Defining and Measuring Cognitive Decline and Clinical Relevance

Abstract

Current frameworks for cognitive impairment increasingly incorporate biomarker information, yet clinical classification remains grounded in the demonstration of objective cognitive decline and its functional consequences. This paper examines the balance between biological and clinical definitions and discusses implications for diagnosis, care, and research. Mild cognitive impairment (MCI) or mild neurocognitive disorder represents a clinically meaningful intermediate stage between normal aging and dementia, enabling early detection, timely intervention, and longitudinal monitoring. In routine care, comprehensive neuropsychological testing for all patients is not feasible; instead, a tiered diagnostic approach combining brief screening, clinical assessment, informant information, and targeted referral appears most practical and diagnostically robust. In research settings, outcomes that integrate cognitive performance with functional measures better capture clinically meaningful change than cognition-only endpoints. However, heterogeneity in definitions and outcome measures limits comparability across studies, and challenges remain regarding feasibility, cultural validity, and the integration of patient-relevant outcomes. Clinically useful definitions of cognitive impairment should integrate objective deficits with real-world impact. Pragmatic staged diagnostic pathways are best suited for routine care, while future work should focus on standardization, feasibility, and the alignment of research outcomes with patient-relevant benefits.

Key Summary Points

Cognitive decline is increasingly defined biologically, but clinical relevance remains insufficiently operationalized.

Objective cognitive deficits, and when available informant information, should form the backbone of diagnostic decision-making.

Multimodal assessment is ideal but often not feasible in routine care.

Adjustment for demographic, education and cultural variables remains a major challenge.

Clinically meaningful definitions must be applicable in real-world care settings.

Patient-relevant outcomes, lived experience, and real-world functioning must be integrated into definitions of clinically meaningful decline.

Introduction

The prevalence of cognitive impairment and dementia is steadily increasing, placing a growing strain on healthcare systems worldwide [1]. Alongside this epidemiological development, there is increasing recognition that how these conditions are defined and diagnosed critically shapes clinical care, research, and health policy. In this context, the conceptualization of Alzheimer’s disease (AD) and related disorders is undergoing a fundamental shift: traditionally, AD has been defined as a clinical entity, with diagnosis and treatment decisions based primarily on the presence of cognitive symptoms and their functional consequences [2]. However, advances in biomarker research now allow underlying neurodegenerative processes to be detected long before overt clinical symptoms appear, enabling a biologically grounded definition of disease to be established [2, 3]. In the context of AD, the most established biomarkers include cerebrospinal fluid Aβ42/40 ratio and phosphorylated tau (p-tau), molecular imaging biomarkers obtained through nuclear medicine techniques such as amyloid positron emission tomography (PET) and tau PET, and emerging blood-based biomarkers such as plasma p-tau217. These biomarkers reflect distinct pathological processes including amyloid deposition, tau pathology, and neurodegeneration and currently provide the strongest evidence base for biomarker-supported diagnosis [3]. Comparable biomarker frameworks remain substantially less developed for most non-AD dementias. They also provide a foundation for the development of disease-modifying therapies that target specific pathophysiological mechanisms. Nevertheless, important limitations remain. Biomarker positivity does not necessarily indicate current or future clinical impairment at an individual level and interpreting such findings in routine care is often challenging, particularly if measured in asymptomatic individuals. In fact, the Alzheimer’s Association Workgroup currently discourages biomarker testing for asymptomatic individuals in clinical practice [3, 4]. Overreliance on biological definitions can disconnect diagnosis from clinically meaningful outcomes, such as functional decline, patient experience, care partner burden, and real-world impact [2].

Consequently, a gap persists between the biological definition of disease and its pragmatic application in clinical practice. Although biomarkers can improve diagnostic accuracy, clinical decision-making still relies on a detailed history from the patient, and, when available, a reliable informant, a comprehensive neurological examination, assessing cognitive performance, determining functional status, and applying individual context [5–7]. Therefore, balancing these perspectives is essential to ensure that advances in disease characterization translate into meaningful benefits for patients.

