Get Real: A How-to Framework on Designing and Implementing a Regulatory and HTA-Grade External Comparator Study

Author(s)

Aimee Hamblin1, Hopin Lee2, Kellyn F. Arnold, PhD3, Lourens Bloem, PhD4, Emmanuelle Boutmy, PhD5, Natasha Bury, MSc3, Stephen Duffield, PhD, MD6, Wim Goettsch, MSc, PhD7, Ashley Jaksa, MPH8, Carmen Tsang, BSc, MSc, PhD9, Anke van Engen, MSc10.
1IQVIA Ltd, London, United Kingdom, 2London, United Kingdom, 3IQVIA, London, United Kingdom, 4Utrecht University, Utrecht, Netherlands, 5Merck KGaA, Darmstadt, Germany, 6NICE, Liverpool, United Kingdom, 7Zorginstituut Nederland, Diemen, Netherlands, 8Aetion, New York, NY, USA, 9Pfizer UK, Tadworth, United Kingdom, 10IQVIA, Amsterdam, Netherlands.

Presentation Documents

OBJECTIVES: External control (EC) arms from real-world data (RWD) are increasingly used to generate comparative evidence when Randomized Clinical Trials (RCTs) are impractical or unethical. However, it is unclear to what extent EC studies are fit for purpose. The Get Real Institute developed an External Comparator Best Practices Framework to help decision-makers determine when to consider an EC study, what requirements should be met, and considerations for designing and executing such studies.
METHODS: An internal review was conducted using the knowledge base of the GetReal Institute multistakeholder working group across public and private sectors, including healthcare decision-makers (5), academia (5), patient networks (1) and industry (15). This was then supplemented by a targeted literature review to address identified gaps. The first draft of this framework was developed and discussed with the GetReal working group members at the GetReal conference in Utrecht. The framework subsequently underwent 2 rounds of development to reach consensus across all parties.
RESULTS: This best practice framework document consolidates varying operational guidance from healthcare decision-makers to clarify study objectives, improve research economy and ensure methodological robustness of EC studies. By consolidating published guidance documents, the framework offers practical recommendations for investigators on the suitability (part 1), requirements (part 2) and data and design considerations (part 3) across the stages of planning, designing, and executing EC studies.
CONCLUSIONS: By providing structured guidance on data selection, study design, statistical analysis, and regulatory engagement, this framework seeks to improve the credibility, consistency, and utility of EC studies in the clinical development plan of innovative medicines.

Conference/Value in Health Info

2025-11, ISPOR Europe 2025, Glasgow, Scotland

Value in Health, Volume 28, Issue S2

Code

SA46

Topic

Health Technology Assessment, Methodological & Statistical Research, Study Approaches

Topic Subcategory

Meta-Analysis & Indirect Comparisons

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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