Globally, 371 million people have diabetes with half unaware of their condition and over 80% living in low- and middle-income countries. An important strategy for tackling the diabetes burden is to screen for undiagnosed diabetes and for future risk of developing diabetes.
Diabetes risk scores are a cheap and simple way of assessing an individual’s risk of having undiagnosed diabetes and risk of future diabetes. With limited resources in low- and middle-income countries, diabetes risk scores can be a simple and cost effective way to identify people at risk of or who have undiagnosed diabetes. However, currently available diabetes risk scores only work well in populations which the risk scores were developed for. Low- and middle-income countries do not have the data required to develop diabetes risk prediction scores for their populations.
The risk prediction tools for identifying people at high risk of developing type 2 diabetes (PREDICT-2) project, an initiative of the International Diabetes Federation, has been formed to establish and validate a methodology for adapting diabetes risk prediction scores for populations with locally available demographic data. This will allow countries without longitudinal data to develop their own country specific diabetes prediction score based on a set of instructions from PREDICT-2 and local diabetes risk factor variables that are easily obtainable within their countries. The PREDICT-2 dataset currently includes eight longitudinal and three cross-sectional studies from eight countries. Caucasians comprise 80% of participants and the remaining 20% of participants are mostly migrants or descendents of migrants. For this project to be globally relevant, PREDICT-2 will require data from other ethnic populations to modify, develop and validate risk scores that will be suitable for use in most populations.
The PREDICT-2 analysis team is, therefore, calling for researchers to assist with the project through the contribution of datasets. Researchers interested in the PREDICT-2 project should contact Dr. Crystal Lee at firstname.lastname@example.org.