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基于APRI的新型预测列线图在乙型肝炎病毒相关性小孤立性肝细胞癌立体定向体部放疗中的开发与评估

Development and Assessment of Novel Predictive Nomograms Based on APRI for Hepatitis B Virus-associated Small Solitary Hepatocellular Carcinoma with Stereotactic Body Radiotherapy.

作者信息

Lai Lin, Su Tingshi, Liang Zhongguo, Lu Yunxing, Hou Encun, Lian Zuping, Gao Hongjun, Zhu Xiaodong

机构信息

Department of Radiotherapy, Guangxi Medical University Cancer Hospital, Nanning 530021, Guangxi, People's Republic of China.

Department of Medical Oncology, Ruikang Hospital Affiliated to Guangxi Traditional Chinese Medical University, Nanning 530011, Guangxi, People's Republic of China.

出版信息

J Cancer. 2020 Sep 23;11(22):6642-6652. doi: 10.7150/jca.47291. eCollection 2020.

DOI:10.7150/jca.47291
PMID:33046985
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7545675/
Abstract

The correlation between serum inflammatory marker before treatment and the survival of patients with hepatitis B virus (HBV)-associated small solitary hepatocellular carcinoma (HCC) after stereotactic body radiotherapy (SBRT) remains unclear. The objective of our study is to estimate survival in such patients using multivariable prediction models and investigate the prognostic value of aspartate aminotransferase-to-platelet index (APRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) for HBV-associated small solitary HCC patients treated with SBRT. Patients with HBV-associated small solitary HCC who were newly treated with SBRT were retrospectively analysed in our hospital from 2009 to 2016. We counted the APRI, NLR, PLR, and LMR before treatment and calculated their cut-off values for predicting overall survival (OS) and progression-free survival (PFS) by receiver operating characteristic (ROC) analysis. The random forest model combined with least absolute shrinkage and selection operator (LASSO) regression model for OS and PFS were used to screen potentially prognostic factors from serum inflammatory markers, demographic data, and clinical characteristics. Predictive models for OS and PFS were developed by multivariable COX regression and nomograms were constructed. Discrimination was assessed using the C-index. Internal validation was assessed using the Bootstrap method. Survival analysis was carried out to assess the prognostic value of serum inflammatory markers, and OS and PFS curves were compared by Kaplan-Meier analysis and Log-Rank test, respectively. A total of 72 patients with HBV-associated small solitary HCC were recruited for the study. The median follow-up time was 2015 days (range, 232-3823 days). Age, tumor size, NLR, PLR, and APRI were used to construct nomogram for OS, while gender, age, TNM stage, portal hypertension, AFP, APRI were for PFS. The two models displayed good discriminations with C-indexes of 0.738 (95% CI: 0.632-0.844) and 0.657 (95% CI: 0.538-0.777), and their C-indexes in the internal validation cohort reached 0.790 (95% CI: 0.684-0.896) and 0.739 (95% CI: 0.619-0.859). The multivariable cox analysis indicated that APRI<0.47 was favourable independent prognostic factors for OS and PFS. Compared to APRI≥0.47, APRI<0.47 predicts better OS (=0.003) and PFS (=0.003). Nomograms based on APRI are superior in predicting OS and PFS in HBV-associated small solitary HCC patients who have received SBRT. APRI before treatment is a feasible and convenient prognostic indicator for OS and PFS, which helpfully determines the beneficial population of SBRT for HBV-associated small solitary HCC.

摘要

治疗前血清炎症标志物与接受立体定向体部放疗(SBRT)的乙型肝炎病毒(HBV)相关小孤立性肝细胞癌(HCC)患者生存情况之间的相关性尚不清楚。我们研究的目的是使用多变量预测模型评估此类患者的生存情况,并探讨天冬氨酸转氨酶与血小板比值指数(APRI)、中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)及淋巴细胞与单核细胞比值(LMR)对接受SBRT治疗的HBV相关小孤立性HCC患者的预后价值。2009年至2016年,我们对我院新接受SBRT治疗的HBV相关小孤立性HCC患者进行了回顾性分析。我们计算了治疗前的APRI、NLR、PLR和LMR,并通过受试者工作特征(ROC)分析计算其预测总生存期(OS)和无进展生存期(PFS)的临界值。采用随机森林模型联合最小绝对收缩和选择算子(LASSO)回归模型对OS和PFS进行分析,从血清炎症标志物、人口统计学数据和临床特征中筛选潜在的预后因素。通过多变量COX回归建立OS和PFS的预测模型,并构建列线图。使用C指数评估辨别力。采用Bootstrap法进行内部验证。进行生存分析以评估血清炎症标志物的预后价值,并分别通过Kaplan-Meier分析和Log-Rank检验比较OS和PFS曲线。本研究共纳入72例HBV相关小孤立性HCC患者。中位随访时间为2015天(范围:232 - 3823天)。年龄、肿瘤大小、NLR、PLR和APRI用于构建OS列线图,而性别、年龄、TNM分期、门静脉高压、甲胎蛋白(AFP)、APRI用于构建PFS列线图。这两个模型显示出良好的辨别力,OS模型的C指数为0.738(95%CI:0.632 - 0.844),PFS模型的C指数为0.657(95%CI:0.538 - 0.777),其在内部验证队列中的C指数分别达到0.790(95%CI:0.684 - 0.896)和0.739(95%CI:0.619 - 0.859)。多变量COX分析表明,APRI<0.47是OS和PFS的有利独立预后因素。与APRI≥0.47相比,APRI<0.47预测的OS(P = 0.003)和PFS(P = 0.003)更好。基于APRI的列线图在预测接受SBRT的HBV相关小孤立性HCC患者的OS和PFS方面更具优势。治疗前的APRI是OS和PFS的一个可行且便捷的预后指标,有助于确定SBRT对HBV相关小孤立性HCC的受益人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7a3/7545675/47f3979a500d/jcav11p6642g006.jpg
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