基于临床及多参数磁共振成像/经直肠超声融合衍生数据的回顾性分析，构建并验证用于预测前列腺特异性抗原处于灰色区间男性前列腺癌的列线图。

Development and validation of a nomogram for predicting prostate cancer in men with prostate-specific antigen grey zone based on retrospective analysis of clinical and multi-parameter magnetic resonance imaging/transrectal ultrasound fusion-derived data.

作者信息

Ding Zhimin, Wu Huaiyu, Song Di, Tian Hongtian, Ye Xiuqin, Liang Weiyu, Jiao Yang, Hu Jintao, Xu Jinfeng, Dong Fajin

机构信息

Department of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.

Department of Pathology, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen, China.

出版信息

Transl Androl Urol. 2020 Oct;9(5):2179-2191. doi: 10.21037/tau-20-1154.

BACKGROUND

Urologists face a dilemma when deciding whether prostate biopsy is required for patients with prostate-specific antigen (PSA) levels in the grey zone (4 to 10 ng/mL).

METHODS

We retrospectively analyzed data from consecutive patients with PSA levels in grey zone, who underwent targeted multiparametric magnetic resonance imaging (MP-MRI)/transrectal ultrasound (TRUS) fusion biopsy with elastography between November 2017 and December 2019 in our hospital. The patientse data including age, PSA, fPSA (free PSA), fPSA/PSA, PSA density (PSAD), prostate volume, elastography Q-analysis score (EQS), and prostate imaging-reporting and data system (PI-RADS) score were collected. The nomogram was built using logistic regression and the final cohort of patients was randomly divided into a training cohort (70%) and a validation cohort (30%) by R software. The models were evaluated by receiver operating characteristic curve (ROC) analysis and calibration curve analysis. The nomogram was constructed from the best model.

RESULTS

The final study cohort consisted of 155 patients (training cohort, 109 patients; validation cohort, 46 patients) with PSA in the grey zone, of which 36 patients were pathologically diagnosed with PCa. The EQS model, -EQS model, +EQS model were built. The +EQS model that consisted of fPSA/PSA, EQS, and PI-RADS score had the best PCa diagnostic accuracy (development and validation, 0.783 and 0.781) and probability score (development and validation, 0.939 . 0.622). The new nomogram based on this model was constructed, in which fPSA/PSA ratio had the largest impact, followed by PI-RADS and EQS.

CONCLUSIONS

Elastography and pre-biopsy MP-MRI has clinical significance for patients with PSA in the grey zone. The new nomogram, which is based on pre biopsy data including serological analysis, PI-RADS score, and EQS, can be helpful for clinical decision-making to avoid unnecessary biopsy.

背景

对于前列腺特异性抗原（PSA）水平处于灰色区域（4至10 ng/mL）的患者，泌尿外科医生在决定是否需要进行前列腺活检时面临两难境地。

方法

我们回顾性分析了2017年11月至2019年12月期间在我院接受靶向多参数磁共振成像（MP-MRI）/经直肠超声（TRUS）融合活检及弹性成像检查的连续PSA水平处于灰色区域患者的数据。收集患者的年龄、PSA、游离PSA（fPSA）、fPSA/PSA、PSA密度（PSAD）、前列腺体积、弹性成像Q分析评分（EQS）以及前列腺影像报告和数据系统（PI-RADS）评分等数据。使用逻辑回归构建列线图，并通过R软件将最终患者队列随机分为训练队列（70%）和验证队列（30%）。通过受试者操作特征曲线（ROC）分析和校准曲线分析对模型进行评估。根据最佳模型构建列线图。

结果

最终研究队列包括155例PSA处于灰色区域的患者（训练队列109例，验证队列46例），其中36例经病理诊断为前列腺癌（PCa）。构建了EQS模型、-EQS模型、+EQS模型。由fPSA/PSA、EQS和PI-RADS评分组成的+EQS模型具有最佳的PCa诊断准确性（训练集和验证集分别为0.783和0.781）和概率评分（训练集和验证集分别为0.939、0.622）。基于该模型构建了新的列线图，其中fPSA/PSA比值影响最大，其次是PI-RADS和EQS。