DOI: 10.5061/dryad.ttdz08m28
title: Data from: Pharmacoeconomic study of anti-influenza virus drugs in Japan based on a network meta-analysis

description: Objectives: An analysis was conducted in Japan to determine the most
 cost-effective neuraminidase inhibitor for the treatment of influenza
 virus infections from the healthcare payer’s standpoint. Methods: This
 study reanalyzed the findings of a previous study that had some
 limitations (no probabilistic sensitivity analysis, quality of life scores
 measured by the EQ-5D-3L instead of the EQ-5D-5L, and the use of a
 decision tree model with only three health conditions) by using data from
 a network meta-analysis study. A decision tree model with eight health
 conditions was constructed, and costs were identified as medical costs and
 drug prices (the 2020 version of the Japanese medical fee index). The
 effectiveness outcomes were measured using EQ-5D-5L questionnaires for
 adult patients who had previously experienced influenza virus infections.
 The time horizon was 14 days. Both deterministic and probabilistic
 sensitivity analyses were performed to examine the robustness of the
 results. Results: The base-case cost-effectiveness analysis revealed that
 oseltamivir outperformed laninamivir, zanamivir, and peramivir, making it
 the most cost-effective neuraminidase inhibitor. The deterministic and
 probabilistic sensitivity analyses showed robust results that validated
 oseltamivir as the most cost-effective among the four neuraminidase
 inhibitors. Conclusions: This study thus reconfirmed oseltamivir’s
 position as the most cost-effective neuraminidase inhibitor for the
 treatment of influenza virus infections in Japan from the standpoint of
 healthcare payment. These findings can help decision-makers and healthcare
 providers in Japan, including pharmacists, create and manage formularies.
description: # Data from: Pharmacoeconomic study of anti-influenza virus drugs in Japan
 based on a network meta-analysis
 [https://doi.org/10.5061/dryad.ttdz08m28](https://doi.org/10.5061/dryad.ttdz08m28) **Author(s)** Naoto Nakagawa, Pharm.D., Ph.D\ School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan\ 31-1 Misumido, Tomita-machi, Koriyama, Fukushima 963-8611, Japan\ Email: [n-nakagawa@pha.ohu-u.ac.jp (opens in new window)](mailto:n-nakagawa@pha.ohu-u.ac.jp) Yukinori Kanazawa, B.S., R.Ph.\ Pharma Brie, Sendai, Miyagi, Japan\ 100-2 Odawarayuminomachi, Miyagino, Sendai, Miyagi, 983ｰ0812, Japan\ Email: [y.kanazawa@medical-briller.co.jp (](mailto:y.kanazawa@medical-briller.co.jp)[opens in new window)](mailto:n-nakagawa@pha.ohu-u.ac.jp) Akimasa Morikawa, B.S., R.Ph.\ Pharma Brie, Sendai, Miyagi, Japan\ 100-2 Odawarayuminomachi, Miyagino, Sendai, Miyagi, 983ｰ0812, Japan\ Email: [akimasa-m@nifty.com](mailto:akimasa-m@nifty.com)[ (](mailto:y.kanazawa@medical-briller.co.jp)[opens in new window)](mailto:n-nakagawa@pha.ohu-u.ac.jp) Leanne Lai, Ph.D.\ College of Pharmacy, Kaohsiung Medical University,  Kaohsiung City, Taiwan\ No. 100, Shiquan 1st Rd., Sanmin Dist., Kaohsiung City 807, Taiwan\ Email: [LL33317@gmail.com ](mailto:LL33317@gmail.com)[(opens in new window)](mailto:n-nakagawa@pha.ohu-u.ac.jp) **File list**\ CEA input data for 1st examination CEA input data for 2nd examination PSA input data. for 1st examination PSA input data. for 2nd examination **File descriptions** Details for: CEA input data for 1st examination\ The file is a table to analyze for input with TreeAge Pro. \ Format(s): .csv\ Dimensions: 30 rows x 5 columns\ Variables:\ *Name: c_XXX means cost variables (unit is 'yen'), p_XXX means probability variables, and u_XXX means utility variables (unit is 'QALY').\ *Description: definition of each variable.\ *Root Definition: individual variables for a base-case scenario.\ *Low and High columns: the low and the high numbers for one-way sensitivity analysis. Details for: CEA input data for 2nd examination\ The file is a table to analyze for input with TreeAge Pro. \ Format(s): .csv\ Dimensions: 31 rows x 5 columns\ Variables:\ *Name: c_XXX means cost variables (unit is 'yen'), p_XXX means probability variables, and u_XXX means utility variables (unit is 'QALY').\ *Description: definition of each variable.\ *Root Definition: individual variables for a base-case scenario.\ *Low and High columns: the low and the high numbers for one-way sensitivity analysis. Details for: PSA input data. for 1st examination\ Format(s): .csv\ Dimensions:20 rows x 6 columns\ Variables: * Type: A type of distribution for probabilistic sensitivity analysis * Name: Individual variables for a base-case scenario. * Description: Description of individual variables for a base-case scenario. * Param 1: Input data as alpha. Numbers in a formula indicate 'mean' and 'standard deviation'. * Param 2: Input data as beta. Numbers in a formula indicate 'mean' and 'standard deviation'. * Help/Explanation: Description of Param 1 and Param 2. Details for: PSA input data. for 2nd examination\ Format(s): .csv\ Dimensions:20 rows x 6 columns\ Variables: * Type: A type of distribution for probabilistic sensitivity analysis * Name: Individual variables for a base-case scenario. * Description: Description of individual variables for a base-case scenario. * Param 1: Input data as alpha. Numbers in a formula indicate 'mean' and 'standard deviation'. * Param 2: Input data as beta. Numbers in a formula indicate 'mean' and 'standard deviation'. * Help/Explanation: Description of Param 1 and Param 2.