一种基于血清生物标志物的新型在线计算器，用于检测乙型肝炎患者的肝细胞癌。
A Novel Online Calculator Based on Serum Biomarkers to Detect Hepatocellular Carcinoma among Patients with Hepatitis B.
机构信息
Department of Hepatic Surgery, Second Military Medical University, Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
Peking University Health Science Center, Beijing, China.
出版信息
Clin Chem. 2019 Dec;65(12):1543-1553. doi: 10.1373/clinchem.2019.308965. Epub 2019 Oct 31.
BACKGROUND
Early detection of hepatocellular carcinoma (HCC) among hepatitis B virus (HBV)-infected patients remains a challenge, especially in China. We sought to create an online calculator of serum biomarkers to detect HCC among patients with chronic hepatitis B (CHB).
METHODS
Participants with HBV-HCC, CHB, HBV-related liver cirrhosis (HBV-LC), benign hepatic tumors, and healthy controls (HCs) were recruited at 11 Chinese hospitals. Potential serum HCC biomarkers, protein induced by vitamin K absence or antagonist-II (PIVKA-II), α-fetoprotein (AFP), lens culinaris agglutinin A-reactive fraction of AFP (AFP-L3) and α-l-fucosidase (AFU) were evaluated in the pilot cohort. The calculator was built in the training cohort via logistic regression model and validated in the validation cohort.
RESULTS
In the pilot study, PIVKA-II and AFP showed better diagnostic sensitivity and specificity compared with AFP-L3 and AFU and were chosen for further study. A combination of PIVKA-II and AFP demonstrated better diagnostic accuracy in differentiating patients with HBV-HCC from patients with CHB or HBV-LC than AFP or PIVKA-II alone [area under the curve (AUC), 0.922 (95% CI, 0.908-0.935), sensitivity 88.3% and specificity 85.1% for the training cohort; 0.902 (95% CI, 0.875-0.929), 87.8%, and 81.0%, respectively, for the validation cohort]. The nomogram including AFP, PIVKA-II, age, and sex performed well in predicting HBV-HCC with good calibration and discrimination [AUC, 0.941 (95% CI, 0.929-0.952)] and was validated in the validation cohort [AUC, 0.931 (95% CI, 0.909-0.953)].
CONCLUSIONS
Our results demonstrated that a web-based calculator including age, sex, AFP, and PIVKA-II accurately predicted the presence of HCC in patients with CHB.
CLINICALTRIALSGOV IDENTIFIER
NCT03047603.
背景
在乙型肝炎病毒（HBV）感染者中早期发现肝细胞癌（HCC）仍然是一个挑战，尤其是在中国。我们试图创建一个在线计算器，用于检测慢性乙型肝炎（CHB）患者中的 HCC。
方法
在 11 家中国医院招募了 HBV-HCC、CHB、HBV 相关肝硬化（HBV-LC）、良性肝肿瘤和健康对照（HCs）的参与者。在试点队列中评估了潜在的血清 HCC 生物标志物，维生素 K 缺乏或拮抗剂-II（PIVKA-II）、甲胎蛋白（AFP）、 Lens culinaris agglutinin A-reactive fraction of AFP（AFP-L3）和α-L-岩藻糖苷酶（AFU）。通过逻辑回归模型在训练队列中构建计算器，并在验证队列中进行验证。
结果
在初步研究中，与 AFP-L3 和 AFU 相比，PIVKA-II 和 AFP 显示出更好的诊断敏感性和特异性，因此被选择进行进一步研究。与 AFP 或 PIVKA-II 单独相比，PIVKA-II 和 AFP 的组合在区分 HBV-HCC 患者与 CHB 或 HBV-LC 患者方面具有更好的诊断准确性[训练队列的曲线下面积（AUC）为 0.922（95%CI，0.908-0.935），灵敏度为 88.3%，特异性为 85.1%；验证队列的 AUC 分别为 0.902（95%CI，0.875-0.929）、87.8%和 81.0%]。包含 AFP、PIVKA-II、年龄和性别的列线图在预测 HBV-HCC 方面表现良好，具有良好的校准和区分能力[AUC，0.941（95%CI，0.929-0.952)]，并在验证队列中得到验证[AUC，0.931（95%CI，0.909-0.953)]。
结论
我们的结果表明，基于网络的计算器包括年龄、性别、AFP 和 PIVKA-II，可以准确预测 CHB 患者 HCC 的存在。
临床试验注册号
NCT03047603。
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