Evaluation of the Performance of Biomarkers in Predicting Hemodialysis Patients Survival Using Time-Dependent ROC Curve.

INTRODUCTION: End-stage kidney disease (ESKD) is a growing global public health problem, and patients undergoing hemodialysis (HD) experience a high mortality rate despite advances in medical care. Identifying reliable prognostic biomarkers is therefore essential. Regression-based survival models are widely used in HD studies; however, while they estimate associations, they do not directly quantify the predictive accuracy of biomarkers. This study aimed to evaluate the predictive performance of selected baseline biomarkers for survival in HD patients using the time-dependent receiver operating characteristic (ROC) curve. METHODS: This retrospective cohort study included 2,192 ESKD patients undergoing maintenance HD in Fars province, Iran, between 2011 and 2020. Time-dependent area under the ROC curve (AUC) values were calculated to assess the prognostic performance of baseline biomarkers at 3, 12, 24, and 36 months after initiation of dialysis. RESULTS: Age, serum albumin, creatinine, and calcium showed relatively better predictive performance for survival. For age, the AUCs at 3, 12, 24, and 36 months were 64.2, 57.1, 57.1, and 58.8, respectively, while corresponding values for serum albumin were 67.5, 62.3, 61.4, and 59.8. Serum albumin and calcium demonstrated higher discrimination for early survival, whereas serum creatinine showed more stable predictive performance over the follow-up period. The combined risk score outperformed individual biomarkers, with AUCs of 71.2, 63.9, 63.5, and 64.1 at 3, 12, 24, and 36 months, respectively. CONCLUSION: Time-dependent ROC analysis revealed time-varying prognostic performance of baseline biomarkers in HD patients and demonstrated improved discrimination when biomarkers were combined into a composite risk score.