title: Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa.
abstract: BACKGROUND
  Guidelines increasingly encourage the use of multivariable risk models to predict the presence of prevalent undiagnosed type 2 diabetes mellitus worldwide. However, no single model can perform well in all settings and available models must be tested before implementation in new populations. We assessed and compared the performance of five prevalent diabetes risk models in mixed-ancestry South Africans.
  
  
  METHODS
  Data from the Cape Town Bellville-South cohort were used for this study. Models were identified via recent systematic reviews. Discrimination was assessed and compared using C-statistic and non-parametric methods. Calibration was assessed via calibration plots, before and after recalibration through intercept adjustment.
  
  
  RESULTS
  Seven hundred thirty-seven participants (27 % male), mean age, 52.2 years, were included, among whom 130 (17.6 %) had prevalent undiagnosed diabetes. The highest c-statistic for the five prediction models was recorded with the Kuwaiti model [C-statistic 0.68: 95 % confidence: 0.63-0.73] and the lowest with the Rotterdam model [0. 64 (0.59-0.69)]; with no significant statistical differences when the models were compared with each other (Cambridge, Omani and the simplified Finnish models). Calibration ranged from acceptable to good, however over- and underestimation was prevalent. The Rotterdam and the Finnish models showed significant improvement following intercept adjustment.
  
  
  CONCLUSIONS
  The wide range of performances of different models in our sample highlights the challenges of selecting an appropriate model for prevalent diabetes risk prediction in different settings.
authors.affiliation: Division of Chemical Pathology, Stellenbosch University, Cape Town, South Africa ; Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa.
authors.forename: Katya
authors.initials: K
authors.lastname: Masconi
authors.affiliation: Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa.
authors.forename: Tandi E
authors.initials: TE
authors.lastname: Matsha
authors.affiliation: Division of Chemical Pathology, Stellenbosch University, Cape Town, South Africa.
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 ; Department of Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa.
authors.forename: Andre P
authors.initials: AP
authors.lastname: Kengne