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EARLY DETECTION OF MILD COGNITIVE IMPAIRMENT (MCI) IN PRIMARY CARE

 

M.N. Sabbagh1, M. Boada2, S. Borson3, M. Chilukuri4, B. Dubois5, J. Ingram6, A. Iwata7, A.P. Porsteinsson8, K.L. Possin9, G.D. Rabinovici9, B. Vellas10, S. Chao11, A. Vergallo12, H. Hampel12

 

1. Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; 2. Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; and Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Spain; 3. University of Washington School of Medicine, Seattle, Washington, and Dementia Care Research and Consulting, Santa Ana, CA, USA; 4. Durham Family Medicine, Durham, North Carolina, USA; 5. Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Center of excellence of neurodegenerative disease (CoEN) and National Reference Center for Rare or Early Dementias Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l’hôpital, Paris, France; 6. Seniors Lead Physician, Central East Region, Ontario and Founder and Medical Director of Kawartha Centre, Peterborough, Ontario, Canada; 7. Department of Neurology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan; 8. Department of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA; 9. Memory & Aging Center, Departments of Neurology, Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA; 10.Gerontopole, Toulouse University Hospital, UMR 1027, University of Toulouse; 11. ClearView Healthcare Partners – Newton, MA, USA; 12. Global Medical Affairs, Neurology Business Group, Eisai Inc., Woodcliff Lake, New Jersey, USA

Corresponding Author: Marwan N. Sabbagh, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA, sabbagm@ccf.org; Tel.: (702) 483-6029; Fax: (702) 722-6584

J Prev Alz Dis 2020;3(7):165-170
Published online April 6, 2020, http://dx.doi.org/10.14283/jpad.2020.21

 


Abstract

Mild cognitive impairment (MCI) is significantly misdiagnosed in the primary care setting due to multi-dimensional frictions and barriers associated with evaluating individuals’ cognitive performance. To move toward large-scale cognitive screening, a global panel of clinicians and cognitive neuroscientists convened to elaborate on current challenges that hamper widespread cognitive performance assessment. This report summarizes a conceptual framework and provides guidance to clinical researchers and test developers and suppliers to inform ongoing refinement of cognitive evaluation. This perspective builds upon a previous article in this series, which outlined the rationale for and potentially against efforts to promote widespread detection of MCI. This working group acknowledges that cognitive screening by default is not recommended and proposes large-scale evaluation of individuals with a concern or interest in their cognitive performance. Such a strategy can increase the likelihood to timely and effective identification and management of MCI. The rising global incidence of AD demands innovation that will help alleviate the burden to healthcare systems when coupled with the potentially near-term approval of disease-modifying therapies. Additionally, we argue that adequate infrastructure, equipment, and resources urgently should be integrated in the primary care setting to optimize the patient journey and accommodate widespread cognitive evaluation.

Key words: Alzheimer’s disease, mild cognitive impairment, cognitive screening, disease-modifying.


 

Introduction

Mild Cognitive Impairment (MCI) is a syndrome defined by clinical, cognitive, and functional criteria and is characterized by an objective cognitive decline in one or more cognitive domains without any significant impairment in daily-life activities. MCI may be associated with a variety of underlying causes, including Alzheimer’s pathophysiology (1, 2).
Late-stage clinical development of drugs with a disease-modifying effect represents unprecedented hope for individuals suffering from Alzheimer’s disease (AD), particularly at preclinical or prodromal stages (i.e., MCI due to AD [MCI-AD]). In addition, the expanding knowledge on non-pharmacological approaches to cognitive decline (e.g., lifestyle-oriented treatments, non-invasive brain stimulation) suggests the possibility to treat secondary causes of MCI. This report represents the second part of a three-part consensus perspective on testing for MCI and is focused on the primary care setting. The suggestions and opinions within these publications represent the consensus opinion of a working group comprised of international experts on MCI and AD that was convened in April 2019 to discuss the challenges of detecting MCI at a large-scale and the potential solutions to overcoming these barriers.
Recommendations described here focus on improvements to MCI detection that may be feasible and ready for widespread use in the near-term (i.e., within approximately three years). The implementation of a system of healthcare delivery focused on dementia screening and large-scale cognitive screening is necessary to accommodate the global rising incidence of AD, and to prepare the public and healthcare providers for the availability of disease-modifying therapies for AD. Blood-based and biologic biomarkers are expected to play a key role in this paradigm shift. Indeed, blood-based biomarker panels are widely accessible, minimally invasive, and less time- and cost-consuming than cerebral spinal fluid (CSF) and neuroimaging assessments. To that end, we have outlined current barriers to the timely and accurate detection of MCI and MCI-AD, provided potential solutions, identified methods and emerging technologies to improve cognitive evaluation, and estimated potential timelines for accomplishing an optimal care pathway for managing MCI and MCI-AD at a large-scale.

 

Current landscape

Barriers Related to Physician Training and Support

The expert panel identified a wide range of barriers, including expertise, schedule, and available assessment tools, that often prevent primary care physicians (PCPs) from evaluating cognition.. The short duration of most primary care visits (frequently less than twenty minutes) represents one of the key logistical barriers to the establishment of cognitive evaluation in a primary care setting. The high prevalence of comorbidities among older adult individuals intensifies this challenge. Cognitive pathways require access to collateral informants, usually family members. Physicians may lack sufficient access to these collateral sources who are close enough to the individual to provide accurate longitudinal insight into his or her cognitive performance and functional abilities. Given these logistical barriers, PCPs may not consider assessing an individuals’ cognitive performance within the context of a standard appointment feasible.
Separate from logistical concerns, PCPs are also likely to encounter barriers around their comfort with cognitive assessment and/or motivation to assess cognition (3). Importantly, many PCPs have reported limited confidence in cognitive assessment. Training programs for Primary Care providers incorporate limited exposure to these skills. As a result, many PCPs are left feeling poorly equipped, inexperienced, or uncomfortable about monitoring cognitive performance (4, 5). In addition, if cognitive impairment is detected, PCPs may face uncertainty about what next steps to pursue (e.g., how to appropriately explain any test results, whether or not to refer to a specialist). Finally, PCPs likely face low motivation to evaluate an individual’s cognitive status, given uncertainty around whether or not identifying MCI provides a clear benefit to the individual. Without effective treatments for MCI, detecting MCI may be perceived only to be detrimental to individuals and their family members. While emergence of a novel disease-modifying therapy may ultimately address physician motivation, challenges to confidence and familiarity with cognitive assessment may require large-scale training efforts.

