Study of the interaction between cardiometabolic index and inflammatory index on the risk of prostate cancer development

Background Prostate cancer (PCa) is an important cause of fatality in older men, with inflammation and metabolic disorders as risk factors for PCa. This study examined how systemic inflammation, measured by inflammatory indices, interacts with the cardiometabolic index (CMI), a marker of obesity and dyslipidemia, to influence the risk of developing PCa. Methods This study consisted of 1,591 male patients recruited from the Department of Urology at the First Affiliated Hospital of Xinjiang Medical University between 2022 and 2024. Propensity score matching was employed to adjust the sample size, resulting in a final cohort of 149 PCa patients and 296 matched controls. Logistic regression models and restricted cubic spline (RCS) analyses were employed to evaluate the associations between CMI and various inflammatory indices (e.g., PIV, SIRI, PLR, NLR, LMR) with prostate cancer. Interaction tests were conducted to investigate the impact of the interplay between inflammatory indices and CMI on the risk of prostate cancer. Results NLR, PLR, PIV, and SIRI were significantly positively associated with prostate cancer (PCa) risk, whereas LMR exhibited a significant negative association. The CMI was significantly associated with an elevated risk of prostate cancer (PCa) (OR = 1.97, 95% CI: 1.38~2.81). Restricted cubic spline (RCS) analysis revealed a nonlinear dose-response relationship between CMI and prostate cancer (PCa) risk, with the risk plateauing at CMI ≈ 0.65. Sensitivity analyses confirmed the robustness of these results. Significant interactions were observed between CMI and inflammatory indices, particularly NLR, PLR, and LMR, suggesting synergistic effects on prostate cancer (PCa) risk. Conclusions The present study demonstrated that inflammation indicators and CMI exhibited a strong association with the risk of PCa. Furthermore, a significant interaction was observed between CMI and inflammation indicators. These findings provide a novel perspective for PCa risk prediction and prevention, suggesting that inflammation and metabolic status should be considered together when assessing PCa risk.