Abstract 13462: 6-minute Walk Test Variability May be Reduced by a Structured Training and Monitoring Program, Potentially Facilitating Detection of Treatment Effects

Background: The 6-minute walk test (6MWT) is well established for evaluation of functional exercise capacity in patients with conditions such as pulmonary hypertension, peripheral arterial disease and heart failure. Its popularity as an endpoint in heart failure trials has increased in parallel with health authority acceptance of the test as a measure of patients' function. Minimizing variability is key to the successful conduct and outcome of trials with 6MWT endpoints. We assessed the impact on walking distance variability of a structured training and monitoring program Methods: After systematically observing conduct of 6MWT worldwide, our core lab developed a multifaceted approach including inspection and standardization of the walking course, standardized training, review of the first 3 tests for each test administrator and random tests thereafter, standardized data collection methods, and assessment of intra-test inconsistencies with feedback. Variability of walking distance using this structured approach is descriptively compared with 6MWT data from the literature. Results: In a multicenter trial which used the structured program, the standard deviation (SD) of distance walked was 21.7% of the mean at baseline and 22.6% at Week 4 (Table). For comparison, we reviewed 2018-19 reports of 6MWT not utilizing this structured approach and identified 5 multicenter studies of patients with heart failure which reported mean and SD of distance walked (Table). Baseline distance walked ranged from 104 to 385 m (weighted mean 220.4 m); SD of distance walked ranged from 28% to 135% of distance walked (weighted mean 70.9%). Conclusion: Standardization of the 6MWT walking course, structured training of test administrators and monitoring of test quality may reduce test variability which could improve accuracy of treatment effect assessment and possibly require smaller sample sizes.