Jin Yanyang, Lv Dong-Shan, Zhou Li-Po, Xiao Li, Tong Guang-Quan, Karim Abdallah, Xue Shuai, Tian Hongyang, Wang Cheng-Cai, Feng Kun, Song Ding-Ming, Guan You-Liang
Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, Liaoning, China.
Department of Obstetrics and Gynecology, Jingzhou Hospital, Yangtze University, Jingzhou, Hubei, China.
Front Nutr. 2025 Jul 8;12:1611848. doi: 10.3389/fnut.2025.1611848. eCollection 2025.
Oxidative stress and dietary micronutrient imbalances have been implicated in prostate cancer (PCa) development and progression. Although flavonoids and antioxidants show promise in experimental models, evidence from population-based studies remains limited.
This research aimed to investigate the relationship between the consumption of antioxidants and flavonoids in the diet and the risk and survival of PCa, as well as to assess the potential of machine learning models in identifying significant dietary factors.
Data from 2,629 male participants aged ≥40 years from National Health and Nutrition Examination Survey (NHANES) 2007-2010 were analyzed. Dietary intake was estimated using two 24-h recalls linked to the USDA Flavonoid Database. PCa status was self-reported. Survey-weighted logistic regression and Cox models evaluated associations with PCa prevalence and all-cause mortality, adjusting for demographic, lifestyle, and clinical covariates. Nine supervised machine learning models, including random forest (RF), were developed and validated. Shapley Additive Explanations (SHAP) values identified key predictors and visualized their effects.
Among 2,629 U.S. male participants from NHANES 2007-2010, 144 reported a history of PCa. Compared with non-cancer individuals, cases had lower intake of selenium, magnesium, quercetin, kaempferol, epicatechin, epigallocatechin, total flavones, and total flavonoids (all < 0.05). Higher intake of selenium, magnesium, catechin, and myricetin was associated with reduced PCa risk in weighted regression models, with selenium remaining significant after multivariable adjustment [odds ratio (OR) = 0.50, 95% confidence interval (CI): 0.33-0.76]. Lower intake of selenium, magnesium, luteolin, quercetin, kaempferol, and total flavones was linked to increased mortality risk, and selenium independently predicted improved survival [hazard ratio (HR) = 0.69, 95% CI: 0.54-0.88]. The RF model showed superior predictive performance [area under the curve (AUC) = 0.740], identifying selenium, luteolin, total flavones, myricetin, catechin, and magnesium as key features. SHAP analysis revealed U-shaped associations for selenium, catechin, and myricetin, and dose-dependent protective effects for luteolin and magnesium.
Our results highlight selenium, magnesium, and select flavonoids as promising dietary factors in reducing PCa risk and improving prognosis. These insights support the development of evidence-based, individualized nutritional strategies and call for further mechanistic and clinical investigations.
氧化应激和饮食中微量营养素失衡与前列腺癌（PCa）的发生和发展有关。尽管黄酮类化合物和抗氧化剂在实验模型中显示出前景，但基于人群研究的证据仍然有限。
本研究旨在调查饮食中抗氧化剂和黄酮类化合物的摄入量与PCa风险及生存率之间的关系，并评估机器学习模型识别重要饮食因素的潜力。
分析了2007 - 2010年美国国家健康与营养检查调查（NHANES）中2629名年龄≥40岁男性参与者的数据。饮食摄入量通过与美国农业部黄酮类化合物数据库相关联的两次24小时饮食回忆来估计。PCa状态通过自我报告获得。采用调查加权逻辑回归和Cox模型评估与PCa患病率和全因死亡率之间关联，并对人口统计学、生活方式和临床协变量进行调整。开发并验证了包括随机森林（RF）在内的9种监督机器学习模型。Shapley值加法解释（SHAP）确定关键预测因素并直观显示其影响。
在2007 - 2010年NHANES的2629名美国男性参与者中，144人报告有PCa病史。与非癌症个体相比，病例组的硒、镁、槲皮素、山奈酚、表儿茶素、表没食子儿茶素、总黄酮和总黄酮类化合物摄入量较低（均P < 0.05）。在加权回归模型中，较高的硒、镁、儿茶素和杨梅素摄入量与降低PCa风险相关，多变量调整后硒仍具有显著性[比值比（OR）= 0.50，95%置信区间（CI）：0.33 - 0.76]。较低的硒、镁、木犀草素、槲皮素、山奈酚和总黄酮摄入量与死亡风险增加有关，硒独立预测生存率提高[风险比（HR）= 0.69，95% CI：0.54 - 0.88]。RF模型显示出卓越的预测性能[曲线下面积（AUC）= 0.740]，确定硒、木犀草素、总黄酮、杨梅素、儿茶素和镁为关键特征。SHAP分析揭示了硒、儿茶素和杨梅素呈U形关联，木犀草素和镁呈剂量依赖性保护作用。
我们的结果突出了硒、镁和特定黄酮类化合物作为降低PCa风险和改善预后的有前景的饮食因素。这些见解支持制定基于证据且个性化的营养策略，并呼吁进一步开展机制和临床研究。
