Correlation of Serum Adiponectin and Metabolic Syndrome Components With Prostate Cancer Susceptibility and Construction of a Nomogram Prediction Model

Background: To investigate the relationship between serum adiponectin, components of metabolic syndrome, and susceptibility to prostate cancer (PCa), and to construct a predictive nomogram model. Methods: A retrospective, 1:1 individual-matched case–control study was conducted. A total of 152 patients diagnosed with PCa at our hospital between January 2018 and May 2025 were enrolled as the PCa group, and 152 age-matched healthy males were selected as the control group. Serum adiponectin levels, metabolic syndrome components, and general demographic data were compared between the two groups. A nomogram prediction model was constructed based on conditional logistic regression analysis. Results: Multivariate conditional logistic regression analysis showed glycated haemoglobin (OR = 6.360), waist-to-hip ratio (OR = 2.394), waist circumference (OR = 1.457), and triglycerides (OR = 3.777) as independent risk factors for PCa susceptibility (all p < 0.05), whereas high-density lipoprotein (OR = 0.341) and adiponectin (OR = 0.513) were identified as independent protective factors (all p < 0.05). The nomogram model constructed based on these six indicators predicted PCa susceptibility with an area under the curve (AUC) of 0.869 (95% CI: 0.843–0.894). Bootstrap validation indicated good model fit, and decision curve analysis suggested a clinical net benefit of the model. Conclusions: Serum adiponectin and components of metabolic syndrome are closely associated with PCa susceptibility. The nomogram model constructed using these indicators demonstrated good predictive performance in this study cohort.