Cranmer, H., Shields, G.E. and Bullement, A. orcid.org/0000-0001-7091-0972 (2020) A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology. Journal of Medical Economics, 23 (10). pp. 1176-1185. ISSN 1369-6998
Abstract
Aims
To construct and compare a partitioned-survival analysis (PartSA) and a semi-Markov multi-state model (MSM) to investigate differences in estimated cost effectiveness of a novel cancer treatment from a UK perspective.
Materials and Methods
Data from a cohort of late-stage cancer patients (N > 700) enrolled within a randomized, controlled trial were used to populate both modelling approaches. The statistical software R was used to fit parametric survival models to overall survival (OS) and progression-free survival (PFS) data to inform the PartSA (package “flexsurv”). The package “mstate” was used to estimate the MSM transitions (permitted transitions: (T1) “progression-free” to “dead”, (T2) “post-progression” to “death”, and (T3) “pre-progression” to “post-progression”). Key costs included were treatment-related (initial, subsequent, and concomitant), adverse events, hospitalizations and monitoring. Utilities were stratified by progression. Outcomes were discounted at 3.5% per annum over a 15-year time horizon.
Results
The PartSA and MSM approaches estimated incremental cost-effectiveness ratios (ICERs) of £342,474 and £411,574, respectively. Scenario analyses exploring alternative parametric forms provided incremental discounted life-year estimates that ranged from +0.15 to +0.33 for the PartSA approach, compared with −0.13 to +0.23 for the MSM approach. This variation was reflected in the range of ICERs. The PartSA produced ICERs between £234,829 and £522,963, whereas MSM results were more variable and included instances where the intervention was dominated and ICERs above £7 million (caused by very small incremental QALYs).
Limitations and conclusions
Structural uncertainty in economic modelling is rarely explored due to time and resource limitations. This comparison of structural approaches indicates that the choice of structure may have a profound impact on cost-effectiveness results. This highlights the importance of carefully considered model conceptualization, and the need for further research to ascertain when it may be most appropriate to use each approach.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
Keywords: | Cost-effectiveness; multi-state model; partitioned survival; decision-analytic model; oncology |
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 Health and Related Research (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 12 Jan 2021 16:20 |
Last Modified: | 12 Jan 2021 16:20 |
Status: | Published |
Publisher: | Informa UK Limited |
Refereed: | Yes |
Identification Number: | 10.1080/13696998.2020.1796360 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169376 |