Chang, J.-Y.A. orcid.org/0000-0001-6660-5246, Chilcott, J.B. orcid.org/0000-0003-1231-7817 and Latimer, N.R. orcid.org/0000-0001-5304-5585 (2024) Challenges and opportunities in interdisciplinary research and real-world data for treatment sequences in health technology assessments. PharmacoEconomics, 42 (5). pp. 487-506. ISSN 1170-7690
Abstract
With an ever-increasing number of treatment options, the assessment of treatment sequences has become crucial in health technology assessment (HTA). This review systematically explores the multifaceted challenges inherent in evaluating sequences, delving into their interplay and nuances that go beyond economic model structures. We synthesised a ‘roadmap’ of literature from key methodological studies, highlighting the evolution of recent advances and emerging research themes. These insights were compared against HTA guidelines to identify potential avenues for future research. Our findings reveal a spectrum of challenges in sequence evaluation, encompassing selecting appropriate decision-analytic modelling approaches and comparators, deriving appropriate clinical effectiveness evidence in the face of data scarcity, scrutinising effectiveness assumptions and statistical adjustments, considering treatment displacement, and optimising model computations. Integrating methodologies from diverse disciplines—statistics, epidemiology, causal inference, operational research and computer science—has demonstrated promise in addressing these challenges. An updated review of application studies is warranted to provide detailed insights into the extent and manner in which these methodologies have been implemented. Data scarcity on the effectiveness of treatment sequences emerged as a dominant concern, especially because treatment sequences are rarely compared in clinical trials. Real-world data (RWD) provide an alternative means for capturing evidence on effectiveness and future research should prioritise harnessing causal inference methods, particularly Target Trial Emulation, to evaluate treatment sequence effectiveness using RWD. This approach is also adaptable for analysing trials harbouring sequencing information and adjusting indirect comparisons when collating evidence from heterogeneous sources. Such investigative efforts could lend support to reviews of HTA recommendations and contribute to synthesising external control arms involving treatment sequences.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s), under exclusive licence to Springer Nature Switzerland AG. This is an author-produced version of a paper subsequently published in PharmacoEconomics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Humans; Decision Support Techniques; Interdisciplinary Research; Models, Economic; Research Design; Technology Assessment, Biomedical; Systematic Reviews as Topic; Clinical Trials as Topic |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Funding Information: | Funder Grant number Wellcome Trust 108903/B/15/Z |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Sep 2024 14:06 |
Last Modified: | 06 Sep 2024 14:06 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1007/s40273-024-01363-1 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216925 |
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Filename: TreatSeq_Soping_Review_manuscript_20240213_v2_Clean.pdf
