Session (CTI)

PURPOSE: The objectives are to present theoretical and practical issues of applying mixture-cure models (MCMs) in health technology assessment (HTA) settings for interventions with curative potential (IwCP), present a case-study to help demonstrate these challenges and propose practical solutions. DESCRIPTION: Extrapolation of time-to-event outcomes for IwCP requires careful consideration to ensure clinical plausibility of estimated long-term survival. MCMs are commonly used in these settings to explicitly model survival for the “cured” and “uncured” cohorts. Despite being commonly used across recent HTA submissions of IwCP, both theoretical and practical issues remain when leveraging MCMs for nested outcomes, such as PFS, PFS2 and OS, in oncology. Relative survival frameworks (RSFs), cure fraction linking, non-MCMs (nMCMs) and Bayesian hierarchical MCMs (BH-MCMs) have been proposed to address MCMs limitations. Mr Conlon will summarise existing HTA guidelines on cure models and their importance to health economics and HTA (5 min.). Professor Baio will briefly describe MCM background and limitations that RSFs, cure fraction linking, nMCMs and BH-MCMS aim to solve (15 min.). Mrs Proskorovsky will present practical statistical and modelling challenges arisen from a case-study in first-line advanced ovarian cancer where MCMs, RSFs and cure fraction linking were explored (15 min.). Professor Owen will discuss a proposed preliminary framework for navigating these challenges, including key considerations and recommendations on best practices for HTA submissions from a NICE committee member and outline priorities for future methodological research (15 min.). Audience participation will involve real-time polling at the start and end of the session, to assess MCMs familiarity, key challenges experienced when using MCMs and what they would have done in the case-study presented, with time reserved at the end for a Q&A session (10 min.). This workshop will be valuable for researchers and professionals interested in statistical methods research and its application to economic modelling and HTA.