Goals of Treatment for Improved Survival in Primary Biliary Cholangitis: Treatment Target Should Be Bilirubin Within the Normal Range and Normalization of Alkaline Phosphatase
Bibliographic record
Abstract
INTRODUCTION: In primary biliary cholangitis (PBC), bilirubin and alkaline phosphatase (ALP) are widely established as independent predictors of prognosis. Current treatment goals do not aim for normalization of surrogate markers because their association with survival has not been defined. METHODS: The patient cohort from the GLOBAL PBC Study Group was used, comprising of long-term follow-up data from European and North American centers. Ursodeoxycholic acid-treated and untreated patients with bilirubin levels ≤1 × upper limit of normal (ULN) at baseline or 1 year were included. The association of normal ALP with transplant-free survival was assessed in a subgroup with ALP ≤1.67 × ULN at 1 year. Optimal thresholds of bilirubin and ALP to predict liver transplantation (LT) or death were evaluated. RESULTS: There were 2,281 patients included in the time zero cohort and 2,555 patients in the 1-year cohort. The bilirubin threshold with the highest ability to predict LT or death at 1 year was 0.6 × ULN (hazard ratio 2.12, 95% CI 1.69-2.66, P < 0.001). The 10-year survival rates of patients with bilirubin ≤0.6 × ULN and >0.6 × ULN were 91.3% and 79.2%, respectively (P < 0.001). The risk for LT or death was stable below the bilirubin levels of 0.6 × ULN, yet increased beyond this threshold. Ursodeoxycholic acid-induced reduction in bilirubin below this threshold was associated with an 11% improvement in 10-year survival. Furthermore, ALP normalization was optimal, with 10-year survival rates of 93.2% in patients with ALP ≤ 1 × ULN and 86.1% in those with ALP 1.0-1.67 × ULN. DISCUSSION: Attaining bilirubin levels ≤0.6 × ULN or normal ALP are associated with the lowest risk for LT or death in patients with PBC. This has important implications for treatment targets.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".