Barriers Related to Healthcare Systems

Barriers associated with healthcare systems also significantly limit widespread early detection of MCI, as exploring all cognitive domains and quantifying overall cognitive performance is currently a time-consuming process. In the context of an individual physician’s office, current medical practice can limit the use of MCI in many different ways. Poor integration of cognitive assessments with EMR systems creates a significant administrative burden, as substantial clerical work is needed to document the output of a cognitive performance assessment. In addition, lack of proper integration with the EMR system also limits the ability to track an individual’s cognition over time, which in turn limits the utility of cognitive evaluation. In some circumstances, testing tools are poorly designed and/or unintuitive for users.
This increases system burden due to cost (e.g. administration time, training, clerical burden etc.), which decreases the frequency of cognitive performance assessment. On the macro scale, inadequate reimbursement of costs associated with assessing cognitive function and providing post-diagnostic care, including physician time, significantly decreases the incentive for wide adoption of MCI detection. Consistent, reliable reimbursement of comprehensive assessment and cognitive testing by payers is therefore required to support extensive evaluation of cognition in the primary care setting.

Barriers Related to Test Design and Validation

The limited length of time of the average PCP visit requires tests to be conducted in 10 minutes or less. This constraint introduces a major limitation, as cognition is multifaceted, and many different cognitive domains can be impacted by MCI. Testing all domains of cognition in a short test is likely not feasible, so tools must strike a proper balance between time and depth of testing to maximize their utility.
Additionally, many cognitive tests have demonstrated limited value when deployed in a heterogeneous patient population. This limitation results from initial development and validation with highly homogeneous populations in mind – specifically, highly-educated English-speakers. Effective tests must be usable in a broader community that includes individuals across multiple levels of educational attainment, various races and ethnicities, and multiple languages (including varying familiarity with English). Validation in homogeneous populations can lead to the development and use of tools that are significantly less accurate than expected when used in a diverse patient population; for example, a patient with fewer years of education may score artificially low on a screening tool developed and validated in college graduates. Many tests also lack validation in multiple languages, which prevents standardization across communities and countries.

Barriers Related to MCI

Early detection of MCI is also inherently challenging due to barriers associated with the disease itself. Symptoms related to the initial onset of MCI can vary significantly between individuals, depending on etiology, cognitive reserve, and variable demands of day-to-day living, among other factors. Additionally, MCI can be less relevant than other medical comorbidities, contributing to a different medical prioritization ahead of monitoring cognition. Furthermore, care partners and patients are likely to be particularly sensitive about cognitive performance in comparison to other health concerns. Patient concerns may result in a scenario where a physician is hesitant to discuss the cognitive performance assessment or the implications these have on other skills (such driving) with patients due to concern about compromising the physician-patient relationship. Similarly, individuals may actively avoid discussing cognitive performance with their physician due to concerns about the implications of cognitive assessment and/or perceived stigma associated with cognitive impairment. All of these issues can limit the utility of even clinically useful tests due to lack of use and compliance.

 

Parameters of an ideal tool

To help guide the refinement of existing cognitive performance evaluations or development of novel tools, we have outlined the parameters of an “ideal” MCI detection tool. This guidance is intended to offer potential solutions to the barriers currently facing MCI detection. While this working group does not recognize a single assessment that meets all of these criteria, multiple cognitive performance assessments include components of an “ideal” tool, suggesting that these promising tools may approach the “ideal” profile with minor refinement and/or additional validation.

Test Methodology

Similar to previous recommendations (6), this panel agreed that a tool for the detection of MCI would ideally incorporate three critical components: cognitive assessment, functional questionnaires, and clinical history-taking. First, cognitive assessment refers to directly assessing cognitive function through objectively evaluated tasks, such as a word recall task, clock-drawing task, etc. To meet the criteria for defining MCI versus dementia, a cognitive tool should also encompass multiple cognitive domains; our working group recommends that, at minimum, memory and executive function be assessed. Ideally, measures of visuospatial and language skills would also be included. Many currently-available cognitive tests encompass multiple cognitive domains, including Cognigram (offered by CogState) (7), CogniSense (offered by Quest Diagnostics) (8), and CANS-MCI (offered by Screen Inc.) (9). Emerging computer-based neuropsychological approaches may also be considered. The Toronto Cognitive Assessment (TorCA) is an example of a computer-based platform integrated across multiple sites, providing consistent analysis and interpretation (10).
Second, functional questionnaires refer to tools that ask the individual or a family member about activities of daily living, which by definition must be returned to diagnose MCI but must be impacted by cognitive challenges to permit the diagnosis of dementia (e.g., ability to carry out financial tasks, driving, shopping). A long-standing example is the Functional Activities Questionnaire (FAQ), a 10-question form with questions around ability to go shopping or prepare a meal (11).
Third, clinical history-taking aims to identify comorbidities and their impact on function and to understand whether the individual himself or a family member has noticed a change in cognitive function over time. Questionnaires such as the AD8 or IQCODE can be utilized to facilitate clinical history-taking (12–14).
Importantly, clinical history-taking will help identify individuals with MCI but may also help identify individuals with subjective cognitive decline (SCD), which is often a precursor to MCI and can be considered a preclinical phase of AD (15, 16). An ideal cognitive assessment would encompass all three of these components; notably, a single questionnaire could incorporate both a functional component as well as questions for clinical history taking. An ideal tool would include a core assessment based on assessment of the individual him/herself, with an optional module that could incorporate feedback from a family member when possible. Furthermore, an ideal tool would allow the family member to complete a survey remotely (e.g., through an online form linked to the assessment). A tool that incorporates these components and features is likely to achieve compelling accuracy, even in individuals with subtle cognitive decline.

Logistics

The working group recommends several logistical characteristics that may optimize ease of use and minimize the time burden associated with detection of MCI. Tests should 1) be administered digitally on a laptop, tablet, or smartphone to facilitate widespread use and allow testing to scale, 2) require less than ten minutes, 3) not require a physician (i.e., should be self-administered or conducted by a technician or nurse). Upon completion, the assessment should automatically create a report that outlines next steps in care specific to each healthcare system and/or region. The automated report should be integrated with EMR systems and should be available to the PCP instantly so that they can easily discuss the results with the individual at the beginning of the patient visit. The cost of administering a test also can be a significant logistical consideration. While this panel recognizes that a highly accurate, validated, and well-designed test will command a higher price than other options, an “ideal” assessment would be offered at a low price point and/or would be reimbursed by payers to maximize access and use of the assessment. Multiple currently available tools align with one or more of these criteria given the recent increase in creation of digitally administered tests. CogniSense, offered by Quest Diagnostics, meets the above mentioned criteria and can be automatically integrated into EMR (17). This panel recommends that creators of assessment tools seek to incorporate features that will optimize functionality and minimize administrative burden associated with detection of MCI.

