The Efficacy of Mycophenolate Mofetil for the Treatment of Autoimmune Hepatitis: A Meta-Analysis and Systematic Review
Bibliographic record
Abstract
Introduction: In patients with autoimmune hepatitis (AIH), standard treatment is azathioprine and prednisone. We performed a systematic review and meta-analysis to determine the safety and efficacy of mycophenolate mofetil (MMF) in the treatment of AIH. Methods: We systematically searched PubMed/MEDLINE, EMBASE and CENTRAL to identify randomized and non-randomized controlled trials of MMF administered to patients with AIH. Two independent investigators assessed trial eligibility and abstracted data. Results: Our study identified 789 citations, of which 14 studies were reviewed in full. Of these, 4 trials with 279 patients met our eligibility criteria. Comparing treatment with MMF versus control, there was no significant difference in rates of clinical remission (OR 0.37, 95% CI 0.01-14.03, p=0.59, I2=79%), AST improvement (OR 0.04, 95% CI 0.00-1.01, p=0.05, I2 n/a), or bilirubin improvement (OR 0.47, 95% CI 0.03-8.60, p=0.61, I2 n/a). There was a trend towards less treatment failure in patients treated with MMF than in patients in the control group (OR 0.88, 95% CI 0.00-394.24, p=0.97, I2=91%). No deaths were reported in either treatment or control groups. Conclusion: There was not a significant difference in the clinical remission rate or improvement in specifi c laboratory values between patients treated with MMF and placebo/control. Given the scant data identified in this comprehensive systematic review, larger controlled studies are needed to evaluate the use of MMF in the treatment of 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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".