Development and validation of a risk prediction model for PICC-related venous thrombosis in patients with cancer: A prospective cohort study

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Objective: To develop and validate a risk prediction model for predicting the risk of Peripherally Inserted Central Catheter-Related venous thrombosis (PICC-RVT) in cancer patients with PICCs. Method: A prospective cohort study of 281 cancer patients with PICCs was conducted from April 2023 to January 2024. Data on patient-, laboratory- and catheter-related risk factors were collected on the day of catheterization. Patients were investigated for PICC-RVT by Doppler sonography in the presence of PICC-RVT signs and symptoms. Univariate and multivariate regression analyses were used to identify independently associated risk factors of PICC-RVT and develop a risk prediction model. Results: 275 patients were finally included for data analysis, and 18 (6.5%) developed PICC-RVT. Four risk factors were identified as key predictors of PICC-RVT, including “diabetes requiring insulin (OR:8.016; 95%CI:1.157-55.536), major surgery (within 1 month and operation time >45 minutes) (OR:0.023; 95%CI:1.296-30.77), reduced limb activities of the PICC arm (OR:6.687; 95%CI:2.024-22.09)” and “catheter material (OR:3.319; 95%CI:0.940-11.723)”. The nomogram model was developed and internally validated with an area under the receiver operating characteristics curve (AUC) of 0.796 (95%CI:0.707-0.885). The Hosmer–Lemeshow goodness-of-ft was 1.685 ( p =0.194). Conclusion: The nomogram prediction model had good predictive performance. This model could help identify patients at the highest risk for PICC-RVT to guide effective prophylaxis. Further external validation studies of this nomogram model on a large sample are required.

Article activity feed