A Two-Compound Product Containing Calcipotriol and Betamethasone Dipropionate Provides Rapid, Effective Treatment of Psoriasis vulgaris regardless of Baseline Disease Severity
Bibliographic record
Abstract
BACKGROUND: A two-compound product containing calcipotriol and betamethasone dipropionate (Daivobet/Dovobet) has been evaluated in a large clinical trial programme, providing a wealth of data on the treatment of psoriasis vulgaris. OBJECTIVE: To determine the effectiveness of the two-compound product in patients with mild, moderate and severe psoriasis vulgaris. METHODS: Data from over 1,534 patients with psoriasis vulgaris who received the two-compound product once daily for at least 4 weeks in four randomised, double-blind studies were pooled. A meta-analysis of the pooled data is presented. Severity of psoriasis at baseline was determined by investigator assessment and Psoriasis Area and Severity Index (PASI) score. RESULTS: For patients with severe disease defined by PASI score (PASI baseline > or = 17), the mean reduction in PASI after up to 4 weeks of treatment was 71.6% compared with 68.9 and 67.2% for those with moderate (PASI baseline 5.1-16.0) and mild disease (PASI baseline < or = 5). Corresponding reductions for investigator-assessed severity were 72.6, 69.1 and 68.7%, respectively. CONCLUSION: Although the meta-analysis of the data from these four studies was performed post hoc, we may conclude that the two-compound product provided highly effective treatment of psoriasis, regardless of the category of baseline disease severity.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".