Correlation of biochemical and imaging markers with hepatic adenoma in patients with glycogen storage disease: a retrospective single-center study

Hepatic adenoma is a serious complication of glycogen storage disease, particularly types I and III. However, noninvasive predictors of adenoma presence and progression for use in clinical practice remain limited. In this retrospective study, we included 93 patients with genetically confirmed glycogen storage disease who underwent liver ultrasonography, FibroScan, shear wave elastography, and routine biochemical testing between December 2020 and March 2025. Patients with and without hepatic adenoma were compared to identify discriminative variables, which were used to construct a logistic regression model. Patients with serial imaging data were assessed for changes in adenoma size and clinical parameters. Of the 93 patients included, 13 (14%) had hepatic adenomas. Age, gamma-glutamyl transferase levels, triglyceride levels, liver stiffness measured by FibroScan, and total cholesterol levels were significantly elevated in patients with adenoma compared to those without adenoma (p < 0.05). A logistic regression model combining age, gamma-glutamyl transferase, triglycerides, liver stiffness as measured by FibroScan, total cholesterol, and liver stiffness as measured by shear wave elastography achieved an area under the curve of 0.87. Adenoma progression was accompanied by changes in gamma-glutamyl transferase levels and the FibroScan Controlled Attenuation Parameter. The simplified thresholds of gamma-glutamyl transferase > 60 IU/L, triglycerides > 300 mg/dL, liver stiffness by FibroScan > 6.0, FibroScan Controlled Attenuation Parameter > 280 dB/m, and total cholesterol > 220 mg/dL were determined from group comparisons and the logistic regression model. The findings suggest that routine biochemical markers, together with selected elastographic parameters for supportive assessment, can aid in the detection and risk stratification of hepatic adenomas in patients with glycogen storage disease. The use of data-derived clinical thresholds may help guide surveillance strategies and facilitate earlier identification of patients potentially at increased risk.