This review primarily focuses on the AD continuum, where biomarker-supported diagnostic pathways are currently most advanced [3]. Other neurodegenerative and vascular cognitive disorders are discussed where relevant to differential diagnosis, mixed pathology, and the broader applicability of clinically meaningful outcome assessment. The limitation of biomarker positivity is that it does not equate to clinical disease [8]. A significant number of cognitively unimpaired older adults show signs of amyloid pathology yet remain clinically stable for extended periods [9]. The risk of progression depends on age, the combination of biomarkers present, coexisting pathologies, genetic background, cognitive reserve, and the length of the follow-up period [10]. Furthermore, predictive values vary substantially according to pre-test probability and clinical setting. Interpreting biomarkers is further complicated by mixed pathologies, assay variability, and uncertainty regarding optimal thresholds [11–13]. Consequently, biomarker findings should be interpreted as probabilistic indicators of underlying pathology rather than as definitive predictors of future cognitive decline [2, 14].

Conceptual Definitions

Biomarkers can refine etiological classification and provide information about underlying pathophysiology, but they do not replace the clinical identification of a cognitive syndrome. Current frameworks, including National Institute on Aging–Alzheimer’s Association (NIA-AA) criteria for mild cognitive impairment (MCI) and dementia, and Diagnostic and Statistical Manual (DSM)-5-based concepts, emphasize that diagnosis must remain anchored in objectively measurable cognitive decline and its functional consequences [5–7, 15]. In particular, the International Working Group (IWG) workgroups distinguish between core clinical criteria applicable across settings and biomarker-informed approaches that currently serve to increase diagnostic certainty, primarily in research contexts [2]. Recent efforts have also proposed broader and potentially less stigmatizing terminology, such as “Adult Cognitive Disorders,” although these concepts have not yet been widely adopted in clinical practice or research frameworks [16]. At the same time, the strictly biological definition proposed by Jack et al. conceptualizes AD based on biomarker profiles independent of clinical symptoms [3]. While this biologically grounded approach offers the potential advantages of perceived objectivity and specificity needed for research purposes such as clinical trials, it may be less directly applicable to real-world clinical decision-making, which continues to depend on the assessment of cognitive performance, functional impact, and clinical context.

To integrate these perspectives, a stage-spanning operational framework is required that links biological disease processes with clinically meaningful outcomes across the disease continuum. As illustrated in Fig. 1, AD can be conceptualized as a continuous process ranging from biomarker-positive asymptomatic states to severe dementia, in which the same core domains—cognition, function, global clinical status, and patient-relevant outcomes—are assessed throughout, but their relative importance shifts with disease stage [2, 17]. In early stages, biomarker status and sensitive cognitive measures dominate, whereas in later stages, functional decline, global clinical status, behavioral manifestations, care partner burden, and quality of life become the primary determinants of clinical relevance [18, 19]. Importantly, this framework reflects regulatory perspectives from both European Medicines Agency (EMA) and U.S. Food and Drug Administration (FDA), which emphasize that clinical benefit cannot be established by cognitive or biomarker changes alone, but requires demonstration of meaningful impact on function, independence, or disease progression [20, 21].

Fig. 1.

Biomarker-informed outcome assessment across the AD continuum, illustrating a stage-based framework spanning from biomarker-positive asymptomatic states, subtle pre-symptomatic change, to dementia. Core domains (cognition, function, global clinical status, quality of life, neuropsychiatric symptoms, and time-to-event outcomes) are assessed across all stages, with shifting emphasis from biomarker detection and subtle cognitive changes in early disease to functional impairment and patient-relevant outcomes in later stages. Early stages may include subjective cognitive concerns despite performance within normal limits on standardized testing. Clinically meaningful progression is reflected by transitions to MCI and dementia. Cognitive outcomes should be interpreted relative to age-, sex-, and education-adjusted normative data and—where possible—ideally reported as standardized scores (e.g., z-scores) to facilitate longitudinal and between-group comparisons

Aside from the definition, the clinical relevance of detecting MCI lies in the fact that it identifies an intermediate and potentially important window for early detection, monitoring, counseling, risk reduction, and emerging disease-modifying treatment strategies [22]. However, the construct is susceptible to diagnostic inaccuracy, as non-specific symptoms and variable thresholds can lead to over diagnosis if objective impairment, longitudinal change, and functional context are not carefully established [23, 24].

