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Abstract:
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Missing data is a concern in clinical trials as it limits one’s ability to draw accurate conclusions based on study data. Sources of missing data can be structural in nature and related to potential trial conduct and design flaws. Unfortunately, even after proactively accounting for these pitfalls, missing data may still arise and needs to be accounted for analytically.
To shed further light on this matter, this poster will present a variety of approaches (e.g., complete case, single imputation, multiple imputation, tipping point analyses) that are currently used to address missing data in medical device trials and a preview of coming analytical methods (i.e., estimands). Through the presentation of 3 recent case studies, one will discover some shifts taking place with respect to currently accepted analytical practices by regulatory authorities. When these practices are accounted for in analysis plans proactively, sponsors have the ability to potentially shorten study review times and provide a more complete picture to reviewers as to a product’s effectiveness.
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