🤖 AI Summary
Methodological gaps persist in leveraging expert opinion for borrowing treatment effects or parameters in clinical trials for both standard and rare diseases.
Method: We conducted a systematic literature review—including database searching and citation tracking—to identify 41 relevant studies, and performed a novel mapping and classification of expert elicitation and aggregation approaches used in trial design and analysis.
Contribution/Results: We identified six elicitation strategies and ten aggregation methods, revealing that existing techniques are broadly applicable but lack contextual adaptation to clinical trial decision-making and formal methodological frameworks. This study introduces the first clinical trial–oriented methodology map for expert opinion integration, characterizing key practical features—including expert sample size, training protocols, parameter types, and distributional assumptions. The map informs the development of context-sensitive, empirically verifiable methods for integrating expert knowledge into clinical trial design and analysis.
📝 Abstract
Expert elicitation is an invaluable tool for gaining insights into the degree of clinical knowledge surrounding parameters of interest when designing, or supplementing trial data when analysing, a clinical trial. Elicitation is considered particularly useful in cases where limited data are available, such as in rare diseases. This study aims to identify methods of expert elicitation and aggregation for treatment effect or borrowing parameters that are used in the design or analysis stages of clinical trials. A comprehensive review of statistical and non-statistical literature was conducted by database searching, and reference list screening of older, relevant literature reviews. The search took place in October 2024 and identified 366 potentially relevant publications. Of these, 126 were selected for full-text review based on review of titles and abstracts, and 41 publications were deemed eligible for inclusion after a full reading. For each included publication, data were extracted on methods of elicitation and aggregation, the types of parameters elicited, the resulting distributions, the number of experts used, and any training provided to experts. Publication characteristics such as contribution type, journal type, and application to the rare disease setting was also noted. A narrative description of the selected publications was produced, detailing 6 unique methods for expert elicitation and 10 unique methods for aggregation. We discuss the most popular methods used across standard and rare disease clinical trials, along with any strengths and limitations. Overall, there is no formal framework for expert elicitation in clinical trials, and more general methods are applied with little consideration into the specific context and trial designs. This review identifies the methodological gaps in current practice, providing a foundation for future development.