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Development and External Validation of a Novel Nomogram to Predict the Probability of Pelvic Lymph-node Metastases in Prostate Cancer Patients Using Magnetic Resonance Imaging and Molecular Imaging with Prostate-specific Membrane Antigen Positron Emission Tomography

列线图 医学 前列腺癌 淋巴结 磁共振成像 前列腺切除术 接收机工作特性 放射科 人口 前列腺特异性抗原 泌尿科 核医学 癌症 肿瘤科 内科学 环境卫生
作者
André N. Vis,Dennie Meijer,Matthew J. Roberts,Amila Siriwardana,Anthony Morton,John Yaxley,Hemamali Samaratunga,Louise Emmett,Peter M. van de Ven,Martijn W. Heymans,Jakko A. Nieuwenhuijzen,Henk G. van der Poel,Maarten L. Donswijk,Thierry N. Boellaard,Ivo G. Schoots,Phillip D. Stricker,Anne‐Maree Haynes,Daniëla E. Oprea-Lager,Geoffrey Coughlin,Pim J. van Leeuwen
出处
期刊:European Urology Oncology [Elsevier]
卷期号:6 (6): 553-563 被引量:5
标识
DOI:10.1016/j.euo.2023.03.010
摘要

Preoperative assessment of the probability of pelvic lymph-node metastatic disease (pN1) is required to identify patients with prostate cancer (PCa) who are candidates for extended pelvic lymph-node dissection (ePLND).To develop a novel intuitive prognostic nomogram for predicting pathological lymph-node (pN) status in contemporary patients with primary diagnosed localized PCa, using preoperative clinical and histopathological parameters, magnetic resonance imaging (MRI), and prostate-specific membrane antigen (PSMA) positron emission tomography (PET).In total, 700 eligible patients who underwent robot-assisted radical prostatectomy and ePLND were included in the model-building cohort. The external validation cohort consisted of 305 surgically treated patients. Logistic regression with backward elimination was used to select variables for the Amsterdam-Brisbane-Sydney nomogram.Performance of the final model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision-curve analyses. Models were subsequently validated in an external population.The Amsterdam-Brisbane-Sydney nomogram included initial prostate-specific antigen value, MRI T stage, highest biopsy grade group (GG), biopsy technique, percentage of systematic cores with clinically significant PCa (GG ≥2), and lymph-node status on PSMA-PET. The AUC for predicting pN status was 0.81 (95% confidence interval [CI] 0.78-0.85) for the final model. On external validation, the Amsterdam-Brisbane-Sydney nomogram showed superior discriminative ability to the Briganti-2017 and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms (AUC 0.75 [95% CI 0.69-0.81] vs 0.67 [95% CI 0.61-0.74] and 0.65 [95% CI 0.58-0.72], respectively; p < 0.05), and similar discriminative ability to the Briganti-2019 nomogram (AUC 0.78 [95% CI 0.71-0.86] vs 0.80 [95% CI 0.73-0.86]; p = 0.76). The Amsterdam-Brisbane-Sydney nomogram showed excellent calibration on external validation, with an increased net benefit at a threshold probability of ≥4%.The validated Amsterdam-Brisbane-Sydney nomogram performs superior to the Briganti-2017 and MSKCC nomograms, and similar to the Briganti-2019 nomogram. Furthermore, it is applicable in all patients with newly diagnosed unfavorable intermediate- and high-risk PCa.We developed and validated the Amsterdam-Brisbane-Sydney nomogram for the prediction of prostate cancer spread to lymph nodes before surgery. This nomogram performs similar or superior to all presently available nomograms.
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