A newly noninvasive model for prediction of non-alcoholic fatty liver disease: utility of serum prolactin levels

Pengzi Zhang, Wenhuan Feng, Xuehui Chu, Xitai Sun, Dalong Zhu, Yan Bi

To investigate the value of prolactin (PRL) in diagnosing non-alcoholic fatty liver disease (NAFLD). Metabolic parameters and serum PRL levels were measured in 452 males and 421 females, who were randomized to the estimation or the validation group as a 1:1 ratio. Hepatic steatosis was diagnosed via abdominal ultrasound. Variables that significantly associated with NAFLD in univariate analysis were included in multiple logistic regression. We used the receiver operator characteristic (ROC) curves to test the model performance. Besides, 147 patients underwent metabolic and liver biopsy were analyzed to validate the diagnostic value of this model. Body mass index, alanine aminotransferase, prolactin, high density lipoprotein cholesterol and HbA1c were included into models. In males, the area under ROC curve (AUC) was 0.86 (95%CI: 0.82-0.91) for the validation group. With two cut-off points (- 0.79 and 1.71), the sensitivity and specificity for predicting NALFD was 95.2 and 91.1% in the validation group, respectively. In females, the AUC was 0.82 (95%CI: 0.76-0.88) for the validation group. With two cut-off points (- 0.68 and 2.16), the sensitivity and specificity for predicting NALFD was 97.1 and 91.4% in the validation group, respectively. In subjects with liver pathology, the AUC was higher than that of fatty liver index. A positive correlation between the scores of the model and the severities of NAFLD was observed. Importantly, we demonstrated a potential value of this model in predicting nonalcoholic steatohepatitis. We established a mathematic model that can conveniently and effectively diagnose the existence and severities of NAFLD.