S1349 Glucagon-Like Peptide-1 Receptor Agonist and Pioglitazone Therapy Have Superior Mortality and Liver Outcomes for Patients With Type 2 Diabetes and a Diagnosis or at Risk for Undiagnosed Non-alcoholic Fatty Liver Disease
Bibliographic record
Abstract
Introduction: Antidiabetic therapies Pioglitazone (PGZ) and Glucagon-Like Peptide-1 receptor Agonists (GLP1A) may have potential benefit in Nonalcoholic Fatty Liver Disease (NAFLD) and Nonalcoholic Steatohepatitis (NASH). We evaluated the efficacy of these agents in Type 2 Diabetes (T2DM) patients with NAFLD/NASH in reducing all-cause mortality and adverse liver outcomes. Methods: We queried TriNetX, a healthcare database that provides up to 20 years of de-identified aggregate data for over 123 million patients from 14 different countries. Patients were selected based on International Classification of Diseases-10th Edition (ICD-10) codes, with all patients having T2DM and either NAFLD or NASH, or a high risk of undiagnosed NAFLD/NASH (RISK) based on age > 50, ALT > 30, and T2DM. Patients could not have or be at risk for other chronic liver diseases or have a baseline high risk of mortality, according to the Charlson-Morbidity Index. We constructed 3 exclusive cohorts based on index event medication: Group 1 (GLP1A), Group 2 (PGZ), and Group 3 (other second-line T2DM medications). We matched Group 1 or Group 2 patients with Group 3 patients that had similar propensity scores on demographics, factors affecting the choice of second line T2DM medication, and factors predicting adverse liver outcomes. Matched patients were followed on an intention-to-treat basis for up to 20 years after medication initiation. Time-to-event analyses were performed using Kaplan-Meier analysis and Hazard ratios (HR) were estimated using Cox-proportional HR models with a P-value < 0.05 considered significant. The potential for unmeasured confounding was evaluated by E-value sensitivity analysis. We performed a sub-analysis on patients with an established diagnosis of cirrhosis. Results: All-cause mortality was noted to be lower among both Group 1 (HR 0.58; 95% CI 0.55 – 0.61) and Group 2 (HR 0.92; 95% CI 0.85 – 0.99) when compared to Group 3. A similar reduction was noted in Group 1 when cirrhotic patients were compared (HR 0.61; 95% CI 0.52 – 0.71). Incidence rates of liver decompensation and HCC were reduced in both Group 1 and 2 when compared with Group 3. Reduction in Liver Transplant was noted only in Group 1 (HR 0.62; 95% CI 0.44 – 0.87). E-value analyses suggested unmeasured confounders were unlikely to change any outcome associations. Conclusion: In a real-world long-term study using a large database, the use of GLP1A and PGZ for T2DM management in NAFLD/NASH population was associated with reduced overall mortality and incidence of hepatic decompensation and HCC (Figure 1 and Table 1).Figure 1.: Kaplan-Meier Curves for All-Cause Mortality and Liver Outcomes in Diabetic Patients with Fatty Liver Disease or At-risk for Undiagnosed Fatty Liver Disease Following Medication Initiation. GLP-1 RA = Glucagon-Like Peptide-1 Receptor Agonist. HR = Hazard Ratio. Table 1. - Hazard Ratios (HR) and E-Value Sensitivity Analysis for Unmeasured Confounding Cohort Outcome Hazard Ratio (95% CI) *E-Value for HR Estimate E-Value for Lower Limit of 95% CI GLP-1 RA All-Cause Mortality 0.579 (0.549 - 0.611) **7.76 8.55 New Cirrhosis 1.10 (0.98 - 1.22) 2.35 1.48 Liver Decompensation Events 0.723 (0.68 - 0.768) 4.85 5.59 Hepatocellular Carcinoma 0.633 (0.579 - 0.692) 6.52 7.76 Liver Transplant 0.615 (0.437 - 0.867) 6.91 12.45 Pioglitazone All-Cause Mortality 0.916 (0.847 - 0.991) 2.27 3.09 New Cirrhosis 0.874 (0.709 - 1.078) 2.77 5.08 Liver Decompensation Events 0.773 (0.695 - 0.861) 4.08 5.32 Hepatocellular Carcinoma 0.631 (0.533 - 0.748) 6.56 9.01 Liver Transplant 0.792 (0.413 - 1.517) 3.81 13.55 Prior Cirrhosis GLP-1 RA All-Cause Mortality 0.607 (0.52 - 0.709) 7.09 9.41 Liver Decompensation Events 0.782 (0.682 - 0.898) 3.95 5.56 Hepatocellular Carcinoma 0.796 (0.623 - 1.016) 3.76 6.73 Liver Transplant 0.587 (0.409 - 0.844) 7.56 13.75 Prior Cirrhosis Pioglitazone All-Cause Mortality 1.189 (0.85 - 1.663) 3.17 3.06 Liver Decompensation Events 1.212 (0.778 - 1.888) 3.37 4.01 Hepatocellular Carcinoma 0.703 (0.351 - 1.405) 5.18 17.05 Liver Transplant 0.815 (0.302 - 2.195) 3.50 20.76 *The E-value is the minimum strength of association to fully explain away a specific treatment–outcome association. If there exists an unmeasured covariate having a relative risk association at least as large as **7.76, then residual confounding could explain the observed association between GLP-1 RA and All-Cause Mortality. CI, Confidence Interval, GLP-1 RA 5 Glucagon-Like Peptide-1 Receptor Agonist.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.005 | 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".