Work

Optimal prediction of peritoneal dialysis to hemodialysis transition: a penalized fine-gray model

Year: 2026

Type: article

Abstract: Background: Traditional Cox proportional hazards models overestimate the risk of progression from peritoneal dialysis (PD) to hemodialysis (HD). This study aims to screen high-risk conversion populations using competing risk models. Methods: In this multicenter retrospective cohort study, we enrolled patients aged ≥16 years who were undergoing regular PD for >1 month; transition from PD to HD was the target event. When death was recognized as a competing event, we employed cause-specific proportional hazards and Fine-Gray models for multivariate analysis. A conventional LASSO-Cox model was also established for comparative purposes. Model performance was evaluated using time-dependent area under the curve (AUC) and C-index curves. The best model was identified to construct the cumulative incidence nomogram for PD to HD at the 3-, 6-, and 9-year time points. Results: = 209). The penalized Fine-Gray model was identified as the optimal model (AUC: 0.716, C-index: 0.662). Body mass index, history of peritonitis hospitalization, and nutrition-related parameters were identified as optimal predictors for transitioning from PD to HD. AUC values for the penalized Fine-Gray model at 3, 6, and 9 years were 0.675, 0.715, and 0.714, respectively. We constructed a nomogram for 3, 6, and 9 years based on the penalized Fine-Gray model, which demonstrated significant clinical utility. Conclusion: The penalized Fine-Gray model serves as the optimal choice for predicting the transition from PD to HD, and the nomogram constructed based on this model exhibits favorable clinical applicability.

Source: Frontiers in Medicine

DOI: 10.3389/fmed.2026.1843381