What is MELODEM?
MELODEM EMERGED TO PROMOTE RIGOROUS METHODS FOR IDENTIFYING CAUSES OF DEMENTIA AND COGNITIVE DECLINE
Several methodological challenges arise in studies of the determinants of dementia risk and cognitive decline. Some challenges, such as unmeasured confounding or missing data, are common in many research areas; others, such as outcome measurement error and lack of a “gold standard” outcome assessment, are more pervasive or more severe in dementia research.
Currently, different researchers handle these challenges in different ways, making it difficult to directly compare studies and combine evidence. Although some methodological differences across studies arise because analytic methods are explicitly tailored to the study design and realities of the data at hand, other differences emerge from less substantive origins.
Modifiable sources of inconsistency include the absence of consensus and definitive standards for best analytic approaches; divergent disciplinary traditions in epidemiology, clinical research, biostatistics, neuropsychology, psychiatry, geriatrics and neurology; and software and technical barriers.
WHEN MELODEM WAS ESTABLISHED IN 2012, IT ORGANIZED AROUND FIVE MAJOR CHALLENGES IN DEMENTIA RESEARCH:
1. SELECTION
Selection issues in dementia research arise from several sources: differential attrition of enrolled participants, differential survival of enrolled participants, and differential enrollment, either due to refusal to participate or differential survival up to the moment of study initiation. Each of these processes can bias effect estimates. Spurious associations between the putative risk factor and cognitive decline or dementia can occur when selection processes are related to cognitive status and the exposure of interest (or their determinants). The bias is not necessarily towards the null (i.e., which would tend to mask an association), and can sometimes reverse the direction of association (i.e., making harmful exposures appear protective or protective exposures appear harmful).2. MEASUREMENT
Measurement challenges in dementia research result from imperfect validity and reliability. For example, performance on neuropsychological tests does not precisely reflect biological functioning and capacity of the brain. Similar measurement challenges pertain to measures of the consequences, severity, and progression of dementia, including functional dependency, neuropsychiatric symptoms and behavioral patterns. Validity refers to whether a measurement instrument assesses the phenomenon of interest. Gold standard measures can be used to assess the validity of alternative measurements, but there is often no clear gold standard in dementia research. Measures valid for one group of people may not be for another, leading to biased estimates of disparities and risk factor effects. Reliability in cognitive testing is subject to measurement error from at least two sources: random fluctuations the performance of the test and random fluctuations an individual’s performance.3. PHENOTYPIC HETEROGENEITY
The potential heterogeneity in cognitive decline and Alzheimer’s disease has implications for prevention and treatment. For example, do the many forms of clinical heterogeneity that have been identified (imaging, cognitive, fluid biomarkers, etc.) reflect the manifestation of distinct etiologies and, therefore, distinct causes and prognoses? It may also be useful to identify groups of individuals who are at high risk of developing AD. Methodologic challenges arising in developing criteria should be considered to ensure that the clusters are clinically meaningful, as well as assessing and validating the final classification.4. TIME-VARYING EXPOSURES
Pathological changes in the brain are evident at least two decades prior to clinical diagnosis of dementia. Thus the effect that an exposure exerts on a cognitive-related outcome may depend critically on that exposure’s timing, and the relevant timing likely differs based on whether the exposure influences pathogenesis, disease progression, and/or maintenance of function. Distinguishing the relevant etiologic period for an exposure is essential for guiding clinical decisions and preventive interventions.5. HIGH-DIMENSIONAL DATA
Research on dementia research, as with research on most health outcomes, is facing new opportunities stemming from growing sources of data and the emergence of high-dimensional data. These data include administrative databases, genomics data, brain imaging data (MRI, PET), fluid biomarkers of neurodegeneration and neuropathology, and biomarkers panels assessing gene expression and metabolic pathways, among many others. Challenges in the statistical analyses of high-dimensional data are numerous, even when the number of observations is much larger than typically available in research cohorts. Big data does not necessarily resolve the familiar internal and external validity challenges in epidemiological studies and may, in some situations, exacerbate challenges with measurement validity and selection bias.
MELODEM’S SCOPE CONTINUES TO EXPAND
The five challenges still lie at the core of MELODEM’s scope. MELODEM has also extended its scope to address other methodologic challenges (e.g., immortal time bias) and challenges specific to topical subdomains (e.g., