Use of Extracorporeal Photopheresis in Scleroderma: A Review
Bibliographic record
Abstract
BACKGROUND: Scleroderma is a heterogeneous group of diseases that can be localized or systemic. Localized scleroderma is a fibrosis of the skin characterized by inflammation and thickening due to excessive collagen deposition, and systemic sclerosis (SSc) is characterized by vasculopathy, immune dysregulation and skin fibrosis. In general, the prognosis of scleroderma highly depends on the degree of visceral involvement and relates to the degree of skin fibrosis. Despite the numerous therapies used for patients with scleroderma, the disease-related morbidity and mortality are high. Studies have explored the effects of extracorporeal photopheresis (ECP) in scleroderma treatment. Originally used in the treatment of cutaneous T-cell lymphoma, ECP is an immunomodulatory procedure in which a patient's white blood cells are treated with 8-methoxypsoralen and exposed to UVA radiation to inhibit cell proliferation and induce immunosuppression. SUMMARY: Multiple lines of evidence suggest that ECP may be a safe and possibly effective therapy for patients with scleroderma, specifically demonstrating improvement in patients with cutaneous manifestations of the disease. However, future studies assessing its role in managing visceral involvement are needed. Our review aims to examine and consolidate the results of clinical studies and propose a possible role for ECP in the management of scleroderma. KEY POINTS: ECP may be an effective and safe procedure for the treatment of SSc.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".