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Trail-based economic analyses and beyond: application of methods to inform clinical practice and research

Student thesis: Doctor of Philosophy

Abstract

This thesis advances the integration of health economic evaluation into clinical trial design and interpretation to produce evidence that is directly relevant to policy and practice. Drawing on four randomized controlled trials (BASICS, SYCAMORE, MYPAN, and ASYMPTOMATIC), it demonstrates how cost-effectiveness analysis can be extended through Budget Impact Analysis, Value of Implementation, and Value of Information methods to address real-world decision-making.

Each case study reflects distinct methodological challenges. BASICS shows how a large trial can generate robust evidence supporting a cost-saving intervention with substantial system-level impact. SYCAMORE illustrates the need for methodological adaptation, using instrumental variable methods to account for treatment crossover and highlighting tensions between clinical benefit and cost-effectiveness. MYPAN, an ultra-rare disease trial, demonstrates the limitations of standard approaches and emphasises the importance of interpreting Value of Information alongside the feasibility of further research. ASYMPTOMATIC highlights how non-inferiority trials may offer value beyond clinical outcomes, such as environmental benefits.

Overall, the thesis proposes a flexible and context-sensitive framework that extends the role of clinical trials beyond efficacy, supporting decision-making on adoption, affordability, and research prioritisation.
Date of Award13 Apr 2026
Original languageEnglish
Awarding Institution
  • Bangor University
SupervisorDyfrig Hughes (Supervisor) & Nicky Welton (Supervisor)

Keywords

  • Health economics, Cost effectiveness analysis, Randomised controlled trials, Value of information (VOI), Expected value of perfect information (EVPI), Expected value of sample information (EVSI), Budget impact analysis (BIA), Value of implementation, Non-inferiority trials, Rare diseases, Decision analytic modelling, Health policy, PhD

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