Global Health technology assessment (HTA) bodies are setting higher standards for rigorous evidence to support access decisions. In this evolving landscape, generating meaningful health economic (HE) models and indirect treatment comparison (ITC) analysis is critical — particularly in rare and chronic disease settings. However, traditional modeling techniques often fall short, prompting the need for more advanced and adaptable approaches. 

Join our upcoming webinar to gain practical insights from a panel of experts from Europe and North America on a range of cutting-edge methodologies. Learn how to identify the most relevant method for your market access scenarios, given your indication, patient population characteristics, and data gaps. 

Key Scenarios Discussed

• How to generate HE or ITC insights for an oncology therapy in a rare disease setting?
  • Use of multi-state modeling approach and survival extrapolation when traditional partitioned survival models are not suitable
  • Use of surrogate endpoints and best practices for their application and reporting
  • Use of matching-adjusted indirect comparisons (MAIC) with random forest weights as an alternative to traditional propensity score-based weighting, particularly when the index trial has small sample size and covariate overlap is poor.

• How to derive HE and ITC insights from trial and RWE data in chronic disease indications
  • Use of sequence modeling to address the complexity of evolving treatment pathways
  • Use of population-adjusted indirect comparisons (PAIC) at the aggregate level – such as Multilevel Network Meta-Regression (ML-NMR) or Network Meta-Regression using Matching (NMI) to address heterogeneity across more than two studies.
  • Use of G-Computation, a flexible outcome modeling approach applied when comparing two studies. G-Computation is especially useful in cases of poor covariate overlap between the index and comparator trial populations, offering greater robustness than standard MAIC or STC.

• How can health inequities be modeled through structural adaptations and assumptions to assess the differential impact of therapies across patient subgroups using a distributional cost-effectiveness analysis

Panel members

Moderator

•  Angie Raad-Faherty, Director Health Economics NA

Speakers

• Hoora Moradian, Director, Comparative Effectiveness
• Victor Laliman-Khara, Research Principal, Comparative Effectiveness
• Peter Wigfield, Associate Director, Health Economics EU
• Michael Dolph, Director, Health Economics NA
• Michael Groff, Associate Director, Health Economics NA