Emerging paradigm shift toward proactive topical treatment of psoriasis: A narrative review
Bibliographic record
Abstract
Abstract Psoriasis (PsO) requires safe and effective long‐term management to reduce the risk of recurrence and decrease the frequency of relapse. Topical PsO therapies are a cornerstone in the management of PsO though safety concerns limit the chronic, continuous use of topical corticosteroids and/or vitamin D3 analogs. Evidence‐based guidelines on optimal treatment targets and maintenance therapy regimens are currently lacking. This review explores the evidence supporting approaches to maintenance topical therapy for PsO including continuous long‐term therapy, chronic intermittent use, step‐down therapy, sequential or pulse therapy regimens, and proactive maintenance therapy. Several unaddressed questions are discussed including how and when to transition from acute to maintenance therapy, strategies for monitoring long‐term treatment, the role of topical maintenance therapy in the context of systemic and biologic therapies, risks of maintenance therapy, prescribing a topical preparation suitable for patients' preferences and skin type, and key concepts for patient education to maximize long‐term outcomes. Overall, emerging evidence supports a paradigm shift toward proactive treatment once skin is completely clear as a strategy to enhance disease control without compromising safety.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".