Abstract
Mild Cognitive Impairment (MCI) is a diagnostic category indicating cognitive impairment which does not meet diagnostic criteria for dementia such as Alzheimer’s disease. There are public health concerns about Alzheimer’s disease (AD) prompting intervention strategies to respond to predictions about the impacts of ageing populations and cognitive decline. This relationship between MCI and AD rests on three interrelated principles, namely, that a relationship exists between AD and MCI, that MCI progresses to AD, and that there is a reliable system of classification of MCI. However, there are also several ethical issues and problems arising in the AD/MCI relationship. These include early diagnosis and interventions, the effects on people with MCI, and the newer neuroimaging and neuropharmacological approaches used in diagnosis and treatment. All these issues pose questions about the principles of MCI in relation to AD, with implications for how MCI is understood, diagnosed, treated, and experienced by patients. This article analyses four challenging areas for neuroethics: the definition and diagnosis of MCI; MCI in relation to AD; clinical implications of MCI for ethical disclosure, diagnosis, and treatment; and the research implications of MCI. The significant connections between these areas are often overlooked, together with uncertainties overall. Patients, healthcare systems and society are best served by informed clinicians, academics and researchers. After 35 years, the store of MCI knowledge is expanding and evolving.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Mild Cognitive Impairment (MCI) is a diagnostic category that indicates an assessable degree of cognitive impairment, yet it does not meet diagnostic criteria for Alzheimer’s disease (AD) [1]. Situated between ageing and the early diagnosis of dementia disorders, MCI is frequently portrayed as a transitional phase between age-related cognitive changes and AD [2].
Early diagnosis cannot offer a cure, but it can offer patients and their families several advantages. For instance, the ability to make decisions about their future care; benefits from expert advice and support; and access to pharmaceutical treatments for possible improvements to cognition [3]. Such treatments may delay the onset of more life-limiting symptoms and the need for institutional care.
The general thinking is that AD is a progressive neurodegenerative disorder with major individual and societal effects. Early diagnosis of AD is essential for patient care and the development of effective treatments. Thus, MCI is a helpful signpost on the pathway of cognitive impairments beginning from normal ageing onwards [4,5,6,7,8].
Indeed a “worldwide pandemic” of MCI, AD, and AD-related dementia (ADRD) is expected, prompting calls for detection, diagnosis, and management of MCI, AD and ADRD [9]. More broadly, dementia is described as the greatest global challenge for health and social care in the twenty-first century where globally approximately 47 million people were living with dementia in 2015 [6]. This figure is projected to increase three-fold by 2050 [6]. Healthcare for the elderly and persons affected by dementia, and the subsequent demands on resources, are crucial matters of public policy and ethical thought [10]. AD is the most common type of dementia [11], and is part of this world health situation.
The relationship of MCI to AD rests on three implicit and interconnected principles, namely, that a relationship exists between AD and MCI, that MCI progresses to AD, and that there is a dependable system of classification of MCI. However, there are also several ethical issues and problems arising in the AD/MCI relationship. These include early diagnosis and interventions, the effects on people with MCI, and the newer neuroimaging and neuropharmacological approaches used in diagnosis and treatment.
At least one or more of these principles, ethical issues and problems, can be linked to MCI research in the last decade or so, including: new systems of classifications [12,13,14]; studies on diagnosis [15], patient experiences [16]; advances in imaging techniques [17], biomarkers [18, 19]; genetics [20, 21]; pharmacotherapies [22]; cognitive and other interventions [23, 24]; research into screening instruments [25]; MCI/AD reversion [26, 27]; and social and ageing studies [1, 28].
Despite an explosion of publications, some hold that no consensus has been reached in several areas such as the clinical and research criteria for MCI, their operationalization, and a deeper grasp of what it is like to live with MCI [4]. Agreement is lacking too about new validated, standardised tests sensitive to the early stages of MCI [4]. This means there are multiple factors which undermine the principles of MCI research and practice. These factors have implications for how MCI diagnostic criteria are understood and utilised.
This article aims to investigate the weighty questions about MCI by analysing four challenging areas involving classifications, practices, and treatments. The four areas are: definition and diagnosis of MCI; MCI in relation to AD; clinical implications of MCI for disclosure, diagnosis, and treatment; and the research implications of MCI. A discussion follows which identifies the significant yet overlooked interrelationships between these areas and the associated uncertainties overall. The article focuses on dementia due to Alzheimer's disease because AD is the most common type of dementia [29], and features noticeably in the literature discussing MCI.
Definition and Diagnosis of MCI
The term Mild Cognitive Impairment was first used in 1988 to characterise a scale which clinically assessed memory deficit [30]. In 1999, Ronald Petersen from the Mayo Clinic, Rochester, Minnesota, outlined diagnostic criteria [31, 32]. Over twenty years later, MCI is a developing yet contested area.
Patients or their close contacts may raise concerns about memory or impaired cognition [33]. Health professionals are recommended to assess for MCI, not assuming the concerns are related to normal ageing [33]. Diagnosis is made by a clinician who takes the patient's history which generally contains indicators of decline in cognition, usually memory [34]. Occasionally neuropsychological testing is needed.
The American Academy of Neurology recommends that for patients for whom screening for MCI is appropriate, clinicians ought to use to validated evaluation tools [33]. For patients who test positive for MCI, clinicians should undertake a more formal MCI clinical assessment.
The Medicare Annual Wellness Visit in the United States requires an assessment to detect cognitive impairment. “Subjective cognitive complaints alone can result in overdiagnosis or underdiagnosis of MCI and thus are insufficient to screen for MCI…. Diagnosis of MCI is based ultimately on a clinical evaluation determining cognitive function and functional status and not solely on a specific test score” [33].
Interestingly, the US Preventive Services Task Force found there is no empirical evidence that “screening for cognitive impairment improves patient or caregiver outcomes or causes harm. It remains unclear whether interventions for patients or caregivers provide clinically important benefits for older adults with earlier detected cognitive impairment or their caregivers” [35].
There is an implied principle that classification of MCI is accurately established. Cognitive functioning is typically characterised into 1 of 5 domains: (1) learning and memory, (2) language, (3) visuospatial, (4) executive, and (5) psychomotor; these domains have approximate correspondence with their location in the brain [36]. For a diagnosis of MCI, only one of these areas must be impaired, However, a diagnosis of dementia requires that more than one domain must be impaired [36].
For MCI patients, if memory loss is the predominant symptom, the term “amnestic MCI" (aMCI) is often used [37]. The patient’s memory impairment does not accord with what is expected for their age and they do not meet the criteria for AD [37]. The others are “non-amnestic” (naMCI).
Yet the psychometric boundaries for diagnosing MCI are unclear. The questions are asked, how many standard deviations lower than reference population norms must a person be to receive the label, and what population(s) should be used as a reference? [14] Another classification is in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [12]. In DSM-V the dementia diagnosis is called “major neurocognitive disorder,” and mild cognitive impairment is now “mild neurocognitive disorder”.
Overall, the various diagnostic systems have several common core characteristics: self- or informant-reported cognitive complaint, objective cognitive impairment, preserved general functional abilities, and no dementia [38]. The MCI diagnostic systems are evolving and not well standardised, resulting in inconsistencies in the samples used in research studies [39]. All these things pose challenges to accurate and useful diagnosis, which is required for world health responses to ageing and dementia.
MCI and Alzheimer's Disease
A condition called “MCI due to AD” refers to the predementia stage of AD when symptoms appear, with cognitive impairment not normal for the age [40]. The evidence for a preclinical stage of AD include studies suggesting there may be very subtle cognitive changes which are detectable years before meeting criteria for MCI, and predicts the progression to AD [41]. Yet, there are two important considerations about staging and progression, which are discussed below.
Evolving Relationship of MCI to AD: Preclinical and Staging
Clinically, the ε4 allele of the apolipoprotein E (APOE) gene is the chief genetic risk factor for AD. The ε4 allele of APOE has predictive capability in relation to a genetic risk factor for AD [42]. There is a 3-times greater risk of AD in individuals with one copy of the ε4 allele, and 15-times greater risk for two copies that ε4 allele [42]. A study following more than 75 MCI patients found that approximately 10% to 15% of the subjects progress to AD each year [43]. Some of these subjects were studied for as long as 5 years. The strongest predictor was their apolipoprotein E status. The patients who possessed an ε4 allele were more likely to convert to AD more rapidly than those who were not carriers.
The other measurement of an elevated risk of AD is biomarker information. Although AD biomarker studies are progressing, they are not yet at the point of predictive capability. The deposition of amyloid in parts of the brain is the first trigger of AD, which leads to the formation of neurofibrillary tangles (NFTs) and eventually to brain cell deaths and dementia [44].
Amyloid changes in the body’s cerebrospinal fluid (CSF) was found to predict brain amyloid deposition, and also phosphorylated tau concentrations [44]. This is the other theory about the causes of AD, that excess or abnormal phosphorylation of tau eventually leads to NFTs, typical of AD.
The research has provided new ideas about the use of AD biomarkers and their associations with cognitive decline, but not a prediction of AD. Moreover, in cognitively unimpaired individuals within a research context, CSF biomarkers have very little personal validity [19, 45, 46].
