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How Sensitive is Sensitivity Analysis?: Evaluation of Pharmacoeconomic Submissions in Korea

Title
How Sensitive is Sensitivity Analysis?: Evaluation of Pharmacoeconomic Submissions in Korea
Authors
Bae S.Lee J.Bae E.-Y.
Ewha Authors
배승진
SCOPUS Author ID
배승진scopus
Issue Date
2022
Journal Title
Frontiers in Pharmacology
ISSN
1663-9812JCR Link
Citation
Frontiers in Pharmacology vol. 13
Keywords
economic evaluationincremental cost effectiveness ratioparametric uncertaintysensitivity analysisstructural uncertaintyuncertainty
Publisher
Frontiers Media S.A.
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Purpose: We aimed to describe the types of uncertainties examined in the economic evaluations submitted for reimbursement in Korea and their impact on the incremental cost-effectiveness ratio (ICER). Method: Fifty dossiers were submitted by pharmaceutical companies to the economic subcommittee of the Pharmaceutical Benefit Coverage Advisory Committee (PBCAC) from January 2014 to December 2018. The types of uncertainties were categorized as structural and parametric, and the frequencies of the sensitivity analysis per variables were analyzed. The impact of uncertainties was measured by the percent variance of the ICER relative to that of the base case analysis. Results: Of the 50 submissions, varying discount rate (44 submissions), followed by time horizon (38 submissions) and model assumptions (29 submissions), were most frequently used to examine structural uncertainty, while utility (42 submissions), resource use (41 submissions), and relative effectiveness (26 submissions) were used to examine parametric uncertainty. A total of 1,236 scenarios (a scenario corresponds to a case where a single variable is varied by a single range) were presented in the one-way sensitivity analyses, where parametric and structural sensitivity analyses comprised 679 and 557 scenarios, respectively. Varying drug prices had the highest impact on ICER (median variance 19.9%), followed by discount rate (12.2%), model assumptions (11.9%), extrapolation (11.8%), and time horizon (10.0%). Conclusions: Variables related to long-term assumptions, such as model assumptions, time horizon, extrapolation, and discounting rate, were related to a high level of uncertainty. Caution should be exercised when using immature data. Copyright © 2022 Bae, Lee and Bae.
DOI
10.3389/fphar.2022.884769
Appears in Collections:
약학대학 > 약학과 > Journal papers
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