Predicting the effects of blood pressure-lowering treatment on major cardiovascular events for individual patients with type 2 diabetes mellitus results from action in diabetes and vascular disease: Preterax and diamicron mr controlled evaluation
Van Der Leeuw J., Visseren FLJ., Woodward M., Zoungas S., Kengne AP., Van Der Graaf Y., Glasziou P., Hamet P., MacMahon S., Poulter N., Grobbee DE., Chalmers J.
© 2014 American Heart Association, Inc. Blood pressure-lowering treatment reduces cardiovascular risk in patients with diabetes mellitus, but the effect varies between individuals. We sought to identify which patients benefit most from such treatment in a large clinical trial in type 2 diabetes mellitus. In Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation (ADVANCE) participants (n=11 140), we estimated the individual patient 5-year absolute risk of major adverse cardiovascular events with and without treatment by perindopril-indapamide (4/1.25 mg). The difference between treated and untreated risk is the estimated individual patient's absolute risk reduction (ARR). Predictions were based on a Cox proportional hazards model inclusive of demographic and clinical characteristics together with the observed relative treatment effect. The group-level effect of selectively treating patients with an estimated ARR above a range of decision thresholds was compared with treating everyone or those with a blood pressure < 140/90 mm Hg using net benefit analysis. In ADVANCE, there was wide variation in treatment effects across individual patients. According to the algorithm, 43% of patients had a large predicted 5-year ARR of 1% (number-needed-to-treat [NNT5] 100) and 40% had an intermediate predicted ARR of 0.5% to 1% (NNT5=100-200). The proportion of patients with a small ARR of 0.5% (NNT5200) was 17%. Provided that one is prepared to treat at most 200 patients for 5 years to prevent 1 adverse outcome, prediction-based treatment yielded the highest net benefit. In conclusion, a multivariable treatment algorithm can identify those individuals who benefit most from blood pressure-lowering therapy in terms of ARR of major adverse cardiovascular events and may be used to guide treatment decisions in individual patients with diabetes.