MRI Features and Neutrophil-to-Lymphocyte Ratio (NLR)-Based Nomogram to Predict Prognosis of Microvascular Invasion-Negative Hepatocellular Carcinoma.

IF 4.2 3区 医学 Q2 ONCOLOGY
Journal of Hepatocellular Carcinoma Pub Date : 2025-02-15 eCollection Date: 2025-01-01 DOI:10.2147/JHC.S486955
Yunyun Wei, Xuegang Huang, Wei Pei, Yang Zhao, Hai Liao
{"title":"MRI Features and Neutrophil-to-Lymphocyte Ratio (NLR)-Based Nomogram to Predict Prognosis of Microvascular Invasion-Negative Hepatocellular Carcinoma.","authors":"Yunyun Wei, Xuegang Huang, Wei Pei, Yang Zhao, Hai Liao","doi":"10.2147/JHC.S486955","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to develop a novel nomogram to predict recurrence-free survival (RFS) for microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) patients after curative resection.</p><p><strong>Patients and methods: </strong>A total of 143 pathologically confirmed MVI-negative HCC patients were analyzed retrospectively. Baseline MRI features and inflammatory markers were collected. We used univariable and multivariable Cox regression analysis to identify the independent risk factors for RFS. And we established a nomogram based on significant MRI features and inflammatory marker. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve were used to evaluate the predictive accuracy and discriminative ability of the nomogram. The decision curve analysis (DCA) was performed to validate the clinical utility of the nomogram.</p><p><strong>Results: </strong>In multivariate Cox regression analysis, neutrophil-to-lymphocyte ratio (NLR) (P = 0.018), tumor size (P = 0.002), and tumor capsule (P = 0.000) were independent significant variables associated with RFS. Nomogram with independent factors was developed and achieved a good C-index of 0.730 (95% confidence interval [CI]: 0.656-0.804) for predicting RFS. In ROC analysis, the areas under curve of the nomogram for 1-, 3- and 5-year RFS prediction were 0.725, 0.784 and 0.798, respectively. The risk score calculated by nomogram could divide MVI-negative HCC patients into high-risk group or low-risk group (P < 0.0001). DCA analysis revealed that the nomogram could increase net benefit and exhibited a wider range of threshold probabilities by the risk stratification than the independent risk factors in the prediction of MVI-negative HCC recurrence.</p><p><strong>Conclusion: </strong>The nomogram prognostic model based on MRI features and NLR for predicting RFS showed high accuracy in MVI-negative HCC patients after curative resection. It can help clinicians make treatment decisions for MVI-negative HCC patients and identify high-risk patients for timely intervention.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"275-287"},"PeriodicalIF":4.2000,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837745/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hepatocellular Carcinoma","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JHC.S486955","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose: This study aimed to develop a novel nomogram to predict recurrence-free survival (RFS) for microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) patients after curative resection.

Patients and methods: A total of 143 pathologically confirmed MVI-negative HCC patients were analyzed retrospectively. Baseline MRI features and inflammatory markers were collected. We used univariable and multivariable Cox regression analysis to identify the independent risk factors for RFS. And we established a nomogram based on significant MRI features and inflammatory marker. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve were used to evaluate the predictive accuracy and discriminative ability of the nomogram. The decision curve analysis (DCA) was performed to validate the clinical utility of the nomogram.

Results: In multivariate Cox regression analysis, neutrophil-to-lymphocyte ratio (NLR) (P = 0.018), tumor size (P = 0.002), and tumor capsule (P = 0.000) were independent significant variables associated with RFS. Nomogram with independent factors was developed and achieved a good C-index of 0.730 (95% confidence interval [CI]: 0.656-0.804) for predicting RFS. In ROC analysis, the areas under curve of the nomogram for 1-, 3- and 5-year RFS prediction were 0.725, 0.784 and 0.798, respectively. The risk score calculated by nomogram could divide MVI-negative HCC patients into high-risk group or low-risk group (P < 0.0001). DCA analysis revealed that the nomogram could increase net benefit and exhibited a wider range of threshold probabilities by the risk stratification than the independent risk factors in the prediction of MVI-negative HCC recurrence.

Conclusion: The nomogram prognostic model based on MRI features and NLR for predicting RFS showed high accuracy in MVI-negative HCC patients after curative resection. It can help clinicians make treatment decisions for MVI-negative HCC patients and identify high-risk patients for timely intervention.

基于中性粒细胞与淋巴细胞比值(NLR)的影像学特征预测微血管浸润阴性肝细胞癌的预后。
目的:本研究旨在开发一种预测微血管侵袭(MVI)阴性肝细胞癌(HCC)患者治愈性切除后无复发生存(RFS)的新nomogram。患者和方法:回顾性分析143例病理证实的mvi阴性HCC患者。收集基线MRI特征和炎症标志物。我们使用单变量和多变量Cox回归分析来确定RFS的独立危险因素。我们建立了基于显著MRI特征和炎症标志物的nomogram。采用受试者工作特征(ROC)曲线、一致性指数(C-index)和校准曲线评价nomogram预测准确度和判别能力。采用决策曲线分析(DCA)验证nomogram临床应用价值。结果:在多因素Cox回归分析中,中性粒细胞与淋巴细胞比值(NLR) (P = 0.018)、肿瘤大小(P = 0.002)、肿瘤包膜(P = 0.000)是与RFS相关的独立显著变量。建立了独立因素的Nomogram, C-index为0.730(95%可信区间[CI]: 0.656-0.804),可以很好地预测RFS。在ROC分析中,1年、3年和5年RFS预测的nomogram curve under area分别为0.725、0.784和0.798。nomogram危险度评分可将mvi阴性HCC患者分为高危组和低危组(P < 0.0001)。DCA分析显示,在预测mvi阴性HCC复发时,nomogram可以增加净收益,并且通过风险分层显示出比独立危险因素更大范围的阈值概率。结论:基于MRI特征和NLR预测RFS的nomogram预后模型对mvi阴性HCC根治性切除患者具有较高的准确性。可以帮助临床医生对mvi阴性HCC患者进行治疗决策,识别高危患者,及时干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
0.50
自引率
2.40%
发文量
108
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信