Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Watson, Samuel; Chen, Yen-Fu; Nguyen-Van-Tam, Jonathan S.; Myles, Puja; Venkatesan, Sudhir; Zambon, Maria; Uthman, Olalekan A.; Chilton, Peter J; Lilford, Richard

doi:10.12688/f1000research.9414.1

Cited by 6 publications

(2 citation statements)

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“…We have used somewhat arbitrary classifications for clinically important and trivial effect sizes. 28 We thus suggest that with appropriate contextual knowledge, clinically important effect sizes should be defined at the planning stage. 23 Creating an explicit necessity to specify clinically important effect sizes up front, should prompt decision makers to think about this important question at the planning stage rather than the interpretation stage.…”

Section: Classification Of Size Of Effectsmentioning

confidence: 99%

A re‐analysis of 150 women's health trials to investigate how the Bayesian approach may offer a solution to the misinterpretation of statistical findings

Hemming

Melo

Luo

et al. 2023

BJOG

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ObjectiveTo investigate whether a Bayesian interpretation might help prevent misinterpretation of statistical findings and support authors to differentiate evidence of no effect from statistical uncertainty.DesignA Bayesian re‐analysis to determine posterior probabilities of clinically important effects (e.g., a large effect is set at a 4 percentage point difference and a trivial effect to be within a 0.5 percentage point difference). Posterior probabilities greater than 95% are considered as strong statistical evidence, and less than 95% as inconclusive.Sample150 major women's health trials with binary outcomes.Main Outcome MeasuresPosterior probabilities of large, moderate, small and trivial effects.ResultsUnder frequentist methods, 48 (32%) were statistically significant (p‐value ≤ 0.05) and 102 (68%) statistically non‐significant. The frequentist and Bayesian point estimates and confidence intervals showed strong concordance. Of the statistically non‐significant trials (n = 102), the Bayesian approach classified the majority (94, 92%) as inconclusive, neither able to confirm or refute effectiveness. A small number of statistically non‐significant findings (8, 8%) were classified as having strong statistical evidence of an effect.ConclusionsWhilst almost all trials report confidence intervals, in practice most statistical findings are interpreted on the basis of statistical significance, mostly concluding evidence of no effect. Findings here suggest the majority are likely uncertain. A Bayesian approach could help differentiate evidence of no effect from statistical uncertainty.

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Section: Classification Of Size Of Effectsmentioning

confidence: 99%

A re‐analysis of 150 women's health trials to investigate how the Bayesian approach may offer a solution to the misinterpretation of statistical findings

Hemming

Melo

Luo

et al. 2023

BJOG

View full text Add to dashboard Cite

show abstract

“…Raw data of ‘stockpiling neuraminidase inhibitors for pandemic influenza usage’, 10.5256/f1000research.9414.d132653 44 .…”

Section: Data Availabilitymentioning

confidence: 99%

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

et al. 2017

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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.

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Potential of Quercetin to Protect Cadmium Induced Cognitive Deficits in Rats by Modulating NMDA-R Mediated Downstream Signaling and PI3K/AKT—Nrf2/ARE Signaling Pathways in Hippocampus

et al. 2023

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Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Abstract: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a

Cited by 6 publications

References 33 publications

A re‐analysis of 150 women's health trials to investigate how the Bayesian approach may offer a solution to the misinterpretation of statistical findings

A re‐analysis of 150 women's health trials to investigate how the Bayesian approach may offer a solution to the misinterpretation of statistical findings

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Potential of Quercetin to Protect Cadmium Induced Cognitive Deficits in Rats by Modulating NMDA-R Mediated Downstream Signaling and PI3K/AKT—Nrf2/ARE Signaling Pathways in Hippocampus

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