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Abstract：
OBJECTIVE: Research on bone metastasis in esophageal cancer (EC) is relatively limited. Once bone metastasis occurs in patients, their prognosis is poor, and it severely affects their quality of life. Currently, there is a lack of convenient tumor markers for early identification of bone metastasis in EC. Our research aims to explore whether neutrophil-lymphocyte ratio (NLR) can predict bone metastasis in patients with EC.
METHODS: Retrospective analysis of clinical indicators was performed on 604 patients with EC. They were divided into groups based on whether or not there was bone metastasis, and the patients\' coagulation-related tests, blood routine, tumor markers and other indicators were collected. The receiver operating characteristic curve (ROC) were used to determine the predictive ability of parameters such as NLR for bone metastasis in EC, and univariate and multivariate logistic regression analyses were conducted to determine the impact of each indicator on bone metastasis. Using binary logistic regression to obtain the predictive probability of NLR combined with tumor markers.
RESULTS: ROC curves analysis suggested that the area under the curve (AUC) of the NLR was 0.681, with a sensitivity of 79.2% and a specificity of 52.6%, which can be used as a predictive factor for bone metastasis in EC. Multivariate logistic regression analysis showed that high NLR (odds ratio [OR]: 2.608, 95% confidence interval [CI]: 1.395-4.874, P = 0.003) can function as an independent risk factor for bone metastasis in patients with EC. Additionally, high PT, high APTT, high FDP, high CEA, high CA724, low hemoglobin, and low platelet levels can also predict bone metastasis in EC. When NLR was combined with tumor markers, the area under the curve was 0.760 (95% CI: 0.713-0.807, P < 0.001), significantly enhancing the predictability of bone metastasis in EC.
CONCLUSIONS: NLR, as a convenient, non-invasive, and cost-effective inflammatory indicator, could predict bone metastasis in EC. Combining NLR with tumor markers can significantly improve the diagnostic accuracy of bone metastasis in EC.
METHODS: Retrospective analysis of clinical indicators was performed on 604 patients with EC. They were divided into groups based on whether or not there was bone metastasis, and the patients\' coagulation-related tests, blood routine, tumor markers and other indicators were collected. The receiver operating characteristic curve (ROC) were used to determine the predictive ability of parameters such as NLR for bone metastasis in EC, and univariate and multivariate logistic regression analyses were conducted to determine the impact of each indicator on bone metastasis. Using binary logistic regression to obtain the predictive probability of NLR combined with tumor markers.
RESULTS: ROC curves analysis suggested that the area under the curve (AUC) of the NLR was 0.681, with a sensitivity of 79.2% and a specificity of 52.6%, which can be used as a predictive factor for bone metastasis in EC. Multivariate logistic regression analysis showed that high NLR (odds ratio [OR]: 2.608, 95% confidence interval [CI]: 1.395-4.874, P = 0.003) can function as an independent risk factor for bone metastasis in patients with EC. Additionally, high PT, high APTT, high FDP, high CEA, high CA724, low hemoglobin, and low platelet levels can also predict bone metastasis in EC. When NLR was combined with tumor markers, the area under the curve was 0.760 (95% CI: 0.713-0.807, P < 0.001), significantly enhancing the predictability of bone metastasis in EC.
CONCLUSIONS: NLR, as a convenient, non-invasive, and cost-effective inflammatory indicator, could predict bone metastasis in EC. Combining NLR with tumor markers can significantly improve the diagnostic accuracy of bone metastasis in EC.
摘要：
目的：关于食管癌（EC）骨转移的研究相对有限。一旦患者发生骨转移，他们的预后很差，严重影响他们的生活质量。目前,缺乏方便的肿瘤标志物来早期识别EC中的骨转移。我们的研究旨在探讨中性粒细胞-淋巴细胞比值（NLR）是否可以预测EC患者的骨转移。
方法：对604例EC患者的临床指标进行回顾性分析。他们根据是否有骨转移分为几组，和患者的凝血相关测试，血常规,收集肿瘤标志物等指标。受试者工作特征曲线(ROC)用于确定NLR等参数对EC骨转移的预测能力,进行单因素和多因素logistic回归分析,以确定各指标对骨转移的影响.采用二元logistic回归得到NLR结合肿瘤标志物的预测概率。
结果：ROC曲线分析表明，NLR的曲线下面积（AUC）为0.681，灵敏度为79.2％，特异性为52.6％，可作为EC骨转移的预测因子。多因素logistic回归分析显示，高NLR（比值比[OR]：2.608，95%置信区间[CI]：1.395～4.874，P=0.003）可作为EC患者骨转移的独立危险因素。此外,高PT,APTT高,高FDP,高CEA,高CA724低血红蛋白,低血小板水平也可以预测EC的骨转移。当NLR与肿瘤标志物结合时，曲线下面积为0.760(95%CI:0.713-0.807,P<0.001),显着提高EC骨转移的可预测性。
结论：NLR，作为一种方便,非侵入性，和具有成本效益的炎症指标，可以预测EC的骨转移。将NLR与肿瘤标志物联合使用可显著提高EC骨转移的诊断准确率。
方法：对604例EC患者的临床指标进行回顾性分析。他们根据是否有骨转移分为几组，和患者的凝血相关测试，血常规,收集肿瘤标志物等指标。受试者工作特征曲线(ROC)用于确定NLR等参数对EC骨转移的预测能力,进行单因素和多因素logistic回归分析,以确定各指标对骨转移的影响.采用二元logistic回归得到NLR结合肿瘤标志物的预测概率。
结果：ROC曲线分析表明，NLR的曲线下面积（AUC）为0.681，灵敏度为79.2％，特异性为52.6％，可作为EC骨转移的预测因子。多因素logistic回归分析显示，高NLR（比值比[OR]：2.608，95%置信区间[CI]：1.395～4.874，P=0.003）可作为EC患者骨转移的独立危险因素。此外,高PT,APTT高,高FDP,高CEA,高CA724低血红蛋白,低血小板水平也可以预测EC的骨转移。当NLR与肿瘤标志物结合时，曲线下面积为0.760(95%CI:0.713-0.807,P<0.001),显着提高EC骨转移的可预测性。
结论：NLR，作为一种方便,非侵入性，和具有成本效益的炎症指标，可以预测EC的骨转移。将NLR与肿瘤标志物联合使用可显著提高EC骨转移的诊断准确率。
