Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa

 

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dc.contributor.author Masconi, Katya L en_ZA
dc.contributor.author Matsha, Tandi en_ZA
dc.contributor.author Erasmus, Rajiv en_ZA
dc.contributor.author Kengne, Andre en_ZA
dc.date.accessioned 2015-12-07T08:52:12Z
dc.date.available 2015-12-07T08:52:12Z
dc.date.issued 2015 en_ZA
dc.identifier.citation Masconi, K., Matsha, T.E., Erasmus, R.T., & Kengne, A.P. (2015).Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa. Diabetology & Metabolic Syndrome, 7(1), 42. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/15653
dc.identifier.uri http://dx.doi.org/10.1186/s13098-015-0039-y
dc.description.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, 52.2years, 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. en_ZA
dc.language.iso eng en_ZA
dc.publisher BioMed Central Ltd en_ZA
dc.rights This is an Open Access article distributed under the terms of the Creative Commons Attribution License en_ZA
dc.rights.uri http://creativecommons.org/licenses/by/4.0 en_ZA
dc.source Diabetology & Metabolic Syndrome en_ZA
dc.source.uri http://www.dmsjournal.com/ en_ZA
dc.subject.other type 2 diabetes en_ZA
dc.subject.other mixed-ancestry South Africans en_ZA
dc.title Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa en_ZA
dc.type Journal Article en_ZA
dc.rights.holder 2015 Masconi et al.; licensee BioMed Central. en_ZA
uct.type.publication Research en_ZA
uct.type.resource Article en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Health Sciences en_ZA
dc.publisher.department Department of Medicine en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Masconi, K. L., Matsha, T., Erasmus, R., & Kengne, A. (2015). Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa. <i>Diabetology & Metabolic Syndrome</i>, http://hdl.handle.net/11427/15653 en_ZA
dc.identifier.chicagocitation Masconi, Katya L, Tandi Matsha, Rajiv Erasmus, and Andre Kengne "Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa." <i>Diabetology & Metabolic Syndrome</i> (2015) http://hdl.handle.net/11427/15653 en_ZA
dc.identifier.vancouvercitation Masconi KL, Matsha T, Erasmus R, Kengne A. Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa. Diabetology & Metabolic Syndrome. 2015; http://hdl.handle.net/11427/15653. en_ZA
dc.identifier.ris TY - Journal Article AU - Masconi, Katya L AU - Matsha, Tandi AU - Erasmus, Rajiv AU - Kengne, Andre AB - 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, 52.2years, 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. DA - 2015 DB - OpenUCT DO - 10.1186/s13098-015-0039-y DP - University of Cape Town J1 - Diabetology & Metabolic Syndrome LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 T1 - Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa TI - Independent external validation and comparison of prevalent diabetes risk prediction models in a mixed-ancestry population of South Africa UR - http://hdl.handle.net/11427/15653 ER - en_ZA


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