In Type 1 Autoimmune Hepatitis, Is Cirrhosis at Presentation or Follow-up Associated With a Poorer Outcome? *
Bibliographic record
Abstract
Verma and Redeker have brought up some valid points for consideration regarding our results. They question whether cirrhosis at presentation as opposed to the development of cirrhosis during follow-up is a greater risk factor for a poor outcome, and they raise the concern that patients with "burned-out" cirrhosis may not actually have AIH. We found that cirrhosis at baseline portended a very poor prognosis with a 78.7% 5-year and 67.2% 10-year survival compared to 96.7% and 94%, respectively, in patients without cirrhosis. Of the 73 patients without cirrhosis at presentation, 11 (15.1%) developed cirrhosis during follow-up, 2 of whom reached an endpoint. Other series have found higher rates of progression to cirrhosis.1, 2 However, it is noteworthy that the diagnosis of cirrhosis at baseline was based on liver biopsy findings, whereas during follow-up, cirrhosis was generally diagnosed from laboratory, clinical, or radiological evidence. Clearly the former is more robust. It was not our practice to routinely repeat liver biopsies on patients and consequently we may have underestimated the rate of progression to cirrhosis. Verma et al. found that patients that progressed to cirrhosis had a poorer outcome than those with cirrhosis at presentation.1 We found the opposite. Although patients who developed cirrhosis over time had a worse outcome than those without cirrhosis (P = .0037), cirrhosis at baseline was associated with an even poorer outcome (P = .0001) (Fig. 1). There was no significant difference between those with cirrhosis at baseline and those with progression to cirrhosis. Effect on survival of cirrhosis at baseline cirrhosis during follow-up. Verma et al. point out that the presence of burned-out cirrhosis makes a definitive diagnosis of AIH difficult. Although it is impossible to be certain that all patients with burned-out cirrhosis did indeed have AIH, this is unlikely to have affected the results. There is no pathognomonic test for AIH and therefore the International AIH scoring system has been advocated for use in clinical studies. All the patients with burned-out disease had an AIH score of at least 14 (range, 14-22), giving them at the minimum, a probable diagnosis of AIH. One patient was anti-HCV positive but HCV RNA negative on repeated testing and all others tested negative for all HCV markers. None of the patients with burned-out disease was AMA positive or had type II AIH. One patient was diabetic but no others had features suggestive of nonalcoholic fatty liver disease. However, even if all patients with burned-out cirrhosis did not actually have AIH, cirrhosis at baseline still predicted a poor outcome. When the survival was reanalyzed excluding all patients with burned-out disease, patients with cirrhosis at baseline still had a significantly worse outcome than those without cirrhosis (P = .0028) (Fig. 2). Effect of cirrhosis on survival with and without "burned out" patients. There is no readily apparent explanation for the worse outcome associated with cirrhosis in our cohort than in other studies.1, 2 The issues raised by Verma et al. are certainly important, but as our reanalysis of the data demonstrates, in our cohort, cirrhosis at presentation in patients with AIH portends a poor prognosis. Perhaps future studies will clarify our discrepant findings. Jordan Feld*, E. Jenny Heathcote*, * University of Toronto, Toronto, Canada
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".