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Activity Number:
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54
- Methods and Modeling for Medical Device and Clinical Studies
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Section on Medical Devices and Diagnostics
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Abstract #314079
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Title:
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Pain Assessment Using Errors-In-Variables Regression
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Author(s):
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Bin Wang*
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Companies:
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Food and Drug Administration CDRH
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Keywords:
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Abstract:
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Visual analogue scale (VAS) is a useful tool to measure the intensity of sensations and feelings. It has been widely used as primary endpoints in many clinical trials to assess the efficacy of medical devices or drugs to treat pain. VAS is subjective and has high level of uncertainty. We propose a measurement error model for VAS and develop new methodology for efficacy assessments. An errors-in-variable non-parametric regression method is developed to benchmark the effectiveness by adjusting the baseline VAS differences in randomized controlled trials.
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Authors who are presenting talks have a * after their name.
