Transplant immunosuppressive agents in non‐transplant chronic autoimmune hepatitis: the Canadian association for the study of liver (CASL) experience with mycophenolate mofetil and tacrolimus
Bibliographic record
Abstract
BACKGROUND: Conventional treatment of autoimmune hepatitis consists of either prednisone alone or in combination with azathioprine. Ten to 20% of patients do not respond to or are intolerant of this treatment. Novel drug treatments include immunosuppressive drugs such as tacrolimus (TAC), mycophenolate mofetil (MMF), methotrexate and cyclosporine. We describe a multi-centre Canadian experience with MMF and TAC. OBJECTIVE: To study a multi-centre patient population who had failed conventional therapy and were treated with non-conventional medical therapy for autoimmune hepatitis and document response. METHODS: Members of the Canadian Association for the Study of Liver (CASL) obtained MMF from Hoffmann-La Roche Ltd, as part of a compassionate release program, were contacted for standardized data on patients with AIH who received MMF or TAC. Response definitions based on aminotransferase changes were: Complete response (CR)-sustained normalization, partial response (PR)-improvement by greater than 50%, non-response (NR)-less than 50% improvement and relapse (RP)-initial CR or PR followed by an increase in aminotransferases. RESULTS: A total of 16 patients were identified: six in Ontario, one in Quebec, five in Alberta and four in British Columbia. Three were treated with TAC, eleven with MMF and two with combination MMF and TAC. CR was observed in 50%, PR in 12.5%, RP in 25% and NR occurred in 12.5%. The CR for MMF without TAC was approximately 64%. CONCLUSIONS: MMF is effective and well tolerated by patients with autoimmune hepatitis who do not respond to, or are intolerant of, conventional immunosuppressive agents.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".