Key result
Combining ABI, hs-cTnT, and GGT with traditional risk factors improved cardiovascular risk prediction in type 2 diabetes (C statistic 0.740; 95% CI 0.699-0.781 vs 0.722 for basic model).
Why the study?
Does the addition of non-traditional biomarkers improve cardiovascular risk prediction over traditional risk factors in older people with type 2 diabetes?
Cohort (n=1,066)
Does the addition of non-traditional biomarkers improve cardiovascular risk prediction over traditional risk factors in older people with type 2 diabetes?
Effect estimate: C statistic 0.740 (95% CI 0.699-0.781)
The addition of non-traditional biomarkers, particularly hs-cTnT individually or combined with ABI and GGT, modestly improves cardiovascular risk prediction beyond traditional risk factors in older patients with type 2 diabetes.
BACKGROUND AND AIMS: We aimed at comparing the impact of multiple non-traditional biomarkers (ankle brachial pressure index (ABI), N-terminal pro-brain natriuretic peptide (NT-proBNP), high sensitivity cardiac troponin (hs-cTnT), gamma-glutamyl transpeptidase (GGT) and four markers of systemic inflammation), both individually and in combination, on cardiovascular risk prediction, over and above traditional risk factors incorporated in the QRISK2 score, in older people with type 2 diabetes. METHODS: We conducted a prospective study of 1066 men and women aged 60-75 years with type 2 diabetes mellitus, living in Lothian, Scotland. RESULTS: After 8 years, 205 cardiovascular events occurred. Higher levels of hs-cTNT and NT-proBNP and lower ABI at baseline were associated with increased risk of CV events, independently of traditional risk factors (basic model). The C statistic of 0.722 (95% CI 0.681, 0.763) for the basic model increased on addition of individual biomarkers, most markedly for hs-cTnT (0.732; 0.690, 0.774)). Models including different combinations of biomarkers had even greater C statistics, with the highest for ABI, hs-cTnT and GGT combined (0.740; 0.699, 0.781). CONCLUSIONS: Individually, hs-cTnT appeared to be the most promising biomarker in terms of improving vascular risk prediction in people with type 2 diabetes, over and above traditional risk factors incorporated in the QRISK2 score. Combining several non-traditional biomarkers added further predictive value, and this approach merits further investigation when developing cost effective risk prediction tools for use in clinical practice.
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Price et al. (2017) conducted a cohort in type 2 diabetes mellitus (n=1,066). Non-traditional biomarkers (ABI, NT-proBNP, hs-cTnT, GGT, and systemic inflammation markers) vs. Traditional risk factors (QRISK2 score) was evaluated on Cardiovascular events (C statistic for risk prediction) (C statistic 0.740, 95% CI 0.699-0.781). Combining ABI, hs-cTnT, and GGT with traditional risk factors improved cardiovascular risk prediction in type 2 diabetes (C statistic 0.740; 95% CI 0.699-0.781 vs 0.722 for basic model).
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