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

Authors
Bae, SeungJinLee, JooheeBae, Eun-Young
Issue Date
16-May-2022
Publisher
FRONTIERS MEDIA SA
Keywords
economic evaluation; uncertainty; structural uncertainty; parametric uncertainty; sensitivity analysis; incremental cost effectiveness ratio
Citation
FRONTIERS IN PHARMACOLOGY, v.13
Indexed
SCIE
SCOPUS
Journal Title
FRONTIERS IN PHARMACOLOGY
Volume
13
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/1267
DOI
10.3389/fphar.2022.884769
ISSN
1663-9812
1663-9812
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.
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