Key result
EHR-CAT model outperforms the Khorana score in predicting cancer-associated thrombosis risk.
Why the study?
Extensive external validation of the newly developed EHR-CAT risk assessment model across diverse patient populations is needed before clinical utilization.
Does the EHR-CAT risk assessment model improve discrimination of cancer-associated thrombosis risk compared to the Khorana score in patients with cancer?
Cohort (n=2,103)
No
Does the EHR-CAT risk assessment model improve discrimination of cancer-associated thrombosis risk compared to the Khorana score in patients with cancer?
The EHR-CAT risk assessment model provides better discrimination for cancer-associated thrombosis risk than the Khorana score, potentially improving targeted thromboprophylaxis.
May refine risk stratification for cancer-associated thrombosis; extends Khorana score in observational data but leaves open need for validation.
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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Neu et al. (2024) conducted a cohort in Cancer-associated thrombosis (n=2,103). EHR-CAT risk assessment model vs. Khorana score was evaluated on Discrimination of the risk of cancer-associated thrombosis (C statistic). The EHR-CAT risk assessment model demonstrated stronger discrimination for cancer-associated thrombosis risk compared to the classic Khorana score (C statistic 0.67 vs 0.58).
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