医学
列线图
前列腺癌
前列腺切除术
磁共振成像
阶段(地层学)
放射科
接收机工作特性
前列腺
前列腺特异性抗原
活检
淋巴结
肿瘤科
癌症
内科学
古生物学
生物
作者
Georges Mjaess,Alexandre Peltier,Jean-Baptiste Roche,Elena Lievore,Vito Lacetera,Giuseppe Chiacchio,Valerio Beatrici,Riccardo Mastroianni,Giuseppe Simone,Olivier Windisch,Daniel Benamran,Alexandre Fourcade,Truong An Nguyen,Georges Fournier,G. Fiard,Guillaume Ploussard,Thierry Roumeguère,Simone Albisinni,Romain Diamand
标识
DOI:10.1016/j.euf.2023.04.008
摘要
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).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.
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