The American Academy of Neurology’s Practice Guideline published in 2018 stated that the “use of biomarkers in patients with MCI is a rapidly evolving field, but to date, there are no biomarkers clearly shown to predict progression in patients with MCI…For patients and families asking about biomarkers in MCI, clinicians should counsel that there are no accepted biomarkers available at this time (Level B)” [47].
MCI to AD: Uncertain Progression, Reversion, and Prediction
The principle of the MCI relationship to AD is not wholly determined. It can be compared to the predisease in cancer. For instance, oral cancer has a definite pre-cancerous stage and develops through a sequence of changes in the tissue which may show signs of movement towards cancer [48]. However, not all skin changes and lumps become cancerous.
Similarly, despite the wider evidence for a preclinical stage of AD, the movement of MCI to AD is not inevitable. Research about the likely progression of MCI to AD is mixed. Some findings confirm progression, e.g. a preclinical stage of accelerated cognitive loss observed 3 to 4 years before the diagnosis of MCI [49]. There is evidence that individuals with MCI appear to be at an increased risk of progressing to AD, at the rate of 10% to 12% per year [31].
Nevertheless, other findings including population studies show that well over a quarter of persons labelled with MCI do not progress to dementia over several-years, and some remain stable or return to normal [14]. In a large population study in Spain of 4057 dementia-free individuals 55 + years of age, most MCI individuals did not convert to dementia at 4.5-year follow-up [15]. Only ~ 15% of individuals with MCI diagnosed with DSM-5 criteria developed dementia over the 4.5-year follow-up. That is, most MCI individuals did not develop dementia.
Still, other data highlights MCI-related deficits reversing [50]. In a community-based study the reversion rates from MCI to normal was accompanied by a decreasing trend with age where older participants were less likely to revert back to normal than younger participants [26]. Indeed, there is the repeated finding that MCI is longitudinally unstable, with up to 48% of those diagnosed with MCI criteria “recovering” to age appropriate levels of functioning over time [51].
In short, the expectation of MCI progressing to AD is countered by mounting evidence which shows: that those diagnosed with MCI do not always progress to dementia; low rates of conversion to dementia observed in population-based studies; and numerous cases where there is reversal.
Clinical Implications of MCI for Disclosure, Diagnosis, and Treatment
In the quest to find effective ways to treat or prevent AD there is a focus on development of disease-modifying therapies MCI [40]. However, several clinical problems arise about disclosure of results, early diagnosis, the use of biomarkers, and a new drug called Aducanumab. The ethical issues concern patients’ well-being; their private information; overdiagnosis and overtreatment; and the economic and human costs of recent innovations. We now examine the clinical problems and issues.
Ethics of Disclosure
Medical disclosure comprises the communication of the state of a person’s health, illness, or the potential future illness [52]. Disclosures often divulge information on the aetiology, diagnosis and prognosis of a particular condition, and the possible risk to others. Disclosures also raise questions of who else needs to be told, in how much detail, the timing of disclosure, and what social supports are needed [52].
During the first decade of the twenty-first century there was a growing interest in addressing disclosure of diagnosis of dementia [53, 54]. First, with ethical debates among researchers and clinicians on “truth telling” and dementia, developing into examining the ideas of those involved in disclosures, and later shifting to investigations of how truth telling is provided [53, 54].
It is still a matter of debate whether disclosing a diagnosis is harmful to an individual when the symptoms are mild and yet demented [55]. Some see a moral duty to speak the truth about diagnosis to competent patients as the information belongs to them despite the consequences [56]. The counterbalancing view is that the decision to disclose or not depends on the clinical situation [56].
Nonetheless, ethics guidelines are open to discussion when it comes to being truthful with patients and withholding what is harmful: “In practice, patients with dementia rarely ask for the information and many doctors seem to believe that because there is no cure to offer, such knowledge may be only detrimental and therefore not needed in therapeutic relationships” [56].
As one old age psychiatrist commented, veracity seems to be “a difficult virtue and a difficult-to-fulfil obligation. It remains difficult to reconcile conflicting principles and to judge how much information a patient should be given. Additional ambiguities may arise because of the difficult, sometimes impossible, task of balancing autonomy and paternalism” [56].
Disclosure is also important for autonomy to make medical decisions about individual life choices e.g. future care and financial planning. Yet, concerns about preventing harm to persons should also be the foundations of evidence-based guidelines on how to disclose relevant information [55, 57, 58].
A single position is not universally upheld, and codes of ethics allow for other interpretations.
Although it can be argued that the principle of autonomy no longer applies to persons who are incapable of understanding what is being disclosed to them, obtaining a clear understanding of the level of insight of persons with dementia is challenging. Moreover, an inability to fully appreciate the implications of a diagnosis need not preclude the possibility of deriving any benefit from diagnostic disclosure [59].
Then in evaluating the issues, ethicists need to ponder the effects of decisions. The consequences of disclosure may be significant in countries where insurance contracts could be affected by the information and legal challenges could result [55].
Disclosure could also have other effects on stigma and possible illness-related discrimination in workplaces [55]. There is known stigma associated with the term “dementia” [60] and AD is one common form. Knowledge of AD biomarker status can influence how individuals feel about themselves: there can be internalised stigma; and how others judge them: public stigma [61]. Intriguingly, as a term, MCI rose in popularity perhaps because it permitted clinicians to avoid applying the stigmatizing label of Alzheimer’s or dementia [62].
Turning to patients and their families, much less is understood about their thoughts regarding MCI stigma compared to AD [63]. The research reflects uncertainties associated with diagnosis of MCI [63]. Confusion between AD and MCI could prolong the stigma linked with AD and may result in new encounters with stigma labels, particularly for earlier diagnoses.
There is a foreseeable increase in “the number of people who perceive themselves to be ‘patients in waiting’, thus leading an MCI diagnosis to elicit the same labeling stigma associated with AD, even for patients without a full diagnosis of dementia due to AD” [64].
These negative consequences associated with a diagnosis are often multilayered even for professionals [58]. Practitioners know about the possibility of causing further harm [58]. Indeed, diagnosis also deepens anxieties for professionals diagnosing, hampering an open and complete discussion of options after diagnosis [65].
Beyond the effects on patients and professionals, there are serious consequences for their families [66]. Voluntary health and advocacy organizations view disclosure of a diagnosis as “the beginning of a journey, and people need support and resources to address the challenges they will face living with the disease, as an individual and as a family” [55]. There are also discrepancies between family and caregivers’ opinions about disclosure and that of physicians, for example, family/caregivers may report the disclosure was insensitive whereas the doctor thought it was handled well [59].
After diagnosis, it can be challenging to provide information about the psychological and behavioural symptoms of dementia as well as the prognosis, since the trajectory of the illness is unpredictable [67]. There are cultural differences too where in some countries close relations of the patients preferred open disclosure of dementia to the patient but in other countries close relatives did not prefer open disclosure [67].
Overall, the ethics of disclosure is characterised by continuing debates and conflicts. There are sound principles to guide decision-making, while fully evaluating the consequences for patients and their families.
Ethics of Early Diagnosis
Like the subject of disclosure, early diagnosis is complex for ethics as it touches on several perspectives: clinicians, care of patients, and what happens in society. These are explored together with some issues which emerge.
From the clinician’s perspective, earlier studies suggest that the number of physicians in favour of early diagnosis was rising and the reluctance to disclose was lessening [68]. A survey of medical professionals at German hospitals and memory clinics found that nearly half of the respondents said that individuals with MCI and pathological cerebrospinal fluid (CSF) biomarkers were informed they had or would soon develop AD [69]. Although 81% were aware of a “right not to know,” 75% said that results were always communicated. They saw benefits of prediction or later life planning. But there would be anticipated high psychological stress (82%) and self-stigmatization (70%) for those tested [69].
Early diagnosis has effects on patient cognition. A phenomenon of “stereotype threat” occurs where individuals in a stigmatised group such as older adults underperform in a particular domain like memory [70]. They are reminded of the stereotype about their group, e.g. “older persons have poor memory.”
If this stereotype threat results in an incorrect diagnosis of MCI, this can have damaging effects on the elderly [70]. A false diagnosis could generate hypervigilance to any signs of cognitive failure. This can result in overstatements of complaints and a lowering of cognitive functions, which can lead back to further worries [70].
A pertinent concept is “mindset effects” [21]. A mindset is a mental outlook that orients individuals to a particular group of expectations and guides them towards reactions in accord with such expectations. These mindsets are altered by reception of new information, impacting cognition and thus behaviour and decision making.
Another patient effect extends beyond cognition and is related to a broader notion of Quality of Life (QOL). This is a subjective, multidimensional concept usually assessed in several areas of individual functioning e.g. health-related domains. In persons with dementia, QOL frequently pertains to: physical and mental wellbeing; experience with cognitive functioning and difficulties; experience of stress; mood; social interactions; and capabilities in daily living, e.g. self-care and mobility [71]. In one case, patients with MCI or AD who were aware about their diagnosis reported lower average physical wellbeing, lower satisfaction with daily life, basic functioning, and more difficulties in daily life—compared with those who were not aware [71].
Early diagnosis also impacts society through overdiagnosis and overtreatment. The risk of overdiagnosis and overtreatment refers to decisions made by physicians that bring no patient benefit, that occurs with the widening of disease categories and how these alter diagnostic processes [72,73,74]. Consequently, patient populations are increased without rigorous study of potential harms.
A policy of widespread “early” diagnosis of dementia in a population is not recommended by the United Kingdom National Screening Committee, since the best screening test for dementia does not accurately identify those who have dementia and those who do not [75]. The example is that for 100 people aged 65 tested, 18 would test positive, yet only six of these would have dementia and one case would be overlooked. Thus, a majority of those tested would be “false positives” [75].
Early diagnosis needs to balance the risks of making a diagnosis too early with cautions about being too late regarding signs of illness and advanced planning [76]. Not recognising an illness can have serious consequences and many experts hold that a timely diagnosis is important [27]. In the Netherlands, support for persons with early-onset dementia and their families are normally only available after obtaining a diagnosis [27]. This means receiving a case manager which differs between municipalities. The kind of care is based on the diagnosis when accessing services at day care centres. It is frequently problematic to decide whether the benefits of obtaining a diagnosis outweighs the potential harms [77, 78].
Another concern is the continuing pursuit of phases of cognitive impairment in the ageing process such as asymptomatic preclinical phases, symptomatic predementia phases such as MCI, and dementia stages. These indicate a persistent “medicalization of underperformance” in old age, which can be ethically queried [77].
The term “Alzheimerisation” [36] has been used to depict the disproportionate attention to AD compared to other kinds of dementia or conditions like MCI. Such attention shapes society’s representations of ageing, for instance when patients are referred to organizations like an Alzheimer’s society for support [36].
The research on early diagnosis prompts considerations that MCI diagnosis which is unclear may be unnecessary, not clinically helpful and ethically doubtful [79]. Then combined with an undefined prognosis, unclear MCI diagnosis may cause early, perhaps unwelcome anxiety about the future in patients and their families.
One critical issue for early diagnosis is suicide. A study of persons with MCI and early dementia in Germany, along with family caregivers, found some participants clearly emphasised suicide as an “option to take control” [80]. The ideas of those with MCI and early dementia were about self-determination and the fear of losing control. They also had a sense of responsibility towards their family carers whom they do not wish to burden. Whereas family caregivers, while not directly experiencing such fear, thought suicide was a benefit of early detection but also a shortcoming, which was consistent with other research [80].
The study’s authors hypothesize that tested persons and family caregivers, who mentioned suicide as a rational option or was morally acceptable, had images of completing a fulfilled life. In recent years in Germany there has a growing public acceptance of suicide and active euthanasia in response to serious incurable disease [80].
The study recommend that disclosure and communication strategies ought to cover the subject of suicide and highlight the alternative of advance care planning. “Ethicists should reflect on how they contribute to a negatively loaded imagery of the fourth age when justifying suicide in particular reference to dementia” [80]. The fourth age serves as a "cultural imaginary" consisting of a collective fear about ageing and agedness [81]. It differs from the third age which tends to exclude people with physical and cognitive impairments for reasons of their limited capacity to act agentically.
In short, early diagnosis presents moral dilemmas and the need to balance risk and benefits. While the matters may be complex, a knowledge of the important factors will ensure decisions are informed ones.
Biomarkers
Technology such as analysing biological characteristics or biomarkers has made early diagnosis increasingly possible, but ethical questions emerge. Research suggests MCI is an intricate entity with subtle distinctions [82]. The criterion of subjective change in cognition remains controversial in view of growing evidence that subjective reports are insufficient predictors of genuine cognitive impairment [51]. Therefore, it may still be hard to distinguish MCI from enduring low levels of function.
Rather than evaluate symptoms, a trend has developed towards biological tests and neuroimaging biomarkers. The US Food and Drug Administration has approved three amyloid-specific positron emission tomography (PET) ligands used in diagnostic neuroimaging [16]. This amyloid PET imaging provides additional information about the cause of a patient’s MCI [16]. Researchers using biomarker tests can study interventions which aim to prevent or slow cognitive decline. One trial used the notion of preclinical AD and investigated older persons with amyloid accumulation at high risk for AD and whether anti-amyloid drug treatment could slow cognitive decline [83, 84].
Biomarkers are a significant advancement because pharmacological treatments to modify AD are elusive, and non-drug methods to try to slow AD progression e.g. exercise, have limited effectiveness [85]. Nonetheless, there are some special ethical questions relevant to biomarkers which are raised briefly below.
Using Biomarker Diagnosis. Whether to Diagnose when the Tests Have Doubts?
As biomarker diagnostic tools and dementia knowledge both advance, investigators and clinicians will face more frequent challenges of disclosing information of indeterminate prognostic significance to patients [86]. Arguments favouring biomarker testing are based on the right to know and respect for autonomy, whereas fear of AD with no effective treatments may produce a negative balance of good over harms outcomes [19]. Greater harm to patients becomes a reason against testing [19]. During diagnosis, patients also have the right to decide whether they undergo particular tests and whether they want to know the results [87].
Accuracy of Diagnosis. Are Biomarkers Accurate and Adding Value?
A positive amyloid PET result is highly predictive of amyloid-beta pathology, a hallmark of AD [16] Yet, some clinical evidence points to positive amyloid PET as not equivalent to AD diagnosis [16]. Other neuroimaging technologies offer possibilities, e.g. magnetic resonance imaging (MRI) using an automated procedure for diagnosing MCI [88].
In one Swedish study, amyloid imaging was examined with respect to diagnosis, management and pharmacotherapy [17]. The cohort of patients had neuropsychological assessments and some had biomarker-based assessments but these could did not offer adequately certain clinical diagnoses. Despite PET imaging using [18F]Flutemetamol, a well-established diagnostic tool in the work-up of dementia disorder patients, the neuroimaging did not provide a sufficient differential diagnosis [17]. Further, a review of PET amyloid imaging concluded that it may promise a beneficial role to diagnose AD in inconclusive cases, nevertheless there are limitations because of numerous variations in protocols and cut-off values for interpreting results [89].
Errors of Diagnosis. Are There False Positives?
Analyses of research found individuals with false positive MCI diagnoses, despite exhibiting AD biomarker profiles, neuropsychological performance, and functional pathways more consistent with cognitively normal participants [90]. Consequences include possible negative psychological reactions, and adverse clinical implications such as unnecessary follow-up testing—causing financial burdens for the patient and the healthcare system [91].
Accessibility of Diagnosis. Who Can Be Diagnosed and How Many?
There is restricted accessibility to these sophisticated tests. Investigations using hi-tech neuroimaging and CSF biomarkers may not be available outside of specialist centres [92]. Studies conducted in a research hospital setting may not incorporate cost-effectiveness parameters in the design [17]. Hence in using PET amyloid imaging for AD management, cost-effectiveness is a recognised inherent limitation [89]. For many patients and their healthcare professionals, the option of even considering biomarker imaging may be financially excluded [36].
What are the Financial and Human Costs?
There are monetary and personal costs associated with biomarker diagnosis, when amyloid PET is expensive [93] and an amyloid PET report does not constitute a clinical diagnosis of AD dementia [94]. South Korean researchers assessed the cost-effectiveness of including amyloid-PET for evaluating persons diagnosed with MCI [95]. The health outcomes were evaluated in quality-adjusted life years (QALYs) and the model demonstrated that amyloid-PET increased QALYs by 0.003 in persons with MCI and was not cost-effective.
This is contrary to previous studies which claimed that amyloid-PET was cost-effective in predementia or similar states. The earlier studies showed the cost-effectiveness of adopting amyloid-PET but they did not selectively target MCI patients where MCI patients are in a prior phase of disease progression compared to the earlier reports [95].
One aspect of costs is insurance. The use of biomarkers for AD diagnosis and their reimbursements from insurance companies both differ internationally. 18F-FDG PET imaging is reimbursed by the US Centers for Medicare and Medicaid Services if used to exclude AD in patients who meet the diagnostic criteria for AD and frontotemporal lobar degeneration [94].
In the United States, public or private insurance does not cover most biomarker tests for AD [96]. Still, testing and treatment costs borne by Medicare will have notable effects on the federal budget and taxpayers [97]. Preclinical AD diagnosis and treatment may have implications for state budgets if expenses are covered by the country’s insurance program for low income earners, Medicaid [97]. This is funded by the states and the federal government jointly.
Other significant insurance issues also arise. Legislation or rules in all fifty states and the District of Columbia regulate long term care (LTC) insurer practices [98]. However, 43 states overtly allow LTC insurers to use health information for underwriting decisions. Thus, the protections offered by the National Association of Insurance Commissioners Model Act would not “meaningfully protect individuals from discrimination based on biomarker status in the context of LTC insurance. Medical underwriting practices would likely create a barrier to individuals seeking LTC insurance policies based on preclinical biomarkers status” [98].
Furthermore, people who are biomarker positive will be prevented from accessing vital resources to prepare for financial burdens of LTC services and support costs [98]. An absence of anti-discrimination protections could result in persons with a positive biomarker test liable to unfavourable insurance decisions without any alternatives.
There is also the issue of the use of private health information. Potential abuse could occur in institutions, such as employers or insurers seeking accurate prognoses of future cognitive performance and mental health status of employees and insured persons [18]. Worldwide, patients are already worried that biomarker and/or genetic information will become part of the medical record and may affect their insurance standings.
In all, one can understand strategies aimed at prevention of AD through early intervention. Nonetheless, there are many questions about early MCI diagnosis using biomarkers as accurate, reliable, beneficial, and sound for ethical use with patients.
Aducanumab
The final clinical problem to consider is treatments. In 2021, the United States Food and Drug Administration (FDA) approved aducanumab (Aduhelm) to treat AD, saying aducanumab is the first treatment targeting amyloid beta plaques in the brain [99]. Until recently, no treatment existed to modify AD and clinical drug trials in the past decade had a 99.6% failure rate [4]. This high failure rate was ascribed to how brain pathology commences before the arrival of objective cognitive symptoms.
While much-debated [100,101,102], the regulator conceded, “as did the FDA’s Peripheral and Central Nervous System Advisory Committee, that the clinical trial data were not adequate on their own to convincingly demonstrate a clinical benefit in reducing clinical decline in patients with Alzheimer disease” [103]. They granted accelerated approval because the clinical trial data offered strong suggestions of clinical benefit in the presence of a surrogate endpoint. Also, because the FDA saw solid data backing the finding that the surrogate endpoint is reasonably likely to predict clinical benefit [103].
Aducanumab is a monoclonal antibody that eliminates amyloid plaques but there are reservations whether the neuropathological amyloid removal guards against functional and cognitive decline in patients [104]. The antibody costs around US$56,000 per year per person [105].
Approval of aducanumab in Europe would be questionable as it is incompatible with the 2018 European Medicines Agency guidance on clinical trials for Alzheimer’s disease [104]. This heightened the need for trials to show functional and cognitive benefits instead of concentrating on surrogate endpoints like amyloid plaques [104]. Similarly, the UK National Institute for Health and Care Excellence would find it difficult to resolve uncertainties in clinical efficacy because of the treatment costs [104]. Patients require monthly intravenous infusions indefinitely and repeated magnetic resonance imaging to monitor for side effects like micro-haemorrhages.
On how to use the new drug, an Expert Panel drew up appropriate use in clinical practice guidelines. They recommended aducanumab for diagnoses of clinical criteria for MCI due to AD or mild AD dementia with amyloid positive PET or CSF findings consistent with AD [106]. A positive beta-amyloid test (PET scan or CSF assay) is useful because a diagnosis of AD through clinical determination does not consistently establish the presence of beta amyloid [107].
Yet, with the approval of aducanumab, several issues identified above are accentuated: accuracy of diagnosis using biomarkers, the accessibility of diagnosis as to who and how many can be diagnosed, and the high costs of biomarker use in clinical practice. The annual cost of the drug and of the patient monitoring required sharpens the MCI issues overall.
In July 2022 an article published in the journal Science by Charles Piller reported how a neuroscientist and physician at Vanderbilt University in the United States, Matthew Schrag, discovered seemingly falsified images in papers by neuroscientist Sylvain Lesné, of the University of Minnesota, Twin Cities [108]. This included a co-authored paper published by Nature in 2006, which linked AD with amyloid-beta (Aβ) protein Aβ*56.
Significantly for Aducanumab (Aduhelm), Piller commented,
Hundreds of clinical trials of amyloid-targeted therapies have yielded few glimmers of promise, however; only the underwhelming Aduhelm has gained FDA approval. Yet Aβ still dominates research and drug development. NIH spent about $1.6 billion on projects that mention amyloids in this fiscal year, about half its overall Alzheimer’s funding. Scientists who advance other potential Alzheimer’s causes, such as immune dysfunction or inflammation, complain they have been sidelined by the “amyloid mafia” [108].
The immediate reactions in digital publications and forums were varied [109,110,111]. References in the professional literature are slowly emerging. One comment was that research on AD has been misdirected for over 16 years, huge amounts of research dollars mis-spent, and “this shocking discovery calls for action and a change in the way we evaluate biomarkers in general” [112].
Another reference came from research on the efficacy of aducanumab, lithium, and a placebo for the treatment of cognitive decline in patients with MCI or AD [113]. Lithium was found to be significantly superior to aducanumab. The researchers cited recent doubts about the papers on the Aβ subtype in rats which could undermine the amyloid hypothesis of AD.
Later, two US House of Representatives committees investigated the regulatory review, approval, pricing, and marketing of aducanumab (Aduhelm). The report published in December 2022 found the FDA review and approval process “consisted of atypical procedures and deviated from the agency’s own guidance. These materials also reveal that Biogen had aggressive launch plans for Aduhelm—including in its label and pricing—despite concerns about efficacy, safety, and affordability” [114].
The congressional report also criticised the clinical trials which were inadequately inclusive of trial participants. The intellectual disability community had concerns that adults with Down syndrome were excluded from the trials and there was insufficient data on the safety and efficacy of aducanumab for use in this group [115], Most recently the FDA approved Leqembi (lecanemab-irmb) for the treatment of AD, via the accelerated approval pathway on January 6, 2023 [116]. Lecanemab targets the markers of amyloid in early AD [117].
Overall, focusing on AD biomarkers and overlooking AD clinical phenotypes are both problematic, since the data shows how a wholly biological definition of AD has low predictive accuracy [118]. AD is complex and it is doubtful that one therapy will generate a huge clinical benefit [119]. Ethicists have much to ponder on the ethics of disclosure, the ethical issues in early diagnosis, the new technology of biomarkers and novel and controversial pharmaceuticals like aducanumab.
Research Implications of MCI
Breakthroughs in cures for diseases come from research, and AD urgently needs some major treatment discovery. A consensus of researchers, clinicians and stakeholders in Manchester, UK, recommended patients be offered participation in research as a routine feature of clinical care [120]. This would involve data collection and clinical trials, subject to shared decision-making between patient and practitioner.
One recent strategy is to draw more participants from community sources for trials. Social networks are a way to improve awareness of trials such as online groups, and the uptake of electronic medical records is a possible technology supporting trial recruitment [121]. Away from the clinic, there are now internet-based computerised cognitive evaluation tools for pre-screening participants into early AD clinical trials [122]. Recruitment could also occur through non-medical sites like exercise and sports facilities which appear to be more successful than Alzheimer centres and memory clinics [123].
But any innovation must be properly evaluated. There are a number of issues specific to MCI research and to patients, which we now turn to.
Design of Trials
Like for most trials, if the sample size is too great then recruitment may take a long time, needlessly lengthening the experiment and delaying synthesis of evidence [124]. If the sample size is too small, then there is insufficient data to power the study. For example, a risk of poor internal validity arises when the MCI population is heterogeneous unless this is remedied by enlisting more volunteers [125].
Clinical trials also require “equipoise,” a situation where there is a current treatment for a defined patient population [126]. A new treatment becomes available, and investigators are genuinely uncertain about the relative merits of both treatments. Furthermore, if it is known that the treatments are not equivalent, ethics entails the superior treatment be recommended.
Some contend there ought to be robust evidence for the indication being treated in the proposed study, namely MCI. However, to be trialling treatments used for AD on some broad category of MCI contravenes ethical standards [127]. Additionally, it is problematic to reach clinical equipoise as there are concerns about the supposed MCI condition as a defined patient group being treated in the trial.
Another question in trial design is how preclinical AD or MCI populations differ in decision-making compared to AD populations. This has implications particularly as many facets of AD trial designs—the outcomes used to assess efficacy, the use of biomarkers, and the need for a study partner—have featured in research which developed to include earlier disease participants [128].
Mild Cognitive Impairment/Alzheimer’s Disease
The issues discussed about the MCI/AD relationship are applicable to trial design. The research essentially concentrates on the presumption that MCI leads to AD which results in published data advantaging current therapies and their limited effectiveness [129].
The goals of researchers simply reaffirm the MCI/AD relationship. They are principally interested in identifying individuals at risk for dementia rather than investigating MCI itself as a multifaceted phenomenon [77]. The trend is towards studying MCI solely as a precursor phase of dementia, yet it does not always progress to dementia [77].
There are associated methodology issues too. AD trial design characteristics in predementia trials are more easily accepted compared to MCI [128]. This overshadows challenging trials using invasive assessment methods e.g. lumbar puncture or PET, or more invasive treatments like vaccines or infusions. Greater willingness exists in participating as dementia patients rather than as MCI ones, suggesting AD dementia clinical trial designs may be problematic when used for preclinical AD and prodromal studies [128].
Harm to Patients
The risk of harm to patients is a pressing concern. Some wonder if it is ethical to trial biological agents on people with no symptoms but deemed at risk for future MCI [77]. This transforms asymptomatic people into patients where there are no indicators of illness.
There is a risk too of participant stigmatization. It becomes a challenge of “balancing the intention not to harm participants by using stigmatizing diagnostic labels such as MCI and informed consent being not valid in such cases because of lack of information” [125].
Patients can also become vulnerable. If recruitment includes those who received a MCI diagnosis, that information can result in a range of emotional responses [130]. Patients come with worries about their memory which prompts questions like, “Is this normal?” and “What is going to happen to me?” [131]. These patients “may or may not get worse. They may or may not get dementia. The ratio on either side of these questions is so large that it gives them no useful answer to their questions” [131].
