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

转氨酶作为非酒精性脂肪肝疾病预测生物标志物的灵活参数生存模型:一项回顾性纵向研究(2012-2022)

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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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