TY - JOUR
T1 - Making Drug Approval Decisions in the Face of Uncertainty
T2 - Cumulative Evidence versus Value of Information
AU - Dijk, Stijntje W.
AU - Krijkamp, Eline
AU - Kunst, Natalia
AU - Labrecque, Jeremy A.
AU - Gross, Cary P.
AU - Pandit, Aradhana
AU - Lu, Chia Ping
AU - Visser, Loes E.
AU - Wong, John B.
AU - Hunink, M. G.Myriam
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/7
Y1 - 2024/7
N2 - Background: The COVID-19 pandemic underscored the criticality and complexity of decision making for novel treatment approval and further research. Our study aims to assess potential decision-making methodologies, an evaluation vital for refining future public health crisis responses. Methods: We compared 4 decision-making approaches to drug approval and research: the Food and Drug Administration’s policy decisions, cumulative meta-analysis, a prospective value-of-information (VOI) approach (using information available at the time of decision), and a reference standard (retrospective VOI analysis using information available in hindsight). Possible decisions were to reject, accept, provide emergency use authorization, or allow access to new therapies only in research settings. We used monoclonal antibodies provided to hospitalized COVID-19 patients as a case study, examining the evidence from September 2020 to December 2021 and focusing on each method’s capacity to optimize health outcomes and resource allocation. Results: Our findings indicate a notable discrepancy between policy decisions and the reference standard retrospective VOI approach with expected losses up to $269 billion USD, suggesting suboptimal resource use during the wait for emergency use authorization. Relying solely on cumulative meta-analysis for decision making results in the largest expected loss, while the policy approach showed a loss up to $16 billion and the prospective VOI approach presented the least loss (up to $2 billion). Conclusion: Our research suggests that incorporating VOI analysis may be particularly useful for research prioritization and treatment implementation decisions during pandemics. While the prospective VOI approach was favored in this case study, further studies should validate the ideal decision-making method across various contexts. This study’s findings not only enhance our understanding of decision-making strategies during a health crisis but also provide a potential framework for future pandemic responses. This study reviews discrepancies between a reference standard (retrospective VOI, using hindsight information) and 3 conceivable real-time approaches to research-treatment decisions during a pandemic, suggesting suboptimal use of resources. Of all prospective decision-making approaches considered, VOI closely mirrored the reference standard, yielding the least expected value loss across our study timeline. This study illustrates the possible benefit of VOI results and the need for evidence accumulation accompanied by modeling in health technology assessment for emerging therapies.
AB - Background: The COVID-19 pandemic underscored the criticality and complexity of decision making for novel treatment approval and further research. Our study aims to assess potential decision-making methodologies, an evaluation vital for refining future public health crisis responses. Methods: We compared 4 decision-making approaches to drug approval and research: the Food and Drug Administration’s policy decisions, cumulative meta-analysis, a prospective value-of-information (VOI) approach (using information available at the time of decision), and a reference standard (retrospective VOI analysis using information available in hindsight). Possible decisions were to reject, accept, provide emergency use authorization, or allow access to new therapies only in research settings. We used monoclonal antibodies provided to hospitalized COVID-19 patients as a case study, examining the evidence from September 2020 to December 2021 and focusing on each method’s capacity to optimize health outcomes and resource allocation. Results: Our findings indicate a notable discrepancy between policy decisions and the reference standard retrospective VOI approach with expected losses up to $269 billion USD, suggesting suboptimal resource use during the wait for emergency use authorization. Relying solely on cumulative meta-analysis for decision making results in the largest expected loss, while the policy approach showed a loss up to $16 billion and the prospective VOI approach presented the least loss (up to $2 billion). Conclusion: Our research suggests that incorporating VOI analysis may be particularly useful for research prioritization and treatment implementation decisions during pandemics. While the prospective VOI approach was favored in this case study, further studies should validate the ideal decision-making method across various contexts. This study’s findings not only enhance our understanding of decision-making strategies during a health crisis but also provide a potential framework for future pandemic responses. This study reviews discrepancies between a reference standard (retrospective VOI, using hindsight information) and 3 conceivable real-time approaches to research-treatment decisions during a pandemic, suggesting suboptimal use of resources. Of all prospective decision-making approaches considered, VOI closely mirrored the reference standard, yielding the least expected value loss across our study timeline. This study illustrates the possible benefit of VOI results and the need for evidence accumulation accompanied by modeling in health technology assessment for emerging therapies.
UR - http://www.scopus.com/inward/record.url?scp=85195638676&partnerID=8YFLogxK
U2 - 10.1177/0272989X241255047
DO - 10.1177/0272989X241255047
M3 - Article
C2 - 38828516
AN - SCOPUS:85195638676
SN - 0272-989X
VL - 44
SP - 512
EP - 528
JO - Medical Decision Making
JF - Medical Decision Making
IS - 5
ER -