ArticleResearch and practice in thrombosis and haemostasis2025
External validation of a novel cancer-associated venous thromboembolism risk assessment score in a safety-net hospital.
Article in Research and practice in thrombosis and haemostasis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Temporal validation of the electronic health record cancer-associated thrombosis model in patients with low bleeding risk.Research and practice in thrombosis and haemostasis · 2026Article
- Prediction of cancer-associated thrombosis by machine learning: results from the Vienna Cancer and Thrombosis Study.ESMO open · 2026Article
- A deep learning model to dynamically predict cancer-associated thromboembolism in large-scale healthcare systems.NPJ digital medicine · 2026Article
- Validation of a Risk Score for Cancer-Associated Thrombosis Using Nationwide EHR Data.JAMA network open · 2025Article
- Radiotherapy-the not-so-insignificant contributor to cancer-associated venous thrombosis.Research and practice in thrombosis and haemostasis · 2025Review
- Diosmetin Inhibits NETs Formation in Neutrophils Through Regulating Nrf2 Signaling.Thoracic cancer · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
Background: Cancer-associated thrombosis (CAT) is a leading cause of death in patients diagnosed with cancer. However, pharmacologic thromboprophylaxis use in cancer patients must be carefully evaluated due to a 2-fold increased risk of experiencing a major bleeding event within this population. The electronic health record CAT (EHR-CAT) risk assessment model (RAM) was recently developed, and reports improved performance over the widely used Khorana score. Extensive RAM external validation is crucial to determine accuracy across diverse patient populations prior to clinical utilization. Objectives: To externally validate EHR-CAT using data from 2103 patients with cancer at the Boston Medical Center (BMC), New England's largest safety-net hospital, and to compare this RAM with the Khorana score. Methods: We conducted a retrospective study of BMC cancer patients diagnosed between January 2014 and December 2022 using data from the BMC tumor registry and EHR system. We validated the RAM using measures of discrimination and calibration. Results: The EHR-CAT score exhibited a strong ability to discriminate the risk of CAT (C statistic, 0.67), which was substantially higher than the classic Khorana score (C statistic, 0.58). This increased discrimination power reflects the 20% of patients that were reclassified into high or low risk by the expanded score. Model calibration was also strong in this dataset. Conclusion: In our external validation, the recently published EHR-CAT score showed clear and improved separation of patients at high and low risk for CAT. The utilization of this expanded CAT score could facilitate improved targeting of at-risk cancer patients for prophylactic therapy.
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