A Novel Nomogram to Identify Candidates for Extended Pelvic Lymph Node Dissection Among Patients with Clinically Localized Prostate Cancer Diagnosed with Magnetic Resonance Imaging-targeted and Systematic Biopsies

Abstract

Background

Available models for predicting lymph node invasion (LNI) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP) might not be applicable to men diagnosed via magnetic resonance imaging (MRI)-targeted biopsies.

Objective

To assess the accuracy of available tools to predict LNI and to develop a novel model for men diagnosed via MRI-targeted biopsies.

Design, setting, and participants

A total of 497 patients diagnosed via MRI-targeted biopsies and treated with RP and extended pelvic lymph node dissection (ePLND) at five institutions were retrospectively identified.

Outcome measurements and statistical analyses

Three available models predicting LNI were evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses. A nomogram predicting LNI was developed and internally validated.

Results and limitations

Overall, 62 patients (12.5%) had LNI. The median number of nodes removed was 15. The AUC for the Briganti 2012, Briganti 2017, and MSKCC nomograms was 82%, 82%, and 81%, respectively, and their calibration characteristics were suboptimal. A model including PSA, clinical stage and maximum diameter of the index lesion on multiparametric MRI (mpMRI), grade group on targeted biopsy, and the presence of clinically significant PCa on concomitant systematic biopsy had an AUC of 86% and represented the basis for a coefficient-based nomogram. This tool exhibited a higher AUC and higher net benefit compared to available models developed using standard biopsies. Using a cutoff of 7%, 244 ePLNDs (57%) would be spared and a lower number of LNIs would be missed compared to available nomograms (1.6% vs 4.6% vs 4.5% vs 4.2% for the new nomogram vs Briganti 2012 vs Briganti 2017 vs MSKCC).

Conclusions

Available models predicting LNI are characterized by suboptimal accuracy and clinical net benefit for patients diagnosed via MRI-targeted biopsies. A novel nomogram including mpMRI and MRI-targeted biopsy data should be used to identify candidates for ePLND in this setting.

Patient summary

We developed the first nomogram to predict lymph node invasion (LNI) in prostate cancer patients diagnosed via magnetic resonance imaging-targeted biopsy undergoing radical prostatectomy. Adoption of this model to identify candidates for extended pelvic lymph node dissection could avoid up to 60% of these procedures at the cost of missing only 1.6% patients with LNI.

Introduction

An anatomically defined extended pelvic lymph node dissection (ePLND) still represents the most accurate method for nodal staging in prostate cancer (PCa) [1]. Even among contemporary patients, up to 15% of men harbor lymph node invasion (LNI) when treated with ePLND [2]. Although ePLND remains the gold standard for nodal staging, it is a time-consuming procedure not devoid of complications such as lymphocele and lymphedema [3]. Considering ePLND only for men at higher risk of LNI (>5% according to the European Association of Urology [EAU]-European Society for Radiotherapy & Oncology [ESTRO]-International Society of Geriatric Oncology [SIOG] guidelines) has been proposed as a reliable approach to minimize the morbidity associated with ePLND while missing only a low proportion of men with nodal metastases [4], [5], [6], [7]. Tools currently available for identifying ePLND candidates are based on clinical parameters and showed excellent predictive accuracy on internal and external validation [4], [5], [8]. However, they are all based on standard systematic biopsies. Recent changes in the diagnostic pathway for clinically localized PCa with the introduction of multiparametric magnetic resonance imaging (mpMRI) and MRI-targeted biopsy might preclude their applicability to contemporary patients for three different reasons. (1) These tools were developed using historical cohorts of men undergoing systematic biopsy and the results might not be generalizable to men diagnosed via MRI-targeted biopsy [9]. (2) mpMRI and targeted biopsy provide additional relevant clinical information that is not considered by current models predicting LNI [10], [11]. (3) A diagnostic strategy based on mpMRI and MRI-targeted biopsy would result in more significant tumors being identified and could reduce the risk of detection of insignificant PCa with a consequent change in disease characteristics identified on radical prostatectomy (RP) [12], [13], [14].

We hypothesized that currently available models predicting LNI might be characterized by suboptimal performance for contemporary patients diagnosed via MRI-targeted biopsy. Our aim was to assess the accuracy of available models for the identification of LNI in a large contemporary cohort of men diagnosed via MRI-targeted biopsy. Moreover, we developed a novel model including mpMRI and MRI-targeted biopsy data to improve the prediction of LNI for better identification of candidates for ePLND.