Effects of Three Different Methods Defining Onset of Peripheral Artery Disease on the Assessments of Incidence and Important Predictors – Results from the German Epidemiological Trial on Ankle Brachial Index (getABI)

PURPOSE: The common definition of asymptomatic peripheral artery disease (PAD) by a single determination of the ankle brachial index (ABI) has some uncertainty due to measurement errors. This may impact estimates of PAD incidence and assessment of PAD risk factors. To investigate this issue, we used three methods to define asymptomatic PAD and made use of data from the German Epidemiological Trial on Ankle Brachial Index (getABI). PATIENTS AND METHODS: A total of 6,880 unselected subjects aged ≥65 years, enrolled by 344 trained general practitioners, had ABI assessments at baseline and four visits during follow-up. The first approach defined asymptomatic PAD onset as soon as a single ABI value was below 0.9 (single ABI). The second approach employed a regression method using all available ABI values (regression A), while for the third approach (regression B), an extended regression beyond the last valid ABI value for the observation time of the study was allowed. For each approach, we calculated PAD incidence rates and assessed the effect of important PAD predictors using multivariable Cox proportional hazards regression. RESULTS: The regression method A showed the lowest (25.0 events per 1,000 person years) and the single ABI method the highest incidence rate (41.2). The regression methods assigned greater impact to several risk factors of incident PAD. Using regression A, the hazard ratios (HR) of active smoking (2.36; 95% CI 1.92 to 2.90) and of diabetes (1.33; 95% CI 1.13 to 1.56), using regression B the HR of older age (1.72; 95% CI 1.50 to 1.97) were about twice as high as the corresponding HR of the single ABI approach. CONCLUSION: Use of the single ABI method leads to higher PAD incidence rates and to lower impact of important PAD predictors compared to regression methods. For an alert risk factor management, multiple ABI determination may be useful.