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Biomarkers of rapid chronic kidney disease progression in type 2 diabetes.

Looker, Helen C; Colombo, Marco; Hess, Sibylle; Brosnan, Mary J; Farran, Bassam; Dalton, R Neil; Wong, Max C; Turner, Charles; Palmer, Colin N A and Nogoceke, Everson, et al. (2015) In Kidney International 88(4). p.888-896
Abstract
Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and... (More)
Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, β2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.Kidney International advance online publication, 22 July 2015; doi:10.1038/ki.2015.199. (Less)
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Kidney International
volume
88
issue
4
pages
888 - 896
publisher
Nature Publishing Group
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  • pmid:26200946
  • wos:000362219600030
  • scopus:84942981476
ISSN
1523-1755
DOI
10.1038/ki.2015.199
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English
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7bfd5c26-dc50-4795-bd7e-8580e7870371 (old id 7721377)
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http://www.ncbi.nlm.nih.gov/pubmed/26200946?dopt=Abstract
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2015-08-10 16:00:25
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2017-11-19 03:20:14
@article{7bfd5c26-dc50-4795-bd7e-8580e7870371,
  abstract     = {Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, β2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.Kidney International advance online publication, 22 July 2015; doi:10.1038/ki.2015.199.},
  author       = {Looker, Helen C and Colombo, Marco and Hess, Sibylle and Brosnan, Mary J and Farran, Bassam and Dalton, R Neil and Wong, Max C and Turner, Charles and Palmer, Colin N A and Nogoceke, Everson and Groop, Leif and Salomaa, Veikko and Dunger, David B and Agakov, Felix and McKeigue, Paul M and Colhoun, Helen M},
  issn         = {1523-1755},
  language     = {eng},
  number       = {4},
  pages        = {888--896},
  publisher    = {Nature Publishing Group},
  series       = {Kidney International},
  title        = {Biomarkers of rapid chronic kidney disease progression in type 2 diabetes.},
  url          = {http://dx.doi.org/10.1038/ki.2015.199},
  volume       = {88},
  year         = {2015},
}