Cargando…
Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia
BACKGROUND AND OBJECTIVE: Since 2016, new therapies have transformed the standard of care for lung cancer, creating a need for up-to-date evidence for health economic modelling. We developed a discrete event simulation of advanced lung cancer treatment to provide estimates of survival outcomes and h...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570197/ https://www.ncbi.nlm.nih.gov/pubmed/37357233 http://dx.doi.org/10.1007/s40273-023-01291-6 |
_version_ | 1785119709310484480 |
---|---|
author | Ngo, Preston Karikios, Deme Goldsbury, David Wade, Stephen Lwin, Zarnie Hughes, Brett G. M. Fong, Kwun M. Canfell, Karen Weber, Marianne |
author_facet | Ngo, Preston Karikios, Deme Goldsbury, David Wade, Stephen Lwin, Zarnie Hughes, Brett G. M. Fong, Kwun M. Canfell, Karen Weber, Marianne |
author_sort | Ngo, Preston |
collection | PubMed |
description | BACKGROUND AND OBJECTIVE: Since 2016, new therapies have transformed the standard of care for lung cancer, creating a need for up-to-date evidence for health economic modelling. We developed a discrete event simulation of advanced lung cancer treatment to provide estimates of survival outcomes and healthcare costs in the Australian setting that can be updated as new therapies are introduced. METHODS: Treatment for advanced lung cancer was modelled under a clinician-specified treatment algorithm for Australia in 2022. Prevalence of lung cancer subpopulations was extracted from cBioPortal and the Sax Institute’s 45 and Up Study, a large prospective cohort linked to cancer registrations. All costs were from the health system perspective for the year 2020. Pharmaceutical and molecular diagnostic costs were obtained from public reimbursement fees, while other healthcare costs were obtained from health system costs in the 45 and Up Study. Treatment efficacy was obtained from clinical trials and observational study data. Costs and survival were modelled over a 10-year horizon. Uncertainty intervals were generated with probabilistic sensitivity analyses. Overall survival predictions were validated against real-world studies. RESULTS: Under the 2022 treatment algorithm, estimated mean survival and costs for advanced lung cancer 10 years post-diagnosis were 16.4 months (95% uncertainty interval [UI]: 14.7–18.1) and AU$116,069 (95% UI: $107,378–$124,933). Survival and costs were higher assuming optimal treatment utilisation rates (20.5 months, 95% UI: 19.1–22.5; $154,299, 95% UI: $146,499–$161,591). The model performed well in validation, with good agreement between predicted and observed survival in real-world studies. CONCLUSIONS: Survival improvements for advanced lung cancer have been accompanied by growing treatment costs. The estimates reported here can be used for budget planning and economic evaluations of interventions across the spectrum of cancer control. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40273-023-01291-6. |
format | Online Article Text |
id | pubmed-10570197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-105701972023-10-14 Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia Ngo, Preston Karikios, Deme Goldsbury, David Wade, Stephen Lwin, Zarnie Hughes, Brett G. M. Fong, Kwun M. Canfell, Karen Weber, Marianne Pharmacoeconomics Original Research Article BACKGROUND AND OBJECTIVE: Since 2016, new therapies have transformed the standard of care for lung cancer, creating a need for up-to-date evidence for health economic modelling. We developed a discrete event simulation of advanced lung cancer treatment to provide estimates of survival outcomes and healthcare costs in the Australian setting that can be updated as new therapies are introduced. METHODS: Treatment for advanced lung cancer was modelled under a clinician-specified treatment algorithm for Australia in 2022. Prevalence of lung cancer subpopulations was extracted from cBioPortal and the Sax Institute’s 45 and Up Study, a large prospective cohort linked to cancer registrations. All costs were from the health system perspective for the year 2020. Pharmaceutical and molecular diagnostic costs were obtained from public reimbursement fees, while other healthcare costs were obtained from health system costs in the 45 and Up Study. Treatment efficacy was obtained from clinical trials and observational study data. Costs and survival were modelled over a 10-year horizon. Uncertainty intervals were generated with probabilistic sensitivity analyses. Overall survival predictions were validated against real-world studies. RESULTS: Under the 2022 treatment algorithm, estimated mean survival and costs for advanced lung cancer 10 years post-diagnosis were 16.4 months (95% uncertainty interval [UI]: 14.7–18.1) and AU$116,069 (95% UI: $107,378–$124,933). Survival and costs were higher assuming optimal treatment utilisation rates (20.5 months, 95% UI: 19.1–22.5; $154,299, 95% UI: $146,499–$161,591). The model performed well in validation, with good agreement between predicted and observed survival in real-world studies. CONCLUSIONS: Survival improvements for advanced lung cancer have been accompanied by growing treatment costs. The estimates reported here can be used for budget planning and economic evaluations of interventions across the spectrum of cancer control. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40273-023-01291-6. Springer International Publishing 2023-06-25 2023 /pmc/articles/PMC10570197/ /pubmed/37357233 http://dx.doi.org/10.1007/s40273-023-01291-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Article Ngo, Preston Karikios, Deme Goldsbury, David Wade, Stephen Lwin, Zarnie Hughes, Brett G. M. Fong, Kwun M. Canfell, Karen Weber, Marianne Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia |
title | Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia |
title_full | Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia |
title_fullStr | Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia |
title_full_unstemmed | Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia |
title_short | Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia |
title_sort | development and validation of txsim: a model of advanced lung cancer treatment in australia |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570197/ https://www.ncbi.nlm.nih.gov/pubmed/37357233 http://dx.doi.org/10.1007/s40273-023-01291-6 |
work_keys_str_mv | AT ngopreston developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT karikiosdeme developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT goldsburydavid developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT wadestephen developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT lwinzarnie developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT hughesbrettgm developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT fongkwunm developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT canfellkaren developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia AT webermarianne developmentandvalidationoftxsimamodelofadvancedlungcancertreatmentinaustralia |