Efficiency of multivariate tests in trials in progressive supranuclear palsy

Measuring disease progression in clinical trials for testing novel treatments for multifaceted diseases as progressive supranuclear palsy (PSP), remains challenging. In this study we assess a range of statistical approaches to compare outcomes as measured by the items of the progressive supranuclear palsy rating scale (PSPRS). We consider several statistical approaches, including sum scores, a modified PSPRS rating scale that had been recommended by FDA in a pre-IND meeting, multivariate tests, and analysis approaches based on multiple comparisons of the individual items. In addition, we propose two novel approaches which measure disease status based on Item Response Theory models. We assess the performance of these tests under various scenarios in an extensive simulation study and illustrate their use with a re-analysis of the ABBV-8E12 clinical trial. Furthermore, we discuss the impact of the FDA-recommended scoring of item scores on the power of the statistical tests. We find that classical approaches as the PSPRS sum score demonstrate moderate to high power when treatment effects are consistent across the individual items. The tests based on Item Response Theory (IRT) models yield the highest power when the simulated data are generated from an IRT model. The multiple testing based approaches have a higher power in settings where the treatment effect is limited to certain domains or items. The study demonstrates that there is no one-size-fits-all testing procedure for evaluating treatment effects using PSPRS items; the optimal method varies based on the specific effect size patterns. The efficiency of the PSPRS sum score, while generally robust and straightforward to apply, varies depending on the specific patterns of effect sizes encountered and more powerful alternatives are available in specific settings. These findings can have important implications for the design of future clinical trials in PSP and similar multifaceted diseases.

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Publication Details

Journal
Scientific Reports
Published
2024-10-26
DOI
https://doi.org/10.1038/s41598-024-76668-4
Citations
3
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
2.13

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article

Efficiency of multivariate tests in trials in progressive supranuclear palsy

Martin Posch, Franziska Hopfner, Robin Ristl, Franz König et al.
3 citations
Scientific Reports
Statistical Methods in Clinical Trials
2.13
article

Efficiency of multivariate tests in trials in progressive supranuclear palsy

Martin Posch, Franziska Hopfner, Robin Ristl, Franz König, Sonja Zehetmayer, Günter U. Höglinger, Mats O. Karlsson, Mohamed Gewily, Elham Yousefi
article en
3 citations

Abstract

Measuring disease progression in clinical trials for testing novel treatments for multifaceted diseases as progressive supranuclear palsy (PSP), remains challenging. In this study we assess a range of statistical approaches to compare outcomes as measured by the items of the progressive supranuclear palsy rating scale (PSPRS). We consider several statistical approaches, including sum scores, a modified PSPRS rating scale that had been recommended by FDA in a pre-IND meeting, multivariate tests, and analysis approaches based on multiple comparisons of the individual items. In addition, we propose two novel approaches which measure disease status based on Item Response Theory models. We assess the performance of these tests under various scenarios in an extensive simulation study and illustrate their use with a re-analysis of the ABBV-8E12 clinical trial. Furthermore, we discuss the impact of the FDA-recommended scoring of item scores on the power of the statistical tests. We find that classical approaches as the PSPRS sum score demonstrate moderate to high power when treatment effects are consistent across the individual items. The tests based on Item Response Theory (IRT) models yield the highest power when the simulated data are generated from an IRT model. The multiple testing based approaches have a higher power in settings where the treatment effect is limited to certain domains or items. The study demonstrates that there is no one-size-fits-all testing procedure for evaluating treatment effects using PSPRS items; the optimal method varies based on the specific effect size patterns. The efficiency of the PSPRS sum score, while generally robust and straightforward to apply, varies depending on the specific patterns of effect sizes encountered and more powerful alternatives are available in specific settings. These findings can have important implications for the design of future clinical trials in PSP and similar multifaceted diseases.

Scientific ReportsVol. 14(1)
Uppsala University (SE), German Center for Neurodegenerative Diseases (DE), LMU Klinikum (DE), Medizinische Hochschule Hannover (DE), Munich Cluster for Systems Neurology (DE), Medical University of Vienna (AT), Ludwig-Maximilians-Universität München (DE)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 12%
Statistical Methods in Clinical Trials
2.13
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