Clinical Relevance Beyond Biomarkers

Functional impairment refers to the extent to which cognitive deficits translate into difficulties and eventual loss of independence in everyday activities, ranging from complex instrumental tasks to basic activities of daily living. Closely related, the concept of everyday cognition captures how cognitive abilities are expressed in real-world contexts, often differing from performance on standardized neuropsychological tests conducted under controlled conditions [25]. Assessing these domains therefore requires approaches beyond traditional testing, including informant-based questionnaires, performance-based measures, and structured evaluations of daily functioning [19]. Common instruments include scales of instrumental activities of daily living, the Everyday Cognition questionnaire, and combined cognitive–functional measures developed for clinical trials [26]. Increasingly, patient-reported outcomes and care partner input are incorporated to capture intra-individual change and patient-relevant impact, such as loss of independence or reduced quality of life. Together, these approaches aim to provide a more ecologically valid and clinically meaningful assessment of cognitive disorders.

Contextualizing Cognitive Assessment: Setting, Resources, and Diagnostic Objectives

The increasing availability of biomarker information does not eliminate the need for cognitive and functional assessments. In fact, biomarker-informed diagnosis makes it even more important to determine whether biological abnormalities lead to clinically significant cognitive decline and functional impairment. Consequently, the long-standing challenges associated with cognitive assessment become more relevant in the biomarker era. Objective cognitive testing remains the foundation of assessing cognitive decline, providing standardized and comparable measures across cognitive domains [25]. However, performance under structured testing conditions does not necessarily reflect cognitive functioning in everyday life [19]. Self-reported complaints and informant-based assessments can provide valuable clinical information, especially in the early stages. However, they may be influenced by factors such as insight, mood, and cultural or educational background. As a result, no single modality can be considered sufficient on its own.

In many clinical contexts—particularly in non-specialist or outpatient settings—assessment strategies need to balance diagnostic depth with feasibility.

A stepped or tiered diagnostic approach may provide a pragmatic framework to achieve this balance, but should not start as a universal population-wide screening in asymptomatic older adults. The entry point should usually be a clinical setting in which concerns have already been raised, such as a primary care setting, a tertiary outpatient clinic (e.g., a memory clinic, neurology clinic, or psychiatry clinic) or structured preventive health assessments, including preventive counseling services for individuals with subjective cognitive complaints, informant concerns, relevant risk factors, or observed functional changes. This distinction is important because current evidence remains insufficient to support universal stand-alone screening for cognitive impairment in asymptomatic older adults, particularly in the absence of clearly defined care pathways, reimbursement structures, and evidence for patient-relevant benefit [27, 28]. In an initial step, low-threshold case finding should integrate brief cognitive testing with clinical history and contextual factors, ideally complemented by subjective and informant-based information, recognizing that such tools can support detection but are insufficient as stand-alone diagnostic measures [29]. In a second step, positive or ambiguous findings should be clinically contextualized through structured assessment of functional status, informant input, neuropsychiatric features, and longitudinal change, as clinical relevance depends on real-world impact, and this helps reduce false positives and improve differential diagnosis [24, 30]. In a third step, targeted escalation should be reserved for cases in which diagnostic clarification would meaningfully affect management, involving selected use of advanced assessments such as neuropsychological testing and biomarkers, which should be interpreted within clinical context rather than as stand-alone screening tools [8, 13]. A key limitation of such approaches lies in their unclear implementation within current healthcare systems, where responsibilities, referral pathways, reimbursement structures, and longitudinal care concepts remain insufficiently defined [31]. Although this review primarily focuses on AD, mixed and vascular pathologies are briefly considered because they may affect biomarker interpretation, clinical presentation, and outcome assessment. Figure 2 highlights the substantial contribution of vascular pathology to dementia burden [11, 32].

Fig. 2.

Frequency of dementia subtypes and implications for pragmatic prevention strategies. Given that vascular pathology contributes to approximately half of dementia cases—either alone or in combination with neurodegenerative disease—prevention and diagnostic strategies should incorporate vascular risk assessment and management rather than focusing solely on Alzheimer-type pathology [11, 33]

Therefore, given these uncertainties, it remains unclear which individuals truly benefit from cognitive assessment and subsequent diagnostic escalation, particularly in settings where biomarker-supported diagnostic pathways and disease-modifying therapies apply only to narrowly defined early AD populations and may not yet translate into broadly accessible or reimbursed care pathways for all eligible patients [34, 35]. Thus, a future-oriented stepped approach should not be limited solely to earlier detection and diagnosis but be embedded in a broader framework of cognitive resilience and dementia prevention in primary care, integrating vascular and lifestyle risk-factor reduction, prevention counseling, longitudinal cognitive monitoring, culturally fair assessment tools, and clearly defined referral criteria [10, 36]. This is further supported by recent evidence showing that modifiable vascular and lifestyle-related factors play a major role even in early-onset dementia [37, 38]. Future studies should therefore evaluate which patient groups truly benefit from such an approach, and whether it can be implemented effectively, equitably, and sustainably within real-world healthcare systems [39, 40].

