大约 7% 的癌症相关静脉血栓栓塞 (CAT) 患者在抗凝治疗期间出现复发。识别高危患者可能有助于指导治疗决策。 确定临床预测因子并开发治疗中复发 CAT 的预测模型。 对于这个个体患者数据荟萃分析，我们使用了四项随机对照试验的数据，这些试验评估了低分子量肝素或直接口服抗凝剂 (DOAC) 治疗 CAT（Hokusai VTE Cancer、SELECT-D、CLOT 和 CATCH）的效果。主要结局是在 6 个月的随访期间判定治疗中复发 CAT。使用后向选择的多变量逻辑回归分析开发了临床预测模型。使用内部-外部交叉验证对该模型进行了验证。通过 c 统计量和校准图来评估性能。 排除使用维生素 K 拮抗剂的患者后，合并数据集包含 2,245 名患有癌症和急性 CAT 的患者，他们接受艾多沙班 (23%)、利伐沙班 (9%)、达肝素 (47%) 或亭扎肝素 (20%) 治疗。在 6 个月的随访期间，有 150 名患者 (6.7%) 复发治疗中 CAT。最终模型中包含的预测因素包括年龄（受限三次样条）、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），DOAC 治疗（OR：0.66；95% CI：0.44-0.98），深静脉血栓仅作为指标事件（OR：1.72；95% CI：1.31-2.27）。内部-外部交叉验证后，模型的 c 统计量为 0.63（95% CI：0.54-0.72）。不同研究的校准各不相同。 复发性 CAT 的预测模型包括五个临床预测因子，并且只有适度的区分度。抗凝治疗开始时预测 CAT 复发仍然具有挑战性。作者。这是 Thieme 根据知识共享署名许可条款发表的开放获取文章，只要正确引用原始作品，就允许不受限制地使用、分发和复制。 （https://creativecommons.org/licenses/by/4.0/）。

 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/).