In recent years, there has been a proliferation of regulatory and industry-wide initiatives on structured benefitrisk (BR) assessment. Examples of structured BR frameworks include the PrOACT-URL (Problem formulation, Objectives, Alternatives, Consequences, Trade-Offs, Uncertainties, Risk Attitude and Linked Decisions) from European Medicines Agency Work Package 3, multiple U.S. Food and Drug Administration guidance documents on benefit-risk assessment for medical devices, and U.S. Food and Drug Administration implementation plans for benefit-risk assessment in drug regulatory decision-making. In June 2016, the ICH Expert Working Group finalized the Common Technical Document (CTD) Section 2.5.6 on Benefit-Risk Evaluations. As a result of these efforts, the uptake and utilization of structured benefit-risk (BR) assessments has been increasing. However, the aforementioned BR frameworks are mostly qualitative in nature, and the utility of quantitative BR approaches has not been systemically explored, creating uncertainty about settings in which quantitative BR assessment (qBRA) could be optimally applied. In this paper, we will provide an overview of the current qBRA methods, discuss challenges of qBRA, and describe a structural qBRA framework. The performance of the described qBRA framework will be evaluated by simulations based on a case study.
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Hop Ambroise Pare, Assistance Publ Hop Paris, Serv Med Interne, Boulogne, FranceHop Ambroise Pare, Assistance Publ Hop Paris, Serv Med Interne, Boulogne, France
Hanslik, Thomas
Boelle, Pierre Yves
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机构:Hop Ambroise Pare, Assistance Publ Hop Paris, Serv Med Interne, Boulogne, France
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Univ British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
Univ British Columbia, Fac Med, Vancouver, BC V6T 1Z3, CanadaUniv British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
Sadatsafavi, Mohsen
Marra, Carlo
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Univ British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, CanadaUniv British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
Marra, Carlo
Marra, Fawziah
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Univ British Columbia, BC Ctr Dis Control, Vancouver, BC V6T 1Z3, CanadaUniv British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
Marra, Fawziah
Moran, Onofre
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Queens Univ, Fac Hlth Sci, Kingston, ON, CanadaUniv British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
Moran, Onofre
FitzGerald, J. Mark
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Univ British Columbia, Fac Med, Vancouver, BC V6T 1Z3, CanadaUniv British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
FitzGerald, J. Mark
Lynd, Larry
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Univ British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, CanadaUniv British Columbia, Collaborat Outcome Res & Evaluat, Fac Pharmaceut Sci, Vancouver, BC V6T 1Z3, Canada
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Gifu Pharmaceut Univ, Global Regulatory Sci, 1-25-4 Daigakunishi, Gifu 5011196, Japan
Syneos Hlth Clin KK, Chuo Ku, 2-1-3 Nihonbashi, Tokyo 1030027, JapanGifu Pharmaceut Univ, Global Regulatory Sci, 1-25-4 Daigakunishi, Gifu 5011196, Japan
Matsumoto, Tomoko
Matsumaru, Naoki
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Gifu Pharmaceut Univ, Global Regulatory Sci, 1-25-4 Daigakunishi, Gifu 5011196, JapanGifu Pharmaceut Univ, Global Regulatory Sci, 1-25-4 Daigakunishi, Gifu 5011196, Japan
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F Hoffmann La Roche, Stat Methods & Res Grp, Welwyn Garden City AL7 1TW, Herts, EnglandF Hoffmann La Roche, Stat Methods & Res Grp, Welwyn Garden City AL7 1TW, Herts, England
Quartey, George
Wang, Jixian
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F Hoffmann La Roche, Stat Methods & Res Grp, Welwyn Garden City AL7 1TW, Herts, EnglandF Hoffmann La Roche, Stat Methods & Res Grp, Welwyn Garden City AL7 1TW, Herts, England