慢性乙型肝炎免疫耐受期患者显著肝损伤的列线图模型及其预测价值分析

王春艳; 杨武才; 谭文辉; 邓亚; 郭畅; 张珊; 王建军; 陈国凤; 纪冬

doi:10.3969/j.issn.1001-5256.2021.07.010

慢性乙型肝炎免疫耐受期患者显著肝损伤的列线图模型及其预测价值分析

DOI: 10.3969/j.issn.1001-5256.2021.07.010

王春艳¹,
杨武才¹,
谭文辉¹,
邓亚²,
郭畅¹,
张珊³,
王建军¹,
陈国凤^{1, 3},
纪冬^{1, 2, 3, ,}

1.
解放军总医院第五医学中心肝病医学部，北京 100039
2.
南方医科大学第二临床医学院，广州 510515
3.
北京大学三〇二临床医学院，北京 100039

基金项目:

解放军总医院医疗大数据与人工智能研发项目 (2019MBD-024);

首都临床特色应用研究特色课题 (Z181100001718034);

菊梅肝胆病防治能力建设专项基金重点项目 (2018JM12603003)

利益冲突声明：本研究不存在研究者、伦理委员会成员、受试者监护人以及与公开研究成果有关的利益冲突

作者贡献声明：王春艳、邓亚、纪冬负责课题设计，资料分析，撰写论文；王春艳、杨武才、谭文辉、邓亚、郭畅、张珊、王建军、陈国凤、纪冬参与收集数据，修改论文；王春艳、纪冬负责拟定写作思路，指导撰写文章并最后定稿。

详细信息

通信作者:
纪冬，jidg302@126.com

中图分类号: R512.62;R575.2
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出版历程
- 收稿日期: 2021-04-07
- 录用日期: 2021-04-21
- 出版日期: 2021-07-20

Value of a nomogram model in predicting significant liver injury in patients with immune-tolerant phase chronic hepatitis B

1.
Department of Liver Diseases, Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China
2.
The Second Clinical Medical School of Southern Medical University, Guangzhou 510515, China
3.
Peking University 302 Clinical Medical School, Beijing 100039, China

Research funding:

Medical Big Data and Artificial Intelligence Development Fund of Chinese PLA General Hospital (2019MBD-024);

the Capital Characteristic Clinic Project of Beijing Municipal Science and Technology Commission (Z181100001718034);

Key Project of Jumei Special Fund for Hepatobiliary Disease Prevention and Treatment (2018JM12603003)

摘要

摘要: 目的分析慢性HBV感染免疫耐受期(IT-CHB)患者显著肝损伤的高危因素并建立列线图预测模型。方法回顾性分析2002年8月—2017年12月在解放军总医院第五医学中心接受肝活检的382例慢性HBV感染者的资料，按照肝组织是否存在显著肝损伤分为2组，显著肝损伤组(≥G2或S2，n=82)和非显著肝损伤组(n=300)。正态分布的计量数据2组间比较采用独立样本t检验；非正态分布数据2组间比较采用Mann- Whitney U检验; 多组比较采用Kruskal-Wallis H检验；计数资料2组间比较采用χ²检验。相关性分析采用Spearman秩相关。采用单/多因素logistic回归方法筛选高危因素，并建立列线图模型，用C-指数、ROC曲线、校准曲线以及Bootstrap法来评价列线图的区分度及校准度。结果 2组年龄、HBV DNA载量、ALT、AST、PLT比较差异均有统计学意义(t=-7.071，Z值别为-4.924、-3.693、-6.945、-0.585、-5.723，P值均＜0.001)。Logistic回归分析显示年龄(OR=1.074，95%CI: 1.043~1.107，P＜0.001)，HBV DNA载量(OR=0.442，95%CI: 0.314~0.624，P＜0.001)，AST(OR=1.096，95%CI: 1.051~1.142，P＜0.001)，PLT(OR=0.992，95%CI: 0.986~0.998，P=0.006)是显著肝损伤的高危因素。基于以上因素建立列线图模型，预测显著肝损伤的C-指数为0.845，并且有拟合度高的校正曲线，其ROC曲线下面积(AUC)为0.845(95%CI: 0.795~0.895)，显著优于APRI(AUC=0.781，95%CI: 0.723~0.840)以及FIB-4 (AUC=0.802，95%CI: 0.746~0.859)。结论免疫耐受期具有显著肝损伤的患者比例并不少见，基于年龄、HBV DNA、AST、PLT构建的列线图模型具有良好的预测准确性，可用于个体化预测IT-CHB患者的显著肝损伤，减少肝活检，为抗病毒的精准治疗提供参考。
- 乙型肝炎, 慢性 /
- 免疫耐受 /
- 列线图
Abstract: Objective To investigate the high-risk factors for significant liver injury in patients with immune-tolerant phase chronic hepatitis B (IT-CHB), and to establish a nomogram predictive model. Methods A retrospective analysis was performed for the data of 382 patients with chronic HBV infection who underwent liver biopsy in The Fifth Medical Center of Chinese PLA General Hospital from August 2002 to December 2017, and according to the presence or absence of significant liver injury, the patients were divided into significant liver injury group (≥G2/S2) with 82 patients and non-significant liver injury group with 300 patients. The independent samples t-test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the Kruskal-Wallis H test was used for comparison between multiple groups; the chi-square test was used for comparison of categorical data between groups. The Spearman rank correlation test was used to investigate correlation. Univariate and multivariate logistic regression analyses were used to screen out high-risk factors and establish a nomogram model. Concordance index (C-index), the receiver operating characteristic (ROC) curve, calibration curve, and the bootstrap method were used to evaluate the discrimination and calibration abilities of the nomogram. Results There were significant differences between the two groups in age, HBV DNA load, alanine aminotransferase, aspartate aminotransferase (AST), and platelet count (PLT) (t=-7.071, Z=-4.924, -3.693, -6.945, -0.585 and -5.723, all P < 0.001). The logistic regression analysis showed that age (odds ratio [OR]=1.074, 95% confidence interval [CI]: 1.043-1.107, P < 0.001), HBV DNA load (OR=0.442, 95%CI: 0.314-0.624, P < 0.001), AST(OR=1.096, 95%CI: 1.051-1.142, P < 0.001), and PLT(OR=0.992, 95%CI: 0.986-0.998, P=0.006) were high-risk factors for significant liver injury. The nomogram model established based on the above factors had a C-index of 0.845 in predicting significant liver injury and had a well-fitted calibration curve, with an area under the ROC curve (AUC) of 0.845 (95%CI: 0.795-0.895), which was significantly better than aspartate aminotransferase-to-platelet ratio index (AUC=0.781, 95%CI: 0.723-0.840) and fibrosis-4(AUC=0.802, 95%CI: 0.746-0.859). Conclusion There is a high proportion of IT-CHB patients with significant liver injury. The nomogram model established based on age, HBV DNA, AST, and PLT has a good predictive accuracy and can be used to predict significant liver injury in IT-CHB patients individually, reduce the need for liver biopsy, and provide a reference for precise antiviral treatment.
- Hepatitis B, Chronic /
- Immune Tolerance /
- Nomograms

