Development of a Decision Model to Estimate the Outcomes of Treatment Sequences in Advanced Melanoma

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 and Pieter H. M. van Baal
Additional contact information
Saskia de Groot: Institute for Medical Technology Assessment (iMTA), Erasmus University Rotterdam, The Netherlands
Hedwig M. Blommestein: Erasmus School of Health Policy and Management, Erasmus University Rotterdam, The Netherlands
Brenda Leeneman: Institute for Medical Technology Assessment (iMTA), Erasmus University Rotterdam, The Netherlands
Carin A. Uyl- de Groot: Institute for Medical Technology Assessment (iMTA), Erasmus University Rotterdam, The Netherlands
John B. A. G. Haanen: Division of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
Michel W. J. M. Wouters: Scientific Bureau, Dutch Institute for Clinical Auditing, Leiden, The Netherlands
Maureen J. B. Aarts: Department of Medical Oncology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
Franchette W. P. J. van den Berkmortel: Department of Medical Oncology, Zuyderland Medical Center Sittard, Sittard-Geleen, The Netherlands
Willeke A. M. Blokx: Department of Pathology, Division of Laboratories, Pharmacy and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
Marye J. Boers-Sonderen: Department of Medical Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
Alfons J. M. van den Eertwegh: Department of Medical Oncology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
Jan Willem B. de Groot: Isala Oncology Center, Isala, Zwolle, The Netherlands
Geke A. P. Hospers: Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Ellen Kapiteijn: Department of Medical Oncology, Leiden University Medical Center, Leiden, The Netherlands
Olivier J. van Not: Scientific Bureau, Dutch Institute for Clinical Auditing, Leiden, The Netherlands
Astrid A. M. van der Veldt: Department of Medical Oncology and Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
Karijn P. M. Suijkerbuijk: Department of Medical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
Pieter H. M. van Baal: Erasmus School of Health Policy and Management, Erasmus University Rotterdam, The Netherlands

Medical Decision Making, 2025, vol. 45, issue 3, 302-317

Abstract: 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.

Keywords: Advanced melanoma; decision model; treatment sequences; semi-Markov; immunotherapies; BRAF plus MEK inhibitors (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:45:y:2025:i:3:p:302-317

DOI: 10.1177/0272989X251319338

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