(1) Background: The hemostatic system and tumor biology display a tight and reciprocal interaction where clotting products enhance tumor growth and dissemination, and the tumor, in turn, triggers a hypercoagulable and inflammatory state. Evaluating circulating biomarkers related to thrombo-inflammatory may provide a promising tool for predicting tumor outcomes, especially in non-small cell lung cancer (NSCLC) characterized by unfavorable outcomes. (2) Aim: In a prospective cohort of NSCLC patients, we evaluated whether thromboinflammatory biomarkers could predict early disease progression (DP) during the first 6 months of first-line anticancer treatment. (3) Methods: 719 newly diagnosed advanced-stage NSCLC patients were included. Complete blood cell count, high-sensitivity C-reactive protein (hs-CRP), FVIII, fibrinogen, D-dimer, thrombin-antithrombin (TAT) complexes, and prothrombin fragment1+2(F1+2) were tested in blood samples collected before starting chemotherapy. DP was gathered during follow-up. (4) Results: The 6-month cumulative incidence rate for DP was 49%. Univariable Cox regression analysis identified metastatic status, BMI, hemoglobin, leukocytes, hs-CRP, FVIII, fibrinogen, TAT, and D-dimer as significant predictors of DP. In a multivariable analysis that included all previously significant variables, only hs-CRP and D-Dimer levels remained strongly associated with DP. The two variables were used to establish a risk stratification model that significantly identified patients at high risk of DP at 6 months (HR 2.9; 95% CI, 2.3–3.7), which can be applied to 3, 9, and 12 months. (5) Conclusions: Our model easily and precisely estimates early DP during chemotherapy. If externally validated, this model can significantly enhance the allocation of medical resources in managing advanced NSCLC, ensuring that patients receive the most effective care possible.
（1）背景：止血系统与肿瘤生物学之间存在紧密且相互作用的关联，其中凝血产物促进肿瘤生长与扩散，而肿瘤则引发高凝及炎症状态。评估与血栓炎症相关的循环生物标志物，可能为预测肿瘤预后提供一种有前景的工具，尤其是在预后不良的非小细胞肺癌（NSCLC）中。（2）目的：在一项NSCLC患者的前瞻性队列研究中，我们评估了血栓炎症生物标志物能否预测一线抗癌治疗前6个月内的早期疾病进展（DP）。（3）方法：研究共纳入719例新诊断的晚期NSCLC患者。在开始化疗前采集血液样本，检测全血细胞计数、高敏C反应蛋白（hs-CRP）、凝血因子VIII、纤维蛋白原、D-二聚体、凝血酶-抗凝血酶复合物（TAT）以及凝血酶原片段1+2（F1+2）。随访期间记录疾病进展情况。（4）结果：6个月内疾病进展的累积发生率为49%。单变量Cox回归分析显示，转移状态、体重指数、血红蛋白、白细胞计数、hs-CRP、凝血因子VIII、纤维蛋白原、TAT及D-二聚体是疾病进展的显著预测因子。在包含所有上述显著变量的多变量分析中，仅hs-CRP和D-二聚体水平与疾病进展保持强相关性。基于这两个变量建立的风险分层模型，能够显著识别出6个月内疾病进展高风险患者（风险比2.9；95%置信区间2.3–3.7），该模型同样适用于3个月、9个月及12个月的预测。（5）结论：我们的模型能够简便而精确地评估化疗期间的早期疾病进展。若经外部验证，该模型可显著优化晚期NSCLC管理中的医疗资源分配，确保患者获得尽可能最有效的治疗。
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