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Integration of PSAd and multiparametric MRI to forecast biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml.
Ren, Lei; Chen, Yanling; Liu, Zixiong; Huang, Guankai; Wang, Weifeng; Yang, Xu; Bai, Baohua; Guo, Yan; Ling, Jian; Mao, Xiaopeng.
Affiliation
  • Ren L; Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Chen Y; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Liu Z; Department of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China.
  • Huang G; Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Wang W; Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Yang X; Department of Urology, Hui Ya Hospital of The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Huizhou, China.
  • Bai B; Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Guo Y; Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Ling J; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
  • Mao X; Department of Radiology, The Eastern Hospital of the First Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Guangzhou, China.
Front Oncol ; 14: 1413953, 2024.
Article in En | MEDLINE | ID: mdl-39026982
ABSTRACT

Introduction:

This study aims to investigate whether the transrectal ultrasound-guided combined biopsy (CB) improves the detection rates of prostate cancer (PCa) and clinically significant PCa (csPCa) in biopsy-naïve patients. We also aimed to compare the Prostate Imaging Reporting and Data System (PI-RADS v2.1) score, ADC values, and PSA density (PSAd) in predicting csPCa by the combined prostate biopsy.

Methods:

This retrospective and single-center study included 389 biopsy-naïve patients with PSA level 4~20 ng/ml, of whom 197 underwent prebiopsy mpMRI of the prostate. The mpMRI-based scores (PI-RADS v2.1 scores and ADC values) and clinical parameters were collected and evaluated by logistic regression analyses. Multivariable models based on the mpMRI-based scores and clinical parameters were developed by the logistic regression analyses to forecast biopsy outcomes of CB in biopsy-naïve patients. The ROC curves measured by the AUC values, calibration plots, and DCA were performed to assess multivariable models.

Results:

The CB can detect more csPCa compared with TRUSB (32.0% vs. 53%). The Spearman correlation revealed that Gleason scores of the prostate biopsy significantly correlated with PI-RADS scores and ADC values. The multivariate logistic regression confirmed that PI-RADS scores 4, 5, and prostate volume were important predictors of csPCa. The PI-RADS+ADC+PSAd (PAP) model had the highest AUCs of 0.913 for predicting csPCa in biopsy-naïve patients with PSA level 4~20 ng/ml. When the biopsy risk threshold of the PAP model was greater than or equal to 0.10, 51% of patients could avoid an unnecessary biopsy, and only 5% of patients with csPCa were missed.

Conclusion:

The prebiopsy mpMRI and the combined prostate biopsy have a high CDR of csPCa in biopsy-naïve patients. A multivariable model based on the mpMRI-based scores and PSAd could provide a reference for clinicians in forecasting biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml and make a more comprehensive assessment during the decision-making of the prostate biopsy.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Oncol Year: 2024 Document type: Article Affiliation country: China Country of publication: Suiza

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Oncol Year: 2024 Document type: Article Affiliation country: China Country of publication: Suiza