Background/Objectives: Cancer patients using implanted venous access devices (ICVADs) for chemotherapy are at increased risk of venous thromboembolism (VTE), but the performance of risk assessment models (RAMs) in this setting is understudied. This study evaluated VTE incidence, risk factors, and the predictive performance of the Khorana, COMPASS-CAT, and ONKOTEV models. Methods: We retrospectively reviewed records of adult cancer patients treated with chemotherapy via ICVADs. The cumulative incidence (CI) of VTEs was estimated using the Fine–Gray method, and RAM performance was assessed by sensitivity, specificity, predictive values, accuracy, and AUC. Overall survival (OS) was analyzed using Kaplan–Meier and log-rank tests. Results: A total of 446 patients were included. The most common cancers were colorectal (29.6%), gastric (26%), pancreatic (18.4%), and breast (13.9%). During a median follow-up of 16.5 months, VTEs occurred in 82 patients (18.4%), including 43 (9.6%) that were ICVAD-related. Median time to VTE was 117 days and 68 days for ICVAD-related events. The CI of VTEs was 9% at 1 year and 18.4% at 2 years. ONKOTEV showed the best performance (accuracy of 74.4%, specificity of 85.7%, and AUC of 0.607), with 1-year incidence higher in the high-risk group (28.5% vs. 12.4%,p< 0.001). In contrast, all RAMs showed limited ability for ICVAD-related VTEs. VTE was independently associated with inferior OS (HR 1.39,p= 0.037). Conclusions: Cancer patients with ICVADs face a substantial risk of early VTEs. Among evaluated RAMs, ONKOTEV performed best for overall but not ICVAD-related events. Prospective studies are needed to guide prophylaxis strategies using validated RAMs.
**背景/目的：** 使用植入式静脉通路装置进行化疗的癌症患者，其静脉血栓栓塞风险增加，但风险预测模型在此类患者中的预测效能尚缺乏充分研究。本研究旨在评估VTE发生率、危险因素，以及Khorana、COMPASS-CAT和ONKOTEV模型的预测性能。 **方法：** 我们回顾性分析了通过ICVAD接受化疗的成年癌症患者的病历资料。采用Fine-Gray法估计VTE的累积发生率，并通过敏感性、特异性、预测值、准确率和曲线下面积评估RAM的预测性能。采用Kaplan-Meier法和log-rank检验分析总生存期。 **结果：** 共纳入446例患者。最常见的癌症类型为结直肠癌（29.6%）、胃癌（26%）、胰腺癌（18.4%）和乳腺癌（13.9%）。中位随访16.5个月期间，82例患者（18.4%）发生VTE，其中43例（9.6%）为ICVAD相关VTE。VTE发生的中位时间为117天，ICVAD相关事件为68天。VTE的1年和2年累积发生率分别为9%和18.4%。ONKOTEV模型表现出最佳预测性能（准确率74.4%，特异性85.7%，AUC 0.607），其高风险组的1年VTE发生率显著高于低风险组（28.5% vs. 12.4%，p < 0.001）。相比之下，所有RAM对ICVAD相关VTE的预测能力均有限。VTE是OS较差的独立相关因素（HR 1.39，p = 0.037）。 **结论：** 使用ICVAD的癌症患者面临较高的早期VTE风险。在评估的RAM中，ONKOTEV模型对总体VTE的预测性能最佳，但对ICVAD相关事件预测不佳。需要前瞻性研究来指导基于有效RAM的预防策略。
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