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Development and Validation of A Nomogram for Prostate Cancer Diagnosis Based on Inflammatory Ratios and PSA Derived
Yong Wang1, Jie Chen2, Jilin Kuang3
1Department of Clinical Laboratory, Shangyu People's Hospital of Shaoxing, Shaoxing University, 312000 Shaoxing, Zhejiang, China.
Background:
This study aimed to investigate the diagnostic value of the C-reactive protein/albumin ratio (CAR) and platelet/albumin ratio (PAR) combined with prostate-specific antigen (PSA)-derived indicators for prostate cancer (PCa) and to develop a visualised nomogram for PCa diagnosis.
Methods:
This retrospective study included 354 patients undergoing initial prostate biopsy between January 2023 and December 2025. Patients were randomly assigned to a training set (n = 248, 70%) and a validation set (n = 106, 30%). The training set included 106 patients with PCa and 142 patients with benign prostatic hyperplasia (BPH). Clinical characteristics and laboratory data were collected to calculate CAR, PAR and PSA-derived indicators. Independent risk factors of PCa were identified using univariate and multivariate logistic regression analyses and incorporated into a nomogram. Model performance was assessed by receiver operating characteristic (ROC) curves, calibration curves, bootstrap internal validation (1000 resamples) and decision curve analysis (DCA).
Results:
Compared with patients with BPH, those with PCa had older age, lower free/total prostate-specific antigen ratio (f/tPSA), and higher prostate-specific antigen density (PSAD), CAR and PAR (all p < 0.05). Multivariate analysis confirmed these five indicators as independent predictors of PCa (all p < 0.05). The combined model yielded an area under the curve (AUC) of 0.882, significantly outperforming single indicators (p < 0.05), with a sensitivity of 92.45% and a specificity of 73.94%. The nomogram achieved AUCs of 0.886 (training) and 0.850 (validation), with an AUC difference of 0.036 and no significant overfitting. Patients with intermediate- to high-risk PCa (Gleason score ≥ 7) showed lower f/tPSA and higher PSAD, CAR, PAR than those with low-risk PCa (all p < 0.05). Calibration curves showed good agreement between predicted and actual observed probabilities, and DCA indicated favourable clinical net benefit.
Conclusions:
Age, f/tPSA, PSAD, CAR and PAR are independent risk factors of PCa. Internal validation of the nomogram incorporating these variables showed no significant overfitting and high preoperative diagnostic value. The nomogram may assist in tumour malignancy assessment, but external multicentre validation is needed to confirm its generalisability.