title: Validation of two prediction models of undiagnosed chronic kidney disease in mixed-ancestry South Africans.
abstract: BACKGROUND
  Chronic kidney disease (CKD) is a global challenge. Risk models to predict prevalent undiagnosed CKD have been published. However, none was developed or validated in an African population. We validated the Korean and Thai CKD prediction model in mixed-ancestry South Africans.
  
  
  METHODS
  Discrimination and calibration were assessed overall and by major subgroups. CKD was defined as 'estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m(2)' or 'any nephropathy'. eGFR was based on the 4-variable Modification of Diet in Renal Disease (MDRD) formula.
  
  
  RESULTS
  In all 902 participants (mean age 55 years) included, 259 (28.7 %) had prevalent undiagnosed CKD. C-statistics were 0.76 (95 % CI: 0.73-0.79) for 'eGFR <60 ml/min/1.73 m(2)' and 0.81 (0.78-0.84) for 'any nephropathy' for the Korean model; corresponding values for the Thai model were 0.80 (0.77-0.83) and 0.77 (0.74-0.81). Discrimination was better in men, older and normal weight individuals. The model underestimated CKD risk by 10 % to 13 % for the Thai and 9 % to 93 % for the Korean model. Intercept adjustment significantly improved the calibration with an expected/observed risk of 'eGFR <60 ml/min/1.73 m(2)' and 'any nephropathy' respectively of 0.98 (0.87-1.10) and 0.97 (0.86-1.09) for the Thai model; but resulted in an underestimation by 24 % with the Korean model. Results were broadly similar for CKD derived from the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula.
  
  
  CONCLUSIONS
  Asian prevalent CKD risk models had acceptable performances in mixed-ancestry South Africans. This highlights the potential importance of using existing models for risk CKD screening in developing countries.
authors.affiliation: Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa. amely.mogueo@yahoo.fr.|School of Health Sciences, Catholic University of Central Africa, Yaounde, Cameroon. amely.mogueo@yahoo.fr.
authors.forename: Amelie
authors.initials: A
authors.lastname: Mogueo
authors.affiliation: Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA. echouffotcheugui@yahoo.com.|Department of Medicine, MedStar Health, Baltimore, MD, USA. echouffotcheugui@yahoo.com.
authors.forename: Justin B
authors.initials: JB
authors.lastname: Echouffo-Tcheugui
authors.affiliation: Faculty of Health and Wellness Science, Cape Peninsula University of Technology, Cape Town, South Africa. tandimatsha@gmail.com.
authors.forename: Tandi E
authors.initials: TE
authors.lastname: Matsha
authors.affiliation: Division of Chemical Pathology, Faculty of Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa. erasmusrajiv@gmail.com.
authors.forename: Rajiv T
authors.initials: RT
authors.lastname: Erasmus
authors.affiliation: Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa. apkengne@yahoo.com.|Department of Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa. apkengne@yahoo.com.
authors.forename: Andre P
authors.initials: AP
authors.lastname: Kengne
mesh_terms: D000328:Adult; D000368:Aged; D044383:Black People; D003661:Decision Support Techniques; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D051436:Renal Insufficiency, Chronic / Q000453:epidemiology*; D018570:Risk Assessment; D013019:South Africa / Q000453:epidemiology; D044465:White People