title: Added value of novel circulating and genetic biomarkers in type 2 diabetes prediction: a systematic review.
abstract: OBJECTIVE
  To provide a systematic overview of the added value of novel circulating and genetic biomarkers in predicting type 2 diabetes (T2DM).
  
  
  METHODS
  We searched MEDLINE and EMBASE (January 2000 to September 2012) for studies that reported a measure of improvement in the performance of T2DM risk prediction models subsequent to adding novel biomarkers to traditional risk factors. We extracted data on study methods and metrics of incremental predictive value of novel biomarkers.
  
  
  RESULTS
  We included 34 publications from 30 studies. All studies reported a change in the area under the receiver-operating characteristic curve, which was modest, ranging from -0.004 to 0.1, with claims of statistically significant improvements in eleven studies. The net reclassification index was evaluated in 11 studies, and ranged from -2.2% to 10.2% after inclusion of genetic markers in six studies (statistically significant in two cases), and from -0.5% to 27.5% after inclusion of non-genetic markers in five studies (non-significant in two studies). The integrated discrimination index (0-2.04) was reported in eight studies, being statistically significant in five of these.
  
  
  CONCLUSIONS
  Currently known novel circulating and genetic biomarkers do not substantially improve T2DM risk prediction above and beyond the ability of traditional risk factors.
authors: Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Road, Northeast Atlanta, GA 30322, USA. Electronic address: jechouf@emory.edu.
authors: Justin B
authors: JB
authors: Echouffo-Tcheugui
authors: Sara D
authors: SD
authors: Dieffenbach
authors: Andre P
authors: AP
authors: Kengne
mesh_terms: D015415:Biomarkers / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000235:genetics*; D005260:Female; D005819:Genetic Markers; D006801:Humans; D008297:Male; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D005819:Genetic Markers
keywords: Biomarkers; Diabetes; Genetics; Prediction