Another issue is the risk of therapeutic misconception being higher in participants with MCI [125]. Therapeutic misconception is where research subjects assume that decisions about their care are being made only in light of their benefits, e g. they exclude the idea they may receive a placebo [132, 133].
Commitments Needed
Recruitment to studies depends on the costs and benefits perceived by participants and family members, e.g. a study of a diagnostic neuropsychological battery needed 1.5 to 2 h to complete [134]. This could have occasioned some distress to MCI patients aware of their impairment as it reminds them of their cognitive difficulties and then lead to reluctance to join [134].
Recruiting persons with MCI often means involving their study partner. While other participants with MCI may be interested to enrol, study partners frequently were unwilling to enrol because of the lack of MCI knowledge, not being available because of distance, and doubts regarding the benefits of research participation [135].
Inequalities
Research also should contemplate the needs of minority groups and possible effects on unequal differences in their health status [79]. Older patients diagnosed with MCI may be perceived like racial minorities who have been excluded from research [136]. This is an ethical challenge in soliciting participation of underserved populations for research, yet underserved and stigmatised groups may show hesitancy to be involved in research too [136].
Furthermore, most of those with MCI in a prevention trial, with or without an amyloid or tau biomarker, will not meaningfully progress over the usual one and half years of treatment and follow-up [124]. If complicated eligibility criteria are used, then it further limits or tilts the group towards the relatively healthier participants. This reduces the proportion of participants who would progress, leading to a healthier, socially advantaged, and non-diverse group rather than a more characteristically representative sample [124].
The Market
A final issue is the power of the market. There are pressures to identify research participants earlier and the determination of MCI also occurs in the context of a pharmaceutical market. This potentially includes up to half of those aged over sixty-five years who experience early phases of cognitive decline, conscious of their social environment and the vulnerability of neurodegeneration [129].
When potential treatments emerge, some scholars think the market ought not classify and assign terms for a disease.
We need to examine the possibility that MCI is principally an entity defined to create a market for a product of unknown value […] the worlds of leading researchers driven by their colleagues' results, and busy clinicians dependent on pharmaceutical representatives, are also laden with opinion and belief. Diagnostic evidence may come from scientific research, a clinician's anticipation of treatment success, or a sufferer's hopes and fears. Research-clinicians, though trying to relieve suffering, may be contributing to premature and speculative hype [129].
Nonetheless, while the pharmaceutical industry may be advancing treatments for MCI at a stride arguably unfavourable to clinical validity, it has a significant role as a market provider [130]. They responded to a shifting social outlook to ageing and quality of life for the elderly.
Others contest the claim that all MCI research and clinical projects are impelled by the pharmaceutical industry. Almost all the MCI research from the Mayo Clinic was supported by the National Institute on Aging (NIA) in the United States [137]. Similarly, Petersen notes the diagnosis from the Canadian Study of Health and Aging called cognitive impairment—no dementia (CIND) was not prompted by any markets expected by the pharmaceutical industry [137]. CIND was not studied in clinical trials since the general concept lacked the specificity needed to assess particular pharmaceutical interventions.
Overall, academics and clinicians acknowledge a need for more research and practice. However, the ethical questions remain. These pertain to the conceptual basis of research and its potential adverse effects on patients when balancing the interests of public health, healthcare services and private providers [79].
Discussion
The four challenges, namely, MCI diagnosis, links with AD, clinical implications, and research efforts, are closely related but their interconnections are not always recognised. The definition and diagnosis of MCI emerges from patients and their clinicians. MCI is also viewed as a preclinical stage of AD. Thus AD influences the definition, theories, and treatment of MCI.
Likewise, the relationship of MCI and AD affects patients and their families, for whom most ethical questions are poignant yet future-oriented. This is when attention turns to delaying dementia in the preclinical phases of the disease and to MCI. The preclinical category of MCI can be compared to the early stage of diseases such as diabetes, cancer, hypertension, and rheumatoid arthritis. Patients should know that MCI is different to age-related cognitive decline [138], and MCI is routinely linked with AD.
In a similar way, the clinical implications of MCI for treatment has natural dependence on the diagnosis and definition of MCI with outcomes for patients, positive and negative. Many will present themselves to services with what is understood as MCI, which occurs in up to a fifth of people aged over 65 years [6]. A study in the United States of 10,342 participants found the 2020 US Census–adjusted prevalence of all-cause MCI was 22.7% [139]. But an agreed definition has yet to be reached.
The prevalence of MCI is also affected by research methodology, sample characteristics and the view that there is no gold standard for assessing objective or subjective cognitive impairment [140]. Apart from conceptual and aetiological issues, AD casts a long shadow over MCI clinics. Yet, those clinics need insights from further research.
The research implications of MCI too cannot be separated from its definitions and diagnosis and the sociocultural perceptions of AD. Vice-versa, patients are perquisites for research and their well-being sets ethical preconditions for what can be approved and funded. Patient ethical considerations are research considerations.
The relationships among the four areas also feature in several uncertainties about MCI. Namely, that a relationship exists between AD and MCI, that MCI progresses to AD, and that there is a dependable system of classification of MCI.
On the AD and MCI relationship, consider predisease as a specific category. It may not always be coherent in a preventive strategy if predisease does not differentiate well, if the interventions offered are not effective, or if the harms exceed the benefits [141]. Here, predisease does not differentiate well: when MCI as preclinical to AD is evolving, MCI progression is not 100% determined, and MCI classification is varied and not dependable. The harms may outweigh the benefits when questions remain about diagnosing MCI and its implications.
Regarding the thinking that MCI likely progresses to AD, parallels can be drawn with cancer where investigation of a lump by a biopsy may turn out to be benign or malignant. Clinicians can explain the need for further diagnostic tests, the therapeutic options and their side-effects, the uncertainty in some treatments, and the possibility of participating in trials [142]. Likewise, MCI patients should be informed about global data which show that those diagnosed with MCI do not always progress to dementia like AD. As discussed, there are low rates of conversion to dementia, and even cases where a reversal has occurred.
The cancer analogy is significant in another sense. A survey of five countries: France, Germany, Spain, Portugal, and the United States, found that in four of those five countries, AD was the second biggest health fear after cancer; and approximately a quarter of adults in four of the five countries said they most feared getting AD [143].
MCI research also faces uncertainties. Biomarker results are perhaps too early now to be clinically useful for patients. In the current practice advice about biomarkers, their main purpose is to identify and characterise higher risk individuals to take part in trials [6]. If the discourse is about global health, then many countries of our world have no access to AD biomarkers [144]. This situation itself presents other ethical challenges. For pharmaceutical breakthroughs, the new drugs should be further investigated for safety and affordability.
Conclusions
The definition and diagnosis of MCI, its identity and relationship with AD, the ethical issues in early diagnosis and disclosures, and how research is necessary yet ethically centred on patients, are all interrelated. However, they are marked by an absence of consensus and directions. An apparent lack of connections in the description of essential terms and concepts can result in research and clinical silos or clusters [145].
Uncertainties in MCI overall as well as the underlying interrelationships invite investigations and solutions from numerous professions and the community. They should look for disciplinary links and collaborations with colleagues: for example, medical scientists joining forces with mental health and psychosocial practitioners. These experts could work alongside public health and public policy administrators and health economists.
Patients, healthcare systems and society are best served by informed clinicians, academics and researchers. After 35 years, the store of MCI knowledge is expanding and maturing.
References
Peters, K.R., and S. Katz. 2015. Voices from the field: expert reflections on mild cognitive impairment. Dementia 14 (3): 285–297.
Petersen, R.C., et al. 2014. Mild cognitive impairment: a concept in evolution. Journal of Internal Medicine 275 (3): 214–28.
Prince, M., R. Bryce, and C. Ferri. 2011. World Alzheimer report 2011: The benefits of early diagnosis and intervention. London: Alzheimer’s Disease International.
Anderson, N.D. 2019. State of the science on mild cognitive impairment (MCI). CNS Spectrums 24 (1): 78–87.
Caselli, R.J., et al. 2018. Personality changes during the transition from cognitive health to mild cognitive impairment. Journal of the American Geriatrics Society 66 (4): 671–678.
Livingston, G., et al. 2017. Dementia prevention, intervention, and care. The Lancet 390 (10113): 2673–734.
Mitchell, S.B., and S.E. Black. 2016. Screening for mild cognitive impairment: if not now, when? CMAJ 188 (1): 15–16.
Bengt, B., et al. 2016. Defeating Alzheimer’s disease and other dementias: a priority for european science and society. The Lancet Neurology 15 (5): 455–532.
Atri, A. 2019. The Alzheimer’s disease clinical spectrum: diagnosis and management. Medical Clinics of North America 103 (2): 263–293.
Brock, D.W. 1988. Justice and the severely demented elderly. The Journal of Medicine and Philosophy 13 (1): 73–99.
Fratiglioni, L., et al. 2000. Incidence of dementia and major subtypes in Europe: A collaborative study of population-based cohorts. Neurology 54 (11)Suppl 5: S10–S15.
American Psychiatric Association. 2013. Diagnostic and statistical manual of mental disorders, 5th Edition DSM-5. Arlington: American Psychiatric Association.
World Health Organization. 2018. 11th Revision of the international classification of diseases (ICD-11). World Health Organization https://icd.who.int/ and https://www.who.int/classifications/icd/revision/en. Accessed 24 May 2019.
