Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium.
Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium.
Eur Urol Focus. 2023 Nov;9(6):992-999. doi: 10.1016/j.euf.2023.04.008. Epub 2023 May 3.
Suitable selection criteria for focal therapy (FT) are crucial to achieve success in localized prostate cancer (PCa).
To develop a multivariable model that better delineates eligibility for FT and reduces undertreatment by predicting unfavorable disease at radical prostatectomy (RP).
DESIGN, SETTING, AND PARTICIPANTS: Data were retrospectively collected from a prospective European multicenter cohort of 767 patients who underwent magnetic resonance imaging (MRI)-targeted and systematic biopsies followed by RP in eight referral centers between 2016 and 2021. The Imperial College of London eligibility criteria for FT were applied: (1) unifocal MRI lesion with Prostate Imaging-Reporting and Data System score of 3-5; (2) prostate-specific antigen (PSA) ≤20 ng/ml; (3) cT2-3a stage on MRI; and (4) International Society of Urological Pathology grade group (GG) 1 and ≥6 mm or GG 2-3. A total of 334 patients were included in the final analysis.
The primary outcome was unfavorable disease at RP, defined as GG ≥4, and/or lymph node invasion, and/or seminal vesicle invasion, and/or contralateral clinically significant PCa. Logistic regression was used to assess predictors of unfavorable disease. The performance of the models including clinical, MRI, and biopsy information was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis. A coefficient-based nomogram was developed and internally validated.
Overall, 43 patients (13%) had unfavorable disease on RP pathology. The model including PSA, clinical stage on digital rectal examination, and maximum lesion diameter on MRI had an AUC of 73% on internal validation and formed the basis of the nomogram. Addition of other MRI or biopsy information did not significantly improve the model performance. Using a cutoff of 25%, the proportion of patients eligible for FT was 89% at the cost of missing 30 patients (10%) with unfavorable disease. External validation is required before the nomogram can be used in clinical practice.
We report the first nomogram that improves selection criteria for FT and limits the risk of undertreatment.
We conducted a study to develop a better way of selecting patients for focal therapy for localized prostate cancer. A novel predictive tool was developed using the prostate-specific antigen (PSA) level measured before biopsy, tumor stage assessed via digital rectal examination, and lesion size on magnetic resonance imaging (MRI) scans. This tool improves the prediction of unfavorable disease and may reduce the risk of undertreatment of localized prostate cancer when using focal therapy.
合适的局部前列腺癌（PCa）的局灶性治疗（FT）选择标准对于获得成功至关重要。
开发一种多变量模型，通过预测根治性前列腺切除术（RP）中不利的疾病，更好地划定 FT 的适应证，并减少治疗不足。
设计、地点和参与者：数据来自 2016 年至 2021 年期间在 8 个转诊中心接受 MRI 靶向和系统活检以及随后进行 RP 的 767 例前瞻性欧洲多中心队列的回顾性收集。伦敦帝国理工学院的 FT 入选标准为：（1）磁共振成像（MRI）评分 3-5 的局灶性 MRI 病变；（2）前列腺特异性抗原（PSA）≤20ng/ml；（3）MRI 上 cT2-3a 期；（4）国际泌尿病理学会（ISUP）分级组（GG）1 级及≥6mm 或 GG 2-3 级。共有 334 例患者纳入最终分析。
主要结局是 RP 时的不利疾病，定义为 GG≥4，和/或淋巴结浸润，和/或精囊浸润，和/或对侧临床显著 PCa。使用逻辑回归评估不利疾病的预测因素。使用受试者工作特征曲线（ROC）下面积（AUC）、校准图和决策曲线分析评估包括临床、MRI 和活检信息的模型的性能。开发了基于系数的列线图，并进行了内部验证。
总体而言，43 例（13%）患者在 RP 病理上有不利疾病。包括 PSA、直肠指诊临床分期和 MRI 上最大病变直径在内的模型在内部验证中的 AUC 为 73%，并构成了列线图的基础。添加其他 MRI 或活检信息并未显著提高模型性能。使用 25%的截断值，89%的患者符合 FT 标准，但会错过 30 例（10%）有不利疾病的患者。在将列线图用于临床实践之前，需要进行外部验证。
我们报告了第一个可改善局灶性前列腺癌 FT 选择标准并限制治疗不足风险的列线图。
我们进行了一项研究，以开发一种更好的方法来选择局部前列腺癌的局灶性治疗患者。使用活检前测量的前列腺特异性抗原（PSA）水平、数字直肠检查评估的肿瘤分期和磁共振成像（MRI）扫描上的病变大小，开发了一种新的预测工具。该工具提高了不利疾病的预测能力，并可能降低使用局灶性治疗时局部前列腺癌治疗不足的风险。
