Predictive value of a nomogram model constructed based on imaging and serological characteristics for prostate biopsy positivity in patients with PSA levels of 4-10 ng/mL
10.3969/j.issn.1005-202X.2024.12.006
- VernacularTitle:基于影像学和血清学特征构建列线图模型对PSA 4～10 ng/mL患者穿刺阳性的预测价值
- Author:
Jianchang LIANG
1
;
Jinfeng WU
;
Yongxin ZHANG
;
Junxin SHEN
;
Zhenjie CHEN
;
Jian TAN
;
Rui ZHONG
;
Wei ZHAO
;
Yangbai LU
;
Runqiang YUAN
Author Information
1. 云浮市中医院检验科,广东 云浮 527300
- Publication Type:Journal Article
- Keywords:
prostate cancer;
nomogram model;
prostate specific antigen;
predictive model;
imaging;
serology
- From:
Chinese Journal of Medical Physics
2024;41(12):1494-1500
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the predictive value of a nomogram model constructed based on imaging combined with prostate-specific antigen(PSA)and its related parameters for biopsy in patients with PSA levels of 4-10 ng/mL.Methods The serological and imaging data of 191 patients who were detected for PSA and related indicators and underwent the first biopsy of prostate by transrectal ultrasound at Zhongshan City People's Hospital and/or Yunfu Hospital of TCM from January 2018 to December 2023 were analyzed retrospectively.Multivariate Logistic regression identified independent risk factors for prostate cancer,and a nomogram model was developed for patients with PSA levels of 4-10 ng/mL.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curves,calibration curves,and decision curves.Results The multivariate Logistic regression analysis showed that free PSA,prostate volume,transition zone volume,PSA density,and the prostate imaging-reporting and data system(PI-RADS v2.1)score were independent risk factors for prostate cancer.The model incorporating these significant variables demonstrated the best performance,with an area under the curve(AUC)of 0.750(95%CI:0.678-0.821),sensitivity of 72.7%,specificity of 77.2%,and accuracy of 74.9%.The calibration curve indicated good agreement between the predicted probability and the actual probability of prostate cancer;and the decision curve analysis further confirmed that the model had high clinical utility.Conclusion The constructed nomogram prediction model can effectively estimate the preoperative risk of prostate cancer in patients with PSA levels of 4-10 ng/mL,providing clinicians with an intuitive tool to adjust treatment plans based on the assessed risk,thereby optimizing patient outcomes.
