A novel prognostic nomogram based on microvascular invasion and hematological biomarkers to predict survival outcome for hepatocellular carcinoma patients
A novel prognostic nomogram based on microvascular invasion and hematological biomarkers to predict survival outcome for hepatocellular carcinoma patients
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DOI：
10.1016/j.suronc.2020.01.006
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发表时间：
2020-06-01
影响因子：
2.3
通讯作者：
Huang, Bin
中科院分区：
文献类型：
--
作者：
Li, Xiufen;Huang, Hao;Huang, Bin
目的：本研究旨在建立并验证一种结合联合收割机临床特征和血液学标志物预测肝细胞癌（HCC）患者总生存期（OS）的诺模图。所有患者的临床资料均通过电子病历（EMR）收集。用考克斯回归分析确定独立预测变量。我们通过辨别和校准测试列线图的准确性，然后绘制决策曲线以评估列线图辅助决策在临床背景下的益处，并与TNM分期系统和微血管浸润（MVI）对HCC预后的影响进行比较。主要队列由2008年至2013年临床病理诊断为HCC的545例患者组成，2014 - 2016年外部验证队列262例。列线图中包括的变量包括TNM分期、微血管侵袭（MVI）、甲胎蛋白（AFP）、血小板与淋巴细胞比率（PLR）和凝血酶原时间（PT）。列线图的C指数为0.768，明显上级原发队列中TNM分期（0.660，P < 0.001）和MVI（0.664，P < 0.001）。在验证队列中，模型的C指数为0.845，与TNM分期（0.687，P < 0.001）和MVI（0.684，P < 0.001）的C指数值相比，也具有统计学意义。校准曲线显示，在整个HCC结局范围内，预测和报告的OS预测具有充分的校准性。决策曲线分析表明，诺模图比TNM分期和MVI更有临床应用价值。结论：诺模图具有较好的预后价值，可用于预测肝癌患者的OS。
Purpose: This study aimed to develop and validate a nomogram for overall survival (OS) prediction in which combine clinical characteristics and hematological biomarkers in patients with hepatocellular carcinoma (HCC).Methods: We performed a retrospective analysis of 807 HCC patients. All the clinical data of these patients were collected through electronic medical record (EMR). The independent predictive variables were identified by cox regression analysis. We tested the accuracy of the nomograms by discrimination and calibration, and then plotted decision curves to assess the benefits of nomogram-assisted decisions in a clinical context, and compared with the TNM staging systems and microvascular invasion (MVI) on HCC prognosis.Results: The primary cohort consisted of 545 patients with clinicopathologically diagnosed with HCC from 2008 to 2013, while 262 patients from 2014 to 2016 in external validation cohort. Variables included in the nomograms were TNM Stage, microvascular invasion (MVI), alpha fetoprotein (AFP), platelet to lymphocyte ratio (PLR) and prothrombin time (PT). The C-index of nomogram was 0.768, which was superior than the C-index of TNM Stage (0.660, P < 0.001) and MVI(0.664, P < 0.001) alone in the primary cohort. In the validation cohort, the models had a C-index of 0.845, and were also statistically higher when compared to C-index values for TNM Stage (0.687, P < 0.001) and MVI(0.684, P < 0.001). Calibration curves showed adequate calibration of predicted and reported OS prediction throughout the range of HCC outcomes. Decision curve analysis demonstrated that the nomogram was clinically useful than the TNM Stage and MVI alone. Moreover, patients were divided into three distinct risk groups for OS by the nomogram: low risk group, middle risk group and a high risk group, respectively.Conclusion: The nomogram presents more accurate and useful prognostic power, which could be used to predict OS for patients with HCC.