Abstract Details
Activity Number:
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680
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #314978
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View Presentation
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Title:
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Two Statistical Approaches to Incorporate Data Uncertainty into Multiple Criteria Decision Analysis (MCDA) for Benefit-Risk Assessment of Medical Products
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Author(s):
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Shihua Wen*
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Companies:
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AbbVie
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Keywords:
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benefit-risk ;
Multiple Criteria Decision Analysis
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Abstract:
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PrOACT-URL framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. To incorporate the uncertainty from clinical data into the MCDA model, two statistical approaches, the delta-method approach and the Monte-Carlo approach, were proposed. The delta-method approach provides a closed form solution to quantify the variability of the overall benefit-risk score in the MCDA model; while the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for further statistical inference. The obtained confidence interval of the overall benefit-risk score based on the MCDA model as well as other probabilistic measures from the two proposed approaches enhance the benefit-risk decision-making among different treatment options. In addition, a case study of comparing the benefit-risk profiles between a hypothetical drug and placebo was conducted to demonstrate the usage of the two approaches.
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Authors who are presenting talks have a * after their name.
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