Katherine G Garlo1,2, William B White3, George L Bakris4, Faiez Zannad5, Craig A Wilson6, Stuart Kupfer6, Muthiah Vaduganathan7, David A Morrow7, Christopher P Cannon8,7, David M Charytan8,2. 1. Division of Cardiometabolic Trials, Baim Institute for Clinical Research, Boston, Massachusetts; kgarlo@bwh.harvard.edu. 2. Department of Medicine, Renal Division, Brigham and Women's Hospital, Boston, Massachusetts. 3. Division of Hypertension and Clinical Pharmacology, Calhoun Cardiology Center, University of Connecticut School of Medicine, Farmington, Connecticut. 4. Department of Medicine and American Society of Hypertension Comprehensive Hypertension Center University of Chicago, University of Chicago School of Medicine, Chicago, Illinois. 5. Department of Medicine, Universite de Lorraine and Centre Hospitalier Universitaire, Nancy, France. 6. Division of Cardiovascular and Metabolic Diseases, Takeda Development Center Americas, Inc., Deerfield, Illinois; and. 7. Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. 8. Division of Cardiometabolic Trials, Baim Institute for Clinical Research, Boston, Massachusetts.
Abstract
BACKGROUND AND OBJECTIVES: Biomarkers may improve identification of individuals at risk of eGFR decline who may benefit from intervention or dialysis planning. However, available biomarkers remain incompletely validated for risk stratification and prediction modeling. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We examined serum cystatin C, urinary kidney injury molecule-1 (uKIM-1), and urinary neutrophil gelatinase-associated lipocalin (UNGAL) in 5367 individuals with type 2 diabetes mellitus and recent acute coronary syndromes enrolled in the Examination of Cardiovascular Outcomes with Alogliptin versus Standard of Care (EXAMINE) trial. Baseline concentrations and 6-month changes in biomarkers were also evaluated. Cox proportional regression was used to assess associations with a 50% decrease in eGFR, stage 5 CKD (eGFR<15 ml/min per 1.73 m2), or dialysis. RESULTS: eGFR decline occurred in 98 patients (1.8%) over a median of 1.5 years. All biomarkers individually were associated with higher risk of eGFR decline (P<0.001). However, when adjusting for baseline eGFR, proteinuria, and clinical factors, only baseline cystatin C (adjusted hazard ratio per 1 SD change, 1.66; 95% confidence interval, 1.41 to 1.96; P<0.001) and 6-month change in urinary neutrophil gelatinase-associated lipocalin (adjusted hazard ratio per 1 SD change, 1.07; 95% confidence interval, 1.02 to 1.12; P=0.004) independently associated with CKD progression. A base model for predicting kidney function decline with nine standard risk factors had strong discriminative ability (C-statistic 0.93). The addition of baseline cystatin C improved discrimination (C-statistic 0.94), but it failed to reclassify risk categories of individuals with and without eGFR decline. CONCLUSIONS: The addition of cystatin C or biomarkers of tubular injury did not meaningfully improve the prediction of eGFR decline beyond common clinical factors and routine laboratory data in a large cohort of patients with type 2 diabetes and recent acute coronary syndrome. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2018_01_16_CJASNPodcast_18_3_G.mp3.
BACKGROUND AND OBJECTIVES: Biomarkers may improve identification of individuals at risk of eGFR decline who may benefit from intervention or dialysis planning. However, available biomarkers remain incompletely validated for risk stratification and prediction modeling. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We examined serum cystatin C, urinary kidney injury molecule-1 (uKIM-1), and urinary neutrophil gelatinase-associated lipocalin (UNGAL) in 5367 individuals with type 2 diabetes mellitus and recent acute coronary syndromes enrolled in the Examination of Cardiovascular Outcomes with Alogliptin versus Standard of Care (EXAMINE) trial. Baseline concentrations and 6-month changes in biomarkers were also evaluated. Cox proportional regression was used to assess associations with a 50% decrease in eGFR, stage 5 CKD (eGFR<15 ml/min per 1.73 m2), or dialysis. RESULTS:eGFR decline occurred in 98 patients (1.8%) over a median of 1.5 years. All biomarkers individually were associated with higher risk of eGFR decline (P<0.001). However, when adjusting for baseline eGFR, proteinuria, and clinical factors, only baseline cystatin C (adjusted hazard ratio per 1 SD change, 1.66; 95% confidence interval, 1.41 to 1.96; P<0.001) and 6-month change in urinary neutrophil gelatinase-associated lipocalin (adjusted hazard ratio per 1 SD change, 1.07; 95% confidence interval, 1.02 to 1.12; P=0.004) independently associated with CKD progression. A base model for predicting kidney function decline with nine standard risk factors had strong discriminative ability (C-statistic 0.93). The addition of baseline cystatin C improved discrimination (C-statistic 0.94), but it failed to reclassify risk categories of individuals with and without eGFR decline. CONCLUSIONS: The addition of cystatin C or biomarkers of tubular injury did not meaningfully improve the prediction of eGFR decline beyond common clinical factors and routine laboratory data in a large cohort of patients with type 2 diabetes and recent acute coronary syndrome. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2018_01_16_CJASNPodcast_18_3_G.mp3.
Authors: Liang Li; Brad C Astor; Julia Lewis; Bo Hu; Lawrence J Appel; Michael S Lipkowitz; Robert D Toto; Xuelei Wang; Jackson T Wright; Tom H Greene Journal: Am J Kidney Dis Date: 2012-01-26 Impact factor: 8.860
Authors: Nattachai Srisawat; Xiaoyan Wen; Minjae Lee; Lan Kong; Michele Elder; Melinda Carter; Mark Unruh; Kevin Finkel; Anitha Vijayan; Mohan Ramkumar; Emil Paganini; Kai Singbartl; Paul M Palevsky; John A Kellum Journal: Clin J Am Soc Nephrol Date: 2011-07-14 Impact factor: 8.237
Authors: David T Gilbertson; Jiannong Liu; Jay L Xue; Thomas A Louis; Craig A Solid; James P Ebben; Allan J Collins Journal: J Am Soc Nephrol Date: 2005-11-02 Impact factor: 10.121
Authors: Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh Journal: Ann Intern Med Date: 2009-05-05 Impact factor: 25.391
Authors: Kathleen D Liu; Wei Yang; Amanda H Anderson; Harold I Feldman; Sevag Demirjian; Takayuki Hamano; Jiang He; James Lash; Eva Lustigova; Sylvia E Rosas; Michael S Simonson; Kaixiang Tao; Chi-yuan Hsu Journal: Kidney Int Date: 2013-01-23 Impact factor: 10.612
Authors: Andreas Heinzel; Michael Kammer; Gert Mayer; Roman Reindl-Schwaighofer; Karin Hu; Paul Perco; Susanne Eder; Laszlo Rosivall; Patrick B Mark; Wenjun Ju; Matthias Kretzler; Peter Gilmour; Jonathan M Wilson; Kevin L Duffin; Moustafa Abdalla; Mark I McCarthy; Georg Heinze; Hiddo L Heerspink; Andrzej Wiecek; Maria F Gomez; Rainer Oberbauer Journal: Diabetes Care Date: 2018-07-06 Impact factor: 19.112
Authors: Rakesh Malhotra; Ronit Katz; Vasantha Jotwani; Walter T Ambrosius; Kalani L Raphael; William Haley; Anjay Rastogi; Alfred K Cheung; Barry I Freedman; Henry Punzi; Michael V Rocco; Joachim H Ix; Michael G Shlipak Journal: Clin J Am Soc Nephrol Date: 2020-02-28 Impact factor: 8.237