A194 CAN NOVEL SEROLOGICAL MARKERS BE USED TO BETTER DEFINE PRIMARY BILIARY CHOLANGITIS (PBC)-AUTOIMMUNE HEPATITIS (AIH) OVERLAP SYNDROME
Bibliographic record
Abstract
It is estimated that up to 18% of patients with Primary Biliary Cholangitis (PBC) can be classified as having overlap features with Autoimmune Hepatitis (AIH). Patients with PBC-AIH overlap syndrome (OS) have been reported to exhibit suboptimal responses to Ursodeoxycholic acid therapy, and are more likely to progress to cirrhosis and its’ complications. Serological markers, including anti-double stranded DNA (anti-dsDNA) and anti-P53, have been suggested to be robust markers for identifying patients with PBC-AIH OS. The identification of serological markers that can be confidently used to identify patients with PBC-AIH OS would be useful for the clinical management of PBC-AIH OS. In our well defined PBC patient cohorts, various serological markers were evaluated for their potential utility for identifying PBC-AIH OS patients. Blood samples from 214 patients from University of Calgary Liver Unit and University of Alberta biobanks were analyzed by Mitogen Diagnostic Laboratory (Calgary, AB Canada) for various classical and novel autoantibodies. Anti-dsDNA was measured by either the Crithidia luciliae immunofluorescence (CLIFT) assay (1:20 dilution) or a chemiluminescent immunoassay (CIA; Inova Diagnostics, SanDiego). Anti-P53, anti-Ro52/TRIM21, anti-YB 1, anti-MPP1, anti-GW182, anti-Ge-1, and anti-Ago 2 were measured by either an Addressable Laser Bead Immunoassay (ALBIA) or Line Immunoassay (LIA). Frequency of autoantibodies were compared between study groups using non-parametric statistical methods. The performance of patient serum biochemistry and autoantibody profiles to predict OS was determined using multivariate analysis. PBC-AIH OS was diagnosed according to the Paris criteria (Chazouilleres et al) and PBC was diagnosed as per European Association for the Study of the Liver guidelines. Of the 214 patients assessed, 16 (7.5%) had a diagnosis of OS. Compared to PBC patients, OS patients had similar age (median: 59 vs. 63, P=0.21) and female predominance (94% vs. 89%, P=1.00). Anti-dsDNA measured by CLIFT (37.5% in OS vs. 9.1% in PBC, P=<0.01), elevated serum ALT (62 IU/L in OS vs. 35 IU/L in PBC, P<0.01), and an elevated serum IgG (17.6 g/L in OS vs. 12.1 g/L in PBC, P<0.01) were associated with OS. In a multivariate model, Anti-dsDNA-by CLIFT, ALT and IgG were significant predictors of OS with area under the receiver operator curve (AUROC) value of 0.84. The combination of presence of anti-dsDNA, elevated serum ALT, and elevated serum IgG can be used to identify patients with PBC-AIH OS. Contrary to previous reports, anti-P53 was not associated with OS. In addition, other autoantibodies including anti-dsDNA (measured via CIA), anti-Ro52/TRIM21, anti-YB 1, anti-MPP1, anti-GW182, anti-Ge-1, and anti-Ago 2 were not associated with OS. CIHRCal Wenzel Family Foundation Chair in Hepatology
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".