Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Prostate Cancer Prostatic Dis. 2023 Sep;26(3):588-595. doi: 10.1038/s41391-023-00660-8. Epub 2023 Mar 27.
To develop nomograms that predict the detection of clinically significant prostate cancer (csPCa, defined as ≥GG2 [Grade Group 2]) at diagnostic biopsy based on multiparametric prostate MRI (mpMRI), serum biomarkers, and patient clinicodemographic features.
Nomograms were developed from a cohort of biopsy-naïve men presenting to our 11-hospital system with prostate specific antigen (PSA) of 2-20 ng/mL who underwent pre-biopsy mpMRI from March 2018-June 2021 (n = 1494). The outcomes were the presence of csPCa and high-grade prostate cancer (defined as ≥GG3 prostate cancer). Using significant variables on multivariable logistic regression, individual nomograms were developed for men with total PSA, % free PSA, or prostate health index (PHI) when available. The nomograms were both internally validated and evaluated in an independent cohort of 366 men presenting to our hospital system from July 2021-February 2022.
1031 of 1494 men (69%) underwent biopsy after initial evaluation with mpMRI, 493 (47.8%) of whom were found to have ≥GG2 PCa, and 271 (26.3%) were found to have ≥GG3 PCa. Age, race, highest PIRADS score, prostate health index when available, % free PSA when available, and PSA density were significant predictors of ≥GG2 and ≥GG3 PCa on multivariable analysis and were used for nomogram generation. Accuracy of nomograms in both the training cohort and independent cohort were high, with areas under the curves (AUC) of ≥0.885 in the training cohort and ≥0.896 in the independent validation cohort. In our independent validation cohort, our model for ≥GG2 prostate cancer with PHI saved 39.1% of biopsies (143/366) while only missing 0.8% of csPCa (1/124) with a biopsy threshold of 20% probability of csPCa.
Here we developed nomograms combining serum testing and mpMRI to help clinicians risk stratify patients with elevated PSA of 2-20 ng/mL who are being considered for biopsy. Our nomograms are available at https://rossnm1.shinyapps.io/MynMRIskCalculator/ to aid with biopsy decisions.
开发列线图,以预测基于多参数前列腺 MRI(mpMRI)、血清生物标志物和患者临床病理特征的前列腺特异性抗原(PSA)为 2-20ng/ml 的初诊男性的临床显著前列腺癌(csPCa,定义为≥GG2 [分级组 2])的检出率。
从 2018 年 3 月至 2021 年 6 月,我们的 11 家医院系统共招募了 1494 名 PSA 为 2-20ng/ml 的初诊男性,他们在接受前列腺 MRI 检查前均未进行过前列腺活检。该研究的结局为 csPCa 和高级别前列腺癌(定义为≥GG3 前列腺癌)的存在。使用多变量逻辑回归分析中的显著变量,为总 PSA、游离 PSA 百分比或前列腺健康指数(PHI)可用的男性分别开发了个体列线图。该列线图在我们医院系统 2021 年 7 月至 2022 年 2 月期间就诊的 366 名男性的独立队列中进行了内部验证和评估。
在初始 mpMRI 评估后,1494 名男性中有 1031 名(69%)接受了活检,其中 493 名(47.8%)发现≥GG2 PCa,271 名(26.3%)发现≥GG3 PCa。年龄、种族、最高 PIRADS 评分、前列腺健康指数(如有)、游离 PSA 百分比(如有)和 PSA 密度是多变量分析中≥GG2 和≥GG3 PCa 的显著预测因素,用于生成列线图。在训练队列和独立验证队列中,列线图的准确性均较高,在训练队列中的曲线下面积(AUC)≥0.885,在独立验证队列中≥0.896。在我们的独立验证队列中,我们的 PHI 用于≥GG2 前列腺癌的模型在活检阈值为 20%的 csPCa 概率时,可节省 39.1%的活检(366 例中有 143 例),同时仅漏诊 0.8%的 csPCa(124 例中有 1 例)。
在这里,我们开发了结合血清检测和 mpMRI 的列线图,以帮助临床医生对 PSA 为 2-20ng/ml 的接受活检的患者进行风险分层。我们的列线图可在 https://rossnm1.shinyapps.io/MynMRIskCalculator/ 上获取,以辅助活检决策。