γ-谷氨酰转肽酶-血小板比值与其构件指标预测慢性乙型肝炎肝脏病理状态的对比评价

张占卿; 陆伟; 李秀芬; 潘云鹤; 金红弟; 丁晓红; 张秀华

doi:10.19428/j.cnki.sjpm.2017.07.001

γ-谷氨酰转肽酶-血小板比值与其构件指标预测慢性乙型肝炎肝脏病理状态的对比评价

Comparative evaluation of γ-glutamyl transpeptidase-to-platelet ratio and its component indexes in predicting liver pathological status of chronic hepatitis B

摘要

摘要:
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。

Abstract:
ObjectiveTo evaluate the efficacy of γ-glutamyl transpeptidase to platelet ratio (GPR) and its component indexes γ-glutamyl transpeptidase (GGT) and platelet (PLT) in predicting the necro-inflammatory and fibrotic levels of liver in HBeAg-positive and -negative patients with chronic hepatitis B (CHB).
MethodsA total of 323 HBeAg-positive and 254 HBeAg-negative CHB patients were enrolled for the study, who had undergone liver biopsy. Liver pathological sates were evaluated using the Scheuer scoring system.
ResultsIn HBeAg-positive patients, the areas under receiver operating characteristic curves (AUROCs) of GPR in predicting pathological grade ≥G2 and ≥G3 (0.795 and 0.831) were significantly larger than those of PLT in predicting pathological grade ≥G2 and ≥G3 (0.695 and 0.742) (P < 0.000 1 and P= 0.004 6, respectively). The AUROCs of GPR in predicting pathological stage ≥S2, ≥S3 and ≥S4 (0.726, 0.818 and 0.850) were significantly larger than those of GGT in predicting pathological stage ≥S2, ≥S3 and ≥4 (0.692, 0.770 and 0.791) (P=0.002 8, P=0.000 1 and P=0.000 1, respectively). According to the Youden indexes, the optimal cutoffs of GPR in predicting pathological grade ≥G2 and ≥G3 were > 0.376 and > 0.662, respectively, and those in predicting pathological stage ≥S2, ≥S3 and ≥S4 were > 0.368, 0.420 and > 1.106, respectively. In HBeAg-negative patients, AUROCs of GPR in predicting pathological grade ≥G2 and ≥G3 (0.853 and 0.908) were significantly larger than those of PLT in predicting pathological grade ≥G2 and ≥G3 (0.701 and 0.718) (P < 0.000 1 and P < 0.000 1, respectively). The AUROCs of GPR in predicting pathological stage ≥S3 and ≥S4 (0.839 and 0.858) were significantly larger than those of GGT in predicting pathological stage ≥S3 and ≥S4 (0.798 and 0.804) (P＝0.002 8 and P＝0.004 6, respectively). According to the Youden indexes, the optimal cutoffs of GPR in predicting pathological grade ≥G2 and ≥G3 were > 0.562 and > 0.943, respectively, and those in predicting pathological stage ≥S2, ≥S3 and ≥S4 were > 0.566, > 0.798 and > 0.963. With reference to the optimal cutoffs, the sensitivity and specificity of GPR in predicting pathological grade ≥G2, ≥G3 and stage ≥S3, ≥S4 were more than 70% regardless of the HBeAg-positive or -negative patients.
ConclusionGPR can effectively predict the different pathological states of the liver whether HBeAg is positive or negative. However, the optimal cutoffs of GPR are not exactly consistent with predicting the same pathological states of HBeAg-positive and -negative patients.

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