Clinical and immunological outcomes of high- and low-dose rituximab treatments in patients with pemphigus: a randomized, comparative, observer-blinded study
Bibliographic record
Abstract
BACKGROUND: Rituximab is a promising therapy in pemphigus. However, there is no consensus on optimum dose. OBJECTIVES: To compare the efficacy, in terms of clinical and immunological outcomes in patients with pemphigus, of a high (2 × 1000 mg) vs. a low dose (2 × 500 mg) of rituximab. METHODS: This was a randomized, observer-blinded trial wherein 22 patients with pemphigus were randomized into two treatment groups. Patients received either two doses (day 0 and day 15) of 1000 mg rituximab or 500 mg rituximab, and were followed up for 48 weeks. Clinical activity was assessed by a blinded investigator. Indices of enzyme-linked immunosorbent assays (ELISAs) for desmoglein (Dsg)1 and Dsg3, and CD19 cell count were examined at regular intervals. RESULTS: There was no statistically significant difference in early and late clinical end points, and total cumulative dose of corticosteroids between the two groups. At week 40, the fall in Ikeda severity score was significantly more in the 2 × 1000 mg group than in 2 × 500 mg group (P = 0·049). Patients in the 2 × 500 mg group received a significantly higher cumulative dose of azathioprine (P = 0·018). The ELISA indices of Dsg1 and Dsg3 showed a statistically significant decline in the 2 × 1000 mg group only. B cell repopulation occurred earlier in the 2 × 500 mg group by 8 weeks. CONCLUSIONS: A few clinical and immunological study parameters have suggested improved outcomes in patients receiving high-dose (2 × 1000 mg) rituximab.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".