Biomarkers in predicting mortality among hemodialysis patients: recent advances

Patients undergoing maintenance hemodialysis face annual mortality rates of 15%-27%, with cardiovascular causes accounting for more than half of all deaths. Despite advances in dialytic technology, conventional prognostic models derived from the general population systematically underestimate risk in end‑stage renal disease, failing to capture the complexity of uremic pathophysiology that drives this excess mortality: immune dysregulation, chronic inflammation, oxidative stress, vascular calcification, uremic cardiomyopathy, protein‑energy wasting, and accelerated vascular aging. This narrative review synthesizes current evidence on biomarkers predicting all‑cause and cardiovascular mortality in hemodialysis patients, spanning established markers (albumin, C‑reactive protein, ferritin, hemoglobin, high‑sensitivity troponins, and N‑terminal pro-B‑type natriuretic peptide) to an emerging frontier encompassing interleukin‑6, pentraxin-3, soluble suppression of tumorigenicity‑2, galectin‑3, fibroblast growth factor-23, Klotho, and multiomics signatures. We further examine composite neutrophil‑derived indices, adipokines, and mineral metabolism markers as tools for pathway‑specific risk interrogation. The evidence converges on a clear practical message: combination and dynamic approaches are better than single, static measurements. Multibiomarker models consistently outperform individual markers, and longitudinal trajectories carry prognostic information (with divergence between survivors and nonsurvivors detectable many months before death) that a single time‑point value cannot replicate. Advances in artificial intelligence and multiomics further support this shift toward dynamic, personalized risk stratification, though these approaches remain at an early, largely exploratory stage. Critically, clinical translation remains limited by the lack of dialysis‑specific thresholds, poor standardization, and the absence of randomized evidence demonstrating that biomarker‑guided strategies improve outcomes. Bridging this gap between prognostic insight and clinical application remains the central challenge of precision nephrology.