What is the Role of the Preoperative Blood-Based Inflammation Biomarkers in the Prognosis of Upper Tract Urothelial Carcinoma With Radical Nephroureterectomy? A Single-Centre Retrospective Study

术前血液炎症生物标志物在根治性肾输尿管切除术治疗上尿路尿路上皮癌预后中的作用是什么?一项单中心回顾性研究

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Abstract

Objective: To assess the prognostic value of preoperative blood-based inflammation biomarkers, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR), on the survival outcomes of patients with upper tract urothelial carcinoma (UTUC) following radical nephroureterectomy (RNU). Methods: We retrospectively studied the data of 172 patients who were diagnosed with UTUC after RNU during 2008 to 2018. We determined the cut-off value by using X-tile software. The area under the curve (AUC) and concordance index (C-index) were utilized to compare the predictive accuracy between subgroups. We also performed decision curve analysis (DCA) to evaluate the clinical net benefit of prognostic models. The Kaplan-Meier method and Cox proportional hazards regression models were performed to evaluate the association between these inflammation biomarkers and survival outcomes. Results: The median follow-up period was 45.5 (range: 1-143; interquartile range, IQR: 27-77) months. Kaplan-Meier analyses showed that a high NLR or PLR significantly reduced overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS) and metastasis-free survival (MFS), and a low LMR markedly decreased RFS and MFS. The multivariate Cox proportional hazards model revealed that the NLR plus PLR was an independent predictor of worse survival (all P < .05). Additionally, the AUC and C-index of the new prognostic models were the largest for the 1- to 5-year OS, CSS, RFS, and MFS were the largest. Conclusion: Our study confirms that the combination of preoperative NLR and PLR could be an independent risk factor for UTUC patients who have undergone RNU. The addition of NLR and PLR may improve the accuracy of current prognostic models and help guide clinical strategies in the treatment of UTUC.

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