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图 1 不同年龄段与肝组织病理炎症及纤维化的关系

下载: 全尺寸图片幻灯片

图 2 HBV DNA载量与不同阶段肝组织病理炎症及纤维化的关系

下载: 全尺寸图片幻灯片

图 3 预测IT-CHB患者显著肝损伤的列线图

下载: 全尺寸图片幻灯片

表 1 患者基线的一般资料

指标	总体(n=382)	非显著肝损伤组(n=300)	显著肝损伤组(n=82)	统计值	P值
男性[例(%)]	261(68.3)	201(67.0)	60(73.2)	χ²=1.133	0.287
年龄(岁)	33.3±10.2	31.5±9.1	39.9±11.2	t=-7.071	＜0.001
年龄段[例(%)]				χ²=56.472	＜0.001
＜30岁	161(42.1)	147(49.0)	14(17.1)
30~39岁	130(34.0)	106(35.3)	24(29.3)
40~49岁	64(16.8)	35(11.7)	29(35.4)
≥50岁	27(7.1)	12(4.0)	15(18.3)
乙型肝炎家族史[例(%)]	221(57.9)	173(57.7)	48(58.5)	χ²=0.020	0.888
BMI(kg/m²)	23.2±3.53	23.0±3.4	23.7±3.9	t=-1.021	0.308
HBV DNA(log₁₀IU/ml)	8.4(7.8~8.8)	8.4(8.0~8.8)	7.9(6.9~8.5)	Z=-4.924	＜0.001
ALT(U/L)	23.0(18.0~28.0)	23.0(18.0~28.0)	25.5(21.0~32.0)	Z=-3.693	＜0.001
AST(U/L)	23.0(19.0~27.0)	21.0(19.0~26.0)	28.0(23.0~34.0)	Z=-6.945	＜0.001
TBil(μmol/L)	11.1(8.3~15.3)	10.9(8.3~15.3)	11.5(8.6~15.4)	Z=-0.585	0.559
PLT(×10⁹/L)	202(164~234)	208(176~239)	161(137~209)	Z=-5.723	＜0.001

下载: 导出CSV

表 2 显著肝损伤的logistic回归分析

因素	单因素分析		多因素分析
因素	OR(95%CI)	P值	OR(95%CI)	P值
年龄	1.084 (1.057~1.113)	＜0.001	1.074(1.043~1.107)	＜0.001
HBV DNA	0.437 (0.324~0.589)	＜0.001	0.442(0.314~0.624)	＜0.001
ALT	1.076(1.036~1.119)	＜0.001	1.009(0.959~1.060)	0.736
AST	1.132 (1.089~1.177)	＜0.001	1.096(1.051~1.142)	＜0.001
PLT	0.985 (0.98~0.991)	＜0.001	0.992(0.986~0.998)	0.006

下载: 导出CSV

表 3 列线图、APRI、FIB-4诊断显著肝损伤的效能比较

诊断参数	AUC	95%CI	界值	敏感度(%)	特异度(%)	阳性预测值(%)	阴性预测值(%)	Youden指数
列线图	0.845	0.795 ~ 0.895	141.4	74.4	84.7	57.0	92.4	0.59
APRI	0.781	0.723 ~ 0.840	0.338	70.7	77.7	46.4	90.7	0.48
FIB-4	0.802	0.746 ~ 0.859	0.882	78.1	72.3	43.5	92.3	0.50

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