Year: 2016
Type: dissertation
Abstract: This thesis focusses on the challenges relating to clinical- and cost-effectiveness\nanalysis in Health Technology Assessment (HTA). It includes methodological\ndevelopments, both statistical and presentational, in evidence synthesis aiming to\naddress those challenges.\nIn HTA, analysts often face problems with limited availability of data required to\ninform economic model. This thesis proposes innovative evidence synthesis approaches\nto address this challenge, illustrated in two examples. Bivariate random-effects meta-analysis\n(BRMA) and network meta-analysis (NMA) were used to synthesise all\navailable evidence to predict progression-free survival (PFS), in metastatic prostate\ncancer. This enabled the specification of a three-state Markov model previously limited\nto two states when PFS was not recorded. In the second example, a scenario in multiple\nsclerosis is considered where utility data for the trials included in a HTA were not\navailable and external utility data from a single study was used instead. This thesis\nillustrates how BRMA can be applied to include all available evidence to inform utility\nestimates for use in a cost-effectiveness analysis.\nNMA, allowing for a simultaneous and coherent comparison of multiple interventions,\nis increasingly used in HTA. However, due to the inherent complexity of presenting\nNMA results, it is important to ease their interpretability. A review of existing methods\nof presenting NMA results in HTA reports revealed that there is no standardised\npresentational tool for their reporting. Novel presentational approaches were developed\nwhich are presented in this thesis.\nThe original contributions of this thesis are the innovative approaches to incorporate\nhistorical data to predict and increase the precision of parameter estimates for cost-effectiveness\nanalysis to better inform health policy decision-making; and three novel\ngraphical tools to aid clear presentation and facilitate interpretation of NMA results.\nUltimately, the hope is that the graphical tools developed will be recommended in\nupdated guidance setting the standards for future HTAs.
Author: Sze Huey Tan
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2379875585