Abstract
Cognitive assessment with wordlist memory tests is a cost-effective and non-invasive method of identifying cognitive changes due to Alzheimer's disease and measuring clinical outcomes. However, with a rising need for more precise and granular measures of cognitive changes, especially in earlier or preclinical stages of Alzheimer's disease, traditional scoring methods have failed to provide adequate accuracy and information. Well-validated and widely adopted wordlist memory tests vary in many ways, including list length, number of learning trials, order of word presentation across trials, and inclusion of semantic categories, and these differences meaningfully impact cognition. While many simple scoring methods fail to account for the information that these features provide, extensive effort has been made to develop scoring methodologies, including the use of latent models that enable capture of this information for preclinical differentiation and prediction of cognitive changes. In this perspective article, we discuss prominent wordlist memory tests in use, their features, how different scoring methods fail or successfully capture the information these features provide, and recommendations for emerging cognitive models that optimally account for wordlist memory test features. Matching the use of such scoring methods to wordlist memory tests with appropriate features is key to obtaining precise measurement of subtle cognitive changes.
Highlights
Wordlist memory (WLM) tests are the most common measures of verbal episodic memory used in clinical and research settings [1, 2]
Alzheimer’s disease (AD) research has recently shifted its focus from mild cognitive impairment (MCI) and moderate AD stages toward asymptomatic or preclinical AD stages, in which the cognitive changes may be very subtle and difficult to measure [4]
A wide variety of WLM tests are in use, and each of them has a distinct set of features which impact the way that individuals learn and remember the words presented in them
Summary
Wordlist memory (WLM) tests are the most common measures of verbal episodic memory used in clinical and research settings [1, 2]. While the literature examining WLM cognitive processes shows the meaningfulness of these more sensitive measures of performance in detecting and predicting underlying memory deficits, many AD studies and clinical trials continue to use summary or memory composite scores with a set cutoff that may be disproportionally impacted by poor performance in one area [39,40,41] This approach dilutes a specific impairment or treatment response and leads to inefficiencies throughout a clinical trial, from screening failures to response failures that may lead to premature discontinuation of a valuable treatment, as was seen in recent AD clinical trials [16, 42]. Wang et al [44] developed ADCOMS, including the ADAS-Cog WLM test, and better measured clinical progression in AD and MCI than constituent tests These and other composite scoring methods have not consistently demonstrated the ability to distinguish preclinical AD from normal individuals [16]. Such a model that incorporates recognition item responses would be able to quantify individuals’ discriminability, and simultaneously model it with account of other cognitive processing parameters, when a WLM test includes recognition task data
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