Development and Validation of a New Clinical Prediction Model of Catheter-Related Thrombosis Based on Vascular Ultrasound Diagnosis in Cancer Patients
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 CR...
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Veröffentlicht in: | Frontiers in cardiovascular medicine 2020-10, Vol.7, p.571227-571227 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 2297-055X 2297-055X |
DOI: | 10.3389/fcvm.2020.571227 |