Rather than uniformly aiming for maximal diagnostic precision, it is often appropriate to combine brief objective cognitive testing with clinical assessment and, where available, informant input. Such a multimodal and scalable approach can accommodate real-world constraints while still capturing clinically meaningful change and enabling the identification of individuals at increased risk for cognitive decline, which is central to dementia prevention efforts across settings.

Global cognitive measures, such as brief screening instruments or composite scores derived from neuropsychological test batteries, provide a practical and widely used estimate of overall cognitive status [41–43]. These approaches are particularly useful for capturing global change over time and for use in routine clinical settings. However, many commonly used instruments were originally developed in the context of AD and are therefore primarily optimized to detect amnestic patterns of impairment. As a result, they may be less sensitive to non-Alzheimer neurodegenerative disorders, including frontotemporal degeneration, Lewy body disease, or vascular cognitive impairment, which often present with non-amnestic cognitive profiles [44, 45]. Alternatively, global indices of cognitive health may predict the risk of future neurodegenerative disease [46].

Accordingly, the selection and depth of cognitive assessment should be aligned with the underlying clinical or research question. While a global cognitive measure may be sufficient for identifying individuals within the AD spectrum, broader diagnostic goals require additional domain-specific testing to capture syndrome-specific profiles. This implies that diagnostic stratification needs to be defined a priori and embedded in the assessment strategy.

Across all stages, cognitive assessment should be complemented by a structured cross-sectional evaluation of patient-centered outcomes, including functional status in activities of daily living [47], health-related quality of life [48], subjective cognitive complaints [49], and informant-based assessments of real-world functioning [50]. Neuropsychiatric and behavioral symptoms, such as those captured by the Mild Behavioral Impairment Checklist, further contribute to clinically meaningful disease characterization [51].

The relative importance of these domains shifts across disease stages. In early stages, sensitive cognitive measures and subjective or informant-reported changes may be most informative, whereas in later stages functional impairment, caregiver report, and global clinical status become the primary determinants of clinical relevance. Accordingly, detailed neuropsychological testing becomes less feasible and less informative in moderate to severe dementia due to floor effects, reduced cooperation, and communication limitations [52]. At these stages, assessment should rely primarily on functional dependency, informant-based information, and clinician-rated global status rather than detailed cognitive profiling. Overall, a staged, question-driven, and patient-centered assessment strategy is essential to capture clinically meaningful change while remaining feasible in real-world clinical settings, and should be adapted to the specific care setting, available resources, and the intended diagnostic target, including differentiation of dementia subtypes.

Norms and Cut-Offs

The biomarker era has emphasized the importance of robust cognitive definitions and threshold determination, since biological evidence of pathology can appear many years before clinically detectable impairment. Consequently, the selection of cognitive cut-offs is becoming an increasingly important factor in the classification and management of biomarker-positive individuals. Although conceptual definitions of cognitive impairment and AD have become increasingly refined in recent years, their operationalization remains heterogeneous across settings [12]. Current frameworks, such as those by the IWG and the NIA-AA provide structured diagnostic principles, but reflect distinct conceptual approaches, with the latter emphasizing a primarily biological definition and the former requiring a clinical–biological combination. Third, the development of harmonized outcome frameworks and core outcome sets, including standardized normative samples and clinically validated cutoffs, may enhance consistency across clinical trials and observational studies [2, 17, 53]. Previous research has demonstrated that the choice of normative reference group can substantially influence cognitive classification, with participants being 1.5–2 times more likely to be classified as having MCI when study-specific healthy control norms rather than published population norms are used, which has implications for both clinical practice and clinical trials [53]. This variability reflects the difficulty of delineating disease states along a continuum spanning asymptomatic, at-risk, prodromal, and clinically manifest stages. In particular, the distinction between “disease,” “preclinical,” and “at-risk” states remains inherently uncertain, especially in biomarker-positive but cognitively unimpaired individuals. The IWG framework explicitly addresses this by classifying such individuals as at risk rather than diseased, acknowledging uncertainty in individual trajectories and progression. At the same time, growing evidence suggests that greater standardization could meaningfully improve comparability, validity, and clinical utility. For example, studies demonstrate substantial diagnostic discordance when applying different criteria to the same individuals, particularly in early disease stages, underscoring the need for harmonized operational definitions [12].

