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评估根治性切除术后肝门周围胆管癌患者中性粒细胞与淋巴细胞比值及血小板与淋巴细胞比值的预后价值:

Assessment of the prognostic value of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in perihilar cholangiocarcinoma patients following curative resection: .

作者信息

Ge Ming-Yang, Liu Zhi-Peng, Pan Yu, Wang Jiao-Yang, Wang Xiang, Dai Hai-Su, Gao Shu-Yang, Zhong Shi-Yun, Che Xiao-Yu, Zuo Jing-Hua, Liu Yun-Hua, Liu Xing-Chao, Fan Hai-Ning, Chen Wei-Yue, Wang Zi-Ran, Yin Xian-Yu, Bai Jie, Zhang Yan-Qi, Jiang Yan, Gong Yi, Chen Zhi-Yu

机构信息

Department of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.

Department of Hepatobiliary Surgery, Sichuan Provincial People's Hospital, Chengdu, China.

出版信息

Front Oncol. 2023 Jan 4;12:1104810. doi: 10.3389/fonc.2022.1104810. eCollection 2022.

DOI:10.3389/fonc.2022.1104810
PMID:36686802
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9845724/
Abstract

BACKGROUND & AIMS: Tumor-associated chronic inflammation has been determined to play a crucial role in tumor progression, angiogenesis and immunosuppression. The objective of this study was to assess the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in perihilar cholangiocarcinoma (pCCA) patients following curative resection.

METHODS

Consecutive pCCA patients following curative resection at 3 Chinese hospitals between 2014 and 2018 were included. The NLR was defined as the ratio of neutrophil count to lymphocyte count. PLR was defined as the ratio of platelet count to lymphocyte count. The optimal cutoff values of preoperative NLR and PLR were determined according to receiver operating characteristic (ROC) curves for the prediction of 1-year overall survival (OS), and all patients were divided into high- and low-risk groups. Kaplan-Meier curves and Cox regression models were used to investigate the relationship between values of NLR and PLR and values of OS and recurrence-free survival (RFS) in pCCA patients. The usefulness of NLR and PLR in predicting OS and RFS was evaluated by time-dependent ROC curves.

RESULTS

A total of 333 patients were included. According to the ROC curve for the prediction of 1-year OS, the optimal cutoff values of preoperative NLR and PLR were 1.68 and 113.1, respectively, and all patients were divided into high- and low-risk groups. The 5-year survival rates in the low-NLR (<1.68) and low-PLR groups (<113.1) were 30.1% and 29.4%, respectively, which were significantly higher than the rates of 14.9% and 3.3% in the high-NLR group (≥1.68) and high-PLR group (≥113.1), respectively. In multivariate analysis, high NLR and high PLR were independently associated with poor OS and RFS for pCCA patients. The time-dependent ROC curve revealed that both NLR and PLR were ideally useful in predicting OS and RFS for pCCA patients.

CONCLUSIONS

This study found that both NLR and PLR could be used to effectively predict long-term survival in patients with pCCA who underwent curative resection.

摘要

背景与目的

肿瘤相关的慢性炎症已被确定在肿瘤进展、血管生成和免疫抑制中起关键作用。本研究的目的是评估中性粒细胞与淋巴细胞比值(NLR)和血小板与淋巴细胞比值(PLR)对肝门部胆管癌(pCCA)患者根治性切除术后的预后价值。

方法

纳入2014年至2018年期间在中国3家医院接受根治性切除的连续性pCCA患者。NLR定义为中性粒细胞计数与淋巴细胞计数之比。PLR定义为血小板计数与淋巴细胞计数之比。根据受试者工作特征(ROC)曲线确定术前NLR和PLR的最佳截断值,以预测1年总生存期(OS),并将所有患者分为高风险组和低风险组。采用Kaplan-Meier曲线和Cox回归模型研究pCCA患者NLR和PLR值与OS和无复发生存期(RFS)值之间的关系。通过时间依赖性ROC曲线评估NLR和PLR在预测OS和RFS方面的有效性。

结果

共纳入333例患者。根据预测1年OS的ROC曲线,术前NLR和PLR的最佳截断值分别为1.68和113.1,并将所有患者分为高风险组和低风险组。低NLR(<1.68)组和低PLR组(<113.1)的5年生存率分别为30.1%和29.4%,显著高于高NLR组(≥1.68)和高PLR组(≥113.1)的14.9%和3.3%。多因素分析显示,高NLR和高PLR与pCCA患者较差的OS和RFS独立相关。时间依赖性ROC曲线显示,NLR和PLR在预测pCCA患者的OS和RFS方面均具有理想的有效性。

结论

本研究发现,NLR和PLR均可有效预测接受根治性切除的pCCA患者的长期生存情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/e0b8a304d084/fonc-12-1104810-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/d3e949f67498/fonc-12-1104810-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/cdfb8f84fac1/fonc-12-1104810-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/228d160eda68/fonc-12-1104810-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/e0b8a304d084/fonc-12-1104810-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/d3e949f67498/fonc-12-1104810-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/cdfb8f84fac1/fonc-12-1104810-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/228d160eda68/fonc-12-1104810-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/581e/9845724/e0b8a304d084/fonc-12-1104810-g004.jpg

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