PDF(Pubmed)
Abstract：
OBJECTIVE: To explore the influence of circulating lymphocyte subsets, serum markers, clinical factors, and their impact on overall survival (OS) in locally advanced nasopharyngeal carcinoma (LA-NPC). Additionally, to construct a nomogram predicting OS for LA-NPC patients using independent prognostic factors.
METHODS: A total of 530 patients with LA-NPC were included in this study. In the training cohort, Cox regression analysis was utilized to identify independent prognostic factors, which were then integrated into the nomogram. The concordance index (C-index) was calculated for both training and validation cohorts. Schoenfeld residual analysis, calibration curves, and decision curve analysis (DCA) were employed to evaluate the nomogram. Kaplan-Meier methods was performed based on risk stratification using the nomogram.
RESULTS: A total of 530 LA-NPC patients were included. Multivariate Cox regression analysis revealed that the circulating CD8+T cell, platelet-to-lymphocyte ratio (PLR), lactate dehydrogenase (LDH), albumin (ALB), gender, and clinical stage were independent prognostic factors for LA-NPC (p < 0.05). Schoenfeld residual analysis indicated overall satisfaction of the proportional hazards assumption for the Cox regression model. The C-index of the nomogram was 0.724 (95% CI: 0.669-0.779) for the training cohort and 0.718 (95% CI: 0.636-0.800) for the validation cohort. Calibration curves demonstrated good correlation between the model and actual survival outcomes. DCA confirmed the clinical utility enhancement of the nomogram over the TNM staging system. Significant differences were observed in OS among different risk stratifications.
CONCLUSIONS: Circulating CD8+ T cell, PLR, LDH, ALB, gender and clinical stage are independent prognostic factors for LA-NPC. The nomogram and risk stratification constructed in this study effectively predict OS in LA-NPC.
METHODS: A total of 530 patients with LA-NPC were included in this study. In the training cohort, Cox regression analysis was utilized to identify independent prognostic factors, which were then integrated into the nomogram. The concordance index (C-index) was calculated for both training and validation cohorts. Schoenfeld residual analysis, calibration curves, and decision curve analysis (DCA) were employed to evaluate the nomogram. Kaplan-Meier methods was performed based on risk stratification using the nomogram.
RESULTS: A total of 530 LA-NPC patients were included. Multivariate Cox regression analysis revealed that the circulating CD8+T cell, platelet-to-lymphocyte ratio (PLR), lactate dehydrogenase (LDH), albumin (ALB), gender, and clinical stage were independent prognostic factors for LA-NPC (p < 0.05). Schoenfeld residual analysis indicated overall satisfaction of the proportional hazards assumption for the Cox regression model. The C-index of the nomogram was 0.724 (95% CI: 0.669-0.779) for the training cohort and 0.718 (95% CI: 0.636-0.800) for the validation cohort. Calibration curves demonstrated good correlation between the model and actual survival outcomes. DCA confirmed the clinical utility enhancement of the nomogram over the TNM staging system. Significant differences were observed in OS among different risk stratifications.
CONCLUSIONS: Circulating CD8+ T cell, PLR, LDH, ALB, gender and clinical stage are independent prognostic factors for LA-NPC. The nomogram and risk stratification constructed in this study effectively predict OS in LA-NPC.
摘要：
目的：探讨循环淋巴细胞亚群的影响，血清标记物,临床因素，以及它们对局部晚期鼻咽癌（LA-NPC）总生存期（OS）的影响。此外,使用独立预后因素构建预测LA-NPC患者OS的列线图。
方法：本研究共纳入530例LA-NPC患者。在训练组中，Cox回归分析用于确定独立的预后因素。然后被整合到列线图中。计算训练和验证队列的一致性指数(C指数)。Schoenfeld残差分析，校正曲线,和决策曲线分析（DCA）用于评估列线图。使用列线图基于风险分层进行Kaplan-Meier方法。
结果：共纳入530例LA-NPC患者。多因素Cox回归分析显示循环CD8+T细胞,血小板与淋巴细胞比率（PLR），乳酸脱氢酶（LDH），白蛋白（ALB），性别,临床分期是LA-NPC的独立预后因素(p<0.05)。Schoenfeld残差分析表明，对Cox回归模型的比例风险假设的总体满意度。训练队列的列线图C指数为0.724（95％CI：0.669-0.779），验证队列为0.718（95％CI：0.636-0.800）。校准曲线表明模型与实际生存结果之间具有良好的相关性。DCA证实了与TNM分期系统相比，列线图的临床实用性增强。在不同的危险分层中观察到OS的显着差异。
结论：循环CD8+T细胞，PLR,LDH,ALB,性别和临床分期是LA-NPC的独立预后因素.本研究中构建的列线图和风险分层可有效预测LA-NPC的OS。
方法：本研究共纳入530例LA-NPC患者。在训练组中，Cox回归分析用于确定独立的预后因素。然后被整合到列线图中。计算训练和验证队列的一致性指数(C指数)。Schoenfeld残差分析，校正曲线,和决策曲线分析（DCA）用于评估列线图。使用列线图基于风险分层进行Kaplan-Meier方法。
结果：共纳入530例LA-NPC患者。多因素Cox回归分析显示循环CD8+T细胞,血小板与淋巴细胞比率（PLR），乳酸脱氢酶（LDH），白蛋白（ALB），性别,临床分期是LA-NPC的独立预后因素(p<0.05)。Schoenfeld残差分析表明，对Cox回归模型的比例风险假设的总体满意度。训练队列的列线图C指数为0.724（95％CI：0.669-0.779），验证队列为0.718（95％CI：0.636-0.800）。校准曲线表明模型与实际生存结果之间具有良好的相关性。DCA证实了与TNM分期系统相比，列线图的临床实用性增强。在不同的危险分层中观察到OS的显着差异。
结论：循环CD8+T细胞，PLR,LDH,ALB,性别和临床分期是LA-NPC的独立预后因素.本研究中构建的列线图和风险分层可有效预测LA-NPC的OS。
