Development and Validation of A Risk Prediction Model for PICC Catheter-Related Infection in Patients with Hematological Malignancies Undergoing Chemotherapy
DING Lei
LI Xiaomin
HE Yusi
HE Xiaoling
YIN Guangli
CHEN Chun
Abstract：Objective To analyze the influencing factors for peripherally inserted central catheter(PICC)-related infections in patients with hematological malignancies after chemotherapy,and to develop and validate a risk prediction model.Methods A total of 311 patients with hematological malignancies admitted to the Department of Hematology(Geriatric)at the First Affiliated Hospital with Nanjing Medical University from June 2022 to December 2024 were randomly assigned to a modeling group(217 cases)or a validation group(94 cases).In the modeling group,patients were divided into an infection group(52 cases)and a non-infection group(165 cases)based on whether PICC-related infection occurred after chemotherapy.A risk prediction model was established using univariate and binary logistic regression analysis.The predictive performance of the model was evaluated using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results Among 311 chemotherapy patients with hematological malignancies,74 developed PICC-related infections.A total of 76 strains of pathogenic bacteria were isolated from blood cultures,including 11 strains of Gram-positive bacteria,50 strains of Gram-negative bacteria,and 15 strains of fungi.Age,number of chemotherapy cycles,number of punctures,catheter extrusion length,procalcitonin,and high-sensitivity C-reactive protein were identified as independent influencing factors for PICC-related infections in patients with hematological malignancies after chemotherapy(P<0.05).ROC curve analysis showed that the nomogram model predicted PICC-related infections in the modeling group with an AUC of 0.861(95%CI:0.806-0.916),a sensitivity of 0.883,and a specificity of 0.709.In the validation group,the AUC was 0.840(95%CI:0.724-0.956),with a sensitivity of 0.853 and a specificity of 0.684.The calibration curve analysis indicated that the calibration curve fitted well with the ideal curve.DCA showed that the net benefit was greater than 0 across all threshold probabilities.Conclusions The risk prediction model constructed in this study demonstrates good performance and can serve as a risk assessment tool for healthcare providers to predict PICC-related infections in patients with hematological malignancies after chemotherapy.It aids in the early identification of high-risk patients,thereby facilitating targeted preventive measures to reduce the incidence of infection and improve patient prognosis.
Keywords：hematological malignancieschemotherapyperipherally inserted central cathetercatheter-related infectionrisk prediction model
Publication Date：2025-10-20
Online Publishing Date：2025-10-28(First online date of this platform, not the publication date of the document)
Pages：6( 12-17 )