Baseline diabetes as a way to predict CV outcomes in a lipid-modifying trial: a meta-analysis of 330,376 patients from 47 landmark studies

BACKGROUND: Diabetes is a major cardiovascular risk factor. However, its influence on the rate of occurrence of cardiovascular (CV) events during a clinical trial that included a diabetes subgroup has not yet been quantified. AIMS: To establish equations relating baseline diabetes prevalence and incident CV events, based on comparator arms data of major lipid-modifying trials. METHODS: Meta-analysis of primary outcomes (PO) rates of key prospective trials, for which the baseline proportion of diabetics was reported, including studies having specifically reported CV outcomes within their diabetic subgroups. RESULTS: 47 studies, representing 330,376 patients (among whom 124,115 diabetics), were analyzed as regards the relationship between CV outcomes rates (including CHD) and the number of diabetics enrolled. Altogether, a total of 18,445 and 16,156 events occurred in the comparator and treatment arms, respectively. There were significant linear relationships between diabetes prevalence and both PO and CHD rates (%/year): y = 0.0299*x + 3.12 [PO] (p = 0.0128); and y = 0.0531*x + 1.54 [CHD] (p = 0.0094), baseline diabetes predicting PO rates between 3.12 %/year (no diabetic included) and 6.11 %/year (all patients diabetic); and CHD rates between 1.54 %/year (no diabetic) and 6.85 %/year (all patients diabetic). The slopes of the equations did not differ according to whether they were derived from primary or secondary prevention trials. CONCLUSIONS: Absolute and relative CV risk associated with diabetes at inclusion can be readily predicted using linear equations relating diabetes prevalence to primary outcomes or CHD rates.