Nicolaiew Nathalie, Ploussard Guillaume, Chun Felix K-H, Xylinas Evanguelos, Allory Yves, Salomon Laurent, de la Taille Alexandre
INSERM, Unité 955, Faculté de Médecine, Créteil, France.
Urol Int. 2013;90(3):306-11. doi: 10.1159/000345603. Epub 2013 Jan 5.
We aimed to build a nomogram allowing to predict the probability of prostate cancer (PC) after an initial 21-core biopsy and with readily available clinical data.
1,490 screened men who underwent an initial 21-core biopsy protocol were included. A multivariate logistic regression was realized including age, prostate volume, prostate-specific antigen (PSA) level, digital rectal examination (DRE) and transrectal ultrasonography (TRUS). Receiver-operating characteristic estimates were used to quantify accuracy of each model.
PC was detected in 41.3% of the patients. Median PSA, age and prostate volume were 6.2 ng/ml (range 0.2-50), 64.6 years (range 33-87) and 40 ml (range 10-270), respectively. Abnormal TRUS findings were detected in 14.7% of patients. Age, PSA level, prostate volume, DRE and TRUS were significantly associated with PC (all p ≤ 0.004) in univariable logistic regression analysis. In multivariate logistic regression analysis, significant associations were found for age, PSA level, prostate volume and DRE. Predictive accuracy estimate of this model was equal to 0.70. TRUS was not an independent predictor of PC.
We constructed the first prebiopsy predictive nomogram based on an extended 21-core biopsy procedure with age, PSA level, DRE and prostate volume which are readily available clinical data to urologists.
我们旨在构建一种列线图,用于预测初次21针穿刺活检后前列腺癌(PC)的发生概率,并利用易于获取的临床数据。
纳入1490例接受初次21针穿刺活检方案筛查的男性。进行多因素逻辑回归分析,纳入年龄、前列腺体积、前列腺特异性抗原(PSA)水平、直肠指检(DRE)和经直肠超声检查(TRUS)。采用受试者操作特征估计值来量化每个模型的准确性。
41.3%的患者检测到PC。PSA中位数、年龄和前列腺体积分别为6.2 ng/ml(范围0.2 - 50)、64.6岁(范围33 - 87)和40 ml(范围10 - 270)。14.7%的患者检测到TRUS异常结果。在单因素逻辑回归分析中,年龄、PSA水平、前列腺体积、DRE和TRUS与PC均显著相关(所有p≤0.004)。在多因素逻辑回归分析中,发现年龄、PSA水平、前列腺体积和DRE存在显著关联。该模型的预测准确性估计值等于0.70。TRUS不是PC的独立预测因素。
我们基于扩展的21针穿刺活检程序,构建了首个活检前预测列线图,纳入了年龄、PSA水平、DRE和前列腺体积,这些都是泌尿外科医生易于获取的临床数据。