Key result
Novel risk score outperforms existing tools in detecting undiagnosed diabetes, achieving 77% AUC.
Why the study?
Most commonly used diabetes risk scores were developed in American or European populations and their applicability to low and middle-income countries like Mongolia remains unquantified.
Does a newly developed diabetes risk score improve the detection of undiagnosed diabetes in the Mongolian population compared to existing risk scores?
Cross-Sectional (n=1,018)
Does a newly developed diabetes risk score improve the detection of undiagnosed diabetes in the Mongolian population compared to existing risk scores?
A newly developed, population-specific diabetes risk score significantly improved the detection of undiagnosed type 2 diabetes in Mongolian adults compared to existing Western tools.
Answers are grounded in this paper and cite their sources.
May support population-specific diabetes screening in Mongolia; leaves open prospective validation before clinical adoption.
BACKGROUND: Most of the commonly used diabetes mellitus screening tools and risk scores have been developed with American or European populations in mind. Their applicability, therefore, to low and middle-income countries remains unquantified. Simultaneously, low and middle-income countries including Mongolia are currently witnessing rising diabetes prevalence. This research aims to develop and validate a diabetes risk score for the screening of undiagnosed type 2 diabetes mellitus in the Mongolian adult population. METHODS: Blood glucose measurements from 1018 Mongolians, as well as information on demography and risk factors prevalence was drawn from 2009 STEPS data. Existing risk scores were applied, measuring sensitivity using area under ROC-curves. Logistic regression models were used to identify additional independent predictors for undiagnosed diabetes. Finally, a new risk score was developed and Hosmer-Lemeshow tests were used to evaluate the agreement between the observed and predicted prevalence. RESULTS: The performance of existing risk scores to identify undiagnosed diabetes was moderate; with the area under ROC curves between 61-64 %. In addition to well-established risk factors, three new independent predictors for undiagnosed diabetes were identified. Incorporating these into a new risk score, the area under ROC curves increased to 77 % (95 % CI 71 %-82 %). CONCLUSIONS: Existing European or American diabetes risk tools cannot be adopted in Asian countries without prior validation in the specific population. With this in mind, a low-cost, reliable screening tool for undiagnosed diabetes was developed and internally validated for Mongolians. The potential for cost and morbidity savings could be significant.
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Dugee et al. (2015) conducted a cross-sectional in Undiagnosed type 2 diabetes (n=1,018). Modified Mongolian diabetes risk score vs. FINDRISC and Rotterdam risk scores was evaluated on Discriminatory ability (Area under ROC curve) for detecting undiagnosed diabetes (AUC 77%, 95% CI 71-82). A newly developed diabetes risk score improved the detection of undiagnosed diabetes in the Mongolian population, achieving an area under the ROC curve of 77% compared to 61-64% for existing scores.
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