文章基本信息

标题：A novel nomogram predicting the risk of positive biopsy for patients in the diagnostic gray area of prostate cancer
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作者：Guang-Dong Hou ; Yu Zheng ; Wan-Xiang Zheng 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2020
卷号：10
期号：1
页码：1-7
DOI：10.1038/s41598-020-74703-8
出版社：Springer Nature
摘要：The roles played by several inflammatory factors in screening for prostate cancer (PCa) among gray area patients, namely those with serum prostate-specific antigen (PSA) levels between 4 and 10 ng/ml, have not been completely identified, and few effective diagnostic nomograms have been developed exclusively for these patients. We aimed to investigate new independent predictors of positive biopsy (PB) results and develop a novel diagnostic nomogram for this group of patients. The independent predictors of PB results were identified, and a nomogram was constructed using multivariate logistic regression analysis based on a cohort comprising 401 Gy area patients diagnosed at Xijing Hospital (Xi’an, China) between January 2016 and December 2019. The predictive accuracy of the nomogram was assessed using the receiver operating characteristic curve, and the nomogram was calibrated by comparing the prediction with the observation. The performance of the nomogram was further validated using an independent cohort. Finally, lymphocyte-to-monocyte ratio (LMR) > 4.11 and red blood cell distribution width (RDW)-standard deviation (SD) > 42.9 fl were identified as independent protective predictors of PB results, whereas PSA density (PSAD) > 0.141 was identified as an independent risk predictor. The nomogram established using PSAD, LMR, and RDW-SD was perfectly calibrated, and its predictive accuracy was superior to that of PSAD in both internal and external validations (0.827 vs 0.769 and 0.765 vs 0.713, respectively). This study is the first to report the importance of LMR and RDW-SD in screening for PCa among gray area patients and to construct an exclusive nomogram to predict the individual risk of positive 13-core biopsy results in this group of patients. With superior performance over PSAD, our nomogram will help increase the accuracy of PCa screening, thereby avoiding unnecessary biopsy.
其他摘要：Abstract The roles played by several inflammatory factors in screening for prostate cancer (PCa) among gray area patients, namely those with serum prostate-specific antigen (PSA) levels between 4 and 10 ng/ml, have not been completely identified, and few effective diagnostic nomograms have been developed exclusively for these patients. We aimed to investigate new independent predictors of positive biopsy (PB) results and develop a novel diagnostic nomogram for this group of patients. The independent predictors of PB results were identified, and a nomogram was constructed using multivariate logistic regression analysis based on a cohort comprising 401 Gy area patients diagnosed at Xijing Hospital (Xi’an, China) between January 2016 and December 2019. The predictive accuracy of the nomogram was assessed using the receiver operating characteristic curve, and the nomogram was calibrated by comparing the prediction with the observation. The performance of the nomogram was further validated using an independent cohort. Finally, lymphocyte-to-monocyte ratio (LMR) > 4.11 and red blood cell distribution width (RDW)-standard deviation (SD) > 42.9 fl were identified as independent protective predictors of PB results, whereas PSA density (PSAD) > 0.141 was identified as an independent risk predictor. The nomogram established using PSAD, LMR, and RDW-SD was perfectly calibrated, and its predictive accuracy was superior to that of PSAD in both internal and external validations (0.827 vs 0.769 and 0.765 vs 0.713, respectively). This study is the first to report the importance of LMR and RDW-SD in screening for PCa among gray area patients and to construct an exclusive nomogram to predict the individual risk of positive 13-core biopsy results in this group of patients. With superior performance over PSAD, our nomogram will help increase the accuracy of PCa screening, thereby avoiding unnecessary biopsy.