A nomogram predicting venous thromboembolism risk in primary liver cancer patients.

IF 2.3 3区医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

Journal of Thrombosis and Thrombolysis Pub Date : 2025-01-01 Epub Date: 2024-09-21 DOI:10.1007/s11239-024-03041-7

Haike Lei, Xiaosheng Li, Zuhai Hu, Qianjie Xu, Qingdong Li, Rong Zhou, Qianwen Yu, Jing Xiao

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引用次数: 0

Abstract

Cancer frequently causes venous thromboembolism (VTE), a leading cause of cancer-related mortality. Primary liver cancer (PLC) is prevalent and highly fatal, with an increased risk of venous thrombotic complications. Thus, we aimed to develop a nomogram model for predicting VTE in patients with PLC. We retrospectively analyzed 1,565 patients diagnosed with PLC between January 2018 and December 2022 at Chongqing University Cancer Hospital. Univariate logistic analysis and multivariate logistic regression identified eight significant risk factors: activated partial thromboplastin time (APTT) ≤ 32.20 s, D-dimer > 1.44 mg/L, lymphocyte count (LYM) ≤ 1.18 × 10⁹/L, monocyte count (MONO) > 0.42 × 10⁹/L, transarterial chemoembolization (TACE), surgical intervention, immunotherapy, and β2-microglobulin. The nomogram model exhibited strong discriminatory power, with C indices of 0.753 and 0.710 for the training and validation cohorts, respectively. The calibration curve showed a strong correlation between predicted and actual probabilities. Additionally, decision curve analysis (DCA) and clinical impact curves (CIC) confirmed the model's clinical utility. This nomogram facilitates the identification of high-risk PLC patients, allowing for timely preventive and therapeutic interventions to reduce the risk of thrombosis.

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预测原发性肝癌患者静脉血栓栓塞风险的提名图。

癌症经常导致静脉血栓栓塞（VTE），这是癌症相关死亡的主要原因。原发性肝癌（PLC）发病率高，死亡率高，静脉血栓并发症的风险增加。因此，我们的目标是建立一个预测 PLC 患者 VTE 的提名图模型。我们回顾性分析了重庆大学附属肿瘤医院2018年1月至2022年12月期间确诊的1565例PLC患者。单变量逻辑分析和多变量逻辑回归确定了8个重要的风险因素：活化部分凝血活酶时间（APTT）≤32.20 s、D-二聚体>1.44 mg/L、淋巴细胞计数（LYM）≤1.18 × 109/L、单核细胞计数（MONO）>0.42 × 109/L、经动脉化疗栓塞（TACE）、手术干预、免疫治疗和β2-微球蛋白。提名图模型具有很强的判别能力，训练组和验证组的 C 指数分别为 0.753 和 0.710。校准曲线显示，预测概率与实际概率之间具有很强的相关性。此外，决策曲线分析（DCA）和临床影响曲线（CIC）证实了该模型的临床实用性。该提名图有助于识别高风险的 PLC 患者，以便及时采取预防和治疗干预措施，降低血栓形成的风险。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Thrombosis and Thrombolysis 医学-外周血管病

CiteScore

9.20

自引率

0.00%

发文量

112

审稿时长

4-8 weeks

期刊介绍： The Journal of Thrombosis and Thrombolysis is a long-awaited resource for contemporary cardiologists, hematologists, vascular medicine specialists and clinician-scientists actively involved in treatment decisions and clinical investigation of thrombotic disorders involving the cardiovascular and cerebrovascular systems. The principal focus of the Journal centers on the pathobiology of thrombosis and vascular disorders and the use of anticoagulants, platelet antagonists, cell-based therapies and interventions in scientific investigation, clinical-translational research and patient care. The Journal will publish original work which emphasizes the interface between fundamental scientific principles and clinical investigation, stimulating an interdisciplinary and scholarly dialogue in thrombosis and vascular science. Published works will also define platforms for translational research, drug development, clinical trials and patient-directed applications. The Journal of Thrombosis and Thrombolysis'' integrated format will expand the reader''s knowledge base and provide important insights for both the investigation and direct clinical application of the most rapidly growing fields in medicine-thrombosis and vascular science.