非创伤性诊断模型在慢性乙型肝炎患者肝纤维化中的应用

doi:10.3969/j.issn.1673-8640.2018.10.004

摘要/Abstract

摘要：

目的用非创伤性指标建立慢性乙型肝炎（CHB）患者肝纤维化诊断模型,并评价建立的模型的诊断价值。方法检测270例行肝脏组织病理学检查的CHB患者的肝纤维化血清学标志物[血小板（PLT）、丙氨酸氨基转移酶（ALT）、天门冬氨酸氨基转移酶（AST）、γ-谷氨酰基转移酶（GGT）、碱性磷酸酶（ALP）、总胆红素（TB）、白蛋白（Alb）、白蛋白/球蛋白（A/G）比值、红细胞分布宽度（RDW）、凝血酶原活动度（PTA）、纤维蛋白原（Fib）、乙型肝炎病毒e抗原（HBeAg）]水平。分析这些检测指标与CHB患者肝纤维化的相关性。采用Logistic回归分析建立诊断模型,采用受试者工作特征（ROC）曲线分析其诊断价值,并与已建立的诊断模型（APRI、FIB-4、AAR、GPR、RPR）进行比较。结果通过Logistic回归分析逐一分析各项指标,得出回归方程建立新的诊断模型AFPPR：AFPPR=1/[1+EXP（-2.584-A/G比值×1.426-PLT×0.013-PTA×0.016-Fib×0.605+RDW×0.364）]。ROC曲线分析显示,AFPPR诊断显著肝纤维化的曲线下面积（AUC）为0.80,明显大于其他5个诊断模型的AUC（P<0.01）,AAR对于显著肝纤维化及严重肝纤维化基本无诊断价值（P>0.05）;AFPPR诊断严重肝纤维化的AUC为0.76,与其他5个模型的AUC比较,除AAR模型（P=0.000）外,差异均无统计学意义（P>0.05）。结论建立的AFPPR诊断模型可用于诊断CHB患者的显著肝纤维化,可作为临床动态监测肝纤维化的补充性证据。

关键词: 非创伤性诊断模型, 肝脏纤维化, 慢性乙型肝炎

Abstract:

Objective To establish the noninvasive diagnostic model for liver fibrosis in patients with chronic hepatitis B（CHB）,and to investigate the role for diagnosis. Methods Serum liver fibrosis markers [platelet（PLT）,alanine aminotransferase（ALT）,aspartate aminotransferase（AST）,gamma-glutamyltransferase（GGT）,alkaline phosphatase（ALP）,total bilirubin（TB）,albumin（Alb）,albumin to globulin（A/G） ratio,red blood cell distribution width（RDW）,prothrombin time activity（PTA）,fibrinogen（Fib） and hepatitis B e antigen（HBeAg）] were determined in 270 patients with CHB undergoing liver biopsy. The correlation between these indices and liver fibrosis stage of CHB patients was analyzed. Logistic regression analysis was performed to establish a diagnostic model,and the results were analyzed by receiver operating characteristic（ROC） curve and compared with established diagnostic models（APRI,FIB-4,AAR,GPR and RPR）. Results By Logistic regression analysis,the indices were analyzed,and the regression equation for new diagnostic model AFPPR,which was AFPPR =1/[1+EXP（-2.584-A/G ratio×1.426-PLT×0.013-PTA×0.016-Fib×0.605+RDW×0.364）],was set up. The area under curve（AUC） of AFPPR for the diagnosis of liver fibrosis was 0.80,which was bigger than those of the other 5 diagnostic models（P<0.01）. AAR had no diagnostic value for significant and severe liver fibrosio（P>0.05）. The AUC of AFPPR for severe liver fibrosis was 0.76,which was bigger than those of the other 5 diagnostic models. Compared with the AUC of the other 5 diagnostic models,there was no statistical significance,except for AAR（P=0.000）. Conclusions The established AFPPR diagnostic model for liver fibrosis can be used as clinical supplementary reference on the dynamic observation of liver fibrosis.

Key words: Noninvasive diagnostic model, Liver fibrosis, Chronic hepatitis B

中图分类号:

R446.1

侯丽, 于璐, 牛瑶, 张媛, 王亮. 非创伤性诊断模型在慢性乙型肝炎患者肝纤维化中的应用[J]. 检验医学, 2018, 33(10): 888-893.