Several concrete strategies for improving standardization have been proposed. First, harmonization of cognitive measures across cohorts—using approaches such as item response theory or cross-cohort composite scores—can reduce bias introduced by heterogeneous test batteries and enable comparability across studies [54, 55]. These approaches explicitly address the problem that differences in instruments, rather than true cognitive variation, often drive observed discrepancies. Second, refinement of diagnostic thresholds through more robust neuropsychological criteria—such as requiring impairment across multiple tests within a domain rather than single-test cut-offs—has been shown to improve diagnostic stability, biomarker associations, and prediction of progression [30]. This suggests that standardization should not only target biomarkers but also cognitive phenotyping. Third, the development of harmonized outcome frameworks and core outcome sets may enhance consistency across clinical trials and observational studies. Consensus efforts highlight the need for combining multiple outcome measures to adequately capture clinically meaningful change and improve ecological validity [18, 56]. Finally, emerging approaches emphasize the importance of anchoring thresholds to clinically meaningful change, for example through minimal clinically important difference frameworks, which aim to link statistical change to patient-relevant outcomes and may support more interpretable cut-offs [57]. Additional approaches include the use of reliable change indices which utilize psychometric properties of the cognitive test to help determine whether an observed change in an individual person is due to change, practice effects, or measurement error [58]. Ecological momentary assessment and other real-world, longitudinal cognitive assessments could improve the detection of subtle changes in cognition and intra-individual variability over time [59]. Additionally, the presence or absence of anticipated practice effects may serve as a sensitive indicator of early cognitive decline.

Taken together, these approaches suggest that the central challenge is not the absence of definitions, but the need for more consistent and empirically grounded operationalization. A pragmatic path forward may therefore lie in combining harmonized measurement strategies, refined threshold definitions, and longitudinal, clinically anchored interpretation, rather than relying on fixed cut-offs alone.

Practical Implementation

A key challenge in translating diagnostic frameworks into clinical practice lies in balancing validity with feasibility. In routine care, particularly in primary care settings, this requires pragmatic, stepwise approaches that integrate brief cognitive assessment with clinical context, rather than relying on comprehensive testing for all individuals [27–29]. At the same time, implementation should be guided by the underlying diagnostic objective and linked to clinically meaningful benefit, recognizing that the value of assessment depends on its impact on patient-relevant outcomes and may vary across disease stages [60, 61].

Feasibility constraints, including time, waiting times for neuropsychological evaluations, resources, and cultural factors, further necessitate scalable and patient-centered strategies that combine risk stratification with contextual interpretation, as subjective cognitive complaints are common but only partly reflect underlying neurodegenerative disease [29, 30, 39, 62–65]. However, several key uncertainties remain that are critical for implementation: more precise data are needed on dementia subtypes and their relative contributions, on which individuals derive meaningful benefit from diagnostic assessment and escalation, and on how assessment strategies should be adapted across the longitudinal disease course, particularly given that differentiation between underlying etiologies may remain difficult in early stages due to overlapping clinical presentations and mixed pathologies [11]. In later stages, where formal cognitive testing becomes less feasible, clinical decision-making increasingly relies on functional and informant-based information.

Research and Trials

In clinical trials, particularly in early disease stages, purely cognitive or biomarker endpoints may be too narrow to adequately capture disease progression and clinically meaningful change [66]. Evidence supports the use of combined cognitive, biological, and functional measures, as these better reflect real-world decline and potential treatment benefit [18, 19, 25].

Many clinical trial endpoints, such as the Clinical Dementia Rating Scale and the Alzheimer’s Disease Assessment Scale–Cognitive Subscale were designed for, and validated within, individuals with Alzheimer’s disease, potentially limiting their utility among individuals with other forms of dementia [44, 45, 67]. Efforts are underway to develop disease-specific composite clinical trial endpoints for cognition [67–69].

