Xiao Yunyun, Tang Bei, Wang Jueqi, Cai Zhiruo, An Hengqing, Tao Ning
School of Public Health, Xinjiang Medical University, Urumqi, China.
Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.
Front Immunol. 2025 Jul 17;16:1591879. doi: 10.3389/fimmu.2025.1591879. eCollection 2025.
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.
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.
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.
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.
前列腺癌（PCa）是老年男性重要的致死原因，炎症和代谢紊乱是前列腺癌的危险因素。本研究探讨了通过炎症指标衡量的全身炎症如何与作为肥胖和血脂异常标志物的心脏代谢指数（CMI）相互作用，以影响前列腺癌的发病风险。
本研究纳入了2022年至2024年间从新疆医科大学第一附属医院泌尿外科招募的1591名男性患者。采用倾向得分匹配法调整样本量，最终队列包括149例前列腺癌患者和296例匹配的对照。采用逻辑回归模型和受限立方样条（RCS）分析评估CMI与各种炎症指标（如PIV、SIRI、PLR、NLR、LMR）与前列腺癌之间的关联。进行交互作用检验以研究炎症指标与CMI之间的相互作用对前列腺癌风险的影响。
NLR、PLR、PIV和SIRI与前列腺癌（PCa）风险显著正相关，而LMR则呈显著负相关。CMI与前列腺癌（PCa）风险升高显著相关（OR = 1.97，95%CI：1.38~2.81）。受限立方样条（RCS）分析显示CMI与前列腺癌（PCa）风险之间存在非线性剂量反应关系，当CMI≈0.65时风险趋于平稳。敏感性分析证实了这些结果的稳健性。观察到CMI与炎症指标之间存在显著交互作用，尤其是NLR、PLR和LMR，提示对前列腺癌（PCa）风险有协同作用。
本研究表明炎症指标和CMI与前列腺癌风险密切相关。此外，观察到CMI与炎症指标之间存在显著交互作用。这些发现为前列腺癌风险预测和预防提供了新的视角，表明在评估前列腺癌风险时应综合考虑炎症和代谢状态。
