一种新型癌症相关静脉血栓栓塞风险评估评分在安全网医院的外部验证。

IF 3.4 3区 医学 Q2 HEMATOLOGY Research and Practice in Thrombosis and Haemostasis Pub Date : 2024-12-03 eCollection Date: 2025-01-01 DOI:10.1016/j.rpth.2024.102650
Karlynn N Dulberger, Jennifer La, Ang Li, Saran Lotfollahzadeh, Asha Jose, Nhan V Do, Mary T Brophy, J Michael Gaziano, Katya Ravid, Vipul C Chitalia, Nathanael R Fillmore
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引用次数: 0

摘要

背景:癌症相关血栓形成(CAT)是癌症患者死亡的主要原因。然而,在癌症患者中使用药物血栓预防必须仔细评估,因为在这一人群中发生大出血事件的风险增加了2倍。最近开发了电子健康记录CAT (EHR-CAT)风险评估模型(RAM),其报告性能优于广泛使用的Khorana评分。在临床应用之前,广泛的RAM外部验证对于确定不同患者群体的准确性至关重要。目的:利用新英格兰最大的安全网医院波士顿医疗中心(BMC)的2103名癌症患者的数据,从外部验证EHR-CAT,并将该RAM与Khorana评分进行比较。方法:我们对2014年1月至2022年12月诊断的BMC癌症患者进行了回顾性研究,使用BMC肿瘤登记处和EHR系统的数据。我们使用判别和校准措施验证RAM。结果:EHR-CAT评分具有较强的判别CAT风险的能力(C统计值,0.67),显著高于经典Khorana评分(C统计值,0.58)。这种增加的辨别力反映了20%的患者被扩大的评分重新划分为高风险或低风险。该数据集的模型校准也很强。结论:在我们的外部验证中,最近公布的EHR-CAT评分明确并改进了CAT高、低风险患者的分离。使用这种扩展的CAT评分有助于提高高危癌症患者的预防治疗靶向性。
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External validation of a novel cancer-associated venous thromboembolism risk assessment score in a safety-net hospital.

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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来源期刊
CiteScore
5.60
自引率
13.00%
发文量
212
审稿时长
7 weeks
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