At the same time, the substantial heterogeneity of outcome measures across studies limits comparability, complicates meta-analyses, and hampers the interpretation of clinical relevance. Harmonization of cognitive and functional endpoints—through standardized composites or cross-cohort alignment approaches—can improve comparability and increase sensitivity to disease-related change [54–56]. Finally, there is increasing recognition that patient-relevant outcomes should be more fully integrated into trial design. Beyond cognitive performance, clinically meaningful endpoints include the preservation of functional independence, longitudinal stability of everyday functioning, and maintenance of social participation. In early disease stages, slowing decline or delaying functional impairment may be more meaningful than short-term cognitive change alone. In addition, quality of life, neuropsychiatric symptoms, and caregiver burden are important dimensions of disease impact. Incorporating such outcomes improves clinical interpretability and aligns trial endpoints more closely with patient and caregiver priorities but will require regulator acceptance of such outcomes and their measures [70].

Clinical Decision-Making

Diagnostic decision-making in cognitive disorders should not rely on isolated test scores but instead integrate objective cognitive performance, functional impact, longitudinal course, and clinical context. Established frameworks emphasize that distinctions such as mild cognitive impairment versus dementia depend on the combination of measurable deficits and their relevance for everyday functioning within the broader clinical picture [5, 7, 30]. With the increasing role of biomarkers, this integrative approach must also account for ethical considerations related to testing and disclosure, including informed consent, communication, and the interpretation of prognostic uncertainty. This is particularly relevant in early or asymptomatic stages, where the predictive value of biomarker positivity remains limited and potential psychological and practical consequences must be carefully weighed [71, 72]. A key unresolved issue in evaluating anti-amyloid therapies is what constitutes a truly patient-relevant outcome, particularly in pre-symptomatic individuals, where changes in biomarkers or cognitive scales may remain below clinical relevance. Slowing of decline is only meaningful if it translates into preserved function or delayed symptom onset, yet reductions in amyloid burden have not consistently resulted in clinically meaningful benefit, and trials in early AD have shown limited clinical efficacy despite target engagement [73, 74]. Regulatory guidance reflects these uncertainties. Both the FDA and EMA emphasize that effects on biomarkers or cognitive scales alone are insufficient to establish clinical benefit, highlighting the need for outcomes that capture tangible clinical change or delay to meaningful disease milestones [20, 21].

Taken together, measurable cognitive effects without corresponding functional benefit are insufficient to demonstrate meaningful efficacy, underscoring a persistent gap between biomarker-driven strategies and clinically relevant outcomes. Accordingly, outcome assessment in AD should be anchored in clinically meaningful change, integrating cognitive performance, functional impact, and patient-relevant outcomes, as outlined in Table 1.

Table 1.

Conceptual framework for outcome domains, operationalization, and clinically meaningful event definitions across the AD continuum [18, 26, 30, 53, 58, 66, 75]

Outcome domain	What should be captured	How it should be operationalized	Clinically meaningful event definition
Cognition	Objective change in cognitive performance across relevant domains	Standardized, longitudinally comparable cognitive assessment; stage-sensitive scoring; composites may be preferable in early stages	Longitudinal cognitive decline confirmed by reliable change indices accounting for practice effects and test reliability, not only cross-sectional impaired performance
Function	Everyday functioning, especially instrumental and later basic daily activities	Structured assessment of daily function using informant-supported and/or performance-relevant approaches	Clinically relevant decline in independence or day-to-day functioning
Global clinical status	Overall clinical change across cognition, function, and clinical context	Integrated clinician-rated global assessment	Global deterioration consistent with syndrome transition
Quality of life	Patient-relevant impact, well-being, participation	Patient-reported where feasible; proxy/informant-supported later	Decline in lived well-being or participation attributable to disease progression
Neuropsychiatric symptoms	Behavioral and psychiatric symptom burden	Structured symptom assessment and impact on functioning	Clinically relevant emergence or worsening of behavioral symptoms
Biomarkers	Biological stratification	Biological profiling for selection, enrichment, prognosis, monitoring	Not a clinical event by itself
Time-to-event	Transition to a clinically meaningful disease stage	Event-based longitudinal analysis with predefined adjudicated transition criteria	Preclinical → MCI: onset of clinically meaningful cognitive impairment MCI → dementia: cognitive decline plus functional consequences sufficient for dementia

