Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China.
Ren Fail. 2022 Jan 23;44(1):241-249. doi: 10.1080/0886022X.2022.2032744.
The risk of death significantly increased from stage 3 chronic kidney disease (CKD) onward. We aimed to construct a novel nomogram to predict the overall survival (OS) of patients afflicted with CKD from stage 3-5.
A total of 882 patients with stage 3-5 CKD were enrolled from the NHANES 2001-2004 survey. Data sets from the 2003-2004 survey population were used to develop a nomogram that would predict the risk of OS. The 2001-2002 survey population was used to validate the nomogram. Least absolute shrinkage and selection operator (Lasso) regression was conducted to screen the significant predictors relative to all-cause death. The multivariate Cox regression based on the screened factors was applied to effectively construct the nomogram. The performance of the nomogram was evaluated according to the C-index, the area under the receiver operating characteristic curve (AUC), and the calibration curve with 1000 bootstraps resample. Kaplan-Meier's curves were used for testing the discrimination of the prediction model.
Five variables (age, urinary albumin-to-creatinine ratio (UACR), potassium, cystatin C (Cys C), and homocysteine) were screened by the Lasso regression. The nomogram was constructed using these factors, as well as the CKD stage. The included factors (age, CKD stage, UACR, potassium, Cys C, and homocysteine) were all significantly related to the death of CKD patients, according to the multivariate Cox regression analysis. The internal validation showed that this nomogram demonstrates good discrimination and calibration (adjusted C-index: 0.70; AUC of 3-, 5-, and 10-year OS were 0.75, 0.78, and 0.77, respectively). External validation also demonstrated exceedingly similar results (C-index: 0.72, 95% CI: 0.69-0.76; AUC of 3-, 5-, and 10-year OS were 0.76, 0.79, and 0.80, respectively).
This study effectively constructed a novel nomogram that incorporates CKD stage, age, UACR, potassium, Cys C, and homocysteine, which can be conveniently used to facilitate the individualized prediction of survival probability in patients with stage 3-5 CKD. It displays valuable potential for clinical application.
从慢性肾脏病(CKD)3 期开始,死亡风险显著增加。我们旨在构建一个新的列线图来预测 3-5 期 CKD 患者的总生存(OS)。
从 NHANES 2001-2004 调查中招募了 882 名 3-5 期 CKD 患者。使用 2003-2004 调查人群的数据来开发预测 OS 风险的列线图。2001-2002 年调查人群用于验证该列线图。使用最小绝对收缩和选择算子(Lasso)回归筛选与全因死亡相关的显著预测因素。基于筛选因素的多变量 Cox 回归用于有效构建列线图。通过 1000 次 bootstrap 重采样评估列线图的性能,以 C 指数、接受者操作特征曲线(AUC)下面积和校准曲线进行评估。Kaplan-Meier 曲线用于检验预测模型的区分度。
通过 Lasso 回归筛选出 5 个变量(年龄、尿白蛋白与肌酐比(UACR)、钾、胱抑素 C(Cys C)和同型半胱氨酸)。该列线图使用这些因素以及 CKD 分期构建。多变量 Cox 回归分析表明,所包含的因素(年龄、CKD 分期、UACR、钾、Cys C 和同型半胱氨酸)均与 CKD 患者的死亡显著相关。内部验证表明,该列线图具有良好的判别力和校准度(调整后的 C 指数:0.70;3、5 和 10 年 OS 的 AUC 分别为 0.75、0.78 和 0.77)。外部验证也得到了非常相似的结果(C 指数:0.72,95%CI:0.69-0.76;3、5 和 10 年 OS 的 AUC 分别为 0.76、0.79 和 0.80)。
本研究有效构建了一个新的列线图,纳入了 CKD 分期、年龄、UACR、钾、Cys C 和同型半胱氨酸,可以方便地用于预测 3-5 期 CKD 患者的生存概率,具有潜在的临床应用价值。