George, D.R., P.J. Whitehouse, and J. Ballenger. 2011. The evolving classification of dementia: placing the DSM-V in a meaningful historical and cultural context and pondering the future of Alzheimer’s. Culture, Medicine, and Psychiatry 35 (3): 417–435.
Marcos, G., et al. 2016. Conversion to dementia in mild cognitive impairment diagnosed with DSM-5 criteria and with Petersen’s criteria. Acta Psychiatrica Scandinavica 133 (5): 378–85.
Grill, J.D., et al. 2017. Communicating mild cognitive impairment diagnoses with and without amyloid imaging. Alzheimer’s Research & Therapy 9: 35. https://doi.org/10.1186/s13195-017-0261-y.
Leuzy, A., et al. 2019. Clinical impact of [18F]Flutemetamol PET among memory clinic patients with an unclear diagnosis. European Journal of Nuclear Medicine and Molecular Imaging 46 (5): 1276–1286.
Prvulovic, D., and H. Hampel. 2011. Ethical considerations of biomarker use in neurodegenerative diseases–a case study of Alzheimer’s Disease. Progress in Neurobiology 95 (4): 517–519.
Smedinga, M., et al. 2018. Ethical arguments concerning the use of Alzheimer’s disease biomarkers in individuals with no or mild cognitive impairment: a systematic review and framework for discussion. Journal of Alzheimer’s Disease. 66 (4): 1309–1322.
Lineweaver, T.T., et al. 2014. Effect of knowledge of APOE genotype on subjective and objective memory performance in healthy older adults. The American Journal of Psychiatry 171 (2): 201–208.
Turnwald, B.P., et al. 2019. Learning one’s genetic risk changes physiology independent of actual genetic risk. Nature Human Behaviour 3 (2019): 48–56.
Campbell, N.L., et al. 2018. Anticholinergics influence transition from normal cognition to mild cognitive impairment in older adults in primary care. Pharmacotherapy 38 (5): 511–519.
Belleville, S. 2008. Cognitive training for persons with mild cognitive impairment. International Psychogeriatrics 20 (1): 57–66.
ten Brinke, L.F., et al. 2015. Aerobic exercise increases hippocampal volume in older women with probable mild cognitive impairment: A 6-month randomised controlled trial. The British Journal of Sports Medicine 49 (4): 248–254.
Holsinger, T., et al. 2012. Screening for cognitive impairment: Comparing the performance of four instruments in primary care. Journal American Geriatrics Society 60 (6): 1027–1036.
Gao, S., et al. 2014. Cognitive impairment, incidence, progression, and reversion: Findings from a community-based cohort of elderly African Americans. The American Journal of Geriatric Psychiatry 22 (7): 670–81.
Hoppe, S. 2019. Shifting uncertainties in the pre-diagnostic trajectory of early-onset dementia. Dementia 18 (2): 613–629.
Katz, S., and B.L. Marshall. 2018. Tracked and fit: Fitbits, brain games, and the quantified aging body. Journal of Aging Studies 45: 63–68.
Slot, R.E.R., et al. 2019. Subjective cognitive decline and rates of incident Alzheimer’s disease and non–Alzheimer’s disease dementia. Alzheimer’s & Dementia 15 (3): 465–476.
Reisberg, B., et al. 1988. Stage-specific behavioral, cognitive, and in vivo changes in community residing subjects with age-associated memory impairment and primary degenerative dementia of the alzheimer type. Drug Development Research 15 (2–3): 101–14.
Petersen, R.C., et al. 1999. Mild cognitive impairment: clinical characterization and outcome. Archives of Neurology 56 (3): 303–308.
Petersen, R.C., et al. 2009. Mild cognitive impairment: ten years later. Archives of Neurology 66 (12): 1447–1455.
Petersen, R.C., O. Lopez, M.J. Armstrong, et al. 2018. Practice guideline update summary: mild cognitive impairment report of the guideline development, dissemination, and implementation subcommittee of the American academy of neurology. Neurology 90 (3): 126–135.
Petersen, R.C. 2011. Mild cognitive impairment. New England Journal of Medicine 364 (23): 2227–2234.
Patnode, C.D., L.A. Perdue, R.C. Rossom, et al. 2020. Screening for cognitive impairment in older adults: updated evidence report and systematic review for the us preventive services task force. JAMA 323 (8): 776.
Knopman, D.S., and R.C. Petersen. 2014. Mild cognitive impairment and mild dementia: a clinical perspective. Mayo Clinic Proceedings 89 (10): 1452–59.48.
Grundman, M., et al. 2004. Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials. Archives of Neurology 61 (1): 59–66.
Vega, J.N., and P.A. Newhouse. 2014. Mild cognitive impairment: diagnosis, longitudinal course, and emerging treatments. Current Psychiatry Reports 16: 490. https://doi.org/10.1007/s11920-014-0490-8.
Gerstenecker, A., and B. Mast. 2015. Mild cognitive impairment: a history and the state of current diagnostic criteria. International Psychogeriatrics 27 (2): 199–211.
Albert, M.S., et al. 2011. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the national institute on Aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia 7 (3): 270–279.
Sperling, R.A., et al. 2011. Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the national institute on Aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia 7 (3): 280–292.
Liu, C., et al. 2013. Apolipoprotein E and Alzheimer disease: Risk, mechanisms and therapy. Nature Reviews Neurology 9: 106–118.
Petersen, R.C., et al. 1997. Aging, memory, and mild cognitive impairment. International Psychogeriatrics 9 (Suppl 1): 65–69.
Krance, S.H., et al. 2019. Reciprocal predictive relationships between Amyloid and Tau Biomarkers in Alzheimer’s disease progression: An empirical model. Journal of Neuroscience 39 (37): 7428–7437.
Bunnik, E.M., et al. 2018. On the personal utility of Alzheimer’s disease-related biomarker testing in the research context. Journal of Medical Ethics 44 (12): 830–834.
Molinuevo, J.L., et al. 2018. The rationale behind the new Alzheimer’s disease conceptualization: lessons learned during the last decades. Journal of Alzheimer’s Disease 62 (3): 1067–1077.
Petersen, R.C., O. Lopez, M.J. Armstrong, T.S.D. Getchius, M. Ganguli, D. Gloss, G.S. Gronseth, et al. 2018. Practice guideline update summary: mild cognitive impairment: report of the guideline development, dissemination, and implementation subcommittee of the American academy of neurology. Neurology 90 (3): 131.
Shridha, K., et al. 2016. DNA methylation markers for oral pre-cancer progression: a critical review. Oral Oncology 53: 1–9.
Howieson, D.B., et al. 2008. Trajectory of mild cognitive impairment onset. Journal of the International Neuropsychological Society 14 (2): 192–198.
Bensadon, B.A., and G.L. Odenheimer. 2013. Current management decisions in mild cognitive impairment. Clinics in Geriatric Medicine 29 (4): 847–871.
Klekociuk, S.Z., N.L. Saunders, and M.J. Summers. 2016. Diagnosing mild cognitive impairment as a precursor to dementia: Fact or fallacy? Australian Psychologist 51 (5): 366–373.
Manderson, L. 2014. Telling points. In Disclosure in health and illness, ed. M. Davis and L. Manderson, 1–15. Routledge: London and New York.
Werner, P., O. Karnieli-Miller, and S. Eidelman. 2013. Current knowledge and future directions about the disclosure of dementia: A systematic review of the first decade of the 21st century. Alzheimer’s & Dementia 9 (2): e74–e88.
Nielsen, K.D., and M. Boenink. 2021. Ambivalent anticipation: How people with Alzheimer’s disease value diagnosis in current and envisioned future practices. Sociology of Health and Illness 43: 510–527.
Porteri, C., et al. 2017. The biomarker-based diagnosis of Alzheimer’s disease. 1—ethical and societal issues. Neurobiology of Aging. 52: 132–140.
Marzanski, M. 2000. Would you like to know what is wrong with you? On telling the truth to patients with dementia. Journal of Medical Ethics 26: 108–113.
Beauchamp, T., and J. Childress. 2019. Principles of biomedical ethics: marking its fortieth anniversary. The American Journal of Bioethics 19 (11): 9–12.
McKinlay, A., J. Leathern, and P. Merrick. 2014. Diagnostic processes and disclosure: A survey of practitioners diagnosing cognitive impairment. New Zealand Journal of Psychology 43 (2): 20–31.
Fisk, J.D., B.L. Beattie, M. Donnelly, A. Byszewski, and F.J. Molnar. 2007. Disclosure of the diagnosis of dementia. Alzheimer’s & Dementia 3: 404–410.
Hategan, A., and G.L. Xiong. 2018. Major or mild neurocognitive disorder due to Alzheimer disease. In Geriatric psychiatry, ed. A. Hategan, et al., 369–401. Cham: Springer.
Stites, S.D., R. Milne, and J. Karlawish. 2018. Advances in Alzheimer’s imaging are changing the experience of Alzheimer’s disease. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring 10: 285–300.
Whitehouse, P.J. 2016. The diagnosis and treatment of Alzheimer’s: Are we being (Ir)Responsible? In Emerging technologies for diagnosing Alzheimer’s disease, ed. M. Boenink, H. van Lente, and E. Moors, 21–39. London: Palgrave Macmillan.
