Outcomes of Isolated Nail Psoriasis Treatment With Roflumilast 0.3% Cream: A Case Series of 7 Patients
Bibliographic record
Abstract
BACKGROUND: Nail psoriasis (NP) is not an uncommon psoriasis variant whose symptoms have a negative impact on patients' quality of life. Treating NP can be a great challenge for the dermatologist, especially when it is presented as isolated subtype or when it is not associated with psoriatic arthritis (PsA). The available treatments, topical or systemic therapies, have limited efficacy and can be associated with adverse effects (AEs). Topical roflumilast is an FDA-approved treatment for skin plaque-psoriasis in patients aged 6 and above, but there is limited evidence for treating NP. We present outcomes of nail psoriasis not associated with PsA treated with roflumilast 0.3% cream in 7 patients. METHODS: A single center, retrospective case series analysis was conducted in a Canadian nail clinic in adult patients with NP refractory to treatment between January 2023 and December 2024. Clinical characteristics (matrix and/or nail bed alterations) were included to calculate the Nail Psoriasis Severity Index (NAPSI) score. Improvement degree was based on NAPSI score reduction. All patients were treated with roflumilast 0.3% cream daily for at least 16 weeks. RESULTS: The case series included 7 patients with NP not associated with PsA. The mean baseline NAPSI score was 19, which decreased to 6.8 after 16 weeks of topical treatment. Roflumilast 0.3% cream was used both as monotherapy and/or in combination with topical steroids or acitretin. Interestingly, all patients reported quality of life improvements, and complete lesion clearance was achieved in almost all patients. CONCLUSIONS: Topical roflumilast showed promising results to treat topically NP. In this case series topical roflumilast was effective, well-tolerated and not associated with AEs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".