P-109 ALKALINE PHOSPHATASE AND CIRRHOSIS AT DIAGNOSIS ARE ASSOCIATED WITH DEEP RESPONSE TO URSODEOXYCHOLIC ACID IN PRIMARY BILIARY CHOLANGITIS
Bibliographic record
Abstract
Conflict of interest: No Introduction and Objectives: Primary biliary cholangitis is a chronic and progressive autoimmune liver disease, whose prognosis can be improved by normalizing alkaline phosphatase and bilirubin. While ursodeoxycholic acid (UDCA) is first line standard of care, approximately 40% of patients exhibit incomplete response. We aimed to identify prognostic markers for deep response to UDCA therapy at presentation. Patients / Materials and Methods: Data from the Brazilian Cholestasis Study Group cohort were analyzed retrospectively. Patients were assessed for deep response (defined as normalization of alkaline phosphatase and bilirubin) after 1 year of UDCA treatment. With the purpose of selecting the set of relevant variables related to the deep response for a parsimonious multivariate model, we applied the Varrank algorithm. Additionally, the performance of the UDCA response score in predicting deep response was evaluated. Results and Discussion: A total of 297 patients were analyzed, with 57.2% achieving an adequate response according to the Toronto criteria, while 22.9% reached deep response. Cirrhosis (OR 0.460; 95% CI 0.225-0.942; p=0.034) and elevated baseline alkaline phosphatase levels (OR 0.629; 95% CI 0.513-0.770; p<0.001) were associated with reduced odds of deep response. The UDCA response score exhibited moderate discrimination power (AUROC=0.769) but lacked calibration. Conclusions: Baseline ALP, and cirrhosis at diagnosis emerge as the most important prognostic factors to predict normalization of alkaline phosphatase and bilirubin after UDCA. The UDCA response score is inadequate for predicting deep response in the Brazilian PBC population.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".