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A systematic review of over 400 studies in type 2 diabetes reveals 13 biomarkers, including NT-proBNP and troponin-t, with potential to significantly enhance cardiovascular disease risk prediction.
Data from a systematic review and analysis of more than 400 studies of people with type 2 diabetes has identified a group of 13 biomarkers investigators purport could significantly improve the ability to predict cardiovascular disease risk in these patients.
Conducted as part of the Precision Medicine in Diabetes Initiative, an international partnership between the American Diabetes Association and the European Association for the Study of Diabetes, results of the study provide insight into the potential utility of a panel of 13 biomarkers, including NT-proBNP, troponin-t (TnT), pulse wave velocity, and others, for predicting the risk of cardiovascular disease among people with type 2 diabetes.1
“The 13 biomarkers, especially NT-proBNP, warrant further testing to evaluate their potential,” said co-senior investigator Ronald Ma, MB BChir, the S.H. Ho Professor of Diabetes at the Chinese University of Hong Kong.2 “If future studies confirm their value in predicting cardiovascular risk in patients with type 2 diabetes, we may be able to change standards of care.”
Through a search of the PubMed and Embase databases, investigators identified 9380 studies for inclusion in their assessments. Among these, 9316 were unique articles. Investigators selected 615 for full-text review and deemed 416 eligible for inclusion in the analysis. Among the 416 studies identified for inclusion, 321 were biomarker studies, 48 were genetic marker studies, and 47 were risk score/model studies.1
Among the studies include, the United States, United Kingdom, China, Japan, and Italy were the most represented countries with regard to origin of study participants. Investigators pointed out the most predominant ancestry among studied populations were European (57.1%), East Asian (19.7%), South Asian (5.5%), and Hispanic or Latin American (4.2%).1
In total, investigators assessed the predictive utility of 195 biomarkers using pooled meta-analyses, non-pooled analyses, and assessments. Of these, 134 had a significant adjusted association for predicting cardiovascular disease.1
Upon analysis, investigators identified 13 associated with improvement in prediction performance. The biomarkers of interest with the greatest predictive utility were:1
Biomarkers considered to add moderate predictive utility were:1
The biomarkers with low predictive utility were:1
“More than 500 million people worldwide live with diabetes,” said co-senior investigator Maria F. Gomez, PhD, research group leader at the Lund University Diabetes Centre and professor of physiology at Lund University.2 “With numbers that high, it’s important to identify readily available ways to accurately classify patients so that those at higher risk of cardiovascular disease can receive the preventative care they need.”