Use of Biologics in Pityriasis Rubra Pilaris Refractory to First-Line Systemic Therapy: A Systematic Review
Bibliographic record
Abstract
Pityriasis rubra pilaris (PRP) is an uncommon, inflammatory, papulosquamous skin disease. Treatment of PRP is challenging as the disease is often refractory to conventional therapies, such as retinoids and methotrexate. There has been an increasing number of studies reporting the successful use of biologic therapy in patients with PRP; however, the data on the efficacy and safety are limited. Our objective was to evaluate the existing evidence for utilizing biologics, whether alone or in combination with established systemic therapies, in patients with treatment-resistant PRP. We systematically reviewed evidence within Medline and Pubmed databases between January 1, 2000, to March 31, 2019. Articles consisted of patients diagnosed with PRP who have failed to respond sufficiently to first-line systemic therapies, or who had comorbidities that precluded their use. In total, 363 unique articles were identified, 56 of which were considered relevant to the clinical question. Of the 56 articles highlighted, 35 met the inclusion criteria and were limited to case series and case studies. Therapy with biologics was found to be successful for both monotherapy (81.1% [27/33]) and when used in combination with existing systemic therapies (87.5% [14/16]). The existing evidence suggests that biologics may be regarded as a tool for PRP treatment alone or in combination therapy with existing treatments, although large-scale randomized clinical trials are necessary to better assess their efficacy and 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".