Management of Guttate Psoriasis: A Systematic Review
Bibliographic record
Abstract
Guttate psoriasis (GP) is a variant of psoriasis characterized by scattered "drop-like" papules and plaques, accounting for up to a quarter of psoriasis cases. Although GP can clear within 3 to 4 months, up to 39% of cases may progress to chronic plaque psoriasis. Currently, there is a paucity of literature investigating the efficacy of different treatment modalities. This systematic review aims to synthesize all available data on GP treatment efficacy. A literature search was conducted using Medline, Embase, Web of Science, and CINAHL with no date limits. A total of 75 studies satisfied eligibility criteria and were analyzed. Most studies were case reports, series, or retrospective studies. Only 5 randomized controlled trials (RCTs) were identified. For topical treatments, corticosteroids and calcipotriol creams had the most evidence for efficacy. Four categories of systemic therapies were identified: traditional immunosuppressants, antibiotics, retinoids, and biologics. Evidence regarding antibiotic therapy suggests minimal connection between underlying infection resolution and GP lesion remission. Phototherapy had the most robust evidence, with narrowband ultraviolet B (UVB) being the most effective. Our findings are limited by high heterogeneity in study design and high risk of bias. Based on our review, we propose the following treatment algorithm. As first-line therapy, we recommend topical corticosteroids and calcipotriol cream, in combination with phototherapy. As supportive therapy, we recommend antibiotics if applicable. For second-line therapy, we recommend methotrexate or cyclosporine. For severe and refractory GP, biologics can be used as third-line treatment. RCTs are needed to provide higher quality evidence to create standardized treatment recommendations.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".