BackgroundOxidative stress plays an important role in the occurrence and development of malignancy. However, the relationship between oxidative stress and upper urinary tract urothelial carcinoma (UTUC) prognosis remains elusive. This study aimed to evaluate the prognostic value of systematic oxidative stress indices as a predictor of patient outcomes in UTUC after radical nephroureterectomy.MethodsClinical data for 483 patients with UTUC who underwent radical nephroureterectomy were analyzed. Patients were categorized according to an optimal value of systematic oxidative stress indices (SOSIs), including fibrinogen (Fib), gamma-glutamyl transpeptidase (γ-GGT), creatinine (CRE), lactate dehydrogenase (LDH) and albumin (ALB). Kaplan–Meier analyses were used to investigate associations of SOSIs with overall survival (OS) and progression-free survival (PFS). Moreover, associations between SOSIs and OS and PFS were assessed with univariate and multivariate analyses.ResultsHigh values of Fib, γ-GGT, CRE, and LDH, and low values of ALB were associated with reduced OS. SOSIs status correlated with age, tumor site, surgical approach, hydronephrosis, tumor size, T stage, and lymph node status. The Kaplan–Meier survival analysis showed a significant discriminatory ability for death and progression risks in the two groups based on SOSIs. Multivariate Cox proportional hazards models showed that SOSIs were an independent prognostic indicator for OS (p = 0.007) and PFS (p = 0.021). SOSIs and clinical variables were selected to establish a nomogram for OS. The 1-, 3-, and 5-year AUC values were 0.77, 0.78, and 0.81, respectively. Calibration curves of the nomogram showed high consistencies between the predicted and observed survival probability. Decision curve analysis curves showed that the nomogram could well predict the 1‐year, 3-year, and 5‐year OS.ConclusionsSOSIs are an independent unfavorable predictor of OS and PFS in patients diagnosed with UTUC undergoing RNU. Therefore, incorporating SOSIs into currently available clinical parameters may improve clinical decision-making.