Jointly assessing multiple endpoints in pilot and feasibility studies

Pilot and feasibility studies are routinely used to determine whether a definitive trial should be pursued; however, the methodologies used to assess feasibility endpoints are often basic and are rarely informed by the requirements of the planned future trial. We propose a new method for analyzing feasibility outcomes which can incorporate relationships between endpoints, utilize a preliminary study design for a future trial and allow for multiple types of feasibility endpoints. The approach specifies a Joint Feasibility Space (JFS) which is the combination of feasibility outcomes that would render a future trial feasible. We estimate the probability of being in the JFS using Bayesian methods and use simulation to create a decision rule based on frequentist operating characteristics. We compare our approach to other general-purpose methods in the literature with simulation and show that our approach has approximately the same performance when analyzing a single feasibility endpoint but is more efficient with more than one endpoint. Feasibility endpoints should be the focus of pilot and feasibility studies. The analyses of these endpoints deserve more attention than they are given, and we have provided a new, effective method their assessment.

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Publication Details

Journal
Statistical Methods in Medical Research
Published
2025-02-12
DOI
https://doi.org/10.1177/09622802241311219
Citations
1
Primary Topic
Optimal Experimental Design Methods
Type
article
Field-Weighted Citation Impact
2.11

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article

Jointly assessing multiple endpoints in pilot and feasibility studies

Eric D. Vidoni, Robert N. Montgomery, Amy E. Bodde
1 citations
Statistical Methods in Medical Research
Optimal Experimental Design Methods
2.11
article

Jointly assessing multiple endpoints in pilot and feasibility studies

Eric D. Vidoni, Robert N. Montgomery, Amy E. Bodde
article en
1 citations

Abstract

Pilot and feasibility studies are routinely used to determine whether a definitive trial should be pursued; however, the methodologies used to assess feasibility endpoints are often basic and are rarely informed by the requirements of the planned future trial. We propose a new method for analyzing feasibility outcomes which can incorporate relationships between endpoints, utilize a preliminary study design for a future trial and allow for multiple types of feasibility endpoints. The approach specifies a Joint Feasibility Space (JFS) which is the combination of feasibility outcomes that would render a future trial feasible. We estimate the probability of being in the JFS using Bayesian methods and use simulation to create a decision rule based on frequentist operating characteristics. We compare our approach to other general-purpose methods in the literature with simulation and show that our approach has approximately the same performance when analyzing a single feasibility endpoint but is more efficient with more than one endpoint. Feasibility endpoints should be the focus of pilot and feasibility studies. The analyses of these endpoints deserve more attention than they are given, and we have provided a new, effective method their assessment.

Statistical Methods in Medical ResearchVol. 34(3)
University of Kansas Medical Center (US)
National Institutes of Health, National Institute on Aging
Peace, Justice and strong institutions
Openalex Percentile: Top 16%
Optimal Experimental Design Methods
2.11
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Jointly assessing multiple endpoints in pilot and feasibility studies — Eric D. Vidoni, Robert N. Montgomery, et al. · Statistical Methods in Medical Research (2025) | TGRS Research Map | TGRS