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Cost-effectiveness of therapeutics for COVID-19 patients: a rapid review and economic analysis

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HEALTH TECHNOLOGY ASSESSMENT
卷 27, 期 14, 页码 1-120

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NIHR JOURNALS LIBRARY
DOI: 10.3310/NAFW3527

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This study assessed the cost-effectiveness of treatments for coronavirus disease 2019. The results showed that these treatments were clinically effective and cost-effective, although there was some uncertainty. However, due to the evolving nature of the decision problem, the conclusions regarding the most clinical and cost-effectiveness of each intervention should be treated with caution.
Background: Severe acute respiratory syndrome coronavirus 2 is the virus that causes coronavirus disease 2019. Over six million deaths worldwide have been associated with coronavirus disease 2019.Objective: To assess the cost-effectiveness of treatments used for the treatment of coronavirus disease 2019 in hospital or used in the community in patients with coronavirus disease 2019 at high risk of hospitalisation.Setting: Treatments provided in United Kingdom hospital and community settings. Methods: Clinical effectiveness estimates were taken from the coronavirus disease-network meta analyses initiative and the metaEvidence initiative. A mathematical model was constructed to explore how the interventions impacted on patient health, measured in quality-adjusted life-years gained. The costs associated with treatment, including those of hospital care, were also estimated and used to form a cost per quality-adjusted life-year gained value which was compared with thresholds published by the National Institute for Health and Care Excellence. Estimates of cost-effectiveness compared against current standard of care were produced in both the hospital and community settings at three different levels of efficacy: mean, low and high. Public list prices were used for interventions with neither confidential patient access schemes nor confidential list prices considered.Results incorporating confidential pricing data were provided to the National Institute for Health and Care Excellence appraisal committee. Results: The treatments were estimated to be clinically effective although not all reached statistical significance. All treatments in the hospital setting, or community, were estimated to plausibly have a cost per quality-adjusted life-year gained value below National Institute for Health and Care Excellence's thresholds when compared with standard of care. However, almost all drugs could plausibly have cost per quality-adjusted life-years above National Institute for Health and Care Excellence's thresholds. However, there is considerable uncertainty in the results as the prevalent severe acute respiratory syndrome coronavirus 2 variant, vaccination status, history of being infected with severe acute respiratory syndrome coronavirus 2 and standard of care have all evolved since the pivotal studies were conducted which could have significant impact on the efficacy of each drug. For drugs used in high-risk patients in the community setting, the proportion of people at high risk who need hospital admission was a large driver of the cost per quality-adjusted life-year.Limitations: No studies were identified that were conducted in current conditions. This may be a large limitation as the severe acute respiratory syndrome coronavirus 2 variant changes. No head-to-head studies of interventions were identified. Conclusions: The results produced could be informative to decision-makers, although conclusions regarding the most clinical - and cost-effectiveness of each intervention should be tentative due to the evolving nature of the decision problem and, in this report, the use of list prices only. Comparisons between interventions should also be treated with caution due to potentially large heterogeneity between studies.Future work: Research assessing the relative clinical effectiveness of interventions within head-to-head studies in current conditions would be beneficial. Contemporary information related to the probability of hospital admission and death for patients at high risk in the community would improve the precision of the estimates generated.

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