Biologic Therapeutics in the Treatment of Psoriasis. Part 1: Review
Bibliographic record
Abstract
BACKGROUND: Psoriasis is a chronic inflammatory skin disease principally mediated by activated T cells, which release proinflammatory cytokines with reactive epidermal changes in the skin, producing the characteristic lesions of psoriasis. New research into possible treatment options has been inspired by increased understanding of the pathophysiology of psoriasis and advances in immunology and molecular biology permitting the development of targeted, highly active biologic agents. OBJECTIVE: The aim of this article is to review the efficacy and safety of five biologic therapeutics in the treatment of moderate to severe psoriasis and to provide practical guidelines for integration of these agents in the management of psoriasis. METHODS: We searched MEDLINE (1966-2005) for articles containing the key words: alefacept, efalizumab, etanercept, infliximab, and adalimumab and searched recent conference abstracts. RESULTS: Emerging immunotherapeutic agents (fusion proteins, recombinant cytokines, fusion toxins, or antibodies) target T cells or cytokines responsible for plaque formation that is characteristic of psoriasis. Alefacept is the first biologic to be approved in both the United States and Canada. More recently, efalizumab and etanercept and infliximab have been approved in the United States and Canada for plaque-type psoriasis. Adalimumab is currently in phase III clinical trials. CONCLUSION: These novel biologics offer an intriguing and effective treatment option for patients with moderate to severe psoriasis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".