Target trial emulation for transparent and robust estimation of treatment effects for health technology assessment using real-world data.

Research question How can target trial emulation (TTE) improve the estimation of treatment effects for health technology assessment (HTA) using real-world data (RWD)?

Background HTA agencies, such as NICE, are increasingly using RWD to estimate the effectiveness and cost-effectiveness of health interventions, but unless HTA studies appropriately address the potential pitfalls arising from RWD, they will lead to biased estimates of treatment effects.

By applying design and analysis principles from randomised controlled trials (RCTs), TTE can enable a more transparent and robust estimation of treatment effects from RWD.

However, there are several methodological and practical challenges that need to be addressed to enable the adoption of TTE in HTA.

Aim To exploit the target trial approach to enable transparent and robust estimation of treatment effects for HTA using RWD, and develop a roadmap for its implementation in HTA. Objectives 1. Extend the target trial approach to evaluate personalised, adaptive treatment strategies 2. Devise a framework to aid the analysis and interpretation of uncontrolled studies in HTA. 3.

Exploit target trial emulation to improve indirect treatment comparisons. 4. Develop a roadmap for the adoption of TTE in HTA.

Methods Work-package 1 (months 1-15): Extend TTE to accommodate the personalisation of treatment strategies by incorporating: i) adaptive treatment strategies, ii) stratification of target trial according to key prognostic factors, and iii) new machine learning methods to improve the targeting of the right treatments for the right patients.

Work-package 2 (months 12-27): Devise and illustrate a framework to improve the relevance and interpretation of uncontrolled studies, such as single-arm trials, and contextualise them with RWD.

This will involve: i) develop protocol of target trial in line with research question of uncontrolled study, ii) derive relevant control group from RWD, iii) devise a strategy for sensitivity analysis to address discrepancies between the protocol and emulated target trial, and iv) develop general recommendations to inform future data collection.

Work-package 3 (months 21-36): Demonstrate how the target trial approach can improve indirect treatment comparisons in the absence of head-to-head RCTs: i) allow head-to-head comparisons using routine datasets, ii) assess the plausibility of assumptions made by the evidence synthesis approaches, and iii) include comparisons of relevant outcomes not included across all RCTs.

Work-package 4 (months 1-36): Develop accessible guidance, software tools, and training to facilitate the implementation of TTE in HTA.

Impact This research will lead to better clinical and resource allocation decisions by improving treatment recommendations within NICE's HTA programme and clinical guideline development.

By exploiting large-scale RWD, this research will provide measures of treatment effectiveness and cost-effectiveness that are of greater relevance to patients, practitioners and commissioners, because they will reflect more closely the diversity of patients and the care they receive in routine practice.

More generally, the project will help researchers gain greater utility from routinely-collected data through more rigorous design and analysis of observational studies in HTA.