Topical treatment of psoriasis: questionnaire results on topical therapy accessibility and influence of body surface area on usage
Bibliographic record
Abstract
BACKGROUND: Topical treatment of mild to moderate psoriasis is first-line treatment and exhibits varying degrees of success across patient groups. Key factors influencing treatment success are physician topical treatment choice (high efficacy, low adverse events) and strict patient adherence. Currently, no formalized, international consensus guidelines exist to direct optimal topical treatment, although many countries have national guidelines. OBJECTIVE: To describe and analyse cross-regional variations in the use and access of psoriasis topical therapies. METHODS: The study was conducted as an observational cross-sectional study. A survey was distributed to dermatologists from the International Psoriasis Council (IPC) to assess topical therapy accessibility in 26 countries and to understand how body surface area (BSA) categories guide clinical decisions on topical use. RESULTS: Variation in the availability of tars, topical retinoids, dithranol and balneotherapy was reported. The vast majority of respondents (100% and 88.4%) used topical therapy as first-line monotherapy in situations with BSA < 3% and BSA between 3% and 10%, respectively. However, with disease severity increasing to BSA > 10%, the number of respondents who prescribe topical therapy decreased considerably. In addition, combination therapy of a topical drug and a systemic drug was frequently reported when BSA measured >10%. CONCLUSION: This physician survey provides new evidence on topical access and the influence of disease severity on topical usage in an effort to improve treatment strategies on a global level.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".