Prognostic Implications of Antibodies to Soluble Liver Antigen in Autoimmune Hepatitis
Bibliographic record
Abstract
Prognostic evaluation is important for the management of patients with autoimmune hepatitis (AIH). Although some autoantibodies have been associated with disease activity and outcomes, the implication of antibodies to soluble liver antigen (anti-SLA) remains controversial. To conduct a meta-analysis of observational studies which addressed differences in clinical characteristics by anti-SLA status in patients with AIH. Three databases PUBMED, EMBASE, and OVID were systemically searched up to January 2015 using the terms "soluble liver antigen" or "liver-pancreas antigen" and "autoimmune hepatitis" with restriction to English-language. Studies were included if at least 50 patients with objective diagnosis of AIH were enrolled, anti-SLA detection was performed for the patients, and prognostic outcomes and/or disease severity were reported. Two investigators independently reviewed retrieved literature and evaluated eligibility. Discrepancy was resolved by discussion and a third investigator. Quality of included studies was evaluated using Newcastle-Ottawa Quality Assessment Scale (NOS). Data were pooled using fixed-effect or random-effect models. Prognostic outcomes included death from hepatic failure or requirement for liver transplantation, and responses to immunosuppressive therapy regarding remission or relapse. Results were combined on the odds ratio (OR) or standardized mean difference (SMD) scales. Eight studies were enrolled in this study, involving a total of 1297 AIH patients among whom 195 with anti-SLA. Pooled serum AST levels tended to be lower in anti-SLA seropositive patients. The presence of anti-SLA conferred 3.1-fold increased risk of hepatic death in AIH patients. The remission rates were comparable between anti-SLA seropositive and seronegative AIH patients, while anti-SLA positivity was associated with nearly 2-fold increased risk of relapse after drug withdrawal. Human leukocyte antigen (HLA) allotype DR3 was positively associated with anti-SLA. Antibodies to SLA may be an indicator of increased risks of hepatic death and treatment relapse for AIH patients. Our findings suggest that the anti-SLA seropositive patients should be maintained indefinitely on individually adjusted medication to improve their prognosis.
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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 | 0.025 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.021 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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 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".