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Evidence synthesis and decision modelling to support complex decisions : stockpiling neuraminidase inhibitors for pandemic influenza usage
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Watson, Samuel I., Chen, Y-F., Nguyen-Van-Tam, Jonathan S., Myles, Puja R., Venkatesan, Sudhir, Zambon, Maria, Uthman, Olalekan A., Chilton, Peter J. and Lilford, Richard (2016) Evidence synthesis and decision modelling to support complex decisions : stockpiling neuraminidase inhibitors for pandemic influenza usage. F1000Research, 5 . 2293. doi:10.12688/f1000research.9414.2
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WRAP-evidence-synthesis-decision-modelling-support-complex-decisions-Watson-2017.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1933Kb) | Preview |
Official URL: https://doi.org/10.12688/f1000research.9414.2
Abstract
Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence.
Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling.
Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile.
Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.
| Item Type: | Journal Article | ||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine | ||||||||
| Divisions: | Faculty of Medicine > Warwick Medical School > Health Sciences Faculty of Medicine > Warwick Medical School > Health Sciences > Population, Evidence & Technologies (PET) Faculty of Social Sciences > Warwick Business School Faculty of Medicine > Warwick Medical School |
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| Library of Congress Subject Headings (LCSH): | Influenza -- Epidemiology, Epidemics, Antiviral agents, Decision making -- Mathematical models, Evidence-based medicine -- Statistical methods | ||||||||
| Journal or Publication Title: | F1000Research | ||||||||
| Publisher: | F1000 Research Ltd | ||||||||
| ISSN: | 2046-1402 | ||||||||
| Official Date: | 12 September 2016 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 16 March 2018 | ||||||||
| Volume: | 5 | ||||||||
| Article Number: | 2293 | ||||||||
| DOI: | 10.12688/f1000research.9414.2 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| RIOXX Funder/Project Grant: |
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