Related Experiment Video
Updated: Jul 15, 2026

08:51
Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
Published on: February 19, 2021
Pooled historical MRI data as a basis for research in multiple sclerosis--a statistical evaluation.
S Schach1, M Scholz, J S Wolinsky
1Department of Statistics, Dortmund University, D-44221 Dortmund, Germany.
Summary
Pooled placebo data can serve as historical controls in therapeutic studies. However, significant heterogeneity exists in magnetic resonance imaging (MRI) measures, even after adjustments, requiring careful statistical consideration.
Area of Science:
- Neuroimaging
- Clinical Trials
- Biostatistics
Background:
- Pooled placebo data are valuable for historical controls and power calculations in therapeutic studies.
- Investigating heterogeneity in placebo arm data is crucial for assessing database utility.
- The Sylvia Lawry Centre for Multiple Sclerosis Research maintains a database of controlled studies.
Purpose of the Study:
- To assess the usefulness of pooled placebo arm data from multiple sclerosis (MS) trials as historical controls.
- To investigate the degree of heterogeneity in magnetic resonance imaging (MRI) measures within the pooled placebo data.
- To determine if adjustments for population differences can mitigate heterogeneity.
Main Methods:
- Analysis of pooled placebo arm data from 14 controlled studies.
- Adjustment of magnetic resonance imaging (MRI) measures for differences in study populations.
- Stratification analysis to account for heterogeneity.
Main Results:
- Significant heterogeneity was observed in MRI measures across pooled placebo groups, even after population adjustments.
- Heterogeneity was substantially reduced when comparing studies from the same image analysis center.
- The pooled database remains useful for analyzing inter-variable relationships when heterogeneity is explicitly managed.
Conclusions:
- Pooled placebo data offer utility for statistical analyses but require careful handling due to inherent heterogeneity.
- Explicitly accounting for heterogeneity as a stratification factor is essential for valid comparisons.
- Comparing new treatment groups with pooled data necessitates caution due to potential variations in MRI measures.
