Establishment of risk predictive nomogram model of upper extremity venous thrombosis associated with peripherally venous inserted central catheter in cancer patients
10.3760/cma.j.cn115355-20200221-00065
- VernacularTitle:肿瘤患者外周静脉置入中心静脉导管相关性上肢静脉血栓风险预测列线图模型构建
- Author:
Fangying YANG
1
;
Rongyu HUA
;
Wanying WU
;
Danfeng BI
;
Yi WU
;
Jinyu WANG
;
Liqin GAO
;
Guanmian LIANG
;
Hongjuan WU
Author Information
1. 中国科学院肿瘤与基础医学研究所 中国科学院大学附属肿瘤医院 浙江省肿瘤医院护理部，杭州 310022
- From:
Cancer Research and Clinic
2020;32(7):456-461
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of nomogram predictive model established by the risk factors of upper extremity venous thrombosis risk associated with peripherally venous inserted central catheter (PICC) in cancer patients.Methods:A total of 1 032 patients who underwent PICC insertion between January 2016 and March 2017 in Zhejiang Cancer Hospital were selected by using prospective cohort study and convenience sampling. Risk factors of upper extremity venous thrombosis risk associated with PICC in cancer patients were evaluated by using Cox regression model. The nomogram predictive model of upper extremity venous thrombosis risk associated with PICC insertion was constructed. Bootstrap method was used to complete the inside check, and figure calibration was used to verify the nomogram.Results:A multivariate Cox regression analysis showed that trombosis history ( HR = 27.82, 95% CI 8.17-94.88, P < 0.01) and hyperlipidemia ( HR = 3.01, 95% CI 1.31-6.93, P = 0.009) were independent risk factors for upper extremity venous thrombosis associated with PICC. The nomogram model C-index was 0.71 (95% CI 0.63-0.80) based on the above risk factors, which indicated that the nomogram had a good differentiation. The calibration curve for predicting the probability of upper extremity venous thrombosis risk associated with PICC within one week, two weeks and one month deviated slightly from the standard curve, suggesting that the model might overestimate the risk of upper extremity venous thrombosis associated with PICC in cancer patients. Conclusions:The nomogram model has a good predictive value and strong operability, which can be used to predict the probability of upper extremity venous thrombosis associated with PICC in cancer patients after PICC insertion. It can provide a reference for identifying the high-risk cancer patients and formulating proper therapeutic strategies.