Validation

An ideal tool would be validated in a diverse population (i.e., varied cultural and educational backgrounds) and validated (not merely translated) in multiple languages. Validating studies should be conducted in populations representative of the distribution of mild cognitive impairment, dementia, and normal cognition in a primary care setting, not in populations enriched for subjects with cognitive impairment. Recently, creators of the Brain Health Assessment (BHA; developed at UCSF) utilized this approach to validate the accuracy of the BHA in a clinically-representative patient population (~55% healthy controls, ~30% MCI individuals, ~10% dementia patients, and ~5% with subjective cognitive concerns) [18]. If a tool is to be utilized broadly in a primary care setting, moderate specificity may be acceptable, given that additional downstream assessment will occur.
High sensitivity will ensure that a high proportion of suitable individuals receives follow-up assessment. The members of this working group acknowledge that validation of a cognitive performance assessment can be challenging. In the absence of an accepted “gold standard” test (or set of tests), multiple tests may be considered suitable. This working group recommends that novel tests continue to be validated in comparison to diagnosis based on a detailed clinical examination supported by multiple long-standing assessment tools.

 

Optimal care pathway

In light of these barriers to MCI detection, the expert panel agreed that it will be necessary to clarify the “optimal care pathway” for the detection of early cognitive impairment. While further work will be needed to understand how cognitive performance assessments can best be integrated across healthcare systems, this panel discussed select characteristics of an “ideal” care pathway. First, given the enduring uncertainty around whether universal screening is beneficial, this group recognized that the most valuable early detection pathway would begin with individuals who already have a cognitive performance concern (initiated either by the individual themselves, a family member, or the healthcare provider) or individuals who actively opt-in to cognitive assessment. Indeed, it is likely that individuals with a concern about their own cognitive performance are most likely to benefit from cognitive assessment given that subjective memory complaint (i.e., a self-reported loss of memory performance without objective cognitive decline) represents a condition at-risk for developing MCI in general. Moreover, SCD may underlie the beginning of the AD clinical continuum (1, 19, 20). Therefore, large-scale cognitive screening may also involve subjects with SCD in light of initiating therapeutic interventions targeting preclinical AD. The assessment of the SCD condition starts from a self-reported dysfunction and requires an assessment of the whole cognitive battery test employed for investigating if an objective cognitive decline exists (and per definition as to be negative). Therefore, the screening of potential preclinical stages of AD would be included in the same protocol to identify MCI.
Individuals identified with MCI then must be efficiently and thoroughly evaluated and guided toward appropriate next steps. We discussed two potential pathways: in one pathway, individuals undergo a brief cognitive assessment in parallel with a standard primary care appointment (e.g., a Medicare Annual Wellness Visit in the U.S. or MINT Clinic in Canada). In a second pathway, the individual may schedule a separate optional cognitive assessment appointment with their physician. In both pathways, the brief cognitive assessment should be either self-administered or administered by trained medical personnel (potentially a medical technician or nurse).
In some medical systems, creation of embedded nursing personnel trained to carry out cognitive evaluations on an as-needed basis have been well received. Creation of primary care clinicians with special training and expertise in this area, coupled with specific memory teams in primary care, has received wide-spread endorsement (https://www.hqontario.ca/Quality-Improvement/Quality-Improvement-in-Action/ARTIC/ARTIC-Projects/Primary-Care-Collaborative-Memory-Clinics). System-based changes in healthcare delivery are required to achieve the desired impact. Ultimately, individual choice of cognitive screening tools should decrease as pathways, including assessments, aligned with prior parameters become operationalized.
Importantly, an optimal care pathway must effectively support individuals and their caregivers following the cognitive assessment. After the assessment, the physician must allow sufficient time to help the individual understand the results and to provide guidance on next steps. Depending on the healthcare system and the capabilities of each primary care practice, this pathway may include further assessment in the primary care office, referral to a specialist, or simple monitoring of cognitively intact individuals to potentially detect a decline in subsequent years. To ensure maximal compliance with testing practices, we recommend that the next steps be clearly outlined by each healthcare system, in EMR systems, and/or by evaluative tools themselves.

 

Potential Future Blood-based Testing

If blood-based biomarkers become available earlier than anticipated, this is expected to significantly accelerate the diagnosis of AD and improve global accessibility of diagnostic tools. However, despite the promise of blood-based testing, our panel agreed that cognitive performance assessments will remain critical for distinguishing MCI and MCI-AD in the future, even after blood-based biomarkers are implemented into primary care practice. Cognitive testing and functional evaluation will remain necessary to understand the individual’s current cognitive performance, monitor changes in cognitive function, and identify cognitive changes not associated with a distinct biological signature (e.g., secondary causes of MCI).
Blood-based biomarkers are expected to facilitate critical clinical solutions catalyzed by the global threat of the evolving AD epidemic. The negative predictive value of blood-based biomarkers will support early screening and identification of individuals with a very low probability of developing AD-related pathophysiology and increase the probability that individuals with AD pathophysiology are being selected for further investigation by using more specific, expensive, and/or more invasive methods with reduced accessibility (e.g., PET imaging or CSF assessment). Blood-based biomarkers have excellent potential to be routinely and rapidly assessed in all healthcare settings and in asymptomatic individuals due to minimal invasiveness, cost-efficiency, accessibility (i.e., blood can even be withdrawn in an individual’s home), and reduced time and resource utilization compared with neuroimaging- and CSF-based techniques used for AD.
Indeed, growing optimism exists regarding blood-based biomarkers reflecting distinctive AD pathophysiological mechanisms, supported by increasing evidence that core biomarkers and proteins associated with inflammatory and neurodegenerative pathways can be detected in blood (21, 22). While the sensitivity of conventional immunoassays may be insufficient to detect changes in the blood in individuals with MCI and MCI-AD, promising assays using novel technologies are in development. Multiplex digital ELISA platforms (e.g., Quanterix® Simoa®) have been used by multiple groups to distinguish MCI and MCI-AD using blood levels of various proteins, including neurofilaments, Aβ, and tau (23–25). Another approach that has improved sensitivity of immunoassays is immunomagnetic reduction (IMR) via the use of superconducting quantum interference devices (SQUIDs). In one study, use of an IMR-SQUID assay combining analysis of Aβ42 and tau, enabled detection of AD with an AUC of 0.98 (26). Promising results also have been achieved in the academic setting using mass spectrometry. Multiple publications have distinguished between AD, MCI, and normal controls using ratios of Aβ and APP isoforms (27), or by using composite protein profiles detected via mass spectrometry (28). While further research is needed, development of an accurate, cost-effective, scalable blood-based biomarker for cognitive decline will shift the clinical paradigm dramatically, increasing diagnostic confidence and comfort of physicians, and integrating the novel biomarker test into the diagnostic paradigm will be critical.

