Comparative Evaluation of Risk Assessment Models for Predicting Venous Thromboembolic Events in Cancer Patients with Implanted Central Venous Access Devices

Background/Objectives: Cancer patients using implantable venous access devices for chemotherapy have an elevated risk of venous thromboembolism (VTE), but the utility of existing risk models in this group is understudied. This study aims to evaluate the VTE incidence, risk factors, and the predictive performance of the Khorana, COMPASS, and ONKOTEV models. Methods: Medical records of adult cancer patients who received chemotherapy via ICVADs were retrospectively reviewed. Cumulative incidence (CI) of VTEs was estimated using the Fine and Gray method. RAM performance was assessed by sensitivity, specificity, predictive values, and accuracy. 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%). Over a median follow-up of 16.5 months, VTEs occurred in 82 (18.4%) patients, with 43 (9.6%) being ICVAD-related. Median time to VTE was 117 days overall and 68 days for ICVAD-related events. The CI of VTEs at 30, 90, 180, 360, and 720 days was 0.9%, 5.8%, 8.1%, 9.0%, and 18.4%, respectively. ONKOTEV showed the best predictive performance (sensitivity 33.3%, specificity 85.7%, accuracy 74.4%). The 1-year VTE incidence was significantly higher in the ONKOTEV high-risk group (28.5%) versus low-risk (12.4%, p<0.001). VTE was independently associated with inferior OS (HR 1.39, p=0.037). Conclusions: Cancer patients with ICVADs have an increased risk of early VTEs. Among the RAMs, ONKOTEV showed superior predictive ability. Prospective studies are warranted to assess individualized VTE prophylaxis guided by validated RAMs.