Modeling the Path to Cure: How (NEO)Adjuvant Drug Therapies are Evaluated in Health Technology Assessment (HTA)
Author(s)
Christopher Black, MPH, PhD1, Sophie Boukouvalas, BSc, MSc2, Jennifer Sander, BSc, MSc2, Jan McKendrick, BSc, MSc2;
1Merck &Co., Inc., Rahway, NJ, USA, 2Avalere Health, London, United Kingdom
1Merck &Co., Inc., Rahway, NJ, USA, 2Avalere Health, London, United Kingdom
OBJECTIVES: (Neo)adjuvant drug therapies for solid tumors have shown substantial clinical benefit, but Health Technology Assessment (HTA) agencies face challenges in evaluating their cost-effectiveness, partially due to reliance on cure assumptions. Understanding how cure is presented, estimated, and assessed by different HTA agencies can inform future model development.
METHODS: A targeted review was conducted on HTA assessments between 2018-2023 for (neo)adjuvant drug therapies with submissions across Australia, Canada, France, Ireland, and the UK. This review focused on non-small cell lung cancer (atezolizumab), melanoma (dabrafenib+trametinib), and early breast cancer (olaparib, pembrolizumab). The study aimed to compare approaches among HTA agencies concerning estimating cure and incorporating assumptions into cost-effectiveness models.
RESULTS: 23 HTA assessments were reviewed. Dabrafenib+trametinib submissions were the only ones including manufacturer cure models. Agencies expressed uncertainty about proportional hazards assumptions noting treatment effect variation over time. Different responses were observed: NICE and HAS accepted cure assumptions while PBAC, CDA, and NCPE considered delaying recurrence as more plausible. For atezolizumab, all agencies conceptually accepted cure, although the final models varied in parametric forms and cure timepoint assumptions. For olaparib, despite differences in assumed cure timepoints submitted across agencies, common concerns arose about trial subgroup differences (i.e. related to breast cancer subtypes) affecting parametric form choices and cure timepoint assumptions. For pembrolizumab, differences between agencies emerged in selected parametric forms for survival extrapolation, with HAS proposing fractional polynomials. For all submissions reviewed, local expert clinicians informed many of the differences between agencies leading to model adaptations, or modifications of cure assumptions or model structures. The level of scrutiny of cure assumptions varied between agencies.
CONCLUSIONS: A variety of cure modeling approaches have been employed with mixed receptivity. Thoughtful, integrated approaches across agencies would be beneficial to address key challenges such as variability in timepoint and cure assumptions within subgroups.
METHODS: A targeted review was conducted on HTA assessments between 2018-2023 for (neo)adjuvant drug therapies with submissions across Australia, Canada, France, Ireland, and the UK. This review focused on non-small cell lung cancer (atezolizumab), melanoma (dabrafenib+trametinib), and early breast cancer (olaparib, pembrolizumab). The study aimed to compare approaches among HTA agencies concerning estimating cure and incorporating assumptions into cost-effectiveness models.
RESULTS: 23 HTA assessments were reviewed. Dabrafenib+trametinib submissions were the only ones including manufacturer cure models. Agencies expressed uncertainty about proportional hazards assumptions noting treatment effect variation over time. Different responses were observed: NICE and HAS accepted cure assumptions while PBAC, CDA, and NCPE considered delaying recurrence as more plausible. For atezolizumab, all agencies conceptually accepted cure, although the final models varied in parametric forms and cure timepoint assumptions. For olaparib, despite differences in assumed cure timepoints submitted across agencies, common concerns arose about trial subgroup differences (i.e. related to breast cancer subtypes) affecting parametric form choices and cure timepoint assumptions. For pembrolizumab, differences between agencies emerged in selected parametric forms for survival extrapolation, with HAS proposing fractional polynomials. For all submissions reviewed, local expert clinicians informed many of the differences between agencies leading to model adaptations, or modifications of cure assumptions or model structures. The level of scrutiny of cure assumptions varied between agencies.
CONCLUSIONS: A variety of cure modeling approaches have been employed with mixed receptivity. Thoughtful, integrated approaches across agencies would be beneficial to address key challenges such as variability in timepoint and cure assumptions within subgroups.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
HTA47
Topic
Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
SDC: Oncology