Open‐label, clinical trial extension: Two‐year safety and efficacy results of seladelpar in patients with primary biliary cholangitis
Bibliographic record
Abstract
BACKGROUND: Seladelpar is a potent and selective peroxisome proliferator-activated receptor-δ agonist that targets multiple cell types involved in primary biliary cholangitis (PBC), leading to anti-cholestatic, anti-inflammatory and anti-pruritic effects. AIMS: To evaluate the long-term safety and efficacy of seladelpar in patients with PBC. METHODS: In an open-label, international, long-term extension study, patients with PBC completing seladelpar lead-in studies continued treatment. Seladelpar was taken orally once daily at doses of 5 or 10 mg with dose adjustment permitted for safety or tolerability. The primary analysis was for safety and the secondary efficacy analysis examined biochemical markers of cholestasis and liver injury. The study was terminated early due to the unexpected histological findings in a concurrent study for non-alcoholic steatohepatitis, which were subsequently found to predate treatment. Safety and efficacy data were analysed through 2 years. RESULTS: There were no serious treatment-related adverse events observed among 106 patients treated with seladelpar for up to 2 years. There were four discontinuations for safety, one possibly related to seladelpar. Among 53 patients who completed 2 years of seladelpar, response rates increased from years 1 to 2 for the composite endpoint (alkaline phosphatase [ALP] <1.67 × ULN, ≥15% decrease in ALP, and total bilirubin ≤ULN) and ALP normalisation from 66% to 79% and from 26% to 42%, respectively. In those with elevated bilirubin at baseline, 43% achieved normalisation at year 2. CONCLUSIONS: Seladelpar was safe, and markedly improved biochemical markers of cholestasis and liver injury in patients with PBC. These effects were maintained or improved throughout the second year. CLINICALTRIALS: gov: NCT03301506; Clinicaltrialsregister.eu: 2017-003910-16.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".