The Use of Alefacept in the Treatment of Psoriasis
Bibliographic record
Abstract
Psoriasis is a chronic, incurable disease with associated morbidity and a profound negative impact on the quality of life of affected patients. Current systemic therapies for moderate to severe psoriasis are effective but have potential for side effects, and may require chronic, continual use, as most are suppressive in nature. For example, cyclosporine is associated with hypertension, with functional and structural damage to the kidneys. Methotrexate can result in hepatotoxicity with psoriasis and requires liver biopsy for monitoring. Long-term use of psoralen plus ultraviolet A (PUVA) is associated with higher risk of nonmelanoma and possibly melanoma skin cancer. Given the chronic nature of psoriasis and the limitation of existing therapies, there is an unmet need for therapies with fewer side effects and durable remissions. 1,2 There has been considerable progress in understanding the pathophysiology of psoriasis and this has resulted in the development of targeted biologic therapies. Biologic agents are emerging that target pathogenic T-cells directly (i.e., reduction in pathogenic T-cells, inhibition of T-cell activation, prevention of T-cell trafficking) or target pathogenic cytokines [e.g., tumor necrosis factor (TNF)-a], resulting in favorable efficacy and improved safety in comparison with the currently available systemic therapies. 2
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".