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目的对比评价γ-谷氨酰转肽酶-血小板比值(GPR)及其构件指标γ-谷氨酰转肽酶(GGT)和血小板(PLT)预测HBeAg阳性和阴性慢性乙型肝炎(CHB)肝脏炎症坏死和纤维化程度的效能。方法 323例HBeAg阳性和254例HBeAg阴性接受肝脏活检的CHB患者纳入本研究。肝脏病理学诊断采用Scheuer评分系统。结果HBeAg阳性患者,GPR预测病理学分级≥G2和≥G3的AUROC(0.795和0.831)分别明显大于PLT预测分级≥G2和≥G3的AUROC(0.623和0.742)(P<0.000 1和P=0.004 6)。预测病理学分期≥S2、≥S3和≥S4的受试者工作特征曲线下面积(AUROC)(0.726、0.818和0.850)分别明显大于GGT预测病理学分期≥S2、≥S3和≥S4的AUROC(0.692、0.770和0.791)(P=0.002 8、P=0.000 1和P=0.000 1)。参照Youden指数,GPR预测病理学分级≥G2和≥G3的最佳截断值分别为>0.376和>0.662,预测病理学分期≥S2、≥S3和≥S4的最佳截断值分别为>0.368、>0.420和>1.106。HBeAg阴性患者,GPR预测病理学分级≥G2和≥G3的AUROC(0.853和0.908)分别明显大于PLT预测病理学分级≥G2和≥G3的AUROC(0.701和0.718)(P<0.000 1和P<0.000 1);预测病理学分期≥S3和≥S4的AUROC(0.839和0.858)分别明显大于GGT预测病理学分期≥S3和≥S4的AUROC(0.798和0.804)(P=0.002 8和P=0.004 6)。参照Youden指数,GPR预测病理学分级≥G2、≥G3的最佳截断值分别为>0.562、>0.943,预测病理学分期≥S2、≥S3和≥S4的最佳截断值分别为>0.566、>0.798和>0.963。以最佳截断值为标准,无论HBeAg阳性或阴性患者,GPR预测HBeAg阳性和阴性患者病理学分级≥G2、≥G3和分期≥S3、≥S4的灵敏度和特异度均大于70%。结论无论HBeAg阳性或阴性患者,GPR能有效预测肝脏不同病理状态,GPR预测HBeAg阳性与阴性患者肝脏相同病理状态的最佳截断值不完全一致。
OBJECTIVE: To evaluate the predictive value of γ-glutamyl transpeptidase-platelet ratio (GPR) and its components γ-glutamyl transpeptidase (GGT) and platelet (PLT) in the liver of HBeAg positive and negative chronic hepatitis B Inflammatory necrosis and the degree of fibrosis efficacy. Methods 323 HBeAg-positive and 254 HBeAg-negative CHB patients undergoing liver biopsy were enrolled in this study. Hepatic pathology was diagnosed using the Scheuer scoring system. Results AUROC (0.795 and 0.831) of GPR-predicted pathological grade ≥G2 and ≥G3 were significantly higher in patients with HBeAg-positive than those in PLT with predictive grading ≥G2 and ≥G3 (0.623 and 0.742, respectively) (P <0.0001 and P = 0.0046 ). AUROC (0.726, 0.818 and 0.850) in subjects with pathological staging ≥ S2, ≥S3 and ≥ S4 were significantly greater than those in GURT with GGT predicted pathology staging ≥ S2, ≥ S3 and ≥ S4, respectively 0.692, 0.770 and 0.791) (P = 0.002 8, P = 0.000 1 and P = 0.000 1). According to the Youden index, the optimal cut-off values of GPR predicted pathological grade≥G2 and≥G3 were> 0.376 and> 0.662, respectively. The predicted cutoffs of pathological staging≥S2, ≥S3 and≥S4 were> 0.368, 0.420 and> 1.106. In patients with HBeAg-negative disease, AUROC (0.853 and 0.908) in GPR with pathologic grade≥G2 and≥G3 were significantly higher than those with PLT in pathologic grade≥G2 and≥G3 (0.701 and 0.718, respectively) (P <0.0001 and P <0.000 1). The AUROCs (0.839 and 0.858) for predicting the pathological staging ≥S3 and ≥ S4 were significantly greater than those for the GURTs for ≥3 and ≥4 for GGT (0.798 and 0.804, P = 0.002 8 and P = 0.004 6, respectively) . According to the Youden index, the best cutoff values of GPR predicted pathological grade≥G2, ≥G3 were> 0.562,> 0.943, the predicted pathological staging≥S2, ≥3S and≥S4 were> 0.566, 0.798 and> 0.963. According to the best cutoff value, the GPR predicts HBeAg positive and negative patients pathological grade ≥G2, ≥G3 and staging ≥S3, ≥4 sensitivity and specificity ≥4% in both HBeAg positive and negative patients. Conclusion GPR can effectively predict different pathological states of liver in both HBeAg positive and negative patients. The best cutoff value of GPR in predicting the same pathological state of liver in HBeAg-positive and negative patients is not exactly the same.