Mycophenolate Mofetil (CellCept�) for Psoriasis: A Two-Center, Prospective, Open-Label Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Mycophenolate mofetil (MMF) is an immune suppressant that selectively inhibits activated lymphocytes. Its usefulness in treating psoriasis has not been systematically investigated. OBJECTIVE: To evaluate efficacy and safety of MMF as a monotherapy for psoriasis. METHODS: This is a two-center, prospective, open-label clinical trial. RESULTS: Twenty-three patients with moderate to severe psoriasis [mean psoriasis area and severity index (PASI) of 21.7] were treated with MMF 2-3 g/day for 12 weeks. Eighteen patients completed the study. The PASI was reduced by 24% (p < 0.001) at 6 weeks, and by 47% (p < 0.001) at 12 weeks. At the end of the treatment phase, 77% of the patients had significant reduction of PASI while 22% did not respond. The treatment was well tolerated. Five patients experienced mild nausea. One patient each had periorbital edema and pruritus. One patient had transient leukopenia. CONCLUSION: In this noncontrolled trial, the majority of patients with moderate to severe psoriasis responded to mycophenolate mofetil monotherapy with few adverse events. A randomized, controlled trial should be considered to confirm the usefulness of MMF as a monotherapy for psoriasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".