Evidence mapPaperPMID 38828516Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2024

Making Drug Approval Decisions in the Face of Uncertainty: Cumulative Evidence versus Value of Information.

Stijntje W Dijk, Eline Krijkamp, Natalia Kunst, Jeremy A Labrecque, Cary P Gross, Aradhana Pandit, Chia-Ping Lu, Loes E Visser, John B Wong, M G Myriam Hunink

Abstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Stijntje W DijkDepartment of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.ORCID 0000-0003-2905-4128
Eline KrijkampErasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.ORCID 0000-0003-3970-2205
Natalia KunstCentre for Health Economics, University of York, York, UK.ORCID 0000-0002-2409-4246
Jeremy A LabrecqueDepartment of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Cary P GrossCancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale University School of Medicine, New Haven, CT, USA.
Aradhana PanditDepartment of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Chia-Ping LuDepartment of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Loes E VisserDepartment of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands.
John B WongDivision of Clinical Decision Making, Tufts Medical Center, Boston, USA.
M G Myriam HuninkDepartment of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.

Funding

Yale Clinical and Translational Science AwardUL1TR001863 · YALE UNIVERSITY · 2025 to 2025
$9.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

backgroundThe 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.

methodsWe 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.

resultsOur 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).

conclusionOur 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.

Indexed as

COVID-19COVID-19 Drug TreatmentDecision MakingDrug ApprovalSARS-CoV-2Antibodies, MonoclonalHumansPandemicsUncertaintyUnited StatesUnited States Food and Drug AdministrationAntibodies, Monoclonalantibodiescost-benefit analysisCOVID-19decision support techniquesdrug approvalmeta-analysismonoclonalpolicy analyses

Identifiers

PMID38828516
PMCPMC11283736

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.