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A More Nuanced Metric: Z-Scores in Neurodegenerative Disease Research

Research presented at the 2023 Clinical Trials on Alzheimer’s Disease conference highlighted the efficacy of Z-score analysis in capturing a more comprehensive range of performance metrics in clinical trials for neurodegenerative diseases.

The poster, “The Use of Composite Z-Scores in Place of Normative-Based Scaling to Improve Signal Detection in Clinical Trials Involving Signal Detection in Clinical Trials Involving Neurodegenerative Diseases,” details a study aimed at enhancing signal detection in clinical trials and it explores potential advantages of using composite Z-scores over traditional normative-based scaling methods.


Population-based norming for neuropsychological tests such as the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) plays a critical role in the clinical setting. However, the scaling that transforms raw scores into index scores constrain score ranges at the upper and lower limits of performance. This may reduce the sensitivity of such tests to detect change at the outer limits of score ranges.

This limitation is critical in the context of neurodegenerative diseases, where detecting subtle changes over time is vital.

About the Z-Score

A Z-score is a statistical measure that quantifies the distance of a data point from the mean of a group, expressed in terms of standard deviations. By measuring how far an individual’s results deviate from the average, Z-scores offer a sensitive and detailed method for detecting a wide spectrum of changes.

This enhanced ability to discern both minor and major shifts makes Z-scores particularly valuable for studying neurodegenerative disorders, where tracking nuanced changes over time is crucial.

About the Research

The study examines data from pooled clinical trials of Alzheimer’s disease (AD)  and pooled data from progressive supranuclear palsy (PSP) trials. It compared traditional index scores with a composite Z-score approach.

Researchers used the baseline data from the AD and PSP trials to calculate Z-scores, aligning them with domain and total scale index score composites. The aim was to capture a broader range of performance changes.

They succeeded.

Findings and What They Mean

At baseline, both AD and PSP groups were nearly two standard deviations below the normal age-adjusted mean on the RBANS total scale index score. The Z-score approach showed more normal distributions and larger effect sizes reflecting disease progression over time compared to the normative-based index score approach.

The Z-score method led to more normal distributions and was significantly more sensitive to changes due to disease progression than the traditional index score method.

All this suggests that the Z-score method could be a more effective tool in clinical trials for neurodegenerative diseases, offering enhanced sensitivity to changes in patient conditions over time.

Z-scores offer a sophisticated way to monitor and analyze changes in clinical trials, particularly for conditions like AD and PSP, where understanding subtle changes over time is key to assessing disease progression and treatment effectiveness, according to the authors. “We recommend the use of the Z-score methodology for tracking changes in populations where performance is expected to fall at or below these levels relative to the normal population.”

Jacobs E., et al. The Use of Composite Z-Scores in Place of Normative-Based Scaling to Improve Signal Detection in Clinical Trials Involving Signal Detection In Clinical Trials Involving Neurodegenerative Diseases .CTAD23 Poster. The Journal of Prevention of Alzheimer’s Disease, Volume 10, Supplement 1, 2023

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