多中心外部验证及对前列腺特异性膜抗原PET/CT在生化复发中准确性的拟用列线图的优化

Multicenter External Validation and Optimization of a Proposed Nomogram for Prostate-Specific Membrane Antigen PET/CT Accuracy in Biochemical Recurrence.

作者信息

Castillo Laura Chamorro, Belenchón Inés Rivero, Sanz Ignacio Puche, Marenco Rocío Saiz, Ojeda Claro Ana Victoria, Martínez Néstor Sánchez, Medina López Rafael, Juárez Soto Alvaro, Álvarez Ossorio Jose Luis, García Galisteo Emilio, Carrasco Valiente Julia, Imbroda Bernardo Herrera, Moreno Jiménez Juan, Casas Juan Antonio Vallejo, Rodríguez Antonio, Ortiz Adrián Santiago, Hernández Juan Pablo Campos, Gómez Gómez Enrique

机构信息

Urology Department, Reina Sofia University Hospital, IMIBIC, UCO, Córdoba, Spain.

Urology and Nephrology Department, Virgen del Rocío University Hospital, Biomedical Institute of Seville (IBiS)/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain.

出版信息

Prostate. 2025 Aug;85(11):1016-1023. doi: 10.1002/pros.24910. Epub 2025 May 6.

DOI:10.1002/pros.24910

PMID:40329523

Abstract

INTRODUCTION

Prostate-specific membrane antigen (PSMA) PET/CT has been established as the standard imaging technique after biochemical recurrence (BCR) of prostate cancer (PCa). However, its availability is not widespread, thus, patient selection criteria are necessary. For this reason, a European nomogram was recently developed with the intention of helping to predict and identify those patients with BCR at high risk for a positive PSMA PET/CT. The aim of our study was to test the external validity of this nomogram in a large regional cohort of patients and its impact as a selective tool for patients with BCR who should undergo a PSMA PET/CT.

METHODOLOGY

A multicenter, observational, and retrospective study to validate, calibrate, and readjust the European PSMA PET/CT positivity prediction nomogram in a cohort of patients with BCR after radical treatments for localized PCa. Clinical and demographic data were analyzed. We evaluated the detection rate of PSMA PET/CT, the association of different variables with a positive PSMA PET/CT, and the accuracy of the nomogram, summarized in an ROC curve and a clinical decision curve. The nomogram was then modified and improved for our cohort.

RESULTS

A cohort of 413 patients with BCR undergoing PSMA PET/CT was evaluated. Median age, PSA, and PSAdt were 66 years, 0.52 ng/mL, and 7 months, respectively. Median time to BCR was 34 months and the predominant ISUP was 3 (31%). Most patients underwent radical prostatectomy (88%). PSMA PET/CT was positive in 67% of patients, with pelvic involvement in 32% and 24% positivity outside the pelvis. The independent variables associated with a positive PSMA PET/CT were PSA value (OR: 1.94 (1.2-3.19), with a PSA level ≥ 0.5 ng/dL), and a PSA persistence after primary treatment (OR 2.95 (95% CI 1.37-7.14)). The original nomogram had a low predictive ability, with an AUC of 0.57 (95% CI: 0.52-0.62). It was necessary to adjust and calibrate this to obtain a novel nomogram with an AUC of 0.84 (95% CI 0.70-0.98). The DCA showed a greater net benefit from the use of this nomogram at intermediate threshold levels.

CONCLUSION

The nomogram showed a low predictive ability in our external validation. Nevertheless, our novel nomogram demonstrated a moderate-high predictive ability, which could thus optimize the selection of BCR patients who are candidates for PSMA PET/CT.

摘要

引言

前列腺特异性膜抗原（PSMA）PET/CT已成为前列腺癌（PCa）生化复发（BCR）后的标准成像技术。然而，其应用并不广泛，因此，需要患者选择标准。出于这个原因，最近开发了一种欧洲列线图，旨在帮助预测和识别那些BCR患者中PSMA PET/CT阳性的高危患者。我们研究的目的是在一个大型区域患者队列中测试该列线图的外部有效性，以及它作为BCR患者是否应接受PSMA PET/CT的选择工具的影响。

方法

一项多中心、观察性和回顾性研究，以验证、校准和重新调整欧洲PSMA PET/CT阳性预测列线图，该队列中的患者为局限性PCa接受根治性治疗后的BCR患者。分析了临床和人口统计学数据。我们评估了PSMA PET/CT的检测率、不同变量与PSMA PET/CT阳性的相关性以及列线图的准确性，这些总结在ROC曲线和临床决策曲线中。然后针对我们的队列对列线图进行了修改和改进。

结果

评估了413例接受PSMA PET/CT的BCR患者队列。中位年龄、PSA和PSAdt分别为66岁、0.52 ng/mL和7个月。BCR的中位时间为34个月，主要的国际泌尿病理学会（ISUP）分级为3级（31%）。大多数患者接受了根治性前列腺切除术（88%）。67%的患者PSMA PET/CT呈阳性，其中盆腔受累的占32%，盆腔外阳性的占24%。与PSMA PET/CT阳性相关的独立变量是PSA值（OR：1.94（1.2 - 3.19），PSA水平≥0.5 ng/dL）和初次治疗后PSA持续存在（OR 2.95（95%CI 1.37 - 7.14））。原始列线图的预测能力较低，AUC为0.57（95%CI：0.52 - 0.62）。有必要对其进行调整和校准，以获得AUC为0.84（95%CI 0.70 - 0.98）的新型列线图。决策曲线分析（DCA）显示，在中等阈值水平使用该列线图有更大的净效益。