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Activity Number:
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385
- Biomarkers, Endpoint Validation and Other Topics
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Type:
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Contributed
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Date/Time:
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Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #318823
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Title:
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Impact of Informative Follow-Up Visits on Longitudinal Real-World Data and Evidence Studies of Comparative Effectiveness: An Application in Multiple Sclerosis
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Author(s):
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Paramita Saha Chaudhuri and Gabrielle Simoneau* and Shirley Liao and Changyu Shen and Fabio Pellegrini and Carl de Moor
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Companies:
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University of Vermont and Biogen and Biogen and Biogen and Biogen and Biogen
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Keywords:
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simulation study;
informative visits;
linear mixed model;
comparative effectiveness
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Abstract:
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Longitudinal studies are helpful for understanding evolution of patient characteristics and outcomes over time. In multiple sclerosis (MS), several markers of disease severity are measured longitudinally using magnetic resonance imaging (MRI) to assess the neurological health of patients. While the typical recommendation is at least yearly MRI visits to help guide treatment, the visit patterns for patients in real-world data (RWD) sources are usually heterogeneous and substantially different from the recommendation. In addition, factors such as age at diagnosis or treatment history could impact the visit pattern. Not appropriately accounting for informative follow-up could result in bias. We compare two new methods (weighted approach and within-cluster resampling) and linear mixed model via extensive simulation studies to understand the impact of informative visit process on treatment effect estimates. In a MS case study, we compare the methods to understand the effect of different disease-modifying therapies on different disease severity markers using MS PATHS. We conclude with relevant analytical recommendations and guidance for RWD studies.
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Authors who are presenting talks have a * after their name.
