Performance of Risk Assessment Models for Prevalent or Undiagnosed Type 2 Diabetes Mellitus in a Multi-Ethnic Population-The Helius Study.

Morgan O Obura,Irene Gm Van Valkengoed,Joline Wj Beulens,Marieke B Snijder,Leen M ’T Hart,Eric Moll Van Charante,Simone P Rauh,Femke Rutters

doi:10.5334/gh.846

Abstract

Background:Most risk assessment models for type 2 diabetes (T2DM) have been developed in Caucasians and Asians; little is known about their performance in other ethnic groups.Objective(s):We aimed to identify existing models for the risk of prevalent or undiagnosed T2DM and externally validate them in a multi-ethnic population currently living in the Netherlands.Methods:A literature search to identify risk assessment models for prevalent or undiagnosed T2DM was performed in PubMed until December 2017. We validated these models in 4,547 Dutch, 3,035 South Asian Surinamese, 4,119 African Surinamese, 2,326 Ghanaian, 3,598 Turkish, and 3,894 Moroccan origin participants from the HELIUS (Healthy LIfe in an Urban Setting) cohort study performed in Amsterdam. Model performance was assessed in terms of discrimination (C-statistic) and calibration (Hosmer-Lemeshow test). We identified 25 studies containing 29 models for prevalent or undiagnosed T2DM. C-statistics varied between 0.77–0.92 in Dutch, 0.66–0.83 in South Asian Surinamese, 0.70–0.82 in African Surinamese, 0.61–0.81 in Ghanaian, 0.69–0.86 in Turkish, and 0.69–0.87 in the Moroccan populations. The C-statistics were generally lower among the South Asian Surinamese, African Surinamese, and Ghanaian populations and highest among the Dutch. Calibration was poor (Hosmer-Lemeshow p < 0.05) for all models except one.Conclusions:Generally, risk models for prevalent or undiagnosed T2DM show moderate to good discriminatory ability in different ethnic populations living in the Netherlands, but poor calibration. Therefore, these models should be recalibrated before use in clinical practice and should be adapted to the situation of the population they are intended to be used in.

Highlights

There is evidence that a substantial proportion of people living with T2DM may be undiagnosed [1]
There were no clear patterns in model performance, depending on whether the models were developed in Asian, Caucasian, or multi-ethnic populations
An external evaluation of the performance of 29 non-invasive risk assessment models for prevalent or undiagnosed T2DM in a multi-ethnic cohort showed that the models had a moderate to good discriminatory ability per ethnic group

Summary

Introduction

There is evidence that a substantial proportion of people living with T2DM may be undiagnosed [1]. Due to its asymptomatic nature at onset, T2DM diagnosis is often delayed. By the time of diagnosis, most patients have one or more vascular complications [2]. Early detection of those with T2DM is essential for the initiation of relevant interventions, which could prevent or delay associated complications. Based on recent systematic reviews [3, 4], a substantial number of risk assessment models have been developed for prevalent or undiagnosed T2DM. About 20% of these models have not

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