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

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.