 

Discussion

As outlined above and in the first article of this series, anticipated societal and medical changes (e.g., aging populations and potential advancements in management of MCI, respectively) will necessitate a significant improvement in the early detection of MCI. As PCP’s are the initial point of contact, especially for stoutly progressive chronic illness with subtle initial presentations, the PCP is likely the central player in initial identification and management of MCI. Importantly, PCPs are often inadequately supported to allow widespread evaluation of cognitive and functional performance, and cognitive assessment tools themselves are not optimally designed to support widespread use in the primary care setting. While tools evolve, health care developments and spending should focus on improving training on identification and management of MCI at the PCP’s office. Care pathways and staffing at the primary care physician’s office to support PCP management of cognition are needed (e.g., ensuring visits are long enough to allow for a cognitive evaluation). A critical need exists to refine cognitive performance assessments and to validate tools in diverse, representative populations, ideally in multiple languages. Test makers should also be aware of the barriers that limit early detection of MCI, including barriers associated with the primary care setting and with broader healthcare systems, so that tests can be designed to counteract or limit these barriers
This working group recommends that key stakeholders representing PCPs, regulatory stakeholders, test makers, and patient advocates collectively take action to improve the use and quality of tests for the detection of MCI. In the next and final article of this series, we shall explore the role and value of direct-to-consumer cognitive testing options.

 

Acknowledgements and funding: Medical writing support, under the direction of the authors, was provided by ClearView Healthcare Partners, LLC, funded by Eisai Inc., in accordance with Good Publication Practice (GPP3) guidelines.

Disclosures: MB is affiliated with the Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; and with the Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Spain. Private research funding sources include Grifols SA; Caixabank S.A.; Life Molecular Imaging; Araclon Biotech; Laboratorios Echevarne; Festival Castell Paralada; Bonpreu/Esclat; and Famila Carbó. Public grants include those from Instituto de Salud Carlos III. Ministerio de Salud. Gobierno de España; Dirección General de Farmacia. Ministerio de Salud. Gobierno de España; and European Commission:H2020 program, Innovative Medicine Initiative (IMI-2); and ERA-NET NEURON program, European Marie Sklodowska Curie. Advisory work includes that for Araclon Biotech, Biogen, Bioibérica, Eisai, Grifols, Lilly, Merck, Nutricia, Roche, Oryzon, Schwabe Farma, Servier, and Kyowa Kirin. BD is affiliated with the Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Salpêtrière Hospital, AP-HP, Sorbonne-Université, Paris, France. JI is affiliated as an Assistant Professor-Adjunct (Group1) with the Department of Family Practice at Queen’s University. She was also a panelist for Hoffman-La Roche Limited, Ottawa, on an Alzheimer’s Disease Panel. She is involved with the Canadian Consortium on Neurodegeneration in Aging (CCNA), Extension Study as a Co- Investigator and Research Coordinator. AI received lecture fees from Eisai, Janssen, Otsuka, Eli Lilly, MSD, Chugai-Roche, Daiichi-Sankyo, Alnylam, Takeda, UCB, Ono, Integra Japan, IQVIA, Fuji Rebio, Biogen, and advisory fees from Janssen during the past three years. AP reports personal fees from Acadia Pharmaceuticals, Functional Neuromodulation, Neurim Pharmaceuticals, Grifols, Eisai, BioXcel, Tetra Discovery Partners, and Merck; grants from AstraZeneca, Avanir, Biogen, Biohaven, Eisai, Eli Lilly, Janssen, Genentech/Roche, Novartis, Merck, as well as funding from NIA, NIMH, DOD. KLP receives grant funding from the National Institute on Aging, the National Institute of Neurological Disorders and Stroke, the Global Brain Health Institute, and Quest Diagnostics. BV has consultancy and research grants from Roche, Biogen, EISAI, Nestle, Lilly, Cerecin, and Merck. HH is an employee of Eisai Inc. and serves as Senior Associate Editor for the Journal Alzheimer’s & Dementia; during the past three years he had received lecture fees from Servier, Biogen and Roche, research grants from Pfizer, Avid, and MSD Avenir (paid to the institution), travel funding from Eisai, Functional Neuromodulation, Axovant, Eli Lilly and company, Takeda and Zinfandel, GE-Healthcare and Oryzon Genomics, consultancy fees from Qynapse, Jung Diagnostics, Cytox Ltd., Axovant, Anavex, Takeda and Zinfandel, GE Healthcare, Oryzon Genomics, and Functional Neuromodulation, and participated in scientific advisory boards of Functional Neuromodulation, Axovant, Eisai, Eli Lilly and company, Cytox Ltd., GE Healthcare, Takeda and Zinfandel, Oryzon Genomics and Roche Diagnostics. He is co-inventor in the following patents as a scientific expert and has received no royalties: • In Vitro Multiparameter Determination Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Patent Number: 8916388; • In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Patent Number: 8298784; • Neurodegenerative Markers for Psychiatric Conditions Publication Number: 20120196300; • In Vitro Multiparameter Determination Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number: 20100062463; • In Vitro Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number: 20100035286; • In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Publication Number: 20090263822; • In Vitro Method for The Diagnosis of Neurodegenerative Diseases Patent Number: 7547553; • CSF Diagnostic in Vitro Method for Diagnosis of Dementias and Neuroinflammatory Diseases Publication Number: 20080206797; • In Vitro Method for The Diagnosis of Neurodegenerative Diseases Publication Number: 20080199966; • Neurodegenerative Markers for Psychiatric Conditions Publication Number: 20080131921. AV is an employee of Eisai Inc. and received lecture honoraria from Roche, MagQu LLC, and Servier.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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RATIONALE FOR EARLY DIAGNOSIS OF MILD COGNITIVE IMPAIRMENT (MCI) SUPPORTED BY EMERGING DIGITAL TECHNOLOGIES

 

M.N. Sabbagh1, M. Boada2, S. Borson3, M. Chilukuri4, P.M. Doraiswamy5, B. Dubois6, J. Ingram7, A. Iwata8, A.P. Porsteinsson9, K.L. Possin10, G.D. Rabinovici10, B. Vellas11, S. Chao12, A. Vergallo13, H. Hampel13

 

1. Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; 2. Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; and Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Spain; 3. University of Washington School of Medicine, Seattle, Washington, and Dementia Care Research and Consulting, Santa Ana, CA, USA; 4. Durham Family Medicine, Durham, North Carolina, USA; 5. Departments of Psychiatry and Medicine, Duke University School of Medicine, USA; 6. Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Center of excellence of neurodegenerative disease (CoEN) and National Reference Center for Rare or Early Dementias Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l’hôpital, Paris, France; 7. Seniors Lead Physician, Central East Region, Ontario and Founder and Medical Director of Kawartha Centre, Peterborough, Ontario, Canada; 8. Department of Neurology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan; 9. Department of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA; 10. Memory & Aging Center, Departments of Neurology, Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA; 11. Gerontopole, Toulouse University Hospital, UMR 1027, University of Toulouse, France; 12. ClearView Healthcare Partners – Newton, MA, USA; 13. Global Medical Affairs, Neurology Business Group, Eisai Inc., Woodcliff Lake, New Jersey, USA

Corresponding Author: Marwan N. Sabbagh, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA, sabbagm@ccf.org; Tel.: (702) 483-6029; Fax: (702) 722-6584