Garand, L., J.H. Lingler, K.O. Conner, and M.A. Dew. 2009. Diagnostic 6s, stigma, and participation in research related to dementia and mild cognitive impairment. Research in Gerontological Nursing 2 (2): 112–121.
Rosin, E.R., D. Blasco, A.R. Pilozzi, L.H. Yang, and X. Huang. 2020. A narrative review of Alzheimer’s disease stigma. Journal of Alzheimer’s disease 78 (2): 515–528.
Hagan, R.J. 2020. What next? Experiences of social support and signposting after a diagnosis of dementia. Health & Social Care in the Community 28: 1170–1179.
Dean, K., and G. Wilcock. 2012. Living with mild cognitive impairment: The patient’s and carer’s experience. International Psychogeriatrics 24 (6): 871–881.
Laakkonen, M.-L., et al. 2008. How do elderly spouse care givers of people with alzheimer disease experience the disclosure of dementia diagnosis and subsequent care? Journal of Medical Ethics 34 (6): 427–430.
van den Dungen, P., et al. 2014. Preferences regarding disclosure of a diagnosis of dementia: A systematic review. International Psychogeriatrics 26 (10): 1603–1618.
Schweda, M., et al. 2018. Prediction and early detection of Alzheimer’s dementia: Professional disclosure practices and ethical attitudes. Journal of Alzheimer’s Disease 62 (1): 145–155.
Fresson, M., et al. 2017. The effect of stereotype threat on older people’s clinical cognitive outcomes: Investigating the moderating role of dementia worry. The Clinical Neuropsychologist 31 (8): 1306–1328.
Stites, S.D., et al. 2017. Awareness of mild cognitive impairment and mild Alzheimer’s disease dementia diagnoses associated with lower self-ratings of quality of life in older adults. The Journals of Gerontology: Series B 72 (6): 974–985.
Degeling, C., R. Thomas, and L. Rychetnik. 2019. Citizens’ juries can bring public voices on overdiagnosis into policy making. BMJ 364: l351.
Maughan, D., and A. James. 2017. Diagnosis and treatment: Are psychiatrists choosing wisely? BJPsych Advances 23 (1): 9–15.
van Dijk, W., et al. 2016. Medicalisation and overdiagnosis: What society does to medicine. International Journal of Health Policy Management 5 (11): 619–22.
Brayne, C., and S. Kelly. 2019. Against the stream: Early diagnosis of dementia, is it so desirable? BJPsych Bulletin 43 (3): 123–125.
Strech, D., et al. 2013. The full spectrum of ethical issues in dementia care: Systematic qualitative review. British Journal of Psychiatry 202: 400–406.
Fang, M.L., K. Coatta, M. Badger, W. Sarah, M. Easton, L. Nygård, A. Astell, and A. Sixsmith. 2017. Informing understandings of mild cognitive impairment for older adults: Implications from a scoping review. Journal of Applied Gerontology 36 (7): 808–39.
Blatchford, L., and J. Cook. 2022. Patient perspectives about mild cognitive impairment: A systematic review. Clinical Gerontologist 45 (3): 441–453.
Chambers, D., A. Cantrell, K. Sworn, and A. Booth. 2022. Assessment and management pathways of older adults with mild cognitive impairment: Descriptive review and critical interpretive synthesis. Health and Social Care Delivery Research 10: 10. https://doi.org/10.3310/XLUJ6074.
Lohmeyer, J.L., Z. Alpinar-Sencan, and S. Schicktanz. 2021. Attitudes towards prediction and early diagnosis of late-onset dementia: A comparison of tested persons and family caregivers. Aging & Mental Health 25 (5): 832–843.
Gilleard, C., and P. Higgs. 2014. Studying dementia: The relevance of the fourth age. Quality in Ageing and Older Adults 15 (4): 241–243.
Libon, D.J., et al. 2010. The heterogeneity of mild cognitive impairment: A neuropsychological analysis. Journal of the International Neuropsychological Society 16 (1): 84–93.
R.A. Sperling et al. 2014. The A4 study: Stopping AD before symptoms begin? Science Translational Medicine 6 (228): 228fs13.
The Anti-Amyloid Treatment in Asymptomatic Alzheimer’s study (A4 Study). https://a4study.org. Clinical trial of Solanezumab for older individuals who may be at risk for memory loss (A4). ClinicalTrials.gov. https://clinicaltrials.gov/ct2/show/study/NCT02008357. Accessed 21 Feb 2020
Nelson, L., and N. Tabet. 2015. Slowing the progression of alzheimer’s disease; what works? Ageing Research Reviews 23: 193–209.
Chiong, W. 2018. Challenges in communicating and understanding predictive biomarker imaging for Alzheimer Disease. JAMA Neurology 75 (1): 18–19.
Vanderschaeghe, G., K. Dierickx, and R. Vandenberghe. 2018. Review of the ethical issues of a biomarker-based diagnoses in the early stage of Alzheimer’s disease. Journal of Bioethical Inquiry 15 (2): 219–230.
Zhang, X., et al. 2014. Ontology driven decision support for the diagnosis of mild cognitive impairment. Computer Methods and Programs in Biomedicine 113 (3): 781–791.
Suppiah, S., M.A. Didier, and S. Vinjamuri. 2019. The who, when, why, and how of PET amyloid imaging in management of Alzheimer’s disease—review of literature and interesting images. Diagnostics 9: 65. https://doi.org/10.3390/diagnostics9020065.
Thomas, K.R., et al. 2019. Artificially low mild cognitive impairment to normal reversion rate in the Alzheimer’s disease neuroimaging initiative. Alzheimer’s & Dementia 15 (4): 561–569.
Ferretti, G., A. Linkeviciute, and G. Boniolo. 2017. Comprehending and communicating statistics in breast cancer screening. In Ethical implications and potential solutions in medical ethics, prediction, and prognosis: Interdisciplinary perspectives, ed. M.G. Bondio, F. Sporing, and J.-S. Gordon, 30–41. New York: Routledge.
Larner, A.J. 2016. Short performance-based cognitive screening instruments for the diagnosis of mild cognitive impairment. Progress in Neurology and Psychiatry 20: 21–6.
Frisoni, G.B., M. Boccardi, F. Barkhof, et al. 2017. Strategic roadmap for an early diagnosis of Alzheimer’s disease based on biomarkers. The Lancet Neurology 16 (2017): 661–676.
Johnson, K.A., S. Minoshima, N.I. Bohnen, K.J. Donohoe, N.L. Foster, P. Herscovitch, J.H. Karlawish, et al. 2013. Appropriate use criteria for amyloid PET: A report of the amyloid imaging task force, the society of nuclear medicine and molecular imaging, and the Alzheimer’s association. Journal of Nuclear Medicine 54 (3): 477.
Lee, Y.S., H. Youn, H.G. Jeong, et al. 2021. Cost-effectiveness of using amyloid positron emission tomography in individuals with mild cognitive impairment. Cost Effectiveness and Resource Allocation 19: 50. https://doi.org/10.1186/s12962-021-00300-9.
Pearson, S.D., D.A. Ollendorf, and J.A. Colby. 2013. Biomarker tests for the diagnosis of Alzheimer’s disease: Generating evidence to inform insurance coverage determinations. Alzheimer’s & Dementia 9: 745–752.
Erickson, C.M., L.R. Clark, F.B. Ketchum, N.A. Chin, C.E. Gleason, and E.A. Largent. 2022. Implications of preclinical Alzheimer’s disease biomarker disclosure for US policy and society. Alzheimer’s & Dementia (Amsterdam, Netherlands) 14 (1): e12339. https://doi.org/10.1002/dad2.12339.
Arias, J.J., A.M. Tyler, B.J. Oster, and J. Karlawish. 2018. The proactive patient: Long-term care insurance discrimination risks of Alzheimer’s disease biomarkers. The Journal of Law, Medicine & Ethics 46 (2): 485–498.
Cavazzoni, P. 2021. FDA’s decision to approve new treatment for Alzheimer’s disease. The U.S. Food and Drug Administration. https://www.fda.gov/drugs/news-events-human-drugs/fdas-decision-approve-new-treatment-alzheimers-disease. Accessed 23 Oct 2021.
Mullard, A. 2021. Controversial Alzheimer’s drug approval could affect other diseases. Nature 595: 162–163.
Kuller, L.H., and O.L. Lopez. 2021. ENGAGE and EMERGE: Truth and consequences? Alzheimer’s & Dementia 17: 692–695.
The Lancet Neurology. 2021. A contentious FDA ruling for Alzheimer’s disease. The Lancet Neurology 20 (8): 585.
Dunn, B., P. Stein, and P. Cavazzoni. 2021. Approval of aducanumab for alzheimer disease—The FDA’s perspective. JAMA Internal Medicine 181 (10): 1278.
S. Walsh et al. 2021. Aducanumab for Alzheimer’s disease? BMJ 374 (1682): 5. https://doi.org/10.1136/bmj.n1682. Accessed 23 Oct 2021
Mullard, A. 2021. Landmark Alzheimer’s drug approval confounds research community. Nature 594: 309–310.
Cummings, J., et al. 2021. Aducanumab: Appropriate use recommendations. The Journal of Prevention of Alzheimer’s Disease 8 (4): 398–410.
