A novel nomogram incorporating lymphovascular invasion to predict lymph node invasion in high-risk prostate cancer

Accurate preoperative prediction of lymph node invasion (LNI) is essential for selecting candidates for extended pelvic lymph node dissection (ePLND) in high-risk prostate cancer. Although ePLND provides the most reliable nodal staging, it is associated with increased operative time and postoperative complications. Existing predictive models have limited validation in Asian populations and rarely incorporate lymphovascular invasion (LVI). We retrospectively analyzed 325 patients with high-risk prostate cancer who underwent radical prostatectomy with ePLND between 2019 and 2023. Multivariable logistic regression was used to identify independent predictors of LNI and to develop a novel nomogram integrating LVI with established clinical parameters. Model performance was evaluated using receiver operating characteristic analysis, calibration curves, clinical impact curves, and decision curve analysis, and compared with the Briganti 2012, Briganti 2017, and MSKCC models. LVI, seminal vesicle invasion, biopsy Gleason grade group, clinical stage, and preoperative prostate-specific antigen were independent predictors of LNI. The proposed model demonstrated discrimination (AUC = 0.89; 95% CI 0.85–0.93) and good calibration. At a 7% risk threshold, 31.3% of ePLND procedures could be avoided while missing only 1.7% of LNI cases. Incorporation of LVI significantly improves preoperative prediction of nodal metastasis and may support more individualized surgical decision-making.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-21
DOI
https://doi.org/10.1038/s41598-026-49569-x
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A novel nomogram incorporating lymphovascular invasion to predict lymph node invasion in high-risk prostate cancer

Yige Yang, Yi Tang, Shuiping Yin
Scientific Reports
Prostate Cancer Diagnosis and Treatment
article

A novel nomogram incorporating lymphovascular invasion to predict lymph node invasion in high-risk prostate cancer

Yige Yang, Yi Tang, Shuiping Yin
article en

Abstract

Accurate preoperative prediction of lymph node invasion (LNI) is essential for selecting candidates for extended pelvic lymph node dissection (ePLND) in high-risk prostate cancer. Although ePLND provides the most reliable nodal staging, it is associated with increased operative time and postoperative complications. Existing predictive models have limited validation in Asian populations and rarely incorporate lymphovascular invasion (LVI). We retrospectively analyzed 325 patients with high-risk prostate cancer who underwent radical prostatectomy with ePLND between 2019 and 2023. Multivariable logistic regression was used to identify independent predictors of LNI and to develop a novel nomogram integrating LVI with established clinical parameters. Model performance was evaluated using receiver operating characteristic analysis, calibration curves, clinical impact curves, and decision curve analysis, and compared with the Briganti 2012, Briganti 2017, and MSKCC models. LVI, seminal vesicle invasion, biopsy Gleason grade group, clinical stage, and preoperative prostate-specific antigen were independent predictors of LNI. The proposed model demonstrated discrimination (AUC = 0.89; 95% CI 0.85–0.93) and good calibration. At a 7% risk threshold, 31.3% of ePLND procedures could be avoided while missing only 1.7% of LNI cases. Incorporation of LVI significantly improves preoperative prediction of nodal metastasis and may support more individualized surgical decision-making.

Scientific Reports
Anhui Medical University (CN), First Affiliated Hospital of Anhui Medical University (CN)
National Science Foundation, National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Prostate Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A novel nomogram incorporating lymphovascular invasion to predict lymph node invasion in high-risk prostate cancer — Yige Yang, Yi Tang, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS