Development and internal validation of a clinical model to increase the diagnostic probability of prostate cancer in patients with prostate-specific antigen levels of 4.0-10.0 ng/mL.
- 1Department of Clinical Laboratory, Jiangsu Province (Suqian) Hospital, Suqian, China.
- 2Department of Laboratory Medicine, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Abstract
Distinguishing prostate cancer (PCa) from benign prostatic hyperplasia (BPH) in the prostate-specific antigen (PSA) gray zone (4.0-10.0 ng/mL) remains a clinical challenge due to the limited specificity of PSA. While complex radiomics and AI models exist, their high resource requirements limit accessibility. We constructed a diagnostic model to distinguish PCa from BPH in patients with PSA ranging 4.0 to 10.0 ng/mL. This retrospective study recruited consecutive458 participants from January 2017 to September 2019. Eligible patients had PSA levels between 4.0-10.0 ng/mL and underwent prostate biopsy or surgery with histopathological confirmation of PCa or BPH by two independent pathologists. Candidate predictors included age, PSA, free PSA (FPSA), free/total PSA ratio (F/T ratio), prostate volume (PV), PSA density (PSAD), white blood cell count (WBC), neutrophil (NE), lymphocyte (LY), hemoglobin (HB), platelet (PLT), alanine aminotransferase (ALT), aspartate transaminase (AST), total protein (TP), albumin (ALB), globulin (GLB), creatinine (CREA), urea nitrogen (UREA), and phosphorus (PHOS). Multivariable logistic regression was applied to screen independent risk factors, with bootstrap resampling for internal validation. Model discrimination, calibration and clinical net benefit were assessed via receiver operating characteristic (ROC) curves, calibration plots and decision curve analysis (DCA). Among 458 patients (192 with PCa, 266 with BPH), the PCa group had significantly higher PSA, PSAD, AST, TP, ALB, GLB and PHOS, but lower FPSA, F/T ratio and PV (all P<0.05). Age showed marginal significance (P=0.07) and was entered into the regression according to the P<0.1 screening standard. Age, PSA, FPSA, PV, AST, GLB and PHOS were independent PCa predictors. The model's area under the curve (AUC) was 0.834 [95% confidence interval (CI): 0.799-0.867], with optimism-corrected C-index 0.832 (95% CI: 0.796-0.869). Calibration (calibration: 0.92; Hosmer-Lemeshow test P=0.49) and DCA confirmed stable performance and clinical utility. At the Youden-index cutoff of 0.503, sensitivity reached 69.79% (95% CI: 62.7-76.2%), specificity 80.83% (95% CI: 75.5-85.4%). This clinical model shows promise for identifying PCa risk in patients with PSA 4.0-10.0 ng/mL; however, external validation in independent cohorts is needed before clinical implementation.
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BibTeX
@article{xu2026development,
title = {{Development and internal validation of a clinical model to increase the diagnostic probability of prostate cancer in patients with prostate-specific antigen levels of 4.0-10.0 ng/mL.}},
author = {Bao Xu and Jiahong Jiang and Litao Zhang and Qiuxia Ge and Jingping Liu and Jun Zhou},
journal = {Translational andrology and urology},
year = {2026},
month = sep,
doi = {10.21037/tau-2026-0604},
url = {https://europepmc.org/article/MED/42997172},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Development and internal validation of a clinical model to increase the diagnostic probability of prostate cancer in patients with prostate-specific antigen levels of 4.0-10.0 ng/mL.
AU - Bao Xu
AU - Jiahong Jiang
AU - Litao Zhang
AU - Qiuxia Ge
AU - Jingping Liu
AU - Jun Zhou
PY - 2026
DA - 2026/09/28
JO - Translational andrology and urology
DO - 10.21037/tau-2026-0604
UR - https://europepmc.org/article/MED/42997172
AB - Distinguishing prostate cancer (PCa) from benign prostatic hyperplasia (BPH) in the prostate-specific antigen (PSA) gray zone (4.0-10.0 ng/mL) remains a clinical challenge due to the limited specificity of PSA. While complex radiomics and AI models exist, their high resource requirements limit accessibility. We constructed a diagnostic model to distinguish PCa from BPH in patients with PSA ranging 4.0 to 10.0 ng/mL. This retrospective study recruited consecutive458 participants from January 2017 to September 2019. Eligible patients had PSA levels between 4.0-10.0 ng/mL and underwent prostate biopsy or surgery with histopathological confirmation of PCa or BPH by two independent pathologists. Candidate predictors included age, PSA, free PSA (FPSA), free/total PSA ratio (F/T ratio), prostate volume (PV), PSA density (PSAD), white blood cell count (WBC), neutrophil (NE), lymphocyte (LY), hemoglobin (HB), platelet (PLT), alanine aminotransferase (ALT), aspartate transaminase (AST), total protein (TP), albumin (ALB), globulin (GLB), creatinine (CREA), urea nitrogen (UREA), and phosphorus (PHOS). Multivariable logistic regression was applied to screen independent risk factors, with bootstrap resampling for internal validation. Model discrimination, calibration and clinical net benefit were assessed via receiver operating characteristic (ROC) curves, calibration plots and decision curve analysis (DCA). Among 458 patients (192 with PCa, 266 with BPH), the PCa group had significantly higher PSA, PSAD, AST, TP, ALB, GLB and PHOS, but lower FPSA, F/T ratio and PV (all P<0.05). Age showed marginal significance (P=0.07) and was entered into the regression according to the P<0.1 screening standard. Age, PSA, FPSA, PV, AST, GLB and PHOS were independent PCa predictors. The model's area under the curve (AUC) was 0.834 [95% confidence interval (CI): 0.799-0.867], with optimism-corrected C-index 0.832 (95% CI: 0.796-0.869). Calibration (calibration: 0.92; Hosmer-Lemeshow test P=0.49) and DCA confirmed stable performance and clinical utility. At the Youden-index cutoff of 0.503, sensitivity reached 69.79% (95% CI: 62.7-76.2%), specificity 80.83% (95% CI: 75.5-85.4%). This clinical model shows promise for identifying PCa risk in patients with PSA 4.0-10.0 ng/mL; however, external validation in independent cohorts is needed before clinical implementation.
SN - 2223-4691
ER -