HOU Li, YU Lu, NIU Yao, ZHANG Yuan, WANG Liang. Role of noninvasive diagnostic model for liver fibrosis in patients with chronic hepatitis B[J]. Laboratory Medicine, 2018, 33(10): 888-893.

图/表 5

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检测指标	单因素分析[OR（95%CI）]	P值	多因素分析[OR（95%CI）]	P值
年龄	1.030（0.995~1.066）	0.089
A/G比值	0.252（0.096~0.660）	0.005	0.240（0.093~0.620）	0.003
GGT	0.999（0.989~1.009）	0.878
ALT	1.001（0.996~1.006）	0.787
AST	1.001（0.992~1.011）	0.775
ALP	0.998（0.988~1.008）	0.678
TB	1.020（0.990~1.052）	0.194
PTA	0.983（0.971~0.996）	0.009	0.984（0.973~0.996）	0.009
PLT	0.987（0.980~0.993）	0.000	0.987（0.980~0.993）	0.000
RDW	1.361（1.069~1.733）	0.012	1.438（1.145~1.808）	0.002
Fib	0.514（0.297~0.892）	0.018	0.546（0.325~0.917）	0.022

检测指标	单因素分析[OR（95%CI）]	P值	多因素分析[OR（95%CI）]	P值
年龄	1.030（0.995~1.066）	0.089
A/G比值	0.252（0.096~0.660）	0.005	0.240（0.093~0.620）	0.003
GGT	0.999（0.989~1.009）	0.878
ALT	1.001（0.996~1.006）	0.787
AST	1.001（0.992~1.011）	0.775
ALP	0.998（0.988~1.008）	0.678
TB	1.020（0.990~1.052）	0.194
PTA	0.983（0.971~0.996）	0.009	0.984（0.973~0.996）	0.009
PLT	0.987（0.980~0.993）	0.000	0.987（0.980~0.993）	0.000
RDW	1.361（1.069~1.733）	0.012	1.438（1.145~1.808）	0.002
Fib	0.514（0.297~0.892）	0.018	0.546（0.325~0.917）	0.022

诊断模型	临界值	AUC（95%CI）	敏感性（%）	特异性（%）	正确指数	阳性似然比	阴性似然比	P值
FIB-4	1.003	0.687（0.623~0.751）^*	71.0	60.1	0.311	1.779	0.483	0.000
RPR	0.084	0.738（0.377~0.798）	72.0	67.5	0.395	2.215	0.415	0.000
APRI	0.364	0.698（0.636~0.761）^*	75.7	54.0	0.297	1.646	0.450	0.000
AAR		0.479（0.410~0.549）^*						0.567
GRP	0.253	0.652（0.586~0.718）^*	82.2	42.9	0.251	1.440	0.415	0.000
AFPPR	1.003	0.800（0.747~0.852）	77.6	67.5	0.451	2.388	0.332	0.000

诊断模型	临界值	AUC（95%CI）	敏感性（%）	特异性（%）	正确指数	阳性似然比	阴性似然比	P值
FIB-4	1.003	0.687（0.623~0.751）^*	71.0	60.1	0.311	1.779	0.483	0.000
RPR	0.084	0.738（0.377~0.798）	72.0	67.5	0.395	2.215	0.415	0.000
APRI	0.364	0.698（0.636~0.761）^*	75.7	54.0	0.297	1.646	0.450	0.000
AAR		0.479（0.410~0.549）^*						0.567
GRP	0.253	0.652（0.586~0.718）^*	82.2	42.9	0.251	1.440	0.415	0.000
AFPPR	1.003	0.800（0.747~0.852）	77.6	67.5	0.451	2.388	0.332	0.000

诊断模型	临界值	AUC（95%CI）	敏感性（%）	特异性（%）	正确指数	阳性似然比	阴性似然比	P值
FIB-4	1.404	0.724（0.645~0.804）	63.0	77.2	0.402	2.763	0.479	0.000
RPR	0.081	0.730（0.655~0.806）	84.8	53.6	0.384	1.828	0.284	0.000
APRI	0.405	0.721（0.644~0.799）	80.4	54.9	0.353	1.783	0.357	0.000
AAR		0.528（0.442~0.613）^*						0.555
GRP	0.268	0.731（0.660~0.802）	82.6	56.7	0.393	1.908	0.307	0.000
AFPPR	1.006	0.763（0.692~0.835）	71.7	69.6	0.413	2.359	0.407	0.000