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Use of Joint Modelling in Health Technology Assessment (HTA)

Seminar

This event has now finished.

Event date
Friday 19 July 2024, 12pm to 1pm
Audience
Open to Open to staff, students, and the public.
Admission
Free admission, booking recommended

Event details

Abstract:

Joint Models (JM) are used to simultaneously analyse data on longitudinal biomarkers and time-to-event outcomes. By doing so they enable either prediction of future clinical events, conditional upon biomarker profiles, and/or estimation of biomarker profiles after allowing for dropout due to death when the time-to-event is death. To date they have been developed both within a frequentist and a Bayesian framework, though the latter more easily enables a number of extensions, such as imposing a hierarchical structure and allowing for intermittent missing data. In this talk I will describe the development and application of JMs to a number of settings in Health Technology Assessment (HTA). Specifically the use of a JM approach to; (i) modelling HRQoL with both dropout due to death and intermittent missing data in a trial to evaluate Transcatheter Aortic Valve Implantation (TAVI); (ii) allow for differential associations between tumour burden/size and overall survival (OS) in a tumour agnostic study of Larotrectinib in order to enhance extrapolation of OS; (iii) allow for informative observations in Electronic Health Record (EHR) data and applied in pre-trial screening of routine estimated glomerular filtration rate (eGFR) measurements for patients with Chronic Kidney Disease (CKD); (iv) developing a natural history model in Duchenne Muscular Dystrophy (DMD). I will also discuss further extensions, and in particular how JMs can be estimated in large RWE and EHR databases without a computationally prohibitive burden.

If you are not a member of University of York staff and are interested in attending a seminar, please contact alfredo.palacios@york.ac.uk or shainur.premji@york.ac.uk so that we can ensure we have sufficient space.

Keith Abrams, Warwick Medical School

Keith Abrams

Professor of Statistics & Data Science in the Department of Statistics and Adjunct Professor of Biostatistics in Warwick Medical School (WMS) at the University of Warwick. See more on Keith Abrams' profile.