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基于超声结果和临床信息的癌症化疗患者导管相关性血栓形成预测模型的建立与验证。

Development and validation of a prediction model of catheter-related thrombosis in patients with cancer undergoing chemotherapy based on ultrasonography results and clinical information.

机构信息

Department of Ultrasound, Ningbo First Hospital, 59 Liuting Road, Ningbo, 315010, Zhejiang Province, People's Republic of China.

Department of Respiratory and Critical Care Medicine, Ningbo First Hospital, Ningbo, People's Republic of China.

出版信息

J Thromb Thrombolysis. 2022 Oct;54(3):480-491. doi: 10.1007/s11239-022-02693-7. Epub 2022 Aug 16.

Abstract

Central venous catheters can be used conveniently to deliver medications and improve comfort in patients with cancer. However, they can cause major complications. The current study aimed to develop and validate an individualized nomogram for early prediction of the risk of catheter-related thrombosis (CRT) in patients with cancer receiving chemotherapy. In total, 647 patients were included in the analysis. They were randomly assigned to the training (n = 431) and validation (n = 216) cohorts. A nomogram for predicting the risk of CRT in the training cohort was developed based on logistic regression analysis results. The accuracy and discriminatory ability of the model were determined using area under the receiver operating characteristic curve (AUROC) values and calibration plots. Multivariate logistic regression analysis showed that body mass index, risk of cancer-related thrombosis, D-dimer level, and blood flow velocity were independent risk factors of CRT. The calibration plot showed an acceptable agreement between the predicted and actual probabilities of CRT. The AUROC values of the nomogram were 0.757 (95% confidence interval: 0.717-0.809) and 0.761 (95% confidence interval: 0.701-0.821) for the training and validation cohorts, respectively. Our model presents a novel, user-friendly tool for predicting the risk of CRT in patients with cancer receiving chemotherapy. Moreover, it can contribute to clinical decision-making.

摘要

中心静脉导管在为癌症患者给药和提高舒适度方面非常方便。然而,它们也可能导致严重的并发症。本研究旨在开发和验证一种个体化列线图,以早期预测接受化疗的癌症患者发生导管相关性血栓形成(CRT)的风险。共有 647 例患者纳入分析。他们被随机分配到训练(n=431)和验证(n=216)队列。基于逻辑回归分析结果,在训练队列中开发了预测 CRT 风险的列线图。通过受试者工作特征曲线(AUROC)值和校准图确定模型的准确性和区分能力。多变量逻辑回归分析显示,体重指数、癌症相关血栓形成风险、D-二聚体水平和血流速度是 CRT 的独立危险因素。校准图显示 CRT 的预测概率和实际概率之间存在可接受的一致性。该列线图在训练队列和验证队列中的 AUROC 值分别为 0.757(95%置信区间:0.717-0.809)和 0.761(95%置信区间:0.701-0.821)。我们的模型为预测接受化疗的癌症患者 CRT 风险提供了一种新颖的、易于使用的工具。此外,它还可以为临床决策提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a2f/9553810/b19a9f4c5c02/11239_2022_2693_Fig1_HTML.jpg

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