癌症患者复发性静脉血栓栓塞的风险：个体患者数据的Meta分析及预测模型的建立

Risk of Recurrent Venous Thromboembolism in Patients with Cancer: An Individual Patient Data Meta-analysis and Development of a Prediction Model

THROMBOSIS AND HAEMOSTASIS

影响因子:4.3

分区:医学2区 Top / 血液学2区外周血管病2区

发表日期:2025 Jun

作者: Vincent R Lanting, Toshihiko Takada, Floris T M Bosch, Andrea Marshall, Michael A Grosso, Annie M Young, Agnes Y Y Lee, Marcello Di Nisio, Gary E Raskob, Pieter W Kamphuisen, Harry R Büller, Nick van Es

DOI: 10.1055/a-2418-3960

摘要

约有7%的癌症相关静脉血栓栓塞（CAT）患者在抗凝治疗期间发生复发。识别高风险患者有助于指导治疗决策。本研究旨在识别临床预测因子并建立抗凝治疗期间复发性CAT的预测模型。我们采用来自四项随机对照试验（Hokusai VTE Cancer、SELECT-D、CLOT和CATCH）的数据，评估低分子量肝素或直接口服抗凝剂（DOACs）治疗的CAT患者。主要结局为在6个月随访期间经裁定的复发性CAT。利用多变量Logistic回归分析及向后选择法建立临床预测模型，并通过内部外部交叉验证进行验证。性能通过c-统计量和校准图评估。排除使用维生素K拮抗剂的患者后，合并数据集包含2245例癌症伴急性CAT患者，其中23%使用依度沙班，9%使用利伐沙班，47%使用达肝素，20%使用Tinzaparin。在6个月随访中，150例（6.7%）发生复发性CAT。最终模型的预测因子包括：年龄（限制立方样条）、乳腺癌（比值比[OR]：0.42；95%置信区间[CI]：0.20-0.87）、转移性疾病（OR：1.44；95%CI：1.01-2.05）、使用DOAC（OR：0.66；95%CI：0.44-0.98）及仅深静脉血栓（OR：1.72；95%CI：1.31-2.27）。模型的c-统计量为0.63（95%CI：0.54-0.72），表明区分能力有限。校准结果在不同研究中存在差异。该预测模型包含五个临床预测因子，区分能力有限，预测抗凝起始时的复发性CAT仍具挑战性。本研究由Thieme基于知识共享署名许可证（CC BY 4.0）开放发表，允许在正确引用的前提下自由使用、分发和复制（https://creativecommons.org/licenses/by/4.0/）。

Abstract

About 7% of patients with cancer-associated venous thromboembolism (CAT) develop a recurrence during anticoagulant treatment. Identification of high-risk patients may help guide treatment decisions.To identify clinical predictors and develop a prediction model for on-treatment recurrent CAT.For this individual patient data meta-analysis, we used data from four randomized controlled trials evaluating low-molecular-weight heparin or direct oral anticoagulants (DOACs) for CAT (Hokusai VTE Cancer, SELECT-D, CLOT, and CATCH). The primary outcome was adjudicated on-treatment recurrent CAT during a 6-month follow-up. A clinical prediction model was developed using multivariable logistic regression analysis with backward selection. This model was validated using internal-external cross-validation. Performance was assessed by the c-statistic and a calibration plot.After excluding patients using vitamin K antagonists, the combined dataset comprised 2,245 patients with cancer and acute CAT who were treated with edoxaban (23%), rivaroxaban (9%), dalteparin (47%), or tinzaparin (20%). Recurrent on-treatment CAT during the 6-month follow-up occurred in 150 (6.7%) patients. Predictors included in the final model were age (restricted cubic spline), breast cancer (odds ratio [OR]: 0.42; 95% confidence interval [CI]: 0.20-0.87), metastatic disease (OR: 1.44; 95% CI: 1.01-2.05), treatment with DOAC (OR: 0.66; 95% CI: 0.44-0.98), and deep vein thrombosis only as an index event (OR: 1.72; 95% CI: 1.31-2.27). The c-statistic of the model was 0.63 (95% CI: 0.54-0.72) after internal-external cross-validation. Calibration varied across studies.The prediction model for recurrent CAT included five clinical predictors and has only modest discrimination. Prediction of recurrent CAT at the initiation of anticoagulation remains challenging.The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).