Frontiers in medicine · 2026
Blood inflammatory markers combined with tumor markers for differentiating benign prostatic hyperplasia from prostate cancer.
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Liu Zeqiang, Yang Xinji, Hou Xiaofei, Du Peng, Jia Keke
Аннотация
BACKGROUND: Prostate cancer (PCa) is the second most frequently diagnosed malignancy in men worldwide, whereas benign prostatic hyperplasia (BPH) is among the most prevalent non-malignant prostatic disorders. Differentiating between these two conditions remains challenging because of overlapping clinical manifestations and the limited specificity of currently available biomarkers.
METHODS: This retrospective study enrolled 200 male patients (53 PCa, 147 BPH) who underwent prostate biopsy or surgical resection based on pathological diagnosis. Clinical characteristics, laboratory parameters, and inflammatory indices were compared between the groups. Both univariate and multivariate logistic regression analyses were conducted to identify independent predictors. Nomograms were developed and validated through calibration curves, ROC analysis, and decision curve analysis (DCA).
RESULTS: PCa patients had significantly higher levels of inflammatory markers than BPH patients (p < 0.05). In multivariate analysis, log2-SII (OR = 2.22, 95% CI: 1.13-4.37, p = 0.021) and log2-AISI (OR = 3.27, 95% CI: 1.83-5.85, p < 0.001) emerged as independent risk factors for PCa. The AISI-based model achieved superior diagnostic performance with an AUC of 0.878 (95% CI: 0.825-0.931) compared with the SII-based model (AUC = 0.855, 95% CI: 0.794-0.915). DCA showed greater clinical net benefit for the AISI model across a wide range of threshold probabilities.
CONCLUSION: Blood inflammatory markers, particularly AISI, in combination with conventional biomarkers, offer enhanced diagnostic accuracy for differentiating BPH from PCa, representing a non-invasive and cost-effective approach for clinical decision-making.
METHODS: This retrospective study enrolled 200 male patients (53 PCa, 147 BPH) who underwent prostate biopsy or surgical resection based on pathological diagnosis. Clinical characteristics, laboratory parameters, and inflammatory indices were compared between the groups. Both univariate and multivariate logistic regression analyses were conducted to identify independent predictors. Nomograms were developed and validated through calibration curves, ROC analysis, and decision curve analysis (DCA).
RESULTS: PCa patients had significantly higher levels of inflammatory markers than BPH patients (p < 0.05). In multivariate analysis, log2-SII (OR = 2.22, 95% CI: 1.13-4.37, p = 0.021) and log2-AISI (OR = 3.27, 95% CI: 1.83-5.85, p < 0.001) emerged as independent risk factors for PCa. The AISI-based model achieved superior diagnostic performance with an AUC of 0.878 (95% CI: 0.825-0.931) compared with the SII-based model (AUC = 0.855, 95% CI: 0.794-0.915). DCA showed greater clinical net benefit for the AISI model across a wide range of threshold probabilities.
CONCLUSION: Blood inflammatory markers, particularly AISI, in combination with conventional biomarkers, offer enhanced diagnostic accuracy for differentiating BPH from PCa, representing a non-invasive and cost-effective approach for clinical decision-making.