Dementia is currently a global driver of health care costs, and with an ageing demographic, the disease burden of neurodegenerative disorders will increase exponentially in the future. The prevalence is estimated to double every two decades, reaching approximately 80 million affected patients worldwide in 2030 (1). In 2016, the global costs associated with dementia were 948 billion US dollars and are currently projected to increase to 2 trillion US dollars by 2030, corresponding to roughly 2% of the world’s total current gross domestic product (GDP) (2, 3)..
Dementia, or major neurocognitive disorder (MCD), is an umbrella term for neurodegenerative disorders typically characterized by memory dysfunction with Alzheimer’s disease (AD) constituting approximately 60% of all cases. Other common forms of dementia include vascular dementia, Lewy-Body dementia and Frontotemporal dementia. Modern diagnostic tools, such as various imaging modalities and cerebrospinal fluid biomarkers (4, 5), have improved our diagnostic accuracy substantially. These methods have also provided key insights into the pathological mechanisms associated with neurodegenerative and contributed to the development of concepts such as mild cognitive impairment (MCI) and “preclinical AD” (6, 7). Preclinical AD is defined by the presence of cerebral amyloid or tau pathology, identified by positron emission tomography (PET) imaging or cerebrospinal fluid (CSF) biomarkers, before the onset of clinical symptoms (8).
Nevertheless, assessment of cognitive functions, the primary clinical outcome of interest, still largely relies on analogue “pen and paper” based tests administered to patients by health care providers (9). Although some regional differences exist, two of the most known and used cognitive tests include the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) (10, 11). Both tests assess various cognitive domains, with some inter-test differences, including for example; orientation, memory, concentration, executive functions, language, and visuospatial abilities (9) with scores ranging from 0 to 30 points. MoCA, as compared to MMSE which is mostly focused on memory deficits, includes assessment of more cognitive domains thus increasing its diagnostic accuracy. Although optimal cut-off points vary somewhat between different studies, a score lower than 26 on MoCA and 24 on MMSE are considered indicative of dementia (12–15). MoCA has in a previous meta-analysis shown to have a sensitivity and specificity of 0.94 and 0.60 respectively, at a cut-off of 26 points (16). This indicates a good ability to detect dementia, but at the cost of a high amount of false positives. MMSE has, in a meta-analysis, demonstrated a sensitivity of 0.85 and specificity of 0.9 (14). However, MMSE has limited value in detecting MCI and prodromal AD patients from healthy controls (17). Albeit, in the setting of cognitive screening tests a trade-off between sensitivity and specificity is necessary and screening instruments should favor sensitivity over specificity.
Given the current scientific consensus that potential future disease-modifying drugs for AD need to be administered early on in the disease continuum, there is a clear need to develop accurate and widely available cognitive screening tests in order to facilitate early diagnosis of MCI patients in the future. In the European Union, there are currently approximately 20 million individuals over the age of 55 with MCI, most of whom have not undergone screening for cognitive impairment (18). A previous study investigating the treatment and diagnostic capacity of six European countries (France, Germany, Italy, Spain, Sweden, United Kingdom) estimated that over 1 million patients would progress from MCI to AD due to capacity constraints within current health care systems if a disease modifying treatment were to be available in 2020 (18). As such, digital cognitive screening instruments are likely to be a part of the diagnostic process in the future, especially when considering the advancement of digitalized health care in multiple facets of modern medicine (19).
Cognitive assessment instruments are available in different settings including clinic based and at home testing (20, 21). Current cognitive evaluation methods include both pen-and-paper screening tools, which is the conventional method administrated by a clinical neuropsychologist, and computerized cognitive tests (20, 21). Increasing advances in technology has led clinical trials to move away from the conventional methods and adopt validated digital cognitive tools that are sensitive to capturing cognitive changes in early prevention stages (20, 22). Computerized cognitive assessment tools offer several benefits over the traditional instruments, enabling recording of accuracy and speed of response precisely, minimizing floor and ceiling effects and eliminating the examiner bias by offering a standardized format (20–22). Computerized cognitive assessments may also generate potential time and cost savings as the test can be administrated by the patient or other healthcare professionals than neuropsychologist, as long as appropriate professional will be responsible for the test interpretation and diagnosis (20, 22). Thus, unmonitored digital tools provide practical advantages of reduced need for trained professionals, self-administration, automated test scoring and reporting and ease of repeat adjustments, which enable administration for large-scale screening (22, 23). On the other hand, cognitive assessment tools are typically administrated to elderly population who might lack familiarity with digital tools, which can negatively affect their performance (22, 24). However, the attitude and perception of patients using a computerized cognitive assessment have been investigated in the elderly population, and individuals expressed a growing acceptance of using computerized cognitive assessments and rated them as understandable, easy to use and more acceptable than pen and paper tests (20, 22). They also perceived them as having the potential to improve patient care quality and the relationship between the patient and clinician when human intervention is involved (20).
Currently, there are a number of computerized screening instruments available, and they are either a digital version of the existing standardized tests or new computerized tests and batteries for cognitive function assessment (25). The pen-and-paper version of the MoCA test was recently transformed to an electronic version (eMoCA) (24). eMoCA was tested on a group of adults to compare its performance to MoCA, and most of the subjects performed comparably (24). For the detection of MCI, eMoCA (24, 25) and CogState (26) showed promising psychometric properties (25). Computer test of Inoue (27), CogState (26) and CANS-MCI (28) showed a good sensitivity in detecting AD (25). Unlike the other computerized cognitive screening tools, Geras Solutions is a comprehensive tool that provides, besides the cognitive test, a medical history questionnaire that is administrated by the patient, and a symptom survey that is administrated by the patient’s relatives. Thus, it has the potential to save more time and cost compared to the other digital assessment instruments by providing a more complete clinical evaluation.
The primary objective of this study is to investigate the accuracy and validity of a newly developed digital cognitive test (Geras Solutions Cognitive Test [GSCT]). The GSCT is a self-administered cognitive screening test provided by Geras Solutions predominantly based on MoCA. In this study, we intend to investigate the validity of GSCT, including psychometric properties, agreement with MoCA and diagnostic accuracy by establishing sensitivity, specificity, receiver operating characteristics (ROC), area under the curve values (AUC) and optimal cut-off levels, as well as compare performance with MoCA.