Li Ting, Lin Zaoqiang, Tang Zeyong, Feng Liuchang, Lei Nuo, Chen Hui, Chen Guozi, Tan Qinxiang
Department of Nephrology, Beijing University of Chinese Medicine Shenzhen Hospital (Longgang), Shenzhen, China.
Ren Fail. 2025 Dec;47(1):2476740. doi: 10.1080/0886022X.2025.2476740. Epub 2025 Apr 21.
Frailty predicts poor outcomes in chronic kidney disease (CKD) patients. This study compared frailty's predictive power with other factors and aimed to develop a model for predicting overall survival (OS) in CKD patients.
The study included 3,714 CKD participants from the National Health and Nutrition Examination Survey 2005-2018. The death data were updated to December 31, 2019. Lasso-Cox regression identified significant predictors among 42 factors, resulting in a prognostic nomogram using 11 key variables. Subsequent evaluation of the nomogram involved the C-index, the Areas Under Time-dependent Receiver Operating Characteristic Curves (AUC) and calibration curves.
Over a median follow-up of 5.92 years, 1,234 deaths occurred. The final predictors of OS in CKD patients included age, ethnicity, smoking status, estimated pulse wave velocity, body fat percentage, blood uric acid concentration, blood urea nitrogen concentration, and albumin concentration, neutrophil-to-lymphocyte ratio, urine albumin-to-creatinine ratio level, and frailty index (FI) score. The FI score was the strongest predictor with an HR of 76.54 (95% CI: 42.93, 136.46, < 0.0001). In the training set, the AUC values were 80.11% for 1-year, 79.90% for 3-year, 79.53% for 5-year, and 81.34% for 10-year follow-ups. In the internal validation set, AUC values were 78.66%, 77.78%, 77.56%, and 79.54%, respectively. The nomogram's corrected C-index was 0.76 (95% CI: 0.75 - 0.78), and calibration curves showed satisfactory accuracy.
The FI score is a significant predictor of CKD OS. The developed nomogram based on the FI score is a promising tool for predicting the OS of CKD patients.
衰弱预示着慢性肾脏病(CKD)患者的不良预后。本研究比较了衰弱与其他因素的预测能力,并旨在建立一个预测CKD患者总生存期(OS)的模型。
该研究纳入了2005 - 2018年国家健康与营养检查调查中的3714名CKD参与者。死亡数据更新至2019年12月31日。Lasso - Cox回归在42个因素中确定了显著预测因素,从而得出一个使用11个关键变量的预后列线图。随后对该列线图的评估包括C指数、时间依赖性受试者工作特征曲线下面积(AUC)以及校准曲线。
在中位随访5.92年期间,发生了1234例死亡。CKD患者OS的最终预测因素包括年龄、种族、吸烟状况、估计脉搏波速度、体脂百分比、血尿酸浓度、血尿素氮浓度、白蛋白浓度、中性粒细胞与淋巴细胞比值、尿白蛋白与肌酐比值水平以及衰弱指数(FI)评分。FI评分是最强的预测因素,风险比为76.54(95%置信区间:42.93,136.46,P < 0.0001)。在训练集中,1年随访的AUC值为80.11%,3年为79.90%,5年为79.53%,10年为81.34%。在内部验证集中,AUC值分别为78.66%、77.78%、77.56%和79.54%。该列线图的校正C指数为0.76(95%置信区间:0.75 - 0.78),校准曲线显示出令人满意的准确性。
FI评分是CKD患者OS的重要预测因素。基于FI评分开发的列线图是预测CKD患者OS的一个有前景的工具。