González-Peramato P, Álvarez-Maestro M, Heredia-Soto V, Mendiola Sabio M, Linares E, Serrano Á, Álvarez-Ossorio J L, López Alcina E, Prieto L, Vázquez Alonso F, Aller Rodríguez M, Berglund E
Servicio de Anatomía Patológica, Hospital Universitario La Paz, Universidad Autónoma de Madrid, Madrid, Spain.
Servicio de Urología, Hospital Universitario La Paz, Madrid, Spain.
Actas Urol Esp (Engl Ed). 2025 May 24:501788. doi: 10.1016/j.acuroe.2025.501788.
Prostate cancer (PCa) shows varied aggressiveness, complicating personalised treatment decisions. Traditional risk stratification systems rely on clinical parameters but may miss crucial genetic insights. The Prostatype® score (P-score) integrates gene expression with clinical data to improve PCa risk assessment precision.
To validate the P-score's predictive performance for prostate cancer-specific mortality (PCSM) and metastasis in a Spanish cohort, comparing it with NCCN, D'Amico, and EAU systems.
This study was multicentre, retrospective and included seven Spanish hospitals. Of 154 core needle biopsies, 93 met RNA criteria, and for those, P-score was calculated based on IGFBP3, VGLL3, and F3 genes expression and clinical data. The primary endpoint was PCa-specific mortality (PCSM), with secondary endpoints being development of metastasis, adverse pathology (AP), and International Society of Urological Pathology (ISUP) grading.
The P-score demonstrated superior accuracy in predicting 10-year PCSM, with an AUC of 0.81 and a C-index of 0.75, outperforming NCCN (AUC 0.77, C-index 0.69) and D'Amico/EAU (AUC 0.70, C-index 0.62). For metastasis prediction, the P-score achieved a C-index of 0.77, significantly higher than NCCN, D'Amico, and EAU (0.58). Kaplan-Meier analysis underscored the P-score's ability to better stratify patients by risk, especially high-risk groups. Additionally, the P-score correlated with tumour burden, showing significant associations with positive biopsy cores (p = 0.017) and ISUP grade at radical prostatectomy (p = 0.0028).
In this Spanish cohort, the P-score outperformed traditional clinicopathological systems in predicting PCSM, development of metastasis, and pathological markers, supporting its clinical utility for more personalised PCa management.
前列腺癌（PCa）的侵袭性各不相同，这使得个性化治疗决策变得复杂。传统的风险分层系统依赖临床参数，但可能会遗漏关键的基因信息。Prostatype®评分（P评分）将基因表达与临床数据相结合，以提高PCa风险评估的准确性。
在西班牙队列中验证P评分对前列腺癌特异性死亡率（PCSM）和转移的预测性能，并将其与美国国立综合癌症网络（NCCN）、达米科（D'Amico）和欧洲泌尿外科学会（EAU）系统进行比较。
本研究为多中心回顾性研究，纳入了七家西班牙医院。在154例粗针活检中，93例符合RNA标准，基于胰岛素样生长因子结合蛋白3（IGFBP3）、VGLL3和F3基因表达及临床数据计算这些患者的P评分。主要终点是PCa特异性死亡率（PCSM），次要终点是转移的发生、不良病理（AP）和国际泌尿病理学会（ISUP）分级。
P评分在预测10年PCSM方面显示出更高的准确性，曲线下面积（AUC）为0.81，一致性指数（C指数）为0.75，优于NCCN（AUC 0.77，C指数0.69）和D'Amico/EAU（AUC 0.70，C指数0.62）。对于转移预测，P评分的C指数为0.77，显著高于NCCN、D'Amico和EAU（0.58）。Kaplan-Meier分析强调了P评分按风险更好地对患者进行分层的能力，尤其是高危组。此外，P评分与肿瘤负荷相关，与阳性活检核心（p = 0.017）和根治性前列腺切除时的ISUP分级（p = 0.0028）显示出显著关联。
在这个西班牙队列中，P评分在预测PCSM、转移发生和病理标志物方面优于传统的临床病理系统，支持其在更个性化的PCa管理中的临床应用。
