Urology Department, Urology and Nephrology Center, Mansoura University, Mansoura, Egypt.
Faculty of Science, Biochemistry Department, Mansoura University, Mansoura, Egypt.
Int Urol Nephrol. 2020 Aug;52(8):1483-1490. doi: 10.1007/s11255-020-02426-w. Epub 2020 Mar 12.
To investigate the role of serum fatty acid-binding protein-4 (FABP-4) as a surrogate of obesity and metabolic syndrome in the prediction of the outcome of prostate biopsy.
A prospective pilot study was conducted for patients undergoing prostate needle biopsy (PNB) for clinically suspected prostate cancer (PCa) between June 2016 and August 2017. Fifty consecutive patients with biopsy-proven PCa were included as study group and 50 consecutive patients with negative biopsy were included as a control group. Receiver Operating Characteristic (ROC) curve was used to calculate the area under the curve (AUC) to compare the accuracy of the different parameters in the diagnosis as well as the presence of high-grade PCa (Gleason score 8-9) at PNB. Predictors of the outcome were analyzed using univariate and multivariate logistic regression analysis.
FABP-4 (AUC: 0.75; P < 0.001) and PSA-density (AUC: 0.84; P < 0.001) were the most accurate to detect PCa at PNB. On multivariate analysis, FABP-4 > 22.5 ng/ml (OR: 16.6; 95% CI 2.8-98; P = 0.002) and PSA-density > 0.38 ng/ml/ml OR: 17.7; 95% CI 5.3-59; P < 0.001) were independent predictors of PCa detection. Regarding high-grade PCa at PNB, FABP-4 (AUC: 0.79; P < 0.001) and %Free-PSA (AUC: 0.75; P < 0.001) were the most accurate. Independent predictors of high-grade PCa were FABP-4 > 32.3 ng/ml OR: 9.2; 95% CI 1.8-45; P = 0.006) and %Free-PSA ≤ 21.9 (OR: 5.5; 95% CI 1.1-27; P = 0.03).
FABP-4 is an independent predictor for both the diagnosis and high-grade Gleason score at PNB. This novel biomarker might have a promising role in optimizing PNB outcomes.
探讨血清脂肪酸结合蛋白-4(FABP-4)作为肥胖和代谢综合征替代物在预测前列腺活检结果中的作用。
对 2016 年 6 月至 2017 年 8 月间因临床疑似前列腺癌(PCa)接受前列腺穿刺活检(PNB)的患者进行了前瞻性试点研究。将 50 例经活检证实的 PCa 患者纳入研究组,50 例经活检证实为阴性的患者纳入对照组。采用受试者工作特征(ROC)曲线计算曲线下面积(AUC),比较不同参数在诊断 PCa 以及在 PNB 中检测到高级别 PCa(Gleason 评分 8-9)方面的准确性。采用单变量和多变量逻辑回归分析来分析预测结果的因素。
FABP-4(AUC:0.75;P<0.001)和 PSA 密度(AUC:0.84;P<0.001)是检测 PNB 中 PCa 最准确的参数。多变量分析显示,FABP-4>22.5ng/ml(OR:16.6;95%CI 2.8-98;P=0.002)和 PSA 密度>0.38ng/ml/ml(OR:17.7;95%CI 5.3-59;P<0.001)是检测 PCa 的独立预测因素。关于 PNB 中的高级别 PCa,FABP-4(AUC:0.79;P<0.001)和%游离 PSA(AUC:0.75;P<0.001)是最准确的参数。高级别 PCa 的独立预测因素是 FABP-4>32.3ng/ml(OR:9.2;95%CI 1.8-45;P=0.006)和%游离 PSA≤21.9(OR:5.5;95%CI 1.1-27;P=0.03)。
FABP-4 是 PNB 中诊断和高级别 Gleason 评分的独立预测因素。这种新型生物标志物在优化 PNB 结果方面可能具有广阔的应用前景。