Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Abstract

Standard approaches to modelling outcomes commonly include a range of predictors such as age, sex and co-morbidities. However, there is growing evidence that quality-of-life (QoL) is also an important predictor of
mortality.

Whilst the effects of standard risk factors have been adequately captured to describe mortality in most models, the omission of QoL indicates the assumption of full independence between QoL and life expectancy (LE). This omission could give rise to systematic bias when measuring quality-adjusted life years (QALYs).

Using data from a registry cohort of patients undergoing total knee replacement (TKR), potential correlations between baseline utility, change in utility and survival are explored using parametric survival models. Outcomes such as LE, QALYs, and incremental cost-effectiveness ratios (ICERs) were calculated and compared.

Forthcoming events

Infectious Disease Epidemiology Unit (IDEU) Symposium 2024

Friday, 14 June 2024, 9.30am to 4.15pm @ Big Data Institute LG seminar rooms

Richard Doll Seminar - Adventures in Digital Health Research: Alcohol, Coffee, and Arrhythmias

Tuesday, 03 September 2024, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, OldRoad Campus, University of Oxford, OX3 7LF