Abstract
ObjectiveTo investigate the prognostic significance of metabolic syndrome (MetS) and its components in patients with bladder cancer (BCa) treated with radical cystectomy (RC).MethodsA total of 335 BCa patients who underwent RC between 2004 and 2019 at Peking University Third Hospital (PUTH) were analyzed retrospectively. The Kaplan-Meier method with the log-rank test was performed to assess overall survival (OS) and progression-free survival (PFS). Univariate and multivariate Cox proportional hazard models were conducted to identify the prognostic factors of OS and PFS before and after propensity score matching (PSM).ResultsEnrolled patients were allocated into two groups according to the presence or absence of MetS (n=84 MetS vs n=251 non-MetS), and 82 new matched pairs were identified to balance the baseline characteristics after 1:1 PSM. In the Kaplan-Meier analysis, MetS was associated with better OS (P=0.031) than the group without MetS. In addition, a body mass index (BMI) ≥ 25 was associated with better OS (P=0.011) and PFS (P=0.031), while low high-density lipoprotein cholesterol (HDL-C) was associated with worse OS (P=0.033) and PFS (P=0.010). In all patients, multivariate Cox analysis showed that hemoglobin, pathologic tumor stage and lymph node status were identified as independent prognostic factors for both OS and PFS, while age, MetS and HDL-C were independent prognostic factors only for OS. Reproducible results of multivariate analysis can still be observed in propensity matched patients. The results of further subgroup analysis revealed that the association of MetS with increased OS (P=0.043) and BMI ≥25 with increased OS (P=0.015) and PFS (P=0.029) was observed in non-muscle invasive bladder cancer (NMIBC) patients.ConclusionsMetS was independently associated with better OS in BCa patients after RC, and HDL-C was the only component of MetS that was independently associated with worse OS. MetS and HDL-C may become reliable prognostic biomarkers of OS in BCa patients after RC to provide individualized prognostication and assist in the formulation of clinical treatment strategies.
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