Abstract
Background
Numerous statistically derived composite measures have recently been proposed as clinical outcome assessments (COAs) for clinical trials in the early stages of Alzheimer disease. Critical Path Institute’s Coalition Against Major Diseases (CAMD) advanced a proposed statistically derived composite measure to regulatory agencies with the goal of qualifying it as a COA for pre-dementia trials. In response to FDA’s requirement to demonstrate that proposed COAs are meaningful to patients, this project aimed to identify the most important cognition-related concerns patients and informants report early in the disease and determine how this information maps to what is assessed by several statistically derived composite measures.
Methods
Leveraging qualitative research completed by Critical Path Institute’s Patient-Reported Outcome Consortium, CAMD utilized a summary report that included frequency grids of reported concerns of amnestic mild cognitive impairment patients and their informants, as well as the narrative transcripts from focus groups. Transcripts were reviewed and analyzed to identify which cognitive domains the patient- and informant-reported concerns mapped onto. The results were then compared to see how well these cognitive domains were represented in various statistically derived composite measures.
Results
The patient- and informant-reported concerns primarily mapped to the cognitive domains of episodic memory and, secondarily, orientation and language. Depending on the specified composite, there were varying levels of alignment between their subcomponents and these cognitive domains.
Conclusion
Through secondary analyses of existing qualitative data, this study examined several statistically derived composite measures and found that they generally capture cognitive domains that reflect aspects of day-to-day functioning that patients and informants consider meaningful.
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Ropacki, M.T., Hannesdottir, K., Hendrix, S. et al. Clinically Meaningful Outcomes in Early Alzheimer Disease: A Consortia-Driven Approach to Identifying What Matters to Patients. Ther Innov Regul Sci 51, 380–390 (2017). https://doi.org/10.1177/2168479016689712
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DOI: https://doi.org/10.1177/2168479016689712