Development of a Decision Model to Estimate the Outcomes of Treatment Sequences in Advanced Melanoma
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| Názov: | Development of a Decision Model to Estimate the Outcomes of Treatment Sequences in Advanced Melanoma |
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| Autori: | Saskia de Groot, Hedwig M. Blommestein, Brenda Leeneman, Carin A. Uyl-de Groot, John B. A. G. Haanen, Michel W. J. M. Wouters, Maureen J. B. Aarts, Franchette W. P. J. van den Berkmortel, Willeke A. M. Blokx, Marye J. Boers-Sonderen, Alfons J. M. van den Eertwegh, Jan Willem B. de Groot, Geke A. P. Hospers, Ellen Kapiteijn, Olivier J. van Not, Astrid A. M. van der Veldt, Karijn P. M. Suijkerbuijk, Pieter H. M. van Baal |
| Prispievatelia: | Pathologie Pathologen staf, Cancer, MS Medische Oncologie, Infection & Immunity |
| Zdroj: | Med Decis Making Medical Decision Making, 45, 3, pp. 302-317 |
| Informácie o vydavateľovi: | SAGE Publications, 2025. |
| Rok vydania: | 2025 |
| Predmety: | Proto-Oncogene Proteins B-raf, Decision Support Techniques, COST-EFFECTIVENESS, SDG 3 - Good Health and Well-being, Original Research Articles, Proto-Oncogene Proteins B-raf/genetics, Journal Article, BRAF plus MEK inhibitors, METASTATIC MELANOMA, Humans, Melanoma/drug therapy, Skin Neoplasms/mortality, Medical Oncology - Radboud University Medical Center, Melanoma, treatment sequences, immunotherapies, Advanced melanoma, Prognosis, Markov Chains, Treatment Outcome, Mutation, SURVIVAL, Disease Progression, decision model, semi-Markov, REAL-WORLD |
| Popis: | Background A decision model for patients with advanced melanoma to estimate outcomes of a wide range of treatment sequences is lacking. Objectives To develop a decision model for advanced melanoma to estimate outcomes of treatment sequences in clinical practice with the aim of supporting decision making. The article focuses on methodology and long-term health benefits. Methods A semi-Markov model with a lifetime horizon was developed. Transitions describing disease progression, time to next treatment, and mortality were estimated from real-world data (RWD) as a function of time since starting treatment or disease progression and patient characteristics. Transitions were estimated separately for melanoma with and without a BRAF mutation and for patients with favorable and intermediate prognostic factors. All transitions can be adjusted using relative effectiveness of treatments derived from a network meta-analysis of randomized controlled trials (RCTs). The duration of treatment effect can be adjusted to obtain outcomes under different assumptions. Results The model distinguishes 3 lines of systemic treatment for melanoma with a BRAF mutation and 2 lines of systemic treatment for melanoma without a BRAF mutation. Life expectancy ranged from 7.8 to 12.0 years in patients with favorable prognostic factors and from 5.1 to 8.7 years in patients with intermediate prognostic factors when treated with sequences consisting of targeted therapies and immunotherapies. Scenario analyses illustrate how estimates of life expectancy depend on the duration of treatment effect. Conclusion The model is flexible because it can accommodate different treatments and treatment sequences, and the duration of treatment effects and the transitions influenced by treatment can be adjusted. We show how using RWD and data from RCTs can harness advantages of both data sources, guiding the development of future decision models. Highlights The model is flexible because it can accommodate different treatments and treatment sequences, and the duration of treatment effects as well as the transitions that are influenced by treatment can be adjusted. The long-term health benefits of treatment sequences depend on the place of different therapies within a treatment sequence. Assumptions about the duration of relative treatment effects influence the estimates of long-term health benefits. We show how the use of real-world data and data from randomized controlled trials harness the advantages of both data sources, guiding the development of future decision models. |
| Druh dokumentu: | Article Other literature type |
| Popis súboru: | application/pdf |
| Jazyk: | English |
| ISSN: | 1552-681X 0272-989X |
| DOI: | 10.1177/0272989x251319338 |
| Prístupová URL adresa: | https://pubmed.ncbi.nlm.nih.gov/39985400 https://hdl.handle.net/https://repository.ubn.ru.nl/handle/2066/317779 https://doi.org/10.1177/0272989X251319338 https://pure.eur.nl/en/publications/d251aa20-b9d9-4558-8a6d-1e3132efcf5f https://doi.org/10.1177/0272989X251319338 https://research.rug.nl/en/publications/78b43b9d-b315-43b7-860a-00f5bf5a2ef7 https://hdl.handle.net/11370/78b43b9d-b315-43b7-860a-00f5bf5a2ef7 https://doi.org/10.1177/0272989X251319338 https://cris.maastrichtuniversity.nl/en/publications/dec7d975-1de4-4147-b028-58c982e4f704 https://doi.org/10.1177/0272989X251319338 https://dspace.library.uu.nl/handle/1874/461022 https://hdl.handle.net/2066/317779 https://repository.ubn.ru.nl//bitstream/handle/2066/317779/317779.pdf |
| Rights: | CC BY URL: https://journals.sagepub.com/page/policies/text-and-data-mining-license URL: http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (http://us.sagepub.com/en-us/nam/open-access-at-sage). |
| Prístupové číslo: | edsair.doi.dedup.....6f71dc4ba3039165d5644c57bf0e5d3f |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | Background A decision model for patients with advanced melanoma to estimate outcomes of a wide range of treatment sequences is lacking. Objectives To develop a decision model for advanced melanoma to estimate outcomes of treatment sequences in clinical practice with the aim of supporting decision making. The article focuses on methodology and long-term health benefits. Methods A semi-Markov model with a lifetime horizon was developed. Transitions describing disease progression, time to next treatment, and mortality were estimated from real-world data (RWD) as a function of time since starting treatment or disease progression and patient characteristics. Transitions were estimated separately for melanoma with and without a BRAF mutation and for patients with favorable and intermediate prognostic factors. All transitions can be adjusted using relative effectiveness of treatments derived from a network meta-analysis of randomized controlled trials (RCTs). The duration of treatment effect can be adjusted to obtain outcomes under different assumptions. Results The model distinguishes 3 lines of systemic treatment for melanoma with a BRAF mutation and 2 lines of systemic treatment for melanoma without a BRAF mutation. Life expectancy ranged from 7.8 to 12.0 years in patients with favorable prognostic factors and from 5.1 to 8.7 years in patients with intermediate prognostic factors when treated with sequences consisting of targeted therapies and immunotherapies. Scenario analyses illustrate how estimates of life expectancy depend on the duration of treatment effect. Conclusion The model is flexible because it can accommodate different treatments and treatment sequences, and the duration of treatment effects and the transitions influenced by treatment can be adjusted. We show how using RWD and data from RCTs can harness advantages of both data sources, guiding the development of future decision models. Highlights The model is flexible because it can accommodate different treatments and treatment sequences, and the duration of treatment effects as well as the transitions that are influenced by treatment can be adjusted. The long-term health benefits of treatment sequences depend on the place of different therapies within a treatment sequence. Assumptions about the duration of relative treatment effects influence the estimates of long-term health benefits. We show how the use of real-world data and data from randomized controlled trials harness the advantages of both data sources, guiding the development of future decision models. |
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| ISSN: | 1552681X 0272989X |
| DOI: | 10.1177/0272989x251319338 |