29 April 2026

Researchers at the ALS Center The Netherlands have discovered that the results of studies on ALS treatments are analyzed in many different ways. This makes it difficult to compare studies with one another. There is less certainty about the outcomes that are supposed to demonstrate whether a treatment works or not. These findings have been published in the scientific journal Neurology.

In statistical analysis, researchers use mathematical methods to examine large amounts of study data. This allows them to determine whether a treatment is truly effective. An international working group has been established to develop common guidelines for analyzing clinical trial results.

Measurement Tools in Clinical Trials

In clinical studies, measurement tools that track disease progression are essential for measuring the potential effect of a treatment. A commonly used measurement tool in ALS research is the ALSFRS-R (ALS Functional Rating Scale Revised). This questionnaire measures how a person with ALS functions over time, for example in terms of speech, swallowing, breathing, and physical activity. Tools such as the ALSFRS-R allow researchers to measure disease progression in patients in a standardized way. However, there is a lack of common agreements regarding statistical analysis.

The Study

Researchers at the ALS Center The Netherlands reviewed completed ALS studies to determine how ALSFRS-R outcomes are analyzed. This study is part of GoALS, a multi-year research program aimed at finding treatments for ALS. In total, the researchers reviewed 45 studies. A total of 7,338 patients participated in these studies.

Many different Analysis Methods 

The researchers found that the ALSFRS-R was analyzed in as many as 39 different ways across the various studies. Why is that? Because patients die or withdraw from the study, data is often missing in clinical trials. To address the issue of missing data, researchers opt for different analytical methods. These differences in approach make it difficult to compare studies with one another.

In addition, more than half of the studies reviewed (55.6%) did not utilize all available ALSFRS-R measurements. This means that not all patient data was used to its full potential. This results in reduced statistical precision, which means there is less certainty about the study’s results. Furthermore, 38.9% of the analysis methods used were found to increase the risk of false-positive outcomes: as a result, treatments may be incorrectly labeled as effective when they are not.

International Collaboration

To establish common guidelines for the statistical analysis of measurement tools such as the ALSFRS-R, the researchers have formed an international working group. The goal: to make better use of patient data and find effective treatments for ALS more quickly. The lessons from this study extend beyond ALS studies alone: common guidelines for statistical analysis are important throughout the entire field of clinical research.

                           Translation: Dirk De Valck

      Source: Newsletter ALS Center The Netherlands