Department of Head and Neck Oncology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Cancer Med. 2024 Apr;13(7):e7135. doi: 10.1002/cam4.7135.
Inflammatory markers, including the product of neutrophil count, platelet count, and monocyte count divided by lymphocyte count (PIV) and the platelet-to-white blood cell ratio (PWR), have not been previously reported as prognostic factors in nasopharyngeal carcinoma (NPC) patients. In order to predict overall survival (OS) in NPC patients, our goal was to create and internally evaluate a nomogram based on inflammatory markers (PIV, PWR).
A retrospective study was done on patients who received an NPC diagnosis between January 2015 and December 2018. After identifying independent prognostic indicators linked to OS using Cox proportional hazards regression analysis, we created a nomogram with the factors we had chosen.
A total of 630 NPC patients in all were split into training (n = 441) and validation sets (n = 189) after being enrolled in a population-based study in 2015-2018 and monitored for a median of 5.9 years. In the training set, the age, PIV, and PWR, selected as independent predictors for OS via multivariate Cox's regression model, were chosen to develop a nomogram. Both training and validation cohorts had C-indices of 0.850 (95% confidence interval [CI]: 0.768-0.849) and 0.851 (95% CI: 0.765-0.877). Furthermore, compared with traditional TNM staging, our nomogram demonstrated greater accuracy in predicting patient outcomes. The risk stratification model derived from our prediction model may facilitate personalized treatment strategies for NPC patients.
Our findings confirmed the prognostic significance of the PWR and PIV in NPC. High PIV levels (>363.47) and low PWR (≤36.42) values are associated with worse OS in NPC patients.
炎症标志物，包括中性粒细胞计数、血小板计数、单核细胞计数与淋巴细胞计数之比（PIV）和血小板与白细胞比值（PWR）的产物，以前并未被报道为鼻咽癌（NPC）患者的预后因素。为了预测 NPC 患者的总生存期（OS），我们的目标是基于炎症标志物（PIV、PWR）创建并内部评估一个列线图。
对 2015 年 1 月至 2018 年 12 月期间确诊为 NPC 的患者进行了回顾性研究。使用 Cox 比例风险回归分析确定与 OS 相关的独立预后指标后，我们选择了这些因素来创建一个列线图。
2015-2018 年进行了一项基于人群的研究，共纳入 630 例 NPC 患者，随访中位数为 5.9 年，将其分为训练集（n=441）和验证集（n=189）。在训练集中，通过多变量 Cox 回归模型选择年龄、PIV 和 PWR 作为 OS 的独立预测因素，用于开发列线图。训练集和验证集的 C 指数均为 0.850（95%置信区间[CI]：0.768-0.849）和 0.851（95%CI：0.765-0.877）。此外，与传统的 TNM 分期相比，我们的列线图在预测患者结局方面表现出更高的准确性。我们的预测模型得出的风险分层模型可能有助于为 NPC 患者制定个性化的治疗策略。
我们的研究结果证实了 PWR 和 PIV 在 NPC 中的预后意义。高 PIV 水平（>363.47）和低 PWR（≤36.42）值与 NPC 患者的 OS 较差相关。