Rabinovici, G.D. 2021. Controversy and progress in Alzheimer’s disease — FDA approval of aducanumab. New England Journal of Medicine 385: 771–774.
Piller, C. 2022. Blots on a field? Science 377 (6604): 358–363.
Graham, F. 2022. Red flags’ in key Alzheimer’s research. Nature Briefing. https://www.nature.com/articles/d41586-022-02081-4. Accessed 8 Sept 2022.
Rogers, M.D. 2022. Sylvain Lesné, who found Aβ*56, accused of image manipulation. Alzforum. https://www.alzforum.org/news/community-news/sylvain-lesne-who-found-av56-accused-image-manipulation. Accessed 15 Aug 2022.
Alzheimer’s Research UK. 2022. Research misconduct is serious – but research into Alzheimer’s is still on track. Alzheimer’s Research UK. https://www.alzheimersresearchuk.org/blog/research-misconduct-is-serious-but-alzheimers-research-is-still-on-track. Accessed 14 Sept 2022.
van Dijk, H., M. Koppenberg, and M. Arns. 2023. Towards robust, reproducible, and clinically actionable EEG biomarkers: large open access EEG database for discovery and out-of-sample validation. Clinical EEG and Neuroscience 54 (2): 103–105.
Terao, I., M. Honyashiki, and T. Inoue. 2022. Comparative efficacy of lithium and aducanumab for cognitive decline in patients with mild cognitive impairment or Alzheimer’s disease: A systematic review and network meta-analysis. Ageing Research Reviews 81: 101709. https://doi.org/10.1016/j.arr.2022.101709.
U.S. House of Representatives. 2022. The high price of Aduhelm’s approval: An investigation into FDA’s atypical review process and Biogen’s aggressive launch plans. https://democrats-energycommerce.house.gov/sites/democrats.energycommerce.house.gov/files/documents/Final%20Aduhelm%20Report_12.29.22.pdf
National Task Group on Intellectual Disabilities and Dementia Practices. 2023. Closure on Biogen's Aduhelm launch - congressional report. https://www.the-ntg.org/post/closure-on-biogen-s-aduhelm-launch-congressional-report. Accessed 14 Jan 2023
U.S. Food and Drug Administration. 2023. FDA grants accelerated approval for Alzheimer’s disease treatment. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/fda-grants-accelerated-approval-alzheimers-disease-treatment. Accessed 6 Feb 2023
van Dyck, C.H., C.J. Swanson, P. Aisen, R.J. Bateman, C. Chen, M. Gee, M. Kanekiyo, D. Li, L. Reyderman, S. Cohen, L. Froelich, S. Katayama, M. Sabbagh, B. Vellas, D. Watson, S. Dhadda, M. Irizarry, L.D. Kramer, and T. Iwatsubo. 2023. Lecanemab in early Alzheimer’s disease. New England Journal of Medicine 388 (1): 9–21. https://doi.org/10.1056/NEJMoa2212948.
Liu, K.Y., and R. Howard. 2021. Can we learn lessons from the FDA’s approval of Aducanumab? Nature Reviews Neurology 17: 715–722.
Petersen, R.C. 2021. Aducanumab: What about the patient? Annals of Neurology 90: 334–335.
Dunne, R.A., et al. 2021. Mild cognitive impairment: The Manchester consensus. Age and Ageing 50 (1): 72–80.
J.D. Grill and J.E. Galvin (2014). Facilitating Alzheimer disease research recruitment. Alzheimer Disease & Associated Disorders. 28l (1): 1–8.
Zavitz, K. 2018. A solution for improving recruitment into early Alzheimer’s disease clinical trials. Cambridge Cognition, https://www.cambridgecognition.com/blog/entry/a-solution-for-improving-recruitment-into-prodromal-alzheimers-disease-tria. Accessed 25 Jan 2020
Sanders, M.L., Stuckenschneider, T., Devenney, K.E., …, Schneider, S., Olde Rikkert, M.G.M. 2018. Real world recruiting of older subjects with mild cognitive impairment for exercise trials: Community readiness is pivotal. Journal of Alzheimer's Disease 62 (2): 579–581.
Lee, J., R.S. Howard, and L.S. Schneider. 2022. The current landscape of prevention trials in dementia. Neurotherapeutics. 19: 228–247.
Götzelmann, T.G., D. Strech, and H. Kahrass. 2021. The full spectrum of ethical issues in dementia research: Findings of a systematic qualitative review. BMC Medical Ethics 22: 32. https://doi.org/10.1186/s12910-020-00572-5.
Freedman, B. 1987. Equipoise and the ethics of clinical research. The New England Journal of Medicine 317 (3): 141–145.
Graham, J.E., and K. Ritchie. 2006. Reifying relevance in mild cognitive impairment: An appeal for care and caution. Philosophy, Psychiatry, & Psychology 13 (1): 57–60.
Nuño, M.M., D.L. Gillen, K.K. Dosanjh, et al. 2017. Attitudes toward clinical trials across the Alzheimer’s disease spectrum. Alzheimer’s Research & Therapy 9: 81. https://doi.org/10.1186/s13195-017-0311-5.
Graham, J.E., and K. Ritchie. 2006. Mild cognitive impairment: Ethical considerations for nosological flexibility in human kinds. Philosophy, Psychiatry, & Psychology 13 (1): 31–43.
Guzmán, A., D. Gillanders, A. Stevenson, and K. Ross. 2021. Psychosocial adjustment to mild cognitive impairment: The role of illness perceptions, cognitive fusion and cognitive impairment. Dementia 20 (2): 464–484.
Ticehurst, S. 2006. Mild cognitive impairment: Kinds, ethics, and market forces. Philosophy, Psychiatry, & Psychology 13 (1): 54.
Appelbaum, P.S., L.H. Roth, and C. Lidz. 1982. The therapeutic misconception: Informed consent in psychiatric research. International Journal of Law and Psychiatry 5 (3–4): 319–329.
Appelbaum, P.S., L.H. Roth, C.W. Lidz, P. Benson, and W. Winslade. 1987. False hopes and best data: Consent to research and the therapeutic misconception. The Hastings Center Report 17 (2): 20–24.
Brambilla, M.M., et al. 2021. Challenges to recruitment of participants with MCI in a multicentric neuropsychological study. Aging Clinical and Experimental Research 33 (7): 2007–2010.
Gibson, A., S.H. Bardach, C.N. Pope, E.K. Rhodus, D.C. Oaks, and G.A. Jicha. 2021. Lessons learned on recruiting dyads for mild cognitive impairment clinical trials. Alzheimer’s & Dementia 17: e052397. https://doi.org/10.1002/alz.052397.
Schneider, Christine and Eva Kahana. 2019. Challenges of participating in research about living with mild cognitive impairment among disabled veterans. In: Research involving participants with cognitive disability and difference: Ethics, autonomy, inclusion, and innovation, eds. M. Ariel Cascio and Eric Racine, 99–108. Oxford: Oxford University Press.
Petersen, R.C. 2006. Mild cognitive impairment is relevant. Philosophy, Psychiatry, & Psychology 13 (1): 45–49.
Celsis, P. 2000. Age-related cognitive decline, mild cognitive impairment or preclinical Alzheimer’s disease? Annals of Medicine 32 (1): 6–14.
Rajan, K.B., et al. 2021. Population estimate of people with clinical Alzheimer’s disease and mild cognitive impairment in the United States (2020–2060). Alzheimer’s & Dementia. https://doi.org/10.1002/alz.12362.
Teh, W.L., et al. 2021. Prevalence, lifestyle correlates, and psychosocial functioning among multi-ethnic older adults with mild cognitive impairment in Singapore: Preliminary findings from a 10/66 population study. The Yale Journal of Biology and Medicine 94 (1): 73–83.
Viera, A.J. 2011. Predisease: When does it make sense? Epidemiologic Reviews 33 (1): 122–134.
Fallowfield, L., and V. Jenkins. 2004. Communicating sad, bad, and difficult news in medicine. The Lancet 363: 312–319.
Blendon, R., J. Benson, E. Wikler, K. Weldon, M. Baumgart, S. Jansen, B. Kallmyer, S. Hume, M. Micas, D. Religa, and J. Georges. 2011. P4–395: Five-country survey of public experiences, attitudes and beliefs concerning Alzheimer’s disease and the value of a diagnosis. Alzheimer’s & Dementia 7: e50–e50. https://doi.org/10.1016/j.jalz.2011.09.209.
Jessen, F., and L. Frölich. 2018. ICD-11: Neurokognitive störungen. Fortschritte der Neurologie Psychiatrie 86 (3): 172–177.
Collyer, T.A., and K.E. Smith. 2020. An atlas of health inequalities and health disparities research: “How is this all getting done in silos, and why?” Social Science & Medicine 264: 113330.
Funding
Open Access funding enabled and organized by CAUL and its Member Institutions
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author has no relevant financial or non-financial interests to disclose.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Lee, J. Mild Cognitive Impairment in Relation to Alzheimer’s Disease: An Investigation of Principles, Classifications, Ethics, and Problems. Neuroethics 16, 16 (2023). https://doi.org/10.1007/s12152-023-09522-5
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12152-023-09522-5