A real‐world study focused on the long‐term efficacy of mycophenolate mofetil as first‐line treatment of autoimmune hepatitis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Front-line therapy with mycophenolate mofetil (MMF) in autoimmune hepatitis (AIH) has shown high on-treatment remission rates. AIM: To study prospectively in a real-world fashion the long-term outcome of a large group of consecutive treatment-naïve AIH patients. METHODS: Between 2000 and 2014, 158 patients were recruited but only 131 were eligible for treatment (109 MMF/prednisolone; 22 prednisolone ± azathioprine). Long-term data on outcome after drug withdrawal were evaluated. Patients stopped treatment after having achieved complete response (normal transaminases and IgG) for at least the last 2 years. RESULTS: At diagnosis, 31.6% of patients had cirrhosis and 72.8% insidious presentation. A total of 102 of 109 (93.6%) responded initially to MMF within 2 (1-18) months. A total of 78 of 109 (71.6%) had complete response on treatment and 61 of 78 (78.2%) maintained remission off prednisolone. MMF-treated patients had increased probability of complete response compared to those receiving azathioprine (P = 0.03). Independent predictors of complete response were lower ALT at 6 months (P = 0.001) and acute presentation (P = 0.03). So far, treatment withdrawal was feasible in 40/109 patients and 30 (75%) are still in remission after 24 (2-129) months. Remission maintenance was associated with longer MMF treatment (P = 0.005), higher baseline ALT (P < 0.02), lower IgG on 6 months (P = 0.004) and histological improvement. CONCLUSIONS: Mycophenolate mofetil proved to be an efficient first-line treatment for AIH, achieving so far the highest rates of remission maintenance off treatment (75%) ever published for at least a median of 2 years, although the remission criteria used were strict. However, the risk of potential bias and overestimation of intervention benefits from MMF cannot be completely excluded as this is a real world and not a randomised controlled trial.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it