Cerezo Isis, Cancho Barbara, Rodriguez Sabillon Jorge Alberto, Jorge Alberto, Alvarez Lopez Alvaro, Valladares Julian, Lopez Gomez Juan, Romero Jorge, Robles Nicolas Roberto
Servicio de Nefrologia, Hospital Universitario de Badajoz, Universidad de Extremadura, Badajoz, Spain.
Servicio de Bioquímica Clínica, Hospital Universitario de Badajoz, Universidad de Extremadura, Badajoz, Spain.
J Clin Lab Anal. 2025 Jan;39(2):e25139. doi: 10.1002/jcla.25139. Epub 2024 Dec 23.
Serum creatinine and albuminuria are the core of most CKD prediction and progression risk models. Several biomarkers have been introduced to improve these results such as beta-2-microglobulin (B2M) and cystatin C (CysC). Nevertheless, few clinical comparisons of these biomarkers are available. We have compared serum B2M levels with albuminuria, CysC levels, and the CKD-EPI GFR equations.
A sample of 434 patients were studied: 234 males and 200 females, the mean age was 58.3 ± 15.0 years, and 33.4% have diabetes mellitus. In all patients, plasma B2M, CysC, creatinine, and urinary albumin excretion were analyzed. EGFR was calculated using CKD-EPI equations for creatinine, CysC, and creatinine-CysC. The risk of death and CKD progression was evaluated using ROC curves and Cox proportional hazards survivorship models.
For mortality, the highest area under the curve (AUC) was for CysC (0.775, 0.676-0.875). The lowest sensitivity was shown by eGFR (creatinine) (0.298, 0.195-0.401, p < 0.001), eGFR (CysC) (0.216, 0.118-0.314, p < 0.001), and eGFR (creatinine + CysS) (0.218, 0.124-0.312, p < 0.001). For progression to advanced CKD, the highest AUC was for CysC (0.908, 0.862-0.954). The lowest sensitivity was shown by eGFR (creatinine) (0.184, 0.106-0.261, p < 0.001), eGFR (CysC) (0.095, 0.048-0.14, p < 0.001), and eGFR (creatinine+ CysC) (0.087, 0.040-0.134, p < 0.001). CysC, after age, was the second-best marker of life risk. Contrariwise, for CKD progression, CysC, and albuminuria were the best markers.
The best biomarker of mortality and risk of progression to CKD was CysC. Albuminuria and B2M were the next best options to be used. The lowest sensitivity was shown by estimated eGFR.
血清肌酐和蛋白尿是大多数慢性肾脏病(CKD)预测及进展风险模型的核心指标。已引入多种生物标志物以改善预测结果,如β2微球蛋白(B2M)和胱抑素C(CysC)。然而,关于这些生物标志物的临床比较却很少。我们比较了血清B2M水平与蛋白尿、CysC水平以及CKD-EPI肾小球滤过率(GFR)方程。
对434例患者进行了研究,其中男性234例,女性200例,平均年龄为58.3±15.0岁,33.4%患有糖尿病。对所有患者分析了血浆B2M、CysC、肌酐以及尿白蛋白排泄量。采用CKD-EPI方程分别根据肌酐、CysC以及肌酐-CysC计算估算肾小球滤过率(eGFR)。使用ROC曲线和Cox比例风险生存模型评估死亡风险和CKD进展风险。
对于死亡率,曲线下面积(AUC)最高的是CysC(0.775,0.676 - 0.875)。估算肾小球滤过率(肌酐)[eGFR(肌酐)]的敏感性最低(0.298,0.195 - 0.401,p < 0.001),eGFR(CysC)(0.216,0.118 - 0.314,p < 0.001)以及eGFR(肌酐 + CysC)(0.218,0.124 - 0.312,p < 0.001)。对于进展至晚期CKD,AUC最高的是CysC(0.908,0.862 - 0.954)。eGFR(肌酐)的敏感性最低(0.184,0.106 - 0.261,p < 0.001),eGFR(CysC)(0.095,0.048 - 0.14,p < 0.001)以及eGFR(肌酐 + CysC)(0.087,0.040 - 0.134,p < 0.001)。CysC是仅次于年龄的第二大生命风险标志物。相反,对于CKD进展,CysC和蛋白尿是最佳标志物。
死亡率和CKD进展风险的最佳生物标志物是CysC。蛋白尿和B2M是其次的最佳选择。估算的eGFR敏感性最低。