tender joint counts) and psoriasis assessments, with sustained improvements through week 52. Common adverse events (AEs) over 52 weeks were diarrhoea, nausea, headache and upper respiratory tract infection; most events were mild or moderate. Serious AEs and AEs leading to discontinuation were comparable between groups. Laboratory abnormalities were infrequent and transient. CONCLUSIONS: In DMARD-naive patients, apremilast monotherapy improved PsA signs/symptoms over 52 weeks and was generally well tolerated. TRIAL REGISTRATION: ClinicalTrials.gov (http://clinicaltrials.gov), NCT01307423.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.008 | 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".