(1) Background: The presence of metastatic disease significantly increases the risk of venous thromboembolism (VTE) in breast cancer, particularly during chemotherapy. Although not categorized as a highly thrombogenic malignancy, the elevated global prevalence of this cancer places a substantial number of patients at risk of thrombosis, which cannot yet be accurately predicted by validated risk assessment models (RAMs), highlighting the need for a dedicated model. (2) Aim: This study aims to develop a RAM for VTE in newly diagnosed metastatic breast cancer patients enrolled in a prospective, observational, and multicenter study. (3) Methods: A cohort of 189 patients beginning antitumor therapy were enrolled and prospectively monitored for VTE and mortality. Blood samples collected at enrollment were tested for D-dimer, fibrinogen, FVIII, prothrombin fragment 1 + 2 (F1 + 2), and thrombin generation (TG). Competing risk analyses were performed to identify significant predictors. (4) Results: Within one year, the cumulative incidences of VTE and mortality were 7.0% and 12%, respectively. Univariable analysis identified high Ki-67, D-dimer, FVIII, fibrinogen, and TG levels, along with low hemoglobin levels, as independent predictors of VTE. Only Ki-67, fibrinogen, FVIII, and hemoglobin were retained as significant predictors in multivariable analysis. These variables were further examined by multiple linear regression, which revealed Ki-67 and fibrinogen as the most significant parameters. A continuous RAM was then developed based on Ki-67 and fibrinogen (c-statistics 0.78), categorizing patients into low-risk and high-risk groups for VTE (2% vs. 13%; SHR 3.6,p= 0.018). This stratification could not be achieved using currently validated models for VTE risk. (5) Conclusions: We developed an accurate RAM for VTE that enables the identification of metastatic breast cancer patients at high risk for VTE, which supports clinicians in personalized thromboprophylaxis strategies if externally validated.
（1）背景：转移性疾病的存在显著增加了乳腺癌患者发生静脉血栓栓塞（VTE）的风险，尤其是在化疗期间。尽管乳腺癌未被归类为高血栓形成性恶性肿瘤，但其全球患病率的升高使大量患者面临血栓风险，而目前经过验证的风险评估模型（RAMs）尚无法准确预测此类风险，这凸显了开发专用模型的必要性。（2）目的：本研究旨在基于一项前瞻性、观察性、多中心研究，为新诊断的转移性乳腺癌患者开发一个VTE风险评估模型。（3）方法：研究纳入189名开始抗肿瘤治疗的患者，并对其VTE发生率和死亡率进行前瞻性监测。在入组时采集的血样检测了D-二聚体、纤维蛋白原、凝血因子VIII（FVIII）、凝血酶原片段1+2（F1+2）以及凝血酶生成（TG）。通过竞争风险分析确定显著预测因子。（4）结果：一年内，VTE和死亡率的累积发生率分别为7.0%和12%。单变量分析显示，高Ki-67、D-二聚体、FVIII、纤维蛋白原和TG水平，以及低血红蛋白水平是VTE的独立预测因子。在多变量分析中，仅Ki-67、纤维蛋白原、FVIII和血红蛋白保留为显著预测因子。通过多元线性回归进一步检验这些变量，发现Ki-67和纤维蛋白原是最显著的参数。随后基于Ki-67和纤维蛋白原开发了一个连续风险评估模型（c统计量0.78），将患者分为VTE低风险组和高风险组（2% vs. 13%；SHR 3.6，p=0.018）。使用当前已验证的VTE风险模型无法实现此种风险分层。（5）结论：我们开发了一个准确的VTE风险评估模型，能够识别出具有高VTE风险的转移性乳腺癌患者，若经外部验证，该模型可为临床医生制定个体化血栓预防策略提供支持。
肿瘤(癌症)患者之家