title: Use of urine biomarker-derived clusters to predict the risk of chronic kidney disease and all-cause mortality in HIV-infected women.
abstract: Although individual urine biomarkers are associated with chronic kidney disease (CKD) incidence and all-cause mortality in the setting of HIV infection, their combined utility for prediction remains unknown.
  
  
  
  We measured eight urine biomarkers shown previously to be associated with incident CKD and mortality risk among 902 HIV-infected women in the Women's Interagency HIV Study: N-acetyl-β-d-glucosaminidase (NAG), kidney injury molecule-1 (KIM-1), alpha-1 microglobulin (α1m), interleukin 18, neutrophil gelatinase-associated lipocalin, albumin-to-creatinine ratio, liver fatty acid-binding protein and α-1-acid-glycoprotein. A group-based cluster method classified participants into three distinct clusters using the three most distinguishing biomarkers (NAG, KIM-1 and α1m), independent of the study outcomes. We then evaluated associations of each cluster with incident CKD (estimated glomerular filtration rate <60 mL/min/1.73 m(2) by cystatin C) and all-cause mortality, adjusting for traditional and HIV-related risk factors.
  
  
  
  Over 8 years of follow-up, 177 CKD events and 128 deaths occurred. The first set of clusters partitioned women into three groups, containing 301 (Cluster 1), 470 (Cluster 2) and 131 (Cluster 3) participants. The rate of CKD incidence was 13, 21 and 50% across the three clusters; mortality rates were 7.3, 13 and 34%. After multivariable adjustment, Cluster 3 remained associated with a nearly 3-fold increased risk of both CKD and mortality, relative to Cluster 1 (both P < 0.001). The addition of the multi-biomarker cluster to the multivariable model improved discrimination for CKD (c-statistic = 0.72-0.76, P = 0.0029), but only modestly for mortality (c = 0.79-0.80, P = 0.099). Clusters derived with all eight markers were no better for discrimination than the three-biomarker clusters.
  
  
  
  For predicting incident CKD in HIV-infected women, clusters developed from three urine-based kidney disease biomarkers were as effective as an eight-marker panel in improving risk discrimination.
authors.affiliation: University of California and Veterans Affairs Medical Center, San Francisco, CA, USA.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Scherzer
authors.affiliation: Department of Biostatistics, School of Public Health, Yale University, New Haven, CT, USA.
authors.forename: Haiqun
authors.initials: H
authors.lastname: Lin
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: Alison
authors.initials: A
authors.lastname: Abraham
authors.affiliation: Division of Nephrology, London Health Sciences Centre, Western University, London, ON, Canada.
authors.forename: Heather
authors.initials: H
authors.lastname: Thiessen-Philbrook
authors.affiliation: Section of Nephrology, Department of Medicine, Program of Applied Translational Research, Yale University, New Haven, CT, USA.
authors.forename: Chirag R
authors.initials: CR
authors.lastname: Parikh
authors.affiliation: Division of Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Bennett
authors.affiliation: Department of Medicine, Stroger Hospital and Rush University, Chicago, IL, USA.
authors.forename: Mardge H
authors.initials: MH
authors.lastname: Cohen
authors.affiliation: Department of Medicine, University of Southern California, Los Angeles, CA, USA.
authors.forename: Marek
authors.initials: M
authors.lastname: Nowicki
authors.affiliation: Department of Neurology, State University of New York-Downstate Medical Center, Brooklyn, NY, USA.
authors.forename: Deborah R
authors.initials: DR
authors.lastname: Gustafson
authors.affiliation: Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA.
authors.forename: Anjali
authors.initials: A
authors.lastname: Sharma
authors.affiliation: Division of Infectious Diseases and Travel Medicine, Department of Medicine, Georgetown University Medical Center, Washington, DC, USA.
authors.forename: Mary
authors.initials: M
authors.lastname: Young
authors.affiliation: University of California and Veterans Affairs Medical Center, San Francisco, CA, USA.
authors.forename: Phyllis
authors.initials: P
authors.lastname: Tien
authors.affiliation: University of California and Veterans Affairs Medical Center, San Francisco, CA, USA.
authors.forename: Vasantha
authors.initials: V
authors.lastname: Jotwani
authors.affiliation: University of California and Veterans Affairs Medical Center, San Francisco, CA, USA.
authors.forename: Michael G
authors.initials: MG
authors.lastname: Shlipak
mesh_terms: D000118:Acetylglucosaminidase / Q000652:urine; D000328:Adult; D000510:Alpha-Globulins / Q000652:urine; D015415:Biomarkers / Q000652:urine*; D003404:Creatinine / Q000652:urine; D055316:Cystatin C / Q000652:urine; D050556:Fatty Acid-Binding Proteins; D005260:Female; D015658:HIV Infections / Q000150:complications / Q000401:mortality* / Q000652:urine; D015497:HIV-1 / Q000502:physiology*; D000072596:Hepatitis A Virus Cellular Receptor 1 / Q000032:analysis; D006801:Humans; D020382:Interleukin-18 / Q000652:urine; D000071068:Lipocalin-2 / Q000652:urine; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D051436:Renal Insufficiency, Chronic / Q000209:etiology / Q000401:mortality* / Q000652:urine; D012307:Risk Factors
chemical_list: D000510:Alpha-Globulins; D015415:Biomarkers; D055316:Cystatin C; C493319:FABP1 protein, human; D050556:Fatty Acid-Binding Proteins; D000072596:Hepatitis A Virus Cellular Receptor 1; D020382:Interleukin-18; D000071068:Lipocalin-2; C016001:alpha-1-microglobulin; D003404:Creatinine; D000118:Acetylglucosaminidase
keywords: HIV; biomarker; chronic kidney disease; cluster analysis; risk discrimination