Luo Feng, Guo Jia-Jie, Yuan Xue-Mei, Zhou Heng, Wang Qiu-Yi, Chen Chang-Ming, Yao Xue-Ming, Ma Wu-Kai
Guizhou University of Traditional Chinese Medicine, Guiyang, 550025, China.
Department of Rheumatology and Immunology, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, No. 83 Feishan street, Yunyan district, Guiyang, Guizhou province, 550001, China.
Lipids Health Dis. 2025 May 10;24(1):170. doi: 10.1186/s12944-025-02584-9.
Rheumatoid arthritis (RA) is a chronic inflammatory joint disease with increasing mortality worldwide. Traditional obesity indicators inadequately predict the mortality risk in this population. Thus, the research aimed to evaluate new obesity indicators to explore their close association with RA mortality.
This study analyzed 101,316 National Health and Nutrition Examination Survey participants (1999-2018) to evaluate alternative adiposity indices for RA mortality prediction. Missing data were imputed using the random forest method. Key covariates were selected using the Boruta algorithm and weighted univariate Cox regression. Multivariable-adjusted models generated hazard ratios (95% confidence interval), validated by time-dependent receiver operating characteristic curves and Harrell's C-index. Survival patterns were assessed with restricted cubic splines (RCS) and Kaplan-Meier curves. Threshold effects and robustness were analyzed via segmented Cox models and sensitivity analyses. Extreme gradient boosting (XGBoost) identified A Body Shape Index (ABSI) as the strongest predictor.
Among the 1,266 individuals, 299 deaths occurred during follow-up (190 all-cause, 59 cardiovascular, 50 cancer). ABSI predicted the 5-, 10-, and 20-year mortality (area under the curve: 0.823, 0.801, 0.752, respectively) and outperformed other indices in the Harrell's C-index. Weighted multivariable Cox regression linked higher ABSI × 100 values with increased mortality; Kaplan-Meier curves confirmed reduced survival in the highest quartile (P < 0.001). RCS revealed a U-curve association linking ABSI × 100 to mortality. Moreover, the mediating effects analysis indicated the Monocyte-to-High-Density Lipoprotein Cholesterol Ratio, Neutrophil-to-Lymphocyte Ratio, Advanced Lung Cancer Inflammation Index, and Systemic Immune-Inflammation Index played significant roles as mediators, with mediation ratios of 4.9%, 5.1%, 8.5%, and 4.5%, respectively. Additional sensitivity analyses validated these results. Quartile stratification revealed a pronounced risk amplification in the highest quartile (Q4), particularly in the fully adjusted specification (Hazard ratio = 3.43, 1.45-8.14; P = 0.005). Furthermore, XGBoost results indicate that ABSI is the best obesity metric for predicting the prognosis of patients with RA.
This study revealed a potential clinical value of a new obesity index, specifically the ABSI, in predicting the survival rates among individuals with RA. Inflammatory markers appear to play a partial mediating role in this relationship.
类风湿关节炎（RA）是一种慢性炎症性关节疾病，在全球范围内死亡率呈上升趋势。传统的肥胖指标不足以预测该人群的死亡风险。因此，本研究旨在评估新的肥胖指标，以探讨它们与类风湿关节炎死亡率的密切关联。
本研究分析了101316名国家健康与营养检查调查参与者（1999 - 2018年），以评估用于预测类风湿关节炎死亡率的替代肥胖指数。使用随机森林方法对缺失数据进行插补。使用Boruta算法和加权单变量Cox回归选择关键协变量。多变量调整模型生成风险比（95%置信区间），通过时间依赖性受试者工作特征曲线和Harrell氏C指数进行验证。使用受限立方样条（RCS）和Kaplan - Meier曲线评估生存模式。通过分段Cox模型和敏感性分析分析阈值效应和稳健性。极端梯度提升（XGBoost）确定身体形状指数（ABSI）为最强预测因子。
在1266名个体中，随访期间有299人死亡（190人全因死亡，59人死于心血管疾病，50人死于癌症）。ABSI预测了5年、10年和20年死亡率（曲线下面积分别为：0.823、0.801、0.752），并且在Harrell氏C指数方面优于其他指数。加权多变量Cox回归将较高的ABSI×100值与死亡率增加联系起来；Kaplan - Meier曲线证实最高四分位数组的生存率降低（P < 0.001）。RCS显示ABSI×100与死亡率之间呈U形曲线关联。此外，中介效应分析表明单核细胞与高密度脂蛋白胆固醇比值、中性粒细胞与淋巴细胞比值、晚期肺癌炎症指数和全身免疫炎症指数作为中介发挥了重要作用，中介比例分别为4.9%、5.1%、8.5%和4.5%。额外的敏感性分析验证了这些结果。四分位数分层显示最高四分位数组（Q4）风险显著放大，特别是在完全调整的规范中（风险比 = 3.43，1.45 - 8.14；P = 0.005）。此外，XGBoost结果表明ABSI是预测类风湿关节炎患者预后的最佳肥胖指标。
本研究揭示了一种新的肥胖指数，特别是ABSI，在预测类风湿关节炎患者生存率方面的潜在临床价值。炎症标志物似乎在这种关系中起部分中介作用。
