Baseline Ductopenia and Treatment Response Predict Long-Term Histological Progression in Primary Biliary Cirrhosis
Bibliographic record
Abstract
OBJECTIVES: Laboratory and pathological predictors of future histological progression in primary biliary cirrhosis (PBC) are needed for routine practice and clinical trials. We sought to develop clinically meaningful markers for those with predominantly early disease at risk of progressive liver damage. METHODS: Patients with PBC (n=69) with a follow-up liver biopsy performed approximately 10 years after initial histological diagnosis were identified and reviewed. RESULTS: Histological progression in the stage of fibrosis observed in paired liver biopsies from the same patient was associated with the absence of biochemical response to ursodeoxycholic acid (UDCA) at 2 years: alkaline phosphatase (ALP) >1.67 × ULN (upper limit of normal) (P=0.001, odds ratio (OR) 12.14, 95% confidence interval (CI) 2.69-54.74) when defined as an increase in one stage and ALP > 1.76 × ULN (P=0.03, OR 5.07, 95% CI 1.17-21.95) when defined as an increase in two stages. Ductopenia (>50% loss), as formally evaluated through blinded biopsy review of liver tissue obtained at initial diagnosis in a subset of 34 patients, predicted histological progression (P=0.012), along with biochemical response to UDCA (P=0.002). The presence of interface hepatitis in the same biopsies did not. CONCLUSIONS: Patients with PBC who fail to show a biochemical response to UDCA or who have ductopenia on baseline biopsy progress histologically during extended follow-up. Such patients may benefit from novel treatments, with our exploratory data providing a means of identifying these individuals early in their disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".