Zhilei Zhang1,2, Yongbo Yu1,2, Jilu Zheng1,2, Mingxin Zhang1, Haitao Niu3. 1. Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China. 2. Department of Clinical Medicine, Qingdao University, Qingdao, China. 3. Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China. niuht0532@126.com.
Abstract
BACKGROUND: Inflammatory response biomarkers have been studied as promising prognostic factors in renal cell carcinoma, but few studies have focused on papillary renal cell carcinoma (PRCC). This study was performed to evaluate the prognostic value of the preoperative neutrophil-to-lymphocyte ratio (NLR) in PRCC patients. METHODS: In total, 122 postoperative PRCC patients selected from 366 non-clear cell renal cell carcinoma patients were enrolled from our institution between 2012 and 2020. The optimal cutoff value of the NLR was assessed by receiver operating characteristic (ROC) curve analysis, and the Kaplan-Meier method and Cox's proportional hazards regression models were performed to analyze the association of the NLR with overall survival (OS). In addition, the potential of tumor-node-metastasis (TNM) stage, the NLR and an NLR-TNM system to predict survival were compared with ROC curves, and clinical usefulness of the predicting models were assessed by decision curve analysis. RESULTS: A threshold value of 2.39 for the NLR for OS analysis was determined by ROC curve analysis. An NLR ≥ 2.39 was associated with a more advanced TNM stage (P < 0.01) and larger tumors (P < 0.05) than a low NLR, as well as pathological subtype II (P < 0.05), and the patients with a high NLR also exhibited significantly worse overall survival outcomes (P < 0.05). The NLR was determined to be a significant independent prognostic indicator by univariable and multivariable analyses (HR = 5.56, P < 0.05). Furthermore, TNM stage and the NLR were integrated, and the area under the curve (AUC) of for the NLR-TNM system was larger than that of for the TNM system when predicting overall survival (0.84 vs 0.73, P = 0.04). Decision curve analysis also demonstrated a better clinical value for the NLR-TNM model to predict the prognosis. CONCLUSION: A high preoperative NLR was associated with poor clinical and pathologic parameters in patients with PRCC; moreover, the NLR was also an independent prognostic factor for the OS of patients with PRCC. The NLR-TNM system, which was a model that integrated the NLR with TNM staging, could improve the ability to predict overall survival.
BACKGROUND: Inflammatory response biomarkers have been studied as promising prognostic factors in renal cell carcinoma, but few studies have focused on papillary renal cell carcinoma (PRCC). This study was performed to evaluate the prognostic value of the preoperative neutrophil-to-lymphocyte ratio (NLR) in PRCCpatients. METHODS: In total, 122 postoperative PRCCpatients selected from 366 non-clear cell renal cell carcinomapatients were enrolled from our institution between 2012 and 2020. The optimal cutoff value of the NLR was assessed by receiver operating characteristic (ROC) curve analysis, and the Kaplan-Meier method and Cox's proportional hazards regression models were performed to analyze the association of the NLR with overall survival (OS). In addition, the potential of tumor-node-metastasis (TNM) stage, the NLR and an NLR-TNM system to predict survival were compared with ROC curves, and clinical usefulness of the predicting models were assessed by decision curve analysis. RESULTS: A threshold value of 2.39 for the NLR for OS analysis was determined by ROC curve analysis. An NLR ≥ 2.39 was associated with a more advanced TNM stage (P < 0.01) and larger tumors (P < 0.05) than a low NLR, as well as pathological subtype II (P < 0.05), and the patients with a high NLR also exhibited significantly worse overall survival outcomes (P < 0.05). The NLR was determined to be a significant independent prognostic indicator by univariable and multivariable analyses (HR = 5.56, P < 0.05). Furthermore, TNM stage and the NLR were integrated, and the area under the curve (AUC) of for the NLR-TNM system was larger than that of for the TNM system when predicting overall survival (0.84 vs 0.73, P = 0.04). Decision curve analysis also demonstrated a better clinical value for the NLR-TNM model to predict the prognosis. CONCLUSION: A high preoperative NLR was associated with poor clinical and pathologic parameters in patients with PRCC; moreover, the NLR was also an independent prognostic factor for the OS of patients with PRCC. The NLR-TNM system, which was a model that integrated the NLR with TNM staging, could improve the ability to predict overall survival.
Authors: Seok-Soo Byun; Eu Chang Hwang; Seok Ho Kang; Sung-Hoo Hong; Jinsoo Chung; Tae Gyun Kwon; Hyeon Hoe Kim; Cheol Kwak; Yong-June Kim; Won Ki Lee Journal: Biomed Res Int Date: 2016-11-06 Impact factor: 3.411