A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme

Abstract

BACKGROUND: It is important to use outcome measures for novel interventions in Alzheimer’s disease (AD) that capture the research participants’ views of effectiveness. The electronic Person-Specific Outcome Measure (ePSOM) development programme is underpinned by the need to identify and detect change in early disease manifestations and the possibilities of incorporating artificial intelligence in outcome measures. Objectives: The aim of the ePSOM programme is to better understand what outcomes matter to patients in the AD population with a focus on those at the pre-dementia stages of disease. Ultimately, we aim to develop an app with robust psychometric properties to be used as a patient reported outcome measure in AD clinical trials. Design: We designed and ran a nationwide study (Aug 2019 – Nov 2019, UK), collecting primarily free text responses in five pre-defined domains. We collected self-reported clinical details and sociodemographic data to analyse responses by key variables whilst keeping the survey short (around 15 minutes). We used clustering and Natural Language Processing techniques to identify themes which matter most to individuals when developing new treatments for AD. Results: The study was completed by 5,808 respondents, yielding over 80,000 free text answers. The analysis resulted in 184 themes of importance. An analysis focusing on key demographics to explore how priorities differed by age, gender and education revealed that there are significant differences in what groups consider important about their brain health. Discussion: The ePSOM data has generated evidence on what matters to people when developing new treatments for AD that target secondary prevention and therein maintenance of brain health. These results will form the basis for an electronic outcome measure to be used in AD clinical research and clinical practice.

Impact of clinical symptoms and diagnosis: The electronic Person‐Specific Outcome Measure (ePSOM) development programme

“…We designed and ran a UK-wide population-based online study collecting primarily free text answers. The methods, the survey itself as well as the overall results are described in more detail elsewhere [4]. In brief, the ePSOM study ran from Aug 2019 to Dec 2019 and was divided into sections where respondents were asked to provide free text answers on what they would like to retain or keep being able to do if their brain health got worse.…”

“…We used Natural Language Processing (NLP) techniques to analyse the free text data. We considered it critical that respondents were not limited in predefined answers but had the ability to freely express anything that is relevant for them personally about their brain health within five domains [1], Everyday functioning [2]; Sense of Identity [3]; Relationships and Social Connections [4]; Enjoyable Activities and [5] Thinking problems.…”

“…The ePSOM programme seeks to develop an outcome measure that is considered clinically meaningful and has greatest utility in the pre-dementia stages of neurodegenerative disease. A key methodology of our programme was to use Natural Language Processing to allow analysis of a vast amount of free text data on what matters to individuals about their brain health [4]. This is the route that will allow unrestricted expression of treatment priorities by the individual using free written text (or speech) to define the outcome as opposed to a restricted choice which is characteristic of traditional functional and Quality of Life measures often used as proxies of 'clinically meaningful' .…”

“…This is the route that will allow unrestricted expression of treatment priorities by the individual using free written text (or speech) to define the outcome as opposed to a restricted choice which is characteristic of traditional functional and Quality of Life measures often used as proxies of 'clinically meaningful' . While our initial analyses provided evidence that individuals' priorities may vary significantly based on demographic differences [4], we now explore whether priorities may also vary based on where individuals are on the neurodegenerative disease spectrum.…”

Meaningful benefits: a framework to assess disease-modifying therapies in preclinical and early Alzheimer’s disease

“…Validated PROs are needed in AD trials and some are under development [ 46 , 49 , 50 ]. The Patient-Reported Outcome Consortium’s Cognition Working Group had led efforts to develop a novel, self-reported outcome measure in persons with MCI due to AD, emphasizing two functional domains: (1) complex activities of daily living (e.g., handling personal finances and meal preparation) and (2) interpersonal functioning (e.g., conversational skill or comprehension of written material) [ 49 ].…”