S2558 Primary Biliary Cholangitis: Second-Line Treatment and Outcomes at a Safety Net vs Tertiary Care Hospital Systems
Bibliographic record
Abstract
Introduction: Primary Biliary Cholangitis (PBC) affects women of all racial and economic backgrounds and can lead to progressive liver damage and hepatic decompensation. Limited data exist regarding healthcare disparities and second-line therapy use in safety-net settings. We aimed to compare stages at diagnosis, biochemical responses, second-line therapy initiation rates, and clinical outcomes between patients at a safety-net hospital (SNH) and a tertiary care hospital (TCH) system. Methods: We conducted a retrospective cohort study reviewing 240 adult patients diagnosed with PBC from 2015-2024 at a SNH (n = 120) and a TCH (n = 120) in Dallas, Texas. Data included demographics, laboratory values (alkaline phosphatase, bilirubin, albumin), insurance status, and therapy utilization. Outcomes measured were UDCA biochemical response rates, second-line therapy initiation, and hepatic complications. Statistical analyses included chi-square for categorical variables and T-test for continuous variables. Results: Patients at the SNH were of similar age to those at TCH (53.0 vs 54.6 years) but had significantly higher rates of uninsured or Medicaid status (63% vs 8.3%; P < 0.001), were predominantly Hispanic (78.7% vs 15.0%, P < 0.001) and had AMA-negative disease diagnosed by biopsy more frequently (32.7% vs 4.2% < 0.001). These patients were more likely to receive ursodeoxycholic acid (99.1% vs 94.1%, P = 0.04), but also had a higher rate of cirrhosis at diagnosis (26.9% vs 7.5%, P < 0.0009), higher alkaline phosphatase (280 vs 206 IU/L, P = 0.03) and lower albumin (3.7 vs 4.2 mg/dL, P < 0.001) at 1 year. 72.2% of patients at the SNH met Toronto criteria based on alkaline phosphatase at 1 year after baseline visit. Patients at the TCH who met criteria for second line therapy were more likely to receive second line therapy with obeticholic acid or fenofibrate (14/19 vs 10/40, P = 0.02). However, when excluding the patients who had already decompensated the difference was not significant (82% vs 50%). Patients not receiving second-line therapy had trend toward increased hepatic decompensation (37.8% vs 30.8%). Conclusion: Significant disparities in PBC management exist between SNH and TCH highlighted by more severe disease, with lower biochemical response rates, and increased financial barriers. In spite of these challenges, access to ursodeoxycholic acid and second line therapies is similar between the hospital systems.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".