Mycophenolate mofetil for patients with autoimmune hepatitis and overlap syndromes: authors’ reply
Bibliographic record
Abstract
Sirs, Garcia-Buey and Moreno-Otero nicely summarise the literature on mycophenolate mofetil (MM) in autoimmune hepatitis (AIH) and overlap syndromes.1 The Dutch Autoimmune Hepatitis Group (DAHG) shows that second-line MM induces remission in 67% of patients with AIH and intolerance to azathioprine (AZA).2 In AIH and AZA nonresponse, remission was achieved with MMF in only 13%, and all deaths, liver transplantations and decompensations of cirrhosis occurred in this group. Therefore, in AIH and AZA-nonresponse other options, including liver transplantation, seem more appropriate. This is consistent with the findings of Hennes et al.3 For all patients with overlap syndromes, MM appears a valuable treatment option. In the DAHG cohort, MM induced remission in 63% and 57%, and response in 15% and 14% after AZA intolerance and nonresponse respectively.2 Recently, adding MM and budesonide appeared beneficial in primary biliary cirrhosis (PBC) with insufficient response to ursodeoxycholic acid.4 Further investigations of MM in PBC and overlap seem warranted. As first-line therapy for AIH, one randomised controlled study indicates that budesonide with AZA induces more remission with less side-effects than prednisolone with AZA.5 However, despite the one prospective cohort with MM as first-line therapy in AIH,6 and the limitations of earlier studies, most evidence for first-line therapy in AIH still is with AZA and prednisolone.7 We therefore still consider prednisolone with AZA the first-line treatment in AIH and overlap syndromes until further randomised studies prove otherwise. In case of steroid side-effects, in the absence of cirrhosis, budesonide could be considered, although a prospective maintenance study against prednisolone is still lacking. As second-line therapy in case of AZA-intolerance in AIH, or for all overlap syndrome patients, MM with prednisolone appears useful, but not for AIH with AZA nonresponse. In contrast to AZA, MM is contraindicated in pregnancy. Declaration of personal and funding interests: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".