A nomogram using transition zone PSA density for detecting clinically significant prostate cancer in PI-RADS 3 lesions

This study aimed to explore several transitional zonal (TZ)-adjusted parameters for the prediction of clinically significant prostate cancer (csPCa) that categorized as Prostate Imaging Reporting and Data System (PI-RADS) score 3 lesions. A total of 288 patients who underwent multiparametric MRI (mpMRI) and MRI/US targeted fusion biopsy between January 2017 and March 2024 were included in this retrospective study, which was randomly assigned as training dataset and validation dataset. Diagnostic performance of different variables was analyzed using receiver operating characteristics (ROC) and compared with area under ROC (AUC). Univariable and multivariable logistic regression analysis were used to determine significant variables, and a nomogram integrating these parameters was developed. The calculated AUC for prostate-specific antigen density (PSAD), TZ volume (TZV), PSAD based on TZ (TZ-PSAD), and TZ volume ratio (TZ-ratio) were 0.644 (95% CI 0.558–0.731), 0.710 (95% CI 0.610–0.810), 0.724 (95% CI 0.638–0.809), and 0.735 (95% CI 0.650–0.820), respectively. The Delong test demonstrated that TZ-PSAD and TZ-ratio outperformed PSAD, with P = 0.002 and P = 0.04. AUC for model integrating age, TZ-PSAD, and TZ-ratio was 0.834 (95% CI 0.764–0.904), which outperformed TZ-PSAD (P = 0.003) and TZ-ratio (P = 0.007) alone. Zonal-adjusted variables showed promising diagnostic accuracy for the detection of csPCa among lesions scored as PI-RADS category 3, and both TZ-PSAD and TZ-ratio outperformed the whole gland PSAD. Moreover, the model incorporating age, TZ-PSAD, and TZ-ratio could further improve the overall diagnostic performance.

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Publication Details

Journal
Scientific Reports
Published
2025-09-25
DOI
https://doi.org/10.1038/s41598-025-18336-9
Citations
1
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.52
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A nomogram using transition zone PSA density for detecting clinically significant prostate cancer in PI-RADS 3 lesions

Yi Qiu, B. Zheng, Cheng Wang, Weiwei Zhu et al.
1 citations
Scientific Reports
Prostate Cancer Diagnosis and Treatment
1.52
article

A nomogram using transition zone PSA density for detecting clinically significant prostate cancer in PI-RADS 3 lesions

Yi Qiu, B. Zheng, Cheng Wang, Weiwei Zhu, Jing Han
article en
1 citations

Abstract

This study aimed to explore several transitional zonal (TZ)-adjusted parameters for the prediction of clinically significant prostate cancer (csPCa) that categorized as Prostate Imaging Reporting and Data System (PI-RADS) score 3 lesions. A total of 288 patients who underwent multiparametric MRI (mpMRI) and MRI/US targeted fusion biopsy between January 2017 and March 2024 were included in this retrospective study, which was randomly assigned as training dataset and validation dataset. Diagnostic performance of different variables was analyzed using receiver operating characteristics (ROC) and compared with area under ROC (AUC). Univariable and multivariable logistic regression analysis were used to determine significant variables, and a nomogram integrating these parameters was developed. The calculated AUC for prostate-specific antigen density (PSAD), TZ volume (TZV), PSAD based on TZ (TZ-PSAD), and TZ volume ratio (TZ-ratio) were 0.644 (95% CI 0.558–0.731), 0.710 (95% CI 0.610–0.810), 0.724 (95% CI 0.638–0.809), and 0.735 (95% CI 0.650–0.820), respectively. The Delong test demonstrated that TZ-PSAD and TZ-ratio outperformed PSAD, with P = 0.002 and P = 0.04. AUC for model integrating age, TZ-PSAD, and TZ-ratio was 0.834 (95% CI 0.764–0.904), which outperformed TZ-PSAD (P = 0.003) and TZ-ratio (P = 0.007) alone. Zonal-adjusted variables showed promising diagnostic accuracy for the detection of csPCa among lesions scored as PI-RADS category 3, and both TZ-PSAD and TZ-ratio outperformed the whole gland PSAD. Moreover, the model incorporating age, TZ-PSAD, and TZ-ratio could further improve the overall diagnostic performance.

Scientific ReportsVol. 15(1)
Suzhou Municipal Hospital (CN)
Openalex Percentile: Top 14%
Prostate Cancer Diagnosis and Treatment
1.52
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