November 6: Understanding Survival Modeling with Application to HTA - In Person at ISPOR Europe 2022
Time-to-event (survival) analysis is an important element in many economic analyses of healthcare technologies. This is particularly true in oncology given the requirement to estimate lifetime costs and outcomes (ie, extrapolate) beyond the follow-up typically observed in clinical trials. Cost-effectiveness estimates can be sensitive to the methods applied in modelling survival data. Recommendations for selecting a parametric survival model have recently been published, following a review of extrapolation modelling in National Institute for Health and Care Excellence (NICE) technology appraisals. The purpose of this course is to provide participants with an understanding of the fundamentals of survival analysis and key issues to be considered when comparing alternative survival models for inclusion in cost-effectiveness analysis. This will include an understanding of differences between partitioned survival and Markov-based approaches.
Market Access Director, UK & ROI
Eisai EMEA
Hatfield, UK
Andrew Briggs, DPhil
Professor of Health Economics
London School of Hygiene & Tropical Medicine
London, UK
James Lewsey, PhD, CStat
Professor of Medical Statistics
Health Economics and Technology Assessment
Institute of Health & Wellbeing
University of Glasgow
Glasgow, UK
November 6, 2022
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Understanding Survival Modeling with Application to HTA
LEVEL: Intermediate
TRACK: Methodological & Statistical Research
LENGTH: 4 Hours | Course runs 1 day
This short course will be offered in-person at the ISPOR Europe 2022 conference. Separate registration is required. Visit the ISPOR Europe 2022 website to register and learn more.
Sunday, 6 November 2022 | Course runs 1 Day
DESCRIPTION
Time-to-event (survival) analysis is an important element in many economic analyses of healthcare technologies. This is particularly true in oncology given the requirement to estimate lifetime costs and outcomes (ie, extrapolate) beyond the follow-up typically observed in clinical trials. Cost-effectiveness estimates can be sensitive to the methods applied in modelling survival data. Recommendations for selecting a parametric survival model have recently been published, following a review of extrapolation modelling in National Institute for Health and Care Excellence (NICE) technology appraisals. The purpose of this course is to provide participants with an understanding of the fundamentals of survival analysis and key issues to be considered when comparing alternative survival models for inclusion in cost-effectiveness analysis. This will include an understanding of differences between partitioned survival and Markov-based approaches.FACULTY MEMBERS
Chris Parker, MScMarket Access Director, UK & ROI
Eisai EMEA
Hatfield, UK
Andrew Briggs, DPhil
Professor of Health Economics
London School of Hygiene & Tropical Medicine
London, UK
James Lewsey, PhD, CStat
Professor of Medical Statistics
Health Economics and Technology Assessment
Institute of Health & Wellbeing
University of Glasgow
Glasgow, UK
Basic Schedule:
4 Hours | Course runs 1 Day