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HEOR & RWE Webinar Series

Robust Identification and Adjustment for Effect Modifiers in Indirect Treatment Comparisons; When and How?

Population-adjusted indirect treatment comparisons (PAICs) are commonly used in health technology appraisals to estimate relative treatment effects in presence of bias due to effect modification. Bias due to effect modification occurs when there are distributional differences in the effect modifiers (EMs) across the trials in a network. Standard network meta-analyses (NMAs) are based on aggregated data (AgD) and assume no EMs or that the distributions of EMs are balanced between trials. However, when this is not the case, different methods of PAICs such as matching-adjusted indirect comparison [MAIC], simulated treatment comparison [STC] and the newest method of Multi-Level Network Meta-Regression (ML-NMR) have been proposed to "correct" for the role of EMs by using available individual patient data (IPD) to adjust for differences in EMs through reweighting or regression adjustment.

Key Learning Points:

  1. How should EMs be identified from the literature following evidence-based principles? How to ensure the unbiased selection of EMs for inclusion in PAICs?
  2. How best to navigate across the different methodologies for adjusting for EMs in PAICs and to handle the nuances around each method such as multiple endpoints, sample size considerations and evidence sources?
  3. What is the potential of a novel indirect treatment comparison approach, called Network Meta-Interpolation which challenges the strong assumption of shared effect modification in NMAs and offer an alternative solution?

Live Webinar Series Schedule: 

  • June 9th at 10:00am ET: Effect Modifiers In Indirect Treatment Comparisons; Steps To Ensure the Unbiased Identification to Inform Decision Making
    • Andreas Freitag, Associate Director, Research Principal, Health Economics
  • June 16th at 10:00am ET: When and How to Adjust for Effect Modifiers in Population-Adjusted Indirect Treatment Comparisons? What Not to Do?
    • Michael Groff, Senior Research Consultant, Health Economics
  • June 23rd at 10:00am ET: Network Meta-Interpolation, A Novel Approach to Adjust for Effect Modification in Network Meta-analysis Using Subgroup Analyses; Tunneling through Statistics
    • Ofir Harari, Senior Research Principal, Statistics

Webinar Series Moderator: 

  • Grammati Sarri, Senior Research Principal, Head of RWAA External Research Partnerships, Cytel 

Meet the Speakers: 

  • Andreas Freitag, Associate Director, Research Principal, Health Economics
  • Michael Groff, Senior Research Consultant, Health Economics
  • Ofir Harari, Senior Research Principal, Statistics

Meet The Speakers

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