医学
前列腺癌
下尿路症状
国际前列腺症状评分
接收机工作特性
前列腺
泌尿科
逻辑回归
单变量分析
前列腺特异性抗原
前列腺活检
多元分析
内科学
活检
曲线下面积
癌症
肿瘤科
作者
Antonio Cicione,Luigi Cormio,Francesco Cantiello,Italo M. Palumbo,Cosimo De Nunzio,Estêvão Lima,Giuseppe Ucciero,Giuseppe Carrieri,Rocco Damiano
出处
期刊:Minerva urology and nephrology
[Edizioni Minerva Medica]
日期:2017-07-01
卷期号:69 (5)
被引量:15
标识
DOI:10.23736/s0393-2249.17.02737-0
摘要
The assessment of lower urinary tract symptoms (LUTS) is common part of urological investigation. Furthermore, patients bother of prostate cancer (PCa) when they are affected of LUTS. This study was aimed to determine whether the presence and severity of LUTS, as assessed by the International Prostate Symptoms Score (IPSS), could help to identify patients at higher risk of prostate cancer (PCa) on prostate biopsy (PBx). In this effort, an initial PCa predictive model was calculated and IPSS was subsequently added. The diagnostic accuracy of both models was compared.The analysis of prospectively collected data of patients scheduled for PBx at four academic hospitals between January 2012 and June 2015 was performed. Univariate and multivariate analysis assessed the correlation between the IPSS and the risk of being diagnosed with PCa; Receiver operator characteristic curve (ROC) analysis evaluated the predictive models including or not the IPSS.Of the 1366 enrolled patients, 706 (52%) were diagnosed with PCa. Patients with PCa had a significantly lower IPSS (10.6±7.4 vs. 12.7±8.1) than those with benign diagnosis. Multivariate logistic regression analysis showed that age, prostate-specific antigen (PSA), prostate volume and IPSS were the most significant predictors of PBx outcome, (OR 1.61, P=0.001; OR 1.20, P=0.001; OR 0.97, P=0.001; OR 0.74, P=0.004; respectively). ROC curve analysis showed that the addition of IPSS to the predictive model based on age, PSA, DRE and prostate volume significantly improved the model diagnostic accuracy (AUC: 0.776 vs. 0.652; P=0.001).Presence and severity of LUTS are inversely correlated with the risk of being diagnosed with PCa at PBx. Incorporating the IPSS into predictive models may reduce the risk of unnecessary PBxs.
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