Rituximab for the Treatment of Patients with Autoimmune Hepatitis Who are Refractory or Intolerant to Standard Therapy
Bibliographic record
Abstract
BACKGROUND: Although most patients with autoimmune hepatitis (AIH) respond to treatment with prednisone and⁄or azathioprine, some patients are intolerant or refractory to standard therapy. Rituximab is an anti-CD20 monoclonal antibody that depletes B cells and has demonstrated efficacy in other autoimmune conditions. AIMS: To evaluate the safety and efficacy of rituximab in patients with refractory AIH in an open-label, single-centre pilot study. METHODS: Six patients with definite, biopsy-proven AIH who failed prednisone and azathioprine treatment received two infusions of rituximab 1000 mg two weeks apart and were followed for 72 weeks. RESULTS: Rituximab was well tolerated with no serious adverse events. By week 24, mean (± SD) aspartate aminotransferase (AST) levels had significantly improved (90.0±23.3 U⁄L versus 31.3±4.2 U⁄L; P=0.03) and mean immunoglobulin G levels had fallen (16.4±2.0 g⁄L versus 11.5±1.1 g⁄L; P=0.056). The prednisone dose was weaned in three of four subjects, with one subject flaring after steroid withdrawal. Inflammation grade improved in all four subjects who underwent repeat liver biopsy at week 48. Regulatory T cell levels examined by FoxP3 immunohistochemistry paralleled inflammatory activity and did not increase on follow-up biopsies. There was no significant change in serum chemokine or cytokine levels from baseline to week 24 (n=5), although interferon-gamma-induced protein 10 levels improved in three of five subjects. CONCLUSIONS: Rituximab was safe, well tolerated and resulted in biochemical improvement in subjects with refractory AIH. These results support further investigation of rituximab as a treatment for AIH.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".