前列腺健康指数和前列腺健康指数密度作为提高前列腺癌检测的诊断工具。

Prostate Health Index and Prostate Health Index Density as Diagnostic Tools for Improved Prostate Cancer Detection.

机构信息

Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius 03101, Lithuania.

Laboratory of Molecular Oncology, National Cancer Institute, Vilnius 08660, Lithuania.

出版信息

Biomed Res Int. 2020 Jul 21;2020:9872146. doi: 10.1155/2020/9872146. eCollection 2020.

BACKGROUND

To evaluate the diagnostic potential of [-2] proPSA (p2PSA), %p2PSA, Prostate Health Index (phi), and phi density (PHID) as independent biomarkers and in composition of multivariable models in predicting high-grade prostatic intraepithelial neoplasia (HGPIN) and overall and clinically significant prostate cancer (PCa).

METHODS

210 males scheduled for prostate biopsy with total PSA (tPSA) range 2-10 ng/mL and normal digital rectal examination were enrolled in the prospective study. Blood samples to measure tPSA, free PSA (fPSA), and p2PSA were collected immediately before 12-core prostate biopsy. Clinically significant PCa definition was based on Epstein's criteria or ISUP grade ≥ 2 at biopsy.

RESULTS

PCa has been diagnosed in 112 (53.3%) patients. Epstein significant and ISUP grade ≥ 2 PCa have been identified in 81 (72.3%) and 40 (35.7%) patients, respectively. Isolated HGPIN at biopsy have been identified in 24 (11.4%) patients. Higher p2PSA and its derivative mean values were associated with PCa. At 90% sensitivity, PHID with cut-off value of 0.54 have demonstrated the highest sensitivity of 35.7% for overall PCa detection, so PHID and phi with cut-off values of 33.2 and 0.63 have demonstrated the specificity of 34.7% and 34.1% for ISUP grade ≥ 2 PCa detection at biopsy, respectively. In univariate ROC analysis, PHID with AUC of 0.77 and 0.80 was the most accurate predictor of overall and Epstein significant PCa, respectively, so phi with AUC of 0.77 was the most accurate predictor of ISUP grade ≥ 2 PCa at biopsy. In multivariate logistic regression analysis, phi improved diagnostic accuracy of multivariable models by 5% in predicting ISUP grade ≥ 2 PCa.

CONCLUSIONS

PHID and phi have shown the greatest specificity at 90% sensitivity in predicting overall and clinically significant PCa and would lead to significantly avoid unnecessary biopsies. PHID is the most accurate predictor of overall and Epstein significant PCa, so phi is the most accurate predictor of ISUP grade ≥ 2 PCa. phi significantly improves the diagnostic accuracy of multivariable models in predicting ISUP grade ≥ 2 PCa.

背景

评估 [-2] 前列腺特异性抗原（p2PSA）、%p2PSA、前列腺健康指数（phi）和 phi 密度（PHID）作为独立生物标志物以及在多变量模型中的组成，以预测高级别前列腺上皮内瘤变（HGPIN）和总前列腺癌（PCa）和临床显著前列腺癌（PCa）。

方法

前瞻性研究纳入了 210 名总前列腺特异性抗原（tPSA）范围为 2-10ng/ml 且直肠指检正常的男性，他们计划进行前列腺活检。在进行 12 核前列腺活检前，立即采集血液样本以测量 tPSA、游离前列腺特异性抗原（fPSA）和 p2PSA。根据 Epstein 标准或活检时 ISUP 分级≥2，将临床显著 PCa 定义为阳性。

结果

112 名（53.3%）患者诊断为 PCa。81 名（72.3%）和 40 名（35.7%）患者分别被诊断为 Epstein 显著和 ISUP 分级≥2 的 PCa。24 名（11.4%）患者在活检时仅发现 HGPIN。p2PSA 及其衍生均值较高与 PCa 相关。在 90%的灵敏度下，PHID 的截断值为 0.54，对总 PCa 的检测具有最高的 35.7%的灵敏度，因此 PHID 和 phi 的截断值分别为 33.2 和 0.63，对活检时 ISUP 分级≥2 的 PCa 的检测具有 34.7%和 34.1%的特异性。在单变量 ROC 分析中，AUC 为 0.77 和 0.80 的 PHID 是预测总 PCa 和 Epstein 显著 PCa 的最准确预测因子，因此 AUC 为 0.77 的 phi 是预测活检时 ISUP 分级≥2 PCa 的最准确预测因子。在多变量逻辑回归分析中，phi 在预测 ISUP 分级≥2 PCa 方面将多变量模型的诊断准确性提高了 5%。

结论

PHID 和 phi 在预测总 PCa 和临床显著 PCa 时具有 90%的灵敏度，特异性最高，因此可以显著避免不必要的活检。PHID 是预测总 PCa 和 Epstein 显著 PCa 的最准确预测因子，因此 phi 是预测活检时 ISUP 分级≥2 PCa 的最准确预测因子。phi 显著提高了多变量模型预测 ISUP 分级≥2 PCa 的诊断准确性。