Comparison between the Khorana prediction score and Caprini risk assessment models for assessing the risk of venous thromboembolism in hospitalized patients with cancer: a retrospective case control study

医学 静脉血栓栓塞 风险评估 内科学 肺栓塞 回顾性队列研究 深静脉 静脉血栓形成 逻辑回归 风险因素 急诊医学 接收机工作特性 弗雷明翰风险评分 优势比 外科
作者
Yanfei Hu,Xiaoqian Li,Haixia Zhou,Ping Lin,Jiarui Zhang,Dong Huang,Min Qi,Yanjuan Tang,Qun Yi,Zongan Liang,Maoyun Wang
出处
期刊:Interactive Cardiovascular and Thoracic Surgery [Oxford University Press]
卷期号:31 (4): 454-460 被引量:5
标识
DOI:10.1093/icvts/ivaa137
摘要

Abstract OBJECTIVES This study aimed to evaluate the optimal risk assessment model (RAM) to stratify the risk of venous thromboembolism (VTE) in hospitalized patients with cancer. We examined and compared the VTE predictive ability of the Khorana score (KS) and the Caprini RAM in hospitalized cancer patients. METHODS We performed a retrospective case–control study among hospitalized cancer patients admitted to a comprehensive hospital in China from January 2015 to December 2016. A total of 221 cases were confirmed to have VTE during hospitalization and 221 controls were selected randomly. The Caprini RAM and KS were implemented and the individual scores of each risk factor were summed to generate a cumulative risk score. Meanwhile, the sensitivity, specificity, areas under curve of the receiver operating characteristic curve and calibration of these 2 models were analysed. RESULTS Significant differences were observed in risk factors between VTE and non-VTE hospitalized cancer patients and the VTE risk increased significantly with an increase in the cumulative KS or Caprini RAM score. A classification of ‘high risk’ according to KS and Caprini RAM was associated with 2.272-fold and 3.825-fold increases in VTE risk, respectively. However, the Caprini RAM could identify 82.4% of the VTE cases that required preventive anticoagulant therapy according to American College of Chest Physicians guidelines, whereas the KS could only identify 35.3% of the VTE cases. In addition, the areas under curve of Caprini RAM were significantly higher than those of the KS (0.705 ± 0.024 vs 0.581 ± 0.025, P < 0.001), with a best cut-off value of 5 score, which happened to be the cut-off value for high risk of VTE in Caprini RAM. Both Caprini RAM and KS showed an excellent calibration curve (0.612 vs 0.141, P > 0.05), but the risk of VTE events predicted by Caprini seemed closer to the observed risk of VTE events. CONCLUSIONS The Caprini RAM was found to be more effective than the KS in identifying hospitalized patients with cancer at risk of VTE.
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