This table summarizes a harmonized framework for outcome assessment across the AD continuum. Core domains include cognition, function, global clinical status, quality of life, neuropsychiatric symptoms, biomarkers, and time-to-event measures. Clinically meaningful change requires integration of cognitive and functional outcomes, as neither domain alone is sufficient. Biomarkers provide biological context but do not define clinical benefit. Time-to-event endpoints reflect transitions to clinically meaningful stages, defined by the onset of cognitive impairment (MCI) or the development of dementia with functional decline

Finally, clinical relevance extends beyond statistical significance. For both diagnostic and therapeutic decision-making, it is not sufficient to demonstrate statistically significant group differences; rather, changes must be meaningful in terms of everyday functioning, perceptibility, and impact on patients and caregivers. Concepts such as clinically meaningful benefit and minimal clinically important difference provide important frameworks to interpret whether observed effects translate into real-world relevance [57, 76].

Knowledge Gaps

A central unresolved issue in the field remains the lack of standardization in definitions and cut-offs. Core constructs such as mild cognitive impairment, mild neurocognitive disorder, and subjective cognitive decline are based on differing thresholds, normative references, and outcome concepts, limiting comparability across studies and settings [7, 18, 56, 77].

In addition, many existing instruments show limited applicability in culturally and linguistically diverse populations. Conventional cognitive screening tools are often influenced by language, literacy, and educational background, which can lead to both false-positive and false-negative classifications [78]. This highlights a substantial need for culturally sensitive and adaptable assessment approaches [39, 79, 80].

Finally, patient-reported and everyday-life outcomes remain underrepresented in dementia research. Although clinical relevance is often justified in terms of patient-centered impact, systematic integration of patient-reported outcome measures—particularly regarding quality of life and daily functioning—remains limited, indicating an important gap in current study designs [70, 75, 81].

Conclusion

Clinically meaningful definitions of cognitive impairment should not rely on biomarkers or isolated test scores alone, but instead integrate objective cognitive deficits with their impact on everyday functioning and patient-relevant outcomes.

Translating these principles into practice requires approaches that are not only valid but also feasible. In routine care, tiered diagnostic pathways—combining brief initial screening, functional contextualization, and targeted follow-up assessment—offer a pragmatic solution. Such models are more scalable than universal comprehensive testing and may improve both sensitivity and specificity, particularly when adapted to culturally diverse populations. Across both research and clinical settings, several challenges remain. Definitions and cut-offs for constructs such as MCI and subjective cognitive decline are not fully standardized, limiting comparability across studies. In addition, many assessment tools show limited cultural and linguistic generalizability, and patient-reported as well as everyday-life outcomes remain insufficiently integrated into current frameworks. These gaps highlight the need for approaches that combine standardization with contextual flexibility, ensuring both comparability and real-world applicability.

Taken together, the field is moving toward a more integrated model in which biological markers, cognitive performance, functional impact, and patient perspective are jointly considered. A balanced framework that aligns diagnostic rigor with clinical relevance and feasibility may therefore offer the most robust basis for both research and routine care.

Author Contributions

All authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship. Carolin Kurz drafted the manuscript, and Paul Newhouse, Kate Wyman-Chick, James Galvin, Nicola Theresa Lautenschlager, and Marwan Sabbagh contributed to critical revision for important intellectual content and all authors approved the final version for publication.

Funding

This work did not receive any specific funding. No funding was received for the publication of this article.

Data Availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Declarations

Conflicts of Interest

Kate Wyman serves as the Lead Principal Investigator of the Lewy Body Dementia Association’s Research Center of Excellence at Struthers Parkinson’s Center. She is a member of the Michael J Fox Foundation’s PD/DLB Cognition Measures Task Force (we are working on summarizing and optimizing clinical trial endpoints). Carolin Kurz has received speaker honoraria and consultancy fees from Roche Diagnostics (Penzberg, Germany). Nicola Theresa Lautenschlager and James Galvin report no conflicts of interest. Carolin Kurz is an Editorial Board member of Neurology and Therapy. Carolin Kurz was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions. Paul Newhouse is an Editorial Board member of Neurology and Therapy. Paul Newhouse was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions. Marwan Sabbagh is an Editor-in-Chief of Neurology and Therapy. Marwan Sabbagh was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions.

Ethical Approval

This is a review article and does not involve any studies with human participants or animals performed by any of the authors.