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Updated: Feb 5, 2026

A Patient-Derived Xenograft Model for Venous Malformation
Published on: June 15, 2020
Development of A Risk Assessment Model for Venous Thromboembolism among Patients with Cholangiocarcinoma
Piangrawee Niprapan1, Phichayut Phinyo2,3, Worakitti Lapisatepun4,5
1Division of Hematology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Abstract:
Venous thromboembolism (VTE) has a high incidence among patients with cholangiocarcinoma (CCA). However, appropriate risk assessment models (RAMs) for CCA are limited. This study aimed to develop a RAM for predicting VTE in patients with CCA. We conducted a retrospective study at a single university-based hospital in Thailand. We included consecutive patients who were newly diagnosed with CCA between January 2018 and December 2022. A total of 694 CCA patients were included in the study. A 12-month follow-up period, 91 patients (13.11%) developed VTE. The logistic regression analysis initially considered 18 potential clinical predictors, and after using backward elimination, five key predictors were identified: ECOG score ≥ 2, intrahepatic CCA, stage IV CCA, total bilirubin ≤ 13 mg/dL, and CA19-9 > 1600 U/mL. These predictors formed the basis of the scoring system. The resulting RAM achieved an area under the receiver operating characteristic curve (AuROC) of 0.70 (95% confidence interval [CI] 0.64-0.75), indicating acceptable discrimination. The scoring system, ranging from 0 to 6, was categorized into three groups. For the validation group, the AuROC curve was 0.68 (95% CI: 0.63-0.73). In addition, the model demonstrated consistently high NPV across all risk categories, indicating strong performance in ruling out VTE. Therefore, this score is most useful for identifying non-high-risk patients. In conclusion, a RAM for VTE in CCA was developed by incorporating five critical risk factors. This model may assist clinicians in identifying individuals for risk of VTE. External validation is warranted to confirm its generalizability.
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