Flexible Parametric Survival Modeling of Transaminases as Predictive Biomarkers for Non-Alcoholic Fatty Liver Disease: A Retrospective Longitudinal Study (2012–2022)

TL;DR

This study shows that elevated liver enzymes GOT and GPT can predict the development of non-alcoholic fatty liver disease in at-risk individuals.

Contribution

The study introduces a novel application of flexible parametric survival modeling to assess transaminases as predictive biomarkers for NAFLD.

Findings

Elevated GOT levels were significantly associated with increased NAFLD hazard (HR = 2.71).

Elevated GPT levels also showed a significant association with NAFLD risk (HR = 2.21).

Lipid metabolism disorders had the strongest association with NAFLD incidence (HR = 3.29).

Abstract

Non-alcoholic fatty liver disease (NAFLD) is a common metabolic liver disease linked to obesity and diabetes. This study aimed to assess whether serum GOT and GPT can predict NAFLD early in at-risk individuals. A retrospective cohort study was conducted using hospital records from the University of Debrecen (2012–2022), including 4886 NAFLD-free individuals at baseline. NAFLD incidence was tracked using ICD-10 codes, with transaminase levels (GOT and GPT) and key metabolic comorbidities analyzed as predictors in a longitudinal design. Survival analysis included Fleming–Harrington tests, Kaplan–Meier, and Nelson–Aalen estimators as well as restricted mean survival time. The Royston–Parmar flexible parametric model was used to assess the time-dependent effects of GOT, GPT, and metabolic risk factors on NAFLD incidence. An elevated GOT was significantly associated with an increased NAFLD hazard (HR = 2.71, 95% CI: 1.31–5.58), as was an elevated GPT (HR = 2.21, 95% CI: 1.09–4.43). Disorders of lipid metabolism showed the strongest association (HR = 3.29, 95% CI: 1.51–7.25). Elevated GOT and GPT levels, in combination with demographic and clinical factors, may serve as valuable prognostic biomarkers for NAFLD progression, underscoring the importance of routine liver enzyme monitoring and comprehensive metabolic management to improve long-term patient outcomes.

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