The Library
Methods for survival extrapolation and decision making in health technology assessment
Tools
Gallacher, Daniel C. (2022) Methods for survival extrapolation and decision making in health technology assessment. PhD thesis, University of Warwick.
|
PDF
WRAP_THESIS_Gallacher_2022.pdf - Submitted Version - Requires a PDF viewer. Download (1382Kb) | Preview |
Official URL: http://webcat.warwick.ac.uk/record=b3894959
Abstract
The National Institute for Health and Care Excellence (NICE) is the agency for England and Wales responsible for approving medical technologies for routine use in the National Health Service (NHS). When agencies such as NICE assess the value of health technologies, it is common to rely on predictions and extrapolations to assess their lifetime costs and benefits. The papers featured in this thesis set out to identify and assess the suitability of common extrapolation methods and explore the impact of their implementation within economic evaluations.
A systematic search identified methods of survival extrapolation used in recent NICE technology appraisals. A systematic review of cost-effectiveness studies identified survival methods used outside of NICE appraisals. Monte Carlo simulations explored utility of these methods across multiple scenarios. An economic model was built to investigate whether existing NICE processes incentivise the development of stratified therapies when there is the possibility of a heterogeneous response within a population.
Simulations demonstrated that life-year estimates obtained from routinely used parametric extrapolations were associated with bias and large imprecision. In heterogeneous populations, the bias was more severe. Averaging methods offered an improvement, generally reducing the error and bias of life-year estimates, but the variance remains high. In heterogeneous populations, stakeholders may disagree on their preference for a drug to be developed as a targeted therapy.
Current extrapolation methods are unsuitable for the major role they play in influencing healthcare decision-making. Decisions that rely on parametric extrapolations should encourage continued data collection and be regularly reviewed as new evidence becomes available. Stronger encouragement to explore subgroup effects, consistent with the recently updated NICE Methods Guide, may better incentivise the development of targeted therapies, resulting in better care for patients.
Item Type: | Thesis (PhD) | ||||
---|---|---|---|---|---|
Subjects: | H Social Sciences > HC Economic History and Conditions R Medicine > R Medicine (General) R Medicine > RA Public aspects of medicine R Medicine > RC Internal medicine |
||||
Library of Congress Subject Headings (LCSH): | Medical economics, Medical care, Cost of, Medical technology -- Cost effectiveness, Clinical medicine -- Decision making, Evidence-based medicine, Survival analysis (Biometry) -- Mathematical models | ||||
Official Date: | April 2022 | ||||
Dates: |
|
||||
Institution: | University of Warwick | ||||
Theses Department: | Warwick Medical School | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Kimani, Peter K. ; Stallard, Nigel | ||||
Format of File: | |||||
Extent: | multiple pagings : illustrations, charts | ||||
Language: | eng |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |