Exploring Methodologies for Defining and Modeling Cure in Melanoma: Impacts on Estimating Cure Metrics
Author(s)
Christopher Black, MPH, PhD1, Jennifer Sander, MPH2, Sophie Boukouvalas, MSc3, Jan McKendrick, BSc, MSc4.
1Merck & Co. Inc, Rahway, NJ, USA, 2Avalere Health, Washington, DC, USA, 3Consultant, Avalere Health, Athens, Greece, 4Avalere Health, London, United Kingdom.
1Merck & Co. Inc, Rahway, NJ, USA, 2Avalere Health, Washington, DC, USA, 3Consultant, Avalere Health, Athens, Greece, 4Avalere Health, London, United Kingdom.
OBJECTIVES: As therapeutic options for melanoma evolve to directly target driver mutations, delaying recurrence becomes increasingly achievable and the concept of cure gains importance in early disease stages. This research explores methodologies for defining and modeling cure in melanoma; and their impact of estimating cure in melanoma.
METHODS: A systematic literature review (SLR) using PubMed and EMBASE was conducted for global English publications to analyze key factors influencing the definition of ‘cure’. Health technology assessments (HTA) from seven countries were reviewed to analyze methodological approaches in the adjuvant setting. Results focus solely on melanoma specific findings.
RESULTS: The SLR identified 62 publications, 24 of which included data on melanoma that revealed consistency in emphasizing the concept of a reduced risk of disease-related mortality often indicated by a plateau in survival curves, but variability in terminology of ‘cure’ such as “recurrence-free” or “long-term survivor”. Cure fraction estimates in publications varied from 28% to 95%, with only one publication indicating a time to cure of 3.8-8.8 years. Population heterogeneity influences the estimates of cure metrics, with covariates like disease stage and tumor site impacting estimates. 16 indications were identified for the HTA review, 5 of which were melanoma specific. The HTA review showed that while the same data-cut was used for submissions across all HTA agencies, and majority of models were Markov, different approaches to survival modeling were noted. HTA opinions varied on the acceptance of cure assumptions which were primarily driven by the uncertainty on estimating treatment benefit. Variation of treatment effect over time was often preferred.
CONCLUSIONS: There is not yet agreement on defining ‘cure’ in melanoma, highlighting the need to consider population heterogeneity when assessing the potential for cure. Future economic modeling strategies should choose flexible approaches to capture variations in treatment effects and ensure uncertainty in treatment benefit estimations is addressed.
METHODS: A systematic literature review (SLR) using PubMed and EMBASE was conducted for global English publications to analyze key factors influencing the definition of ‘cure’. Health technology assessments (HTA) from seven countries were reviewed to analyze methodological approaches in the adjuvant setting. Results focus solely on melanoma specific findings.
RESULTS: The SLR identified 62 publications, 24 of which included data on melanoma that revealed consistency in emphasizing the concept of a reduced risk of disease-related mortality often indicated by a plateau in survival curves, but variability in terminology of ‘cure’ such as “recurrence-free” or “long-term survivor”. Cure fraction estimates in publications varied from 28% to 95%, with only one publication indicating a time to cure of 3.8-8.8 years. Population heterogeneity influences the estimates of cure metrics, with covariates like disease stage and tumor site impacting estimates. 16 indications were identified for the HTA review, 5 of which were melanoma specific. The HTA review showed that while the same data-cut was used for submissions across all HTA agencies, and majority of models were Markov, different approaches to survival modeling were noted. HTA opinions varied on the acceptance of cure assumptions which were primarily driven by the uncertainty on estimating treatment benefit. Variation of treatment effect over time was often preferred.
CONCLUSIONS: There is not yet agreement on defining ‘cure’ in melanoma, highlighting the need to consider population heterogeneity when assessing the potential for cure. Future economic modeling strategies should choose flexible approaches to capture variations in treatment effects and ensure uncertainty in treatment benefit estimations is addressed.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
HTA145
Topic
Economic Evaluation, Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
Oncology