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

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.