Validation of two prediction models of undiagnosed chronic kidney disease in mixed-ancestry South Africans
Date
2015-07-04
Journal Title
Journal ISSN
Volume Title
Publisher
BioMed Central
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 m2’ 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 m2’ 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 m2’ 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.
Conclusion: 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.
AFRIKAANSE OPSOMMING: Geen opsomming beskikbaar
AFRIKAANSE OPSOMMING: Geen opsomming beskikbaar
Description
CITATION: Mogueo, A. et al. 2015. Validation of two prediction models of undiagnosed chronic kidney disease in mixed-ancestry South Africans. BMC Nephrology, 16:94, doi:10.1186/s12882-015-0093-6.
The original publication is available at http://bmcnephrol.biomedcentral.com
The original publication is available at http://bmcnephrol.biomedcentral.com
Keywords
Chronic renal failure, Model predictive control
Citation
Mogueo, A. et al. 2015. Validation of two prediction models of undiagnosed chronic kidney disease in mixed-ancestry South Africans. BMC Nephrology, 16:94, doi:10.1186/s12882-015-0093-6.