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一种在MRI靶向活检时代预测侧方特异性前列腺外侵犯的更新模型。

An updated model for predicting side-specific extraprostatic extension in the era of MRI-targeted biopsy.

作者信息

Martini Alberto, Wever Lieke, Soeterik Timo F W, Rakauskas Arnas, Fankhauser Christian Daniel, Grogg Josias Bastian, Checcucci Enrico, Amparore Daniele, Haiquel Luciano, Rodriguez-Sanchez Lara, Ploussard Guillaume, Qiang Peng, Affentranger Andres, Marquis Alessandro, Marra Giancarlo, Ettala Otto, Zattoni Fabio, Falagario Ugo Giovanni, De Angelis Mario, Kesch Claudia, Apfelbeck Maria, Al-Hammouri Tarek, Kretschmer Alexander, Kasivisvanathan Veeru, Preisser Felix, Lefebvre Emilie, Olivier Jonathan, Radtke Jan Philipp, Carrieri Giuseppe, Moro Fabrizio Dal, Boström Peter, Jambor Ivan, Gontero Paolo, Chiu Peter K, John Hubert, Macek Petr, Porpiglia Francesco, Hermanns Thomas, van den Bergh Roderick C N, van Basten Jean-Paul A, Gandaglia Giorgio, Valerio Massimo

机构信息

Department of Urology, La Croix du Sud Hospital, Toulouse, France.

St. Antonius ziekenhuis, Nieuwegein, the Netherlands.

出版信息

Prostate Cancer Prostatic Dis. 2024 Sep;27(3):520-524. doi: 10.1038/s41391-023-00776-x. Epub 2024 Jan 5.

Abstract

PURPOSE

Accurate prediction of extraprostatic extension (EPE) is pivotal for surgical planning. Herein, we aimed to provide an updated model for predicting EPE among patients diagnosed with MRI-targeted biopsy.

MATERIALS AND METHODS

We analyzed a multi-institutional dataset of men with clinically localized prostate cancer diagnosed by MRI-targeted biopsy and subsequently underwent prostatectomy. To develop a side-specific predictive model, we considered the prostatic lobes separately. A multivariable logistic regression analysis was fitted to predict side-specific EPE. The decision curve analysis was used to evaluate the net clinical benefit. Finally, a regression tree was employed to identify three risk categories to assist urologists in selecting candidates for nerve-sparing, incremental nerve sparing and non-nerve-sparing surgery.

RESULTS

Overall, data from 3169 hemi-prostates were considered, after the exclusion of prostatic lobes with no biopsy-documented tumor. EPE was present on final pathology in 1,094 (34%) cases. Among these, MRI was able to predict EPE correctly in 568 (52%) cases. A model including PSA, maximum diameter of the index lesion, presence of EPE on MRI, highest ISUP grade in the ipsilateral hemi-prostate, and percentage of positive cores in the ipsilateral hemi-prostate achieved an AUC of 81% after internal validation. Overall, 566, 577, and 2,026 observations fell in the low-, intermediate- and high-risk groups for EPE, as identified by the regression tree. The EPE rate across the groups was: 5.1%, 14.9%, and 48% for the low-, intermediate- and high-risk group, respectively.

CONCLUSION

In this study we present an update of the first side-specific MRI-based nomogram for the prediction of extraprostatic extension together with updated risk categories to help clinicians in deciding on the best approach to nerve-preservation.

摘要

目的

准确预测前列腺外侵犯(EPE)对于手术规划至关重要。在此,我们旨在提供一种更新的模型,用于预测经MRI靶向活检确诊的患者中的EPE。

材料与方法

我们分析了一个多机构数据集,该数据集包含经MRI靶向活检诊断为临床局限性前列腺癌并随后接受前列腺切除术的男性患者。为了建立一个侧别特异性预测模型,我们分别考虑前列腺叶。采用多变量逻辑回归分析来预测侧别特异性EPE。决策曲线分析用于评估净临床获益。最后,使用回归树来确定三个风险类别,以协助泌尿外科医生选择保留神经、增量保留神经和不保留神经手术的候选者。

结果

总体而言,在排除无活检记录肿瘤的前列腺叶后,共考虑了3169个半前列腺的数据。最终病理显示1094例(34%)存在EPE。其中,MRI能够正确预测EPE的有568例(52%)。一个包含前列腺特异性抗原(PSA)、索引病灶最大直径、MRI上EPE的存在、同侧半前列腺的最高国际泌尿病理学会(ISUP)分级以及同侧半前列腺阳性核心百分比的模型,经内部验证后AUC为81%。总体而言,回归树确定的566、577和2026例观察结果分别属于EPE的低、中、高风险组。低、中、高风险组的EPE发生率分别为5.1%、14.9%和48%。

结论

在本研究中,我们更新了首个基于MRI的侧别特异性列线图,用于预测前列腺外侵犯,并更新了风险类别,以帮助临床医生决定最佳的神经保留方法。

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