J Prev Alz Dis 2020;3(7):158-164
Published online March 6, 2020, http://dx.doi.org/10.14283/jpad.2020.19

 


Abstract

Disease-modifying pharmacotherapies for Alzheimer’s Disease (AD) are currently in late-stage clinical development; once approved, new healthcare infrastructures and services, including primary healthcare, will be necessary to accommodate a huge demand for early and large-scale detection of AD. The increasing global accessibility of digital consumer electronics has opened up new prospects for early diagnosis and management of mild cognitive impairment (MCI) with particular regard to AD. This new wave of innovation has spurred research in both academia and industry, aimed at developing and validating a new “digital generation” of tools for the assessment of the cognitive performance. In light of this paradigm shift, an international working group (the Global Advisory Group on Future MCI Care Pathways) convened to elaborate on how digital tools may be optimally integrated in screening-diagnostic pathways of AD The working group developed consensus perspectives on new algorithms for large-scale screening, detection, and diagnosis of individuals with MCI within primary medical care delivery. In addition, the expert panel addressed operational aspects concerning the implementation of unsupervised at-home testing of cognitive performance. The ultimate intent of the working group’s consensus perspectives is to provide guidance to developers of cognitive tests and tools to facilitate the transition toward globally accessible cognitive screening aimed at the early detection, diagnosis, and management of MCI due to AD.

Key words: Alzheimer’s disease, mild cognitive impairment, cognitive screening, disease modifying, digital, healthcare.


 

Introduction

The late-stage clinical development and potential near-approval of drugs with modifying effectd on Alzheimer’s disease (AD) calls for a substantial paradigm shift in the diagnosis and management of the disease, including the Mild Cognitive Impairment (MCI) stage (also called MCI due to AD or prodromal AD). The availability of disease-modifying therapies will result in unprecedented demand for cognitive performance assessments (i.e., large-scale cognitive screening). Moreover, the progressive rise of lifespan in populous developed countries such as the U.S., EU5, China, and Japan (1, 2) will bring about an exponential increase in the incidence of age-related diseases, including AD,. It is expected that widespread demand for cognitive evaluation will likely overwhelm existing healthcare infrastructures and services at both primary care and specialist levels.
Early detection, of MCI or preclinical AD stages, coupled with timely initiation of disease-modifying treatments,has become the clear path to successfully facing the social and medical threat of AD. Gaps on both sides,particularly a paucity of detection tools suitable for practical use in patient populations and the absence of approved disease-modifying therapies, impede progress toward finding effective therapeutics. We focus here on MCI, a syndrome defined by clinical, cognitive, and functional criteria and characterized by objective cognitive decline in one or more cognitive domains with no significant impairment in daily-life activities (3). MCI may result from a variety of underlying causes, including Alzheimer’s pathophysiology (4, 5). As a result, watchful monitoring of adults with MCI is a crucial step within the work-up for early identification of AD and will be a critical stage of treatment monitoring as novel disease-modifying AD therapies enter the marketplace. In this publication series, we use the term “MCI” to refer to non-dementia cognitive impairment due to any cause and the terms “MCI due to AD” or “MCI-AD” to refer specifically to MCI associated with positive biomarkers of AD pathophysiology, as established in current research diagnostic criteria (3-5).
If disease modifying-therapies enter clinical practice, several issues must be overcome to achieve large-scale cognitive and biological screening of AD.
First, MCI is heterogeneous in its clinical spectrum and has historically been challenging to define, identify, and monitor in clinical practice. In addition, the currently qualified biomarkers for AD are assessed through invasive, expensive, and time- and resource-consuming investigations such as cerebrospinal fluid (CSF) analysis and positron-emission tomography (PET) imaging. The progressive establishment of blood-based biomarkers (6) and the validation of multi-dimensional diagnostic techniques have the potential to make the diagnosis and management of MCI-AD feasible in primary care, as is necessary for early screening and detection.
Primary care physicians (PCPs) currently lack technical support, infrastructure, training, and experience to efficiently detect and manage AD along its clinical continuum, from preclinical phases to MCI and dementia. A 2019 survey conducted among U.S. PCPs reported that short cognitive evaluations are assessed in only half of individuals 65 years of age and older and that cognitive evaluations are frequently omitted due to: i) subtle cognitive impairment, ii) lack of time, and iii) patient resistance to testing (7). In a parallel patient survey, only 16% of Americans aged 65 years and older reported receiving regular cognitive assessments during routine health visits (7). Less than half of older adults report ever having discussed their cognitive performance with a physician, and less than a third have ever been assessed for cognitive impairment. Additionally, a majority of surveyed PCPs reported uncertainty around which cognitive assessment to deploy, how to perform a brief cognitive assessment, and, importantly, what to do after assessing cognition [7]. Referral to specialists (e.g., neurologists, psychiatrists, geriatricians, and neuropsychologists) is the default for evaluating cognition and diagnosing MCI-AD. However, with the expected AD (and other neurodegenerative disease) epidemic burden, access to specialists has been and will become even more challenging. PCPs will need to be fully involved in the process and equipped with the proper means to ensure timely and efficient detection and care.
In recognition of current challenges around the detection of MCI, a working group composed of international experts on MCI and AD convened in April 2019 to elaborate on existing frictions and barriers, in both clinical and non-clinical settings, that prevent widespread cognitive screening for early detection of MCI and particularly MCI-AD. We summarize potential solutions to overcoming those barriers in a series of three manuscripts, of which this is the first. The first manuscript focuses on advantages and disadvantages of early detection of MCI, the current MCI detection landscape, and data-driven hypothetical models on how MCI-AD diagnosis and management may change in the future given recent technological advances and potential approval of disease-modifying therapies. In the second manuscript of this series, we offer recommendations around ways to meaningfully and rapidly implement MCI detection in primary care settings. The third manuscript of this series will focus on the potential for direct-to-consumer cognitive testing intended for use by adults or informants in an at-home setting without direct supervision by a healthcare provider. Given the critical importance of these topics, the recommendations outlined across this suite of manuscripts reflect careful consideration by this group of cognitive neuroscientists and physicians and extensive iteration and discussion from April 2019 through the present.
From the outset of this endeavor, the primary objective of this working group has been to identify actionable methods to improve detection of MCI, thereby providing developers and researchers of novel tools and tests with guidance and tangible recommendations to maximize their potential usability. To that end, the group agreed that the most feasible strategy to optimize early detection of MCI in the near-term will be to boost primary care capacity for detection by providing infrastructure and equipment that improve the accuracy and efficiency of tools for cognitive assessment without substantially increasing workload for primary care clinicians. Recommendations and strategies to facilitate this paradigm shift are described in detail in the second manuscript of this series.
Our group recognized that detection tools intended for use outside of clinical settings present unique challenges, yet they deserve critical future development, because they offer the potential to dramatically improve the scale of MCI detection. With dramatic increases in the use of consumer electronics by aging adults, digital approaches that leverage the capacities of mobile devices and Internet connectivity are a promising avenue for detection of MCI in non-clinical settings, if these consumer-directed resources can be suitably validated and linked to healthcare systems. The third manuscript in this series summarizes the challenges and opportunities relating to the detection of MCI in non-clinical settings, i.e., at an individual’s home or in everyday settings such as pharmacies or community screening events, as has already been accomplished with brief paper and pencil tests (8, 9).
In this initial manuscript, we summarize existing guidelines and consensus statements to provide context around this set of recommendations. We also weigh the advantages and disadvantages of early detection of MCI, and we ultimately support the idea that detection of MCI is an important component of whole person care. Finally, we summarize our expectations of how the MCI detection landscape may continue to shift in the next 3 – 5 years to highlight the need for proactive changes and ongoing research and development.

 

Advantages and drawbacks of MCI detection

Consistent with previous guidelines and consensus statements (10), this panel recognized that early detection of MCI is associated with both advantages and disadvantages, and we acknowledge that the decision to assess an individual’s cognitive function should be made on a case-by-case basis with each individual’s best interests in mind. To support large-scale cognitive screening, the field would requirea clinical consensus on the appropriate course of action for PCPs when an individual is identified as cognitively impaired. Additionally, large-scale cognitive screening algorithms were acknowledged as unlikely to become standard practice in the near-term, given the infrastructural challenges inherent to existing healthcare systems around the world. In this context, we have summarized the most critical benefits and drawbacks of early detection of MCI identified by this working group.

Benefits of Early Detection of MCI

If disease-modifying therapies for delaying or even halting AD at its MCI stage (also called prodromal stage) become available, the necessity of detecting MCI accurately, extensively, and in a timely manner is obvious. Moreover, the inability to robustly identify patients at prodromal stages remains a substantial limitation for developing AD therapies and may, at least in part, contribute to the series of drug failures. Accordingly, early MCI detection may optimize identification of patients eligible for future clinical trials and maximize the likelihood of successfully developing novel AD therapies.
However, even in the absence of a disease-modifying therapy, and regardless of the underlying etiology, multiple advantages remain associated with early detection of MCI. Individuals and healthcare systems can only benefit from an efficient algorithm for investigating MCI at a large-scale.
An early identification of MCI also increases the possibility of a timely diagnosis of the medical condition that may underlie a cognitive impairment (i.e., secondary cause of MCI), which are all potentially treatable or even reversible (e.g., metabolic and endocrine diseases, mood and sleep disorders, iatrogenicity) (11). In addition, growing evidence demonstrates that specific lifestyle habits and activities may slow down or even prevent cognitive decline. Early detection of MCI may provide subjects with greater motivation to implement lifestyle modifications and, at a minimum, will provide physicians with an additional opportunity to counsel individuals on lifestyle changes. In the current screening and diagnostic paradigm, the identification of MCI is likely to escape the therapeutic window where individuals may benefit from these non-pharmacological interventions to slow cognitive decline. Early identification of cognitive impairment also can help individuals and their families better prepare for future care needs and address financial planning considerations, for example. In the absence of a disease-modifying therapy in the immediate future, early detection also can identify potential candidates for research and clinical trials for therapies in development that target individuals in the earlier stages of their cognitive decline and disease.
Emerging evidence also suggests that early detection of MCI may provide an economic benefit to healthcare systems. Although this has been investigated less extensively in individuals with MCI than in individuals with dementia, published literature suggests that the financial burden associated with caring for MCI patients is significant and that routine cognitive assessment may be cost effective (12-16). Tong et al. investigated screening for MCI and dementia by PCPs in England and reported that PCP use of the Mini-Mental State Examination (MMSE), 6-Item Cognitive Impairment Test and the General Practitioner Assessment of Cognition (GPCOG) led to more quality-adjusted life-years (QALYs) than informal PCP assessment alone (i.e., observing individual cognitive ability) (12). While additional research is needed to further understand the economic benefits of early detection of MCI, existing literature suggests that healthcare systems may derive significant benefits from implementing early detection practices.

Drawbacks of Early Detection of MCI

While early detection of MCI offers many positive benefits, even in the absence of a disease-modifying therapy, we acknowledge that early detection efforts may not be universally beneficial. For example, false negatives may provide subjects with false reassurance that their cognitive function has not declined, thereby preventing them from seeking further care. Similarly, false positives may create undue stress for impacted individuals and their families. These potential drawbacks underscore the urgent need for an accurate assessment, with sensitivity and specificity sufficient to minimize the detrimental impact of an incorrect result. In the context of an accurate identification, MCI individuals and their families likely will experience distress upon learning of cognitive impairment. Anecdotally, this panel noted that MCI individuals might react to this distress by distancing themselves from their physician and/or the healthcare system in response to the societal stigma that exists for individuals with a known cognitive impairment.
Importantly, implementing widespread evaluation of MCI in the primary care setting may require significant time and resources, representing a burden that may be untenable for all PCPs. Similarly, as routine wellness exams tend to last fewer than twenty minutes, devoting time to cognitive assessment may limit time spent addressing other health concerns. Limited time in PCP visits is likely to be a particularly pressing issue for the care of geriatric individuals, who are more likely to have cognitive performance issues but also often have more morbidities and preventative health needs that must be addressed during PCP visits. Additionally, expanding cognitive testing may create an administrative burden for medical personnel, although a digital tool can help minimize this impact. Finally, widespread cognitive assessment is likely to increase the burden on specialists, as greater identification of primary care patients with MCI likely will translate to more referrals to specialists for confirmatory diagnosis. However, if the quality of cognitive assessment in a primary care setting can be improved, this may help identify patients in whom a referral is appropriate, limiting referrals for patients with only a subjective memory complaint (i.e., a self-reported loss of memory performance without objective cognitive decline). Subjective memory complaint (SMC) represents a condition at-risk for AD (5, 17-21). Moreover, SMC may underlie the beginning of the AD clinical continuum (5, 17-21), Therefore, it will be even more imperative to provide physicians with the proper tools for timely detection of AD to allow initiation of appropriate care pathways.

 

Summary of previous guidelines and consensus statements

Numerous consensus statements and clinical guidelines have been published in the past to provide perspective and expert guidance on defining and detecting MCI through cognitive testing (3, 22). Previous guidelines have summarized the circumstances when cognitive testing becomes appropriate, examined the current testing landscape for MCI detection, and identified the challenges and uncertainties around the detection of MCI. However, an expert consensus with an updated view on the field of cognitive neuroscience in light of novel testing modalities that are now practical due to consumer digital technology, such as smartphone applications, online games and questionnaires, etc., does not currently exist in the literature. Increasing adoption of consumer digital technology and digital fluency, even among older adults, will allow for novel testing modalities that will improve whole patient care and pave the way for potential novel therapies for AD.
A controversy remains in the field of cognitive neuroscience on the appropriate frequency of cognitive testing, as advocates see the benefit of widespread use, while others are proponents of limited and targeted use of cognitive testing. In the U.S., the 2009 Affordable Care Act (ACA) federal legislature mandated an annual cognitive assessment to be conducted during Medicare Annual Wellness visits for seniors (7, 23). However, the ACA did not mandate or provide any guidance on what type of testing should be used to meet the ACA requirements, leaving this decision to the discretion of the clinical community. In the wake of the ACA mandate, the controversy on the appropriateness of cognitive testing has continued. In 2014, the United States Preventive Services Task Force concluded that the available evidence was insufficient to assess the benefits (e.g., potential lifestyle interventions and better patient management) and drawbacks of screening for cognitive impairment (e.g., false positives and negatives, patient suspicion and alienation from physicians, etc.) and therefore, could not recommend universal screening (24). However, due to the ACA mandate, there was still a clear need for a consensus from the field on best practices for the development, validation, and use of cognitive testing. This view has been validated by the National Institute on Aging and the Alzheimer’s Association AD Framework and the 2015 working group of the International Association of Gerontology and Geriatrics (IAGG) which concluded that early identification of MCI is essential to improving cognitive performance in older adults (25). The IAGG working group found that benefits can be derived from better management of the treatable components of cognitive impairment and lifestyle interventions that may slow cognitive decline (25). Finally, a 2017 Edinburgh consensus group focused on the implications of disease-modifying treatments for AD emphasized the crucial importance of identifying early cognitive impairment, given that therapies will likely be most efficacious early in cognitive decline (26).
In addition to assessing the scenarios in which testing is appropriate, select organizations have published recommendations and advisories on preferred methods for MCI detection. As noted above, the ACA declined to recommend a specific methodology for cognitive assessment in the U.S. given that noconsensus has been reached on a universally accepted screening methodology, and formal guidance has yet to be issued on this topic by federal health authorities (e.g., Centers for Medicare & Medicaid Services, (CMS)).
In response to the “call to arms” that the ACA mandate represents, an Alzheimer’s Association working group outlined specific recommendations for the detection of cognitive impairment in the primary care setting. The expert consensus highlighted that in other countries, such as Canada, the national consensus guidelines have detailed primary care as preferred site for evaluation (https://alzheimer.ca/sites/default/files/files/national/for-hcp/for_hcp_recos_cccdtd4_en.pdf). Moreover, the group recommended that both structured (e.g., use of a formal cognitive test) and unstructured (e.g., informal physician questions about memory) cognitive assessments should be utilized for testing and tracking cognitive function by PCPs (23). A 2018 clinical practices guideline from the American Academy of Neurology noted that relying on subjective cognitive complaints alone is an insufficient assessment criterion for MCI because of the significant potential for over or under-identification (27). The guideline instead recommended that physicians use a validated tool for cognitive assessment and solicit patient history along with informant input (27). The 2015 IAGG working group also recommended utilizing both patient and informant assessments of cognitive function along with physician testing to evaluate subjects for early cognitive impairment (25). The group urged the use of validated tests that take only three to seven minutes to conduct, limiting the time burden for patients and providers. Similarly, the Gerontological Society of America workgroup recommended screening tests that take five or fewer minutes to administer, are free of charge, assess multiple cognitive domains, and are validated in a community-based sample (25). Unfortunately, despite this past guidance, specific and up-to-date recommendations grounded in currently available tools do not yet exist, potentially resulting in uncertainty among PCPs about how best to detect MCI.
In addition to considering when testing is appropriate and what battery of tests is most appropriate, previous groups have also elaborated on how an optimal care pathway may be achieved for early detection of cognitive impairment. This is a critical unmet need in the field, as the uncertainty toward the methodology of assessing for cognitive impairment is compounded by the lack of consensus on what physicians should do in the event of a positive result. Uncertainty about an assessment returns a positive result may de-motivate PCPs from broaching the topic of cognitive impairment or testing with their patients in the first place. In contrast to this PCP-directed recommendation, the 2015 Edinburgh Consensus working group noted that the UK healthcare system would be unable to accommodate the strain on PCPs and specialists if a disease-modifying therapy becomes available, noting that the current role of the PCP in controlling patient access to specialists is unclear (26). This group emphasized that restructuring cognitive healthcare to allow patients to receive care across disciplines may optimize efficiency and improve patient care (26).
Similarly, despite published insight on select aspects of an “ideal” cognitive assessment (25), it remains unclear which specific tools, particularly digital assessments, are best suited for widespread use and how new assessments could be improved to allow higher detection rates of MCI. This panel sought to provide further clarity on technologies that can improve early detection of MCI, including noting how potential modification or validation of existing tools could contribute to enhanced patient care.

 

Anticipated changes to the MCI landscape

The late-stage development of some compounds with a putative disease-modifying effect support optimism that a disease-modifying therapy may become available within the next 3 – 5 years (28). Among these Phase 3 agents, monoclonal antibodies targeting amyloid-β have recently gaining momentum. Several clinical studies indicate that targeting the early phases of AD, including MCI or even preclinical populations, can increase the likelihood of clinical success (28). This recent focus on early intervention in cognitive decline underscores the value of identification of MCI before the onset of more severe cognitive decline to maximize the potential for intervention and minimize the personal, clinical, and economic costs of cognitive decline.
Approval of a novel therapy for MCI-AD is expected to dramatically increase both patient and physician involvement in cognitive screening. In the absence of proactive preparation, demand for cognitive assessment will likely present a significant strain on global healthcare systems around the world, with PCPs shouldering a significant portion of the burden. Specialists are also likely to be strained by a large volume of referrals, likely including a minority of patients with MCI-AD and a majority of individuals with MCI due to other etiologies, or even intact cognition (e.g., misdiagnosed or “worried well” individuals with an SMC). It is in the best interest of patients, physicians, and healthcare systems to implement large-scale cognitive screening and to develop and refine technological solutions that can optimize early and accurate detection of MCI and MCI-AD. Going hand in hand with improved detection will also be better patient-physician alignment on the appropriate care pathways once MCI-AD is observed. For example, prior studies evaluating the impact of cholinesterase inhibitors on cognitive symptoms in patients with mild – moderate AD suggest rivastigmine and galantamine may provide statistically significant symptomatic benefits in patients treated earlier in the disease trajectory, which were not achieved for patients in whom treatment was initiated later in the disease course (29, 31). Though clinical data to support early initiation of cholinesterase inhibitors in individuals with MCI at risk of developing AD is mixed (27, 29, 32), data from clinical trials investigating anti amyloid-β drugs have further supported the importance of early diagnosis and treatment in AD.

 

Conclusion

Current neuroscientific discoveries point toward a compelling need to optimize and harmonize clinical protocols for the timely and accurate detection and diagnosis of MCI-AD, also in light of late-stage clinical development of disease-modifying therapies. In subsequent manuscripts, we will outline potential methods to enhance MCI detection in individuals at risk and across clinical and non-clinical settings, focusing on cognitive, functional, and interview-based approaches. However, we acknowledge the potential for the detection of AD pathology, regardless to the clinical stage, to undergo a substantial change due to technological advances in the future, including blood-based biomarker assays to detect AD. In this case, it may become necessary to compare the utility of various screening modalities in parallel through subsequent clinical trials.
The present working group has identified actionable methods to improve cognitive and functional assessment tools, recognizing thatreassessing the optimal care pathway upon the availability of a blood-based biomarkers test with high clinical utility will be necessary for screening and diagnostic purposes. Consequently, blood-based biomarkers should be integrated into the design of studies evaluating the accuracy of cognitive and functional algorithms to detect MCI-AD. Additionally, both biomarkers and cognitive algorithms remain critical components of inclusion criteria and endpoints in clinical trials designed to evaluate MCI-AD therapies.
In this suite of publications, we hope to promote thoughtful but dramatic changes to the existing management plan for adults with MCI, inclusive of cognitive screening for the early detection of MCI. In subsequent articles, we will provide guidance for designing and validating cognitive assessment tools to enhance their real-world utility, which represents a “call to action” for our colleagues in the cognitive evaluation field.
In summary, this task force seeks to support MCI diagnosis and detection of underlying pathophysiology as a public health imperative, in parallel with other major organizations such as the World Health Organization (WHO) and the Alzheimer’s Association, in order to improve clinical outcomes for aging individuals – not just in preparation for a novel AD therapy but also in the current context of this field.

 

Acknowledgements and funding: Medical writing support, under the direction of the authors, was provided by ClearView Healthcare Partners, LLC, funded by Eisai Inc., in accordance with Good Publication Practice (GPP3) guidelines..

Disclosures: MB is affiliated with the Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; and with the Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Spain. Private research funding sources include Grifols SA; Caixabank S.A.; Life Molecular Imaging; Araclon Biotech; Laboratorios Echevarne; Festival Castell Paralada; Bonpreu/Esclat; and Famila Carbó. Public grants include those from Instituto de Salud Carlos III. Ministerio de Salud. Gobierno de España; Dirección General de Farmacia. Ministerio de Salud. Gobierno de España; and European Commission:H2020 program, Innovative Medicine Initiative (IMI-2); and ERA-NET NEURON program, European Marie Sklodowska Curie. Advisory work includes that for Araclon Biotech, Biogen, Bioibérica, Eisai, Grifols, Lilly, Merck, Nutricia, Roche, Oryzon, Schwabe Farma, Servier, and Kyowa Kirin. PMD has received research grants (through Duke University) from Avid, Lilly, Neuronetrix, Avanir, Bauch, Alzheimer’s Drug Discovery Foundation, Cure Alzheimer’s Fund, Wrenn Trust, DOD, ONR, and NIH. PMD has received speaking or advisory fees from Anthrotronix, Neuroptix, Genomind, Clearview, Cognicity, Nutricia, Living Media, Verily, RBC, Brain Canada, and CEOs Against Alzheimers. PMD owns shares in Muses Labs, Anthrotronix, Evidation Health, Turtle Shell Technologies and Advera Health Analytics whose products are not discussed here. He has received travel support from World Economic Forum, CCABH and Canaan Ventures. PMD served/serves on the board of Baycrest, AHEL, TLLF and TGHF. PMD is a co-inventor (through Duke) on patents relating to dementia biomarkers and therapies. BD is affiliated with the Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Salpêtrière Hospital, AP-HP, Sorbonne-Université, Paris, France. JI is affiliated as an Assistant Professor-Adjunct (Group1) with the Department of Family Practice at Queen’s University. She was also a panelist for Hoffman-La Roche Limited, Ottawa, on an Alzheimer’s Disease Panel. She is involved with the Canadian Consortium on Neurodegeneration in Aging (CCNA), Extension Study as a Co- Investigator and Research Coordinator. AI received lecture fees from Eisai, Janssen, Otsuka, Eli Lilly, MSD, Chugai-Roche, Daiichi-Sankyo, Alnylam, Takeda, UCB, Ono, Integra Japan, IQVIA, Fuji Rebio, Biogen, and advisory fees from Janssen during the past three years. AP reports personal fees from Acadia Pharmaceuticals, Functional Neuromodulation, Neurim Pharmaceuticals, Grifols, Eisai, BioXcel, Tetra Discovery Partners, and Merck; grants from AstraZeneca, Avanir, Biogen, Biohaven, Eisai, Eli Lilly, Janssen, Genentech/Roche, Novartis, Merck, as well as funding from NIA, NIMH, DOD. KLP receives grant funding from the National Institute on Aging, the National Institute of Neurological Disorders and Stroke, the Global Brain Health Institute, and Quest Diagnostics. BV has consultancy and research grants from Roche, Biogen, EISAI, Nestle, Lilly, Cerecin, and Merck. HH is an employee of Eisai Inc. and serves as Senior Associate Editor for the Journal Alzheimer’s & Dementia; during the past three years he had received lecture fees from Servier, Biogen and Roche, research grants from Pfizer, Avid, and MSD Avenir (paid to the institution), travel funding from Eisai, Functional Neuromodulation, Axovant, Eli Lilly and company, Takeda and Zinfandel, GE-Healthcare and Oryzon Genomics, consultancy fees from Qynapse, Jung Diagnostics, Cytox Ltd., Axovant, Anavex, Takeda and Zinfandel, GE Healthcare, Oryzon Genomics, and Functional Neuromodulation, and participated in scientific advisory boards of Functional Neuromodulation, Axovant, Eisai, Eli Lilly and company, Cytox Ltd., GE Healthcare, Takeda and Zinfandel, Oryzon Genomics and Roche Diagnostics. He is co-inventor in the following patents as a scientific expert and has received no royalties: • In Vitro Multiparameter Determination Method for the Diagnosis and Early Diagnosis of Neurodegenerative Disorders Patent Number: 8916388; • In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Patent Number: 8298784; • Neurodegenerative Markers for Psychiatric Conditions Publication Number: 20120196300; • In Vitro Multiparameter Determination Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number: 20100062463; • In Vitro Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number: 20100035286; • In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Publication Number: 20090263822; • In Vitro Method for The Diagnosis of Neurodegenerative Diseases Patent Number: 7547553; • CSF Diagnostic in Vitro Method for Diagnosis of Dementias and Neuroinflammatory Diseases Publication Number: 20080206797; • In Vitro Method for The Diagnosis of Neurodegenerative Diseases Publication Number: 20080199966; • Neurodegenerative Markers for Psychiatric Conditions Publication Number: 20080131921. AV is an employee of Eisai Inc. and received lecture honoraria from Roche, MagQu LLC, and Servier.

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