A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis
View abstract on PubMed
Summary
This summary is machine-generated.A new urine test, the 25G PLNM-Score, accurately detects prostate cancer pelvic lymph node metastasis (PLNM). This non-invasive tool helps avoid unnecessary surgeries and improves treatment decisions for patients.
Area Of Science
- Urology
- Oncology
- Bioinformatics
Background
- Prostate cancer patients with pelvic lymph node metastasis (PLNM) face poor prognoses.
- Current nomograms for PLNM risk assessment have limited accuracy, leading to unnecessary pelvic lymph node dissection (PLND) and potential side effects.
- Accurate identification of PLNM is crucial, but existing tests, including imaging, are insufficient.
Purpose Of The Study
- To develop a highly accurate, non-invasive gene expression-based algorithm for detecting PLNM.
- To create a classifier that can reliably identify patients with and without PLNM before PLND.
Main Methods
- A random forest machine learning algorithm was employed to develop a PLNM classifier using urine samples.
- The algorithm was trained on a multi-center retrospective cohort (n=413) and validated in a prospective cohort (n=243).
- Discriminant analyses compared the algorithm's performance against the MSKCC nomogram score.
Main Results
- The developed 25G PLNM-Score demonstrated high accuracy with an AUC of 0.93 in both retrospective and prospective cohorts.
- The 25G PLNM-Score significantly improved biochemical recurrence-free and distant metastasis-free survival outcomes.
- The algorithm spared 96% (retrospective) and 80% (prospective) of unnecessary PLND with minimal missed PLNM (0.51% and 1%, respectively), outperforming the MSKCC score.
Conclusions
- The 25G PLNM-Score is a novel, highly accurate, non-invasive urine test for identifying PLNM prior to PLND.
- This algorithm offers significant clinical benefits by avoiding unnecessary surgeries and enhancing treatment decision-making in prostate cancer management.

