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治疗前炎症生物标志物对食管原发性小细胞癌的预后价值。

Prognostic value of pretreatment inflammatory biomarkers in primary small cell carcinoma of the esophagus.

机构信息

Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.

出版信息

Thorac Cancer. 2019 Oct;10(10):1913-1918. doi: 10.1111/1759-7714.13164. Epub 2019 Aug 6.

Abstract

BACKGROUND

Growing evidence indicates that several inflammatory biomarkers may predict survival in patients with malignant tumors. The aim of this study was to evaluate the prognostic value of pretreatment biomarkers in patients with primary small-cell carcinoma of the esophagus (PSCCE).

METHODS

A total of 73 PSCCE patients enrolled between January 2009 and December 2017 at the Affiliated Cancer Hospital of Zhengzhou University. The total lymphocyte counts (TLC), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) prior to anticancer therapy were collected as inflammation biomarkers. The cutoff value was determined by Receiver operating characteristic (ROC). The Kaplan-Meier method was utilized to analyze overall survival (OS). Cox proportional hazards regression was used to identify univariate and multivariate prognostic factors.

RESULTS

Univariate analysis showed that high NLR group (hazard ratio [HR] = 1.685; 95% CI: 1.001-2.838; P = 0.047) and high PLR group (hazard ratio [HR] = 1.716; 95% CI: 1.039-2.834; P = 0.033) were associated with poor OS, and TLC was not correlated with OS. On multivariate analysis, high PLR (hazard ratio [HR] = 1.751; 95% CI: 1.042-2.945; P = 0.035) was an independent prognostic factor of unfavorable OS.

CONCLUSIONS

Pretreatment PLR and NLR are correlated with OS. These biomarkers are easily accessible, cost effective, and can serve as a marker to identify high-risk patients for further designing personalized treatment and predicting treatment outcomes.

摘要

背景

越来越多的证据表明,几种炎症生物标志物可预测恶性肿瘤患者的生存情况。本研究旨在评估原发性食管小细胞癌(PSCCE)患者治疗前生物标志物的预后价值。

方法

回顾性分析 2009 年 1 月至 2017 年 12 月在郑州大学附属肿瘤医院就诊的 73 例 PSCCE 患者。收集抗癌治疗前的总淋巴细胞计数(TLC)、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)作为炎症生物标志物。通过接收者操作特征(ROC)曲线确定截断值。采用 Kaplan-Meier 法分析总生存期(OS)。Cox 比例风险回归模型用于识别单因素和多因素预后因素。

结果

单因素分析显示,高 NLR 组(风险比 [HR] = 1.685;95%可信区间:1.001-2.838;P = 0.047)和高 PLR 组(HR = 1.716;95%可信区间:1.039-2.834;P = 0.033)与 OS 不良相关,而 TLC 与 OS 无相关性。多因素分析显示,高 PLR(HR = 1.751;95%可信区间:1.042-2.945;P = 0.035)是 OS 不良的独立预后因素。

结论

治疗前 PLR 和 NLR 与 OS 相关。这些生物标志物易于获取、经济有效,可作为识别高危患者的标志物,进一步制定个体化治疗方案,并预测治疗结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/6775010/5ed4d9708436/TCA-10-1913-g001.jpg

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