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. 2016 Jul 7;11(7):1163-1172.
doi: 10.2215/CJN.10441015. Epub 2016 Jun 8.

Biomarkers of Cardiovascular Disease and Mortality Risk in Patients with Advanced CKD

Affiliations

Biomarkers of Cardiovascular Disease and Mortality Risk in Patients with Advanced CKD

Jia Sun et al. Clin J Am Soc Nephrol. .

Abstract

Background and objectives: The high risk of cardiovascular disease (CVD) and premature death in patients with CKD associates with a plethora of elevated circulating biomarkers that may reflect distinct signaling pathways or simply, are epiphenomena of CKD. We compared the predictive strength of 12 biomarkers analyzed concomitantly in patients with stage 5 CKD.

Design, setting, participants, & measurements: From 1994 to 2014, 543 patients with stage 5 CKD (median age =56 years old; 63% men; 199 patients had CVD) took part in our study on malnutrition, inflammation, and CVD in incident dialysis patients. Circulating levels of albumin, ferritin, high-sensitivity C-reactive protein (hsCRP), IGF-1, IL-6, orosomucoid, troponin T (TnT), TNF, soluble intracellular adhesion molecule, soluble vascular cellular adhesion molecule 1 (sVCAM-1), and platelet and white blood cell (WBC) counts were analyzed as predictors of the presence of clinically overt CVD at baseline, protein-energy wasting (PEW), and subsequent all-cause mortality. During follow-up for a median of 28 months, there were 149 deaths, 81 of which were caused by CVD.

Results: Most biomarkers were elevated compared with reference values and--except for albumin, ferritin, and IGF-1-higher in patients with CVD. In receiver operating characteristic analysis, age, IL-6, TnT, hsCRP, and IGF-1 were classifiers of baseline CVD and predictors of all-cause mortality. In addition to age, diabetes mellitus, smoking (for CVD), and PEW, only IL-6, relative risk (RR) 1.10 and 95% confidence interval ([95% CI], 1.02 to 1.19), sVCAM-1 RR 1.09 (95% CI, 1.01 to 1.17), and serum albumin RR 0.89 (95% CI, 0.83 to 0.95) associated with baseline CVD, and only WBC, hazard ratio (HR) 1.94 (95% CI, 1.34 to 2.82), IL-6 HR 1.79 (95% CI, 1.20 to 2.67), and TNF HR 0.65 (95% CI, 0.44 to 0.97) predicted all-cause mortality.

Conclusions: In addition to age and comorbidities, only IL-6, sVCAM-1, and albumin could-independently of other biomarkers-classify clinical CVD, and only IL-6, WBC, and TNF could-independently of other biomarkers-predict all-cause mortality risk. These data underscore the robustness of IL-6 as a classifier of clinically overt CVD and predictor of all-cause mortality in patients with stage 5 CKD.

Keywords: Biomarkers; C-Reactive Protein; Follow-Up Studies; Humans; Inflammation; Interleukin-6; Renal Insufficiency, Chronic; cardiovascular disease; chronic kidney disease; mortality.

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Figures

Figure 1.
Figure 1.
The optimal predictive cutoff value for each biomarker was defined using receiver operating characteristics curves. In the example shown here, age appeared as a stronger predictor of outcomes than IL-6 and high-sensitivity CRP, a finding which was confirmed by the subsequent analyses. Areas under the curves (AUCs) of receiver operating characteristics in 543 patients with stage 5 CKD for patient age, IL-6, and high–sensitivity C–reactive protein (CRP) in relation to (A) presence of clinically overt cardiovascular disease (CVD) and (B) 60 months all-cause mortality censored for transplantation. (A) The AUC of age, IL-6, and high-sensitivity CRP for CVD in patients with stage 5 CKD (n=543). (B) The AUC of age, IL-6, and high-sensitivity CRP for all-cause mortality in patients with stage 5 CKD (n=543).
Figure 2.
Figure 2.
The predictive strength, expressed as pseudo-r, of using biomarkers to predict presence of clinically overt cardiovascular disease (CVD; upper panel) and all–cause mortality risk (lower panel) during follow-up of up to 60 months censored for transplantation in 543 patients with stage 5 CKD. Model 1: age, sex, diabetes mellitus, smoking, and eGFR (calendar year for all-cause mortality). Model 2: model 1 as well as subjective global assessment of nutritional status, albumin, IGF-1, TNF, soluble intracellular adhesion molecule, and soluble vascular cellular adhesion molecule 1. Model 3: model 2 as well as high–sensitivity C–reactive protein, troponin T, IL-6, and orosomucoid. Model 4: model 3 as well as ferritin, platelet count, and white blood cell count.

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