How to analyze continuous and discrete repeated measures in small-sample cross-over trials?

Publisher: Oxford University Press Country of Publication: England NLM ID: 0370625 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1541-0420 (Electronic) Linking ISSN: 0006341X NLM ISO Abbreviation: Biometrics Subsets: MEDLINE

Publication: March 2024- : [Oxford] : Oxford University Press
Original Publication: Alexandria Va : Biometric Society

Models, Statistical* ; Rare Diseases*; Humans ; Cross-Over Studies ; Data Interpretation, Statistical ; Research Design

To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data. The recommendation of which methodology to use in rare disease trials with a repeated measures cross-over design depends on the type of outcome and the number of time points the treatment has an effect on. The non-parametric marginal model testing the treatment-time-interaction effect is suitable for detecting between group differences in the shapes of the longitudinal profiles. For binary outcomes with the treatment effect on a single time point, the parametric model averaging method is recommended, while in the other cases the unmatched generalized pairwise comparison methodology is recommended. Both provide an easily interpretable effect size measure, and do not require exclusion of periods or subjects due to incompleteness.
(© 2023 The International Biometric Society.)

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20102-F1901166-KZP WISS 2025 project 'IDA-Lab Salzburg'; 20204-WISS/225/197-2019 WISS 2025 project 'IDA-Lab Salzburg'; grant agreement no. 825575 European Joint Programme on Rare Diseases (EJP RD), EU Horizon 2020

Keywords: Barnard test; GEE; cross-over; epidermolysis bullosa simplex; generalized pairwise comparison; model averaging; non-parametric marginal model; rare diseases; repeated measures

Date Created: 20230817 Date Completed: 20231221 Latest Revision: 20240103

20250114

10.1111/biom.13920

37587671