Predictive models, such as the nomograms reported by Briganti [2012, 2017], the Memorial Sloan Kettering Cancer Center (MSKCC) model, Partin tables, and the Roach formula, play a vital role in assessing cancer prognosis and informing treatment decisions. These tools help clinicians estimate the likelihood of lymph node involvement and guide the need for procedures like ePLND, thereby supporting more individualized patient care. Importantly, several major clinical guidelines—including those of the American Urological Association and the National Comprehensive Cancer Network—specifically recommend the use of these predictive models for risk stratification and treatment planning in prostate cancer management. Except for one study, these tools were designed and validated for men without preoperative imaging like MRI scans. An MRI scan is now a cornerstone for selecting patients for Robotic Assisted Laparoscopic Radical Prostatectomy (RALP).
The study that used MRI to predict lymph node metastasis was limited by its relatively small sample size (n=497) and the number of events (62 patients, 12.5%). Moreover, this study exclusively included patients with MRI-visible lesions. Patients who have a non-suspicious MRI (an MRI that does not show any signs of abnormality) and biopsy-proven prostate cancer cannot fit in any available nomograms today. None of the available clinical studies on prostate cancer included tissue-based genomic markers, such as the Decipher test, for predicting lymph node metastases. This omission is noteworthy, as these genomic assays provide critical genetic information that can enhance risk stratification and offer more precise predictions beyond conventional clinical variables.
We tailored our tools for patients with either non-suspicious or suspicious MRI results, as well as those with biopsy genomic classifiers, within a large cohort. By leveraging our advanced diagnostic approach, which integrates clinical parameters with innovative imaging techniques, we can accurately identify candidates for surgery. As a result, 79.3% of extended pelvic lymph node dissections (ePLND)—a procedure often associated with increased patient risk and prolonged recovery—could be safely avoided, while only 1.5% of lymph node metastases would go undetected. This not only minimizes unnecessary interventions but also enhances patient outcomes by reducing exposure to surgical complications.
Evidence shows that up to 15% of patients experience perioperative complications during ePLND. Furthermore, postoperative thromboembolic disease increases by 6 to 10 times, and 14% of patients develop severe lower limb and genital lymphoedema at three months, leading to a diminished quality of life, as highlighted by the LAPPRO trial. Our validated prediction model directly addresses these risks by enabling more precise patient selection for ePLND, thereby reducing unnecessary procedures and their associated complications. For these reasons, we believe our approach will be of great interest to readers.
Written by:
- First Author: Vinayak G Wagaskar, MBBS, MCh Urology, Assistant Professor, Department of Urology, Icahn School of Medicine at Mount Sinai. New York, US.
- Senior Author: Ash Tewari, MBBS, MCh, FRCS (Hon..), Professor and System Chair, Milton and Carroll Petrie Department of Urology, Director of Center of Excellence for Prostate Cancer at the Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, US.