Risk Factors and Predictive Model for Peripherally Inserted Central Catheter Tip Migration in Patients With Bladder Cancer

<p style="text-align:justify;"> Objective: This study aimed to construct a predictive model for assessing the risk of peripherally inserted central catheter (PICC) tip migration in patients with bladder cancer, facilitating early detection and tailored management of high-risk cases through comprehensive risk stratification. <p style="text-align:justify;"> Methods: A total of 280 patients with bladder cancer who underwent PICC placement for chemotherapy at our institution between January 2021 to May 2023 were retrospectively enrolled and randomly allocated into a training set (n = 196) and a validation set (n = 84) in a 7:3 ratio. Independent risk factors were identified through univariate analysis, variable compression via Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression. Subsequently, random forest, support vector machine and K-nearest neighbour models were constructed. The optimal model was selected based on the area under the curve (AUC), calibration curves and decision curve analysis (DCA). Visualisation and interpretability were further assessed using a nomogram and SHapley Additive exPlanations (SHAP) values. <p style="text-align:justify;"> Results: The baseline characteristics were balanced between the training and validation sets (p > 0.05). Multivariate logistic regression analysis further confirmed that body mass index (BMI), abnormal catheter tip position, catheter indwelling duration, number of puncture attempts and range of motion in the limb with the catheter were independent risk factors for PICC tip migration (p < 0.05). The random forest model demonstrated optimal performance, with an AUC of 0.768 in the training set and 0.738 in the validation set. SHAP analysis indicated that the range of motion in the limb with the catheter, BMI and catheter indwelling duration were primary positive contributors. <div style="text-align:justify;"> Conclusions: BMI, abnormal catheter tip position, number of puncture attempts, range of motion in the limb with the catheter and catheter indwelling duration were identified as risk factors for PICC tip migration in patients with bladder cancer. The risk prediction model developed in this study, based on these factors, demonstrates substantial clinical predictive value. </div>

Publication Details

Journal
Archivos Españoles de Urología
Published
2026-01-01
DOI
https://doi.org/10.56434/j.arch.esp.urol.20267902.42
Primary Topic
Urinary Tract Infections Management
Type
article
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article

Risk Factors and Predictive Model for Peripherally Inserted Central Catheter Tip Migration in Patients With Bladder Cancer

Archivos Españoles de Urología
Urinary Tract Infections Management
article

Risk Factors and Predictive Model for Peripherally Inserted Central Catheter Tip Migration in Patients With Bladder Cancer

article en

Abstract

<p style="text-align:justify;"> Objective: This study aimed to construct a predictive model for assessing the risk of peripherally inserted central catheter (PICC) tip migration in patients with bladder cancer, facilitating early detection and tailored management of high-risk cases through comprehensive risk stratification. <p style="text-align:justify;"> Methods: A total of 280 patients with bladder cancer who underwent PICC placement for chemotherapy at our institution between January 2021 to May 2023 were retrospectively enrolled and randomly allocated into a training set (n = 196) and a validation set (n = 84) in a 7:3 ratio. Independent risk factors were identified through univariate analysis, variable compression via Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression. Subsequently, random forest, support vector machine and K-nearest neighbour models were constructed. The optimal model was selected based on the area under the curve (AUC), calibration curves and decision curve analysis (DCA). Visualisation and interpretability were further assessed using a nomogram and SHapley Additive exPlanations (SHAP) values. <p style="text-align:justify;"> Results: The baseline characteristics were balanced between the training and validation sets (p > 0.05). Multivariate logistic regression analysis further confirmed that body mass index (BMI), abnormal catheter tip position, catheter indwelling duration, number of puncture attempts and range of motion in the limb with the catheter were independent risk factors for PICC tip migration (p < 0.05). The random forest model demonstrated optimal performance, with an AUC of 0.768 in the training set and 0.738 in the validation set. SHAP analysis indicated that the range of motion in the limb with the catheter, BMI and catheter indwelling duration were primary positive contributors. <div style="text-align:justify;"> Conclusions: BMI, abnormal catheter tip position, number of puncture attempts, range of motion in the limb with the catheter and catheter indwelling duration were identified as risk factors for PICC tip migration in patients with bladder cancer. The risk prediction model developed in this study, based on these factors, demonstrates substantial clinical predictive value. </div>

Archivos Españoles de UrologíaVol. 79(2)
Openalex Percentile: Top 5%
Urinary Tract Infections Management
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Risk Factors and Predictive Model for Peripherally Inserted Central Catheter Tip Migration in Patients With Bladder Cancer · Archivos Españoles de Urología (2026) | TGRS Research Map | TGRS