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Predictive value of neutrophil-to-lymphocyte ratio in diagnosis of prostate cancer among men who underwent template-guided prostate biopsy

机译:模板指导的前列腺穿刺活检的男性中性粒细胞与淋巴细胞比值对诊断前列腺癌的预测价值

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摘要

To evaluate the predictive value of neutrophil-to-lymphocyte ratio (NLR) in diagnosis of prostate cancer (PCa). Data of 662 patients who underwent prostate biopsy from January 2012 to June 2016 were retrospectively reviewed. The receiver operating characteristic–derived area under the curve analyses were performed to assess the predictive accuracy. Simultaneously, Youden's index was calculated to determine the optimal NLR cutoff. Furthermore, univariate and multivariate logistic regression analyses were performed to determine the association between NLR value and PCa detection. On account of an NLR value of 2.44 was shown with the maximal Youden's index on the receiver operating characteristic curve, the cutoff value of NLR was set at 2.44. Accordingly, patients were classified into high-NLR or low-NLR group. The patients in high-NLR group might have significant higher risk to be diagnosed with PCa (HR 1.640; P = 0.031), especially in the subgroup with prostate-specific antigen (PSA) ranged from 4 to 10 ng mL−1 (hazard ratio [HR] 4.364; P = 0.003). The high-NLR was independent of age of diagnosis, PSA, prostate volume, abnormal digital rectal examination, and hypoechoic lesion on transrectal ultrasound for positive prostate biopsy. In the so-called gray area, combination of NLR value could raise 4.6% of the accuracy of the multivariate logistic model in PCa prediction, but not in advanced PCa prediction.The patients with high-NLR value may have significant higher risk to be diagnosed with PCa, especially among the patients with PSA ranged from 4 to 10 ng mL−1. In this subgroup, the adding of NLR value in the multivariate model can improve the accuracy of PCa prediction in a large degree. If validated, the NLR will become a promising, accessible, inexpensive biomarker for PCa prediction.
机译:评估中性粒细胞与淋巴细胞比率(NLR)在前列腺癌(PCa)诊断中的预测价值。回顾性分析2012年1月至2016年6月间662例行前列腺活检的患者的数据。进行了曲线分析下的接收器工作特性衍生区域以评估预测精度。同时,计算尤登指数以确定最佳的NLR截止值。此外,进行了单因素和多因素logistic回归分析,以确定NLR值与PCa检测之间的关联。由于在接收器工作特性曲线上显示的最大Youden指数显示的NLR值为2.44,因此NLR的截止值设置为2.44。因此,将患者分为高NLR组或低NLR组。高NLR组的患者被诊断为PCa的风险可能更高(HR 1.640; P = 0.031),尤其是在前列腺特异性抗原(PSA)范围为4至10 ng mLmLs-1的亚组中(危险比[HR] 4.364; P = 0.003)。高NLR与阳性前列腺活检经直肠超声检查的诊断年龄,PSA,前列腺体积,直肠指检异常和低回声病变无关。在所谓的灰色区域,NLR值的组合可以提高多元Logistic模型在PCa预测中的准确性的4.6%,而在高级PCa预测中则不能,因此具有较高NLR值的患者被诊断的风险可能更高PCa患者,尤其是PSA患者的范围​​为4至10 ng mL -1 。在该亚组中,在多变量模型中添加NLR值可以在很大程度上提高PCa预测的准确性。如果得到验证,NLR将成为PCa预测的有希望的,可访问的,廉价的生物标志物。

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