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      Pharmacoeconomic Evaluation of Cancer Biosimilars Worldwide: A Systematic Review

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          Abstract

          Background and Purpose: The availability of oncology biosimilars is deemed as a fundamental strategy to achieve sustainable health care. However, there is scarce systematic evidence on economic effectiveness of cancer biosimilars. We aimed to synthesize evidence from pharmacoeconomic evaluation of oncology biosimilars globally, provide essential data and methodological reference for involved stakeholders.

          Materials and Methods: This systematic review was conducted in PubMed, embase, the Cochrane library, CRD, ISPOR and NICE utill December 31, 2019. Information on basic characteristics, evaluation methodology and results were extracted. Quality of included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards Checklist.

          Results: For 17 studies identified (13 from Europe and four from United States), the overall quality was generally acceptable. A total of seven biological molecules involved with filgrastim, EPOETIN α, and trastuzumab leading the three. The mostly common evaluation perspective was payer, but the time horizon varied greatly. There were ten studies which adopted cost minimization analysis to evaluate efficiency while seven studies adopted budget impact analysis to address affordability, with cost ratio and cost saving being its corresponding primary endpoint. Although the comparability of included studies was limited and specific results were largely affected by uptake and price discount rates of the oncology biosimilar, the comprehensive results consistently favored its promotion.

          Conclusion: Globally, the economic evaluation of cancer biosimilars is in its initial phase. However, limited evidence from developed countries consistently supported both cost-effectiveness of efficiency and affordability of oncology biosimilars, while they were largely affected by uptake and price discount rate.

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          Most cited references36

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          Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and publication bias.

          Publication bias is a major problem in evidence based medicine. As well as positive outcome studies being preferentially published or followed by full text publication authors are also more likely to publish positive results in English-language journals. This unequal distribution of trials leads to a selection bias in evidence l level studies, like systematic reviews, meta-analysis or health technology assessments followed by a systematic failure of interpretation and in clinical decisions. Publication bias in a systematic review occurs mostly during the selection process and a transparent selection process is necessary to avoid such bias. For systematic reviews/meta-analysis the PRISMA-statement (formerly known as QUOROM) is recommended, as it gives the reader for a better understanding of the selection process. In the future the use of trial registration for minimizing publication bias, mechanisms to allow easier access to the scientific literature and improvement in the peer review process are recommended to overcome publication bias. The use of checklists like PRISMA is likely to improve the reporting quality of a systematic review and provides substantial transparency in the selection process of papers in a systematic review. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
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            Budget impact analysis-principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force.

            Budget impact analyses (BIAs) are an essential part of a comprehensive economic assessment of a health care intervention and are increasingly required by reimbursement authorities as part of a listing or reimbursement submission. The objective of this report was to present updated guidance on methods for those undertaking such analyses or for those reviewing the results of such analyses. This update was needed, in part, because of developments in BIA methods as well as a growing interest, particularly in emerging markets, in matters related to affordability and population health impacts of health care interventions. The Task Force was approved by the International Society for Pharmacoeconomics and Outcomes Research Health Sciences Policy Council and appointed by its Board of Directors. Members were experienced developers or users of BIAs; worked in academia and industry and as advisors to governments; and came from several countries in North America and South America, Oceania, Asia, and Europe. The Task Force solicited comments on the drafts from a core group of external reviewers and, more broadly, from the membership of the International Society for Pharmacoeconomics and Outcomes Research. The Task Force recommends that the design of a BIA for a new health care intervention should take into account relevant features of the health care system, possible access restrictions, the anticipated uptake of the new intervention, and the use and effects of the current and new interventions. The key elements of a BIA include estimating the size of the eligible population, the current mix of treatments and the expected mix after the introduction of the new intervention, the cost of the treatment mixes, and any changes expected in condition-related costs. Where possible, the BIA calculations should be performed by using a simple cost calculator approach because of its ease of use for budget holders. In instances, however, in which the changes in eligible population size, disease severity mix, or treatment patterns cannot be credibly captured by using the cost calculator approach, a cohort or patient-level condition-specific model may be used to estimate the budget impact of the new intervention, accounting appropriately for those entering and leaving the eligible population over time. In either case, the BIA should use data that reflect values specific to a particular decision maker's population. Sensitivity analysis should be of alternative scenarios chosen from the perspective of the decision maker. The validation of the model should include at least face validity with decision makers and verification of the calculations. Data sources for the BIA should include published clinical trial estimates and comparator studies for the efficacy and safety of the current and new interventions as well as the decision maker's own population for the other parameter estimates, where possible. Other data sources include the use of published data, well-recognized local or national statistical information, and, in special circumstances, expert opinion. Reporting of the BIA should provide detailed information about the input parameter values and calculations at a level of detail that would allow another modeler to replicate the analysis. The outcomes of the BIA should be presented in the format of interest to health care decision makers. In a computer program, options should be provided for different categories of costs to be included or excluded from the analysis. We recommend a framework for the BIA, provide guidance on the acquisition and use of data, and offer a common reporting format that will promote standardization and transparency. Adherence to these good research practice principles would not necessarily supersede jurisdiction-specific BIA guidelines but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines. © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Published by International Society for Pharmacoeconomics and Outcomes Research (ISPOR) All rights reserved.
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              Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement.

              Economic evaluations of health interventions pose a particular challenge for reporting. There is also a need to consolidate and update existing guidelines and promote their use in a user friendly manner. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement is an attempt to consolidate and update previous health economic evaluation guidelines efforts into one current, useful reporting guidance. The primary audiences for the CHEERS statement are researchers reporting economic evaluations and the editors and peer reviewers assessing them for publication. The need for new reporting guidance was identified by a survey of medical editors. A list of possible items based on a systematic review was created. A two round, modified Delphi panel consisting of representatives from academia, clinical practice, industry, government, and the editorial community was conducted. Out of 44 candidate items, 24 items and accompanying recommendations were developed. The recommendations are contained in a user friendly, 24 item checklist. A copy of the statement, accompanying checklist, and this report can be found on the ISPOR Health Economic Evaluations Publication Guidelines Task Force website: (www.ispor.org/TaskForces/EconomicPubGuidelines.asp). We hope CHEERS will lead to better reporting, and ultimately, better health decisions. To facilitate dissemination and uptake, the CHEERS statement is being co-published across 10 health economics and medical journals. We encourage other journals and groups, to endorse CHEERS. The author team plans to review the checklist for an update in five years.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                12 November 2020
                2020
                : 11
                : 572569
                Affiliations
                [ 1 ]Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
                [ 2 ]Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
                [ 3 ]Institute of Cancer and Basic Medicine, Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China
                [ 4 ]Office for Cancer Control and Research, Henan Cancer Hospital, Zhengzhou University, Zhengzhou, China
                [ 5 ]Pfizer Investment Co., Ltd., Shanghai, China
                [ 6 ]Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
                Author notes

                These authors have contributed equally to this work

                Edited by: Philippe Van Wilder, Université libre de Bruxelles, Belgium

                Reviewed by: Mark J. C. Nuijten, Ars Accessus Medica (a2m), Netherlands

                Joël Daems, National Institute for Health and Disability Insurance (RIZIV), Belgium

                This article was submitted to Pharmaceutical Medicine and Outcomes Research, a section of the journal Frontiers in Pharmacology

                Article
                572569
                10.3389/fphar.2020.572569
                7849203
                33536905
                d2ea3c7a-f9a4-4862-a267-06e07410573e
                Copyright © 2020 Huang, Liu, Yu, Wang, Wu, Guo, Wang, Fang, Bai, Fang, Fan, Sun, Wu, Shi, Ma, Tang, Dai and Li.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 June 2020
                : 06 October 2020
                Page count
                Pages: 0
                Categories
                Pharmacology
                Systematic Review

                Pharmacology & Pharmaceutical medicine
                cancer,biosimilars,pharmacoeconomic evaluation,cost minimization analysis,budget impact analysis,systematic review

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