Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China.
Cancer Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Mediators Inflamm. 2022 Aug 22;2022:9215311. doi: 10.1155/2022/9215311. eCollection 2022.
Venous thromboembolism (VTE) is considered a common complication in lung cancer patients. Despite its widespread use, the Khorana score performed moderately in predicting VTE risk. This study aimed to determine the diagnostic utility of the Systemic Immunoinflammatory Index (SII) and to create a novel nomogram for predicting VTE in patients with pulmonary carcinoma.
The data, like clinical features and laboratory indicators, of inpatients diagnosed with lung cancer from March 2019 to March 2020 were collected and analyzed. Univariate and multivariate logistic analyses were performed to confirm the risk factors and then construct a nomogram model. The calibration curve and clinical decision curve analysis (DCA) were used to assess the model's fitting performance. The receiver-operating characteristic (ROC) curve and the area under the ROC curve (AUC) were used to evaluate the diagnostic value of SII and the nomogram.
This study enrolled 369 lung patients with a VTE morbidity rate of 23.33%. The patients with VTE had higher SII levels than the non-VTE group (1441.47 ± 146.28 vs. 626.76 ± 26.04, < 0.001). SII is the stronger correlator for VTE among inflammatory markers, of which the optimal cut-off value was 851.51. Univariate and multivariate analysis revealed that the age, metastasis, antitumor treatment, hemoglobin<100 g/L, SII>851.51 × 10/L, and D-dimer>2 folds were independent risk factors for lung cancer-related VTE, and a new prediction nomogram model was constructed based on them. ROC curve analysis showed the AUC of the new model and Khorana score were 0.708 (0.643-0.772) and 0.600 (0.531-0.699).
The SII was a simple and valuable biomarker for VTE, and the new nomogram model based on it can accurately forecast the occurrence of VTE. They can be utilized in clinical practice to identify those at high risk of VTE in lung cancer patients.
静脉血栓栓塞症（VTE）被认为是肺癌患者的常见并发症。尽管 Khorana 评分被广泛应用，但它在预测 VTE 风险方面的表现仅为中等。本研究旨在确定 SII 的诊断效用，并为预测肺癌患者 VTE 风险建立新的列线图模型。
收集并分析了 2019 年 3 月至 2020 年 3 月期间住院诊断为肺癌的患者的临床特征和实验室指标等数据。采用单因素和多因素逻辑回归分析确定风险因素，然后构建列线图模型。采用校准曲线和临床决策曲线分析（DCA）评估模型拟合性能。采用受试者工作特征（ROC）曲线和 ROC 曲线下面积（AUC）评估 SII 和列线图的诊断价值。
本研究共纳入 369 例肺癌患者，VTE 发生率为 23.33%。VTE 患者的 SII 水平高于非 VTE 组（1441.47±146.28 比 626.76±26.04，<0.001）。SII 是炎症标志物中与 VTE 相关性更强的指标，其最佳截断值为 851.51。单因素和多因素分析显示，年龄、转移、抗肿瘤治疗、血红蛋白<100 g/L、SII>851.51×10/L 和 D-二聚体>2 倍是肺癌相关 VTE 的独立危险因素，并基于这些因素构建了新的预测列线图模型。ROC 曲线分析显示，新模型和 Khorana 评分的 AUC 分别为 0.708（0.643-0.772）和 0.600（0.531-0.699）。
SII 是一种简单且有价值的 VTE 生物标志物，基于 SII 的新列线图模型可准确预测 VTE 的发生。它们可用于临床实践，以识别肺癌患者中 VTE 风险较高的患者。
