Predictive value of bpMRI for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L.
- Author:
Lai DONG
1
;
Rong-Jie SHI
1
;
Jin-Wei SHANG
1
;
Zhi-Yi SHEN
1
;
Kai-Yu ZHANG
1
;
Cheng-Long ZHANG
1
;
Bin YANG
1
;
Tian-Bao HUANG
1
;
Ya-Min WANG
1
;
Rui-Zhe ZHAO
1
;
Wei XIA
1
;
Shang-Qian WANG
1
;
Gong CHENG
1
;
Li-Xin HUA
1
Author Information
1. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
- Publication Type:Journal Article
- Keywords:
prostate cancer;
lymph node metastasis;
MRI;
prostate specific antigen;
nomogram
- MeSH:
Humans;
Male;
Prostatic Neoplasms/diagnostic imaging*;
Lymphatic Metastasis;
Retrospective Studies;
Nomograms;
Prostate-Specific Antigen/blood*;
Lymph Nodes/pathology*;
Pelvis;
Predictive Value of Tests;
Prostatectomy;
Lymph Node Excision;
Risk Factors;
Magnetic Resonance Imaging;
Logistic Models;
Middle Aged;
Aged
- From:
National Journal of Andrology
2025;31(5):426-431
- CountryChina
- Language:Chinese
-
Abstract:
Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
