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. HIGHLIGHTS 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.

中文翻译：

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面对不确定性做出药物审批决策：累积证据与信息价值。


背景 COVID-19 大流行凸显了新疗法批准和进一步研究决策的重要性和复杂性。我们的研究旨在评估潜在的决策方法，这种评估对于完善未来公共卫生危机应对措施至关重要。方法 我们比较了药物审批和研究的 4 种决策方法：食品和药物管理局的政策决策、累积荟萃分析、前瞻性信息价值 (VOI) 方法（使用决策时可用的信息）以及参考标准（使用事后可用信息进行回顾性 VOI 分析）。可能的决定是拒绝、接受、提供紧急使用授权或仅允许在研究环境中使用新疗法。我们使用为住院的 COVID-19 患者提供的单克隆抗体作为案例研究，检查了 2020 年 9 月至 2021 年 12 月的证据，并重点关注每种方法优化健康结果和资源分配的能力。结果 我们的研究结果表明，政策决策与参考标准回顾性 VOI 方法之间存在显着差异，预计损失高达 2690 亿美元，这表明在等待紧急使用授权期间资源使用不理想。仅仅依靠累积荟萃分析进行决策会导致最大的预期损失，而政策方法显示的损失高达 160 亿美元，而预期 VOI 方法的损失最小（高达 20 亿美元）。结论 我们的研究表明，纳入 VOI 分析可能对于大流行期间的研究优先顺序和治疗实施决策特别有用。 虽然前瞻性 VOI 方法在本案例研究中受到青睐，但进一步的研究应该在各种情况下验证理想的决策方法。这项研究的结果不仅增强了我们对健康危机期间决策策略的理解，而且还为未来的大流行应对提供了潜在的框架。要点 本研究回顾了大流行期间参考标准（回顾性 VOI，使用后见之明信息）与 3 种可能的实时研究治疗决策方法之间的差异，表明资源使用不理想。在考虑的所有前瞻性决策方法中，VOI 密切相关反映了参考标准，在我们的研究时间范围内产生了最小的预期价值损失。这项研究说明了 VOI 结果的可能好处以及证据积累的必要性以及新兴疗法的健康技术评估建模的必要性。