AUTHOR=Liu Binliang , Xie Junying , Sun Xiaoying , Wang Yanfeng , Yuan Zhong , Liu Xiyu , Huang Zhou , Wang Jiani , Mo Hongnan , Yi Zongbi , Guan Xiuwen , Li Lixi , Wang Wenna , Li Hong , Ma Fei , Zeng Yixin
TITLE=Development and Validation of a New Clinical Prediction Model of Catheter-Related Thrombosis Based on Vascular Ultrasound Diagnosis in Cancer Patients
JOURNAL=Frontiers in Cardiovascular Medicine
VOLUME=7
YEAR=2020
URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2020.571227
DOI=10.3389/fcvm.2020.571227
ISSN=2297-055X
ABSTRACT=Background: Central venous catheters are convenient for drug delivery and improved comfort for cancer patients, but they also cause serious complications. The most common complication is catheter-related thrombosis (CRT).
Objectives: This study aimed to evaluate the incidence and risk factors for CRT in cancer patients and develop an effective prediction model for CRT in cancer patients.
Methods: The development of our prediction model was based on a retrospective cohort (n = 3,131) from the National Cancer Center. Our prediction model was confirmed in a prospective cohort from the National Cancer Center (n = 685) and a retrospective cohort from the Hunan Cancer Hospital (n = 61). The predictive accuracy and discriminative ability were determined by receiver operating characteristic (ROC) curves and calibration plots.
Results: Multivariate analysis demonstrated that sex, cancer type, catheter type, position of the catheter tip, chemotherapy status, and antiplatelet/anticoagulation status at baseline were independent risk factors for CRT. The area under the ROC curve of our prediction model was 0.741 (CI: 0.715–0.766) in the primary cohort and 0.754 (CI: 0.704–0.803) and 0.658 (CI: 0.470–0.845) in validation cohorts 1 and 2, respectively. The model also showed good calibration and clinical impact in the primary and validation cohorts.
Conclusions: Our model is a novel prediction tool for CRT risk that accurately assigns cancer patients into high- and low-risk groups. Our model will be valuable for clinicians when making decisions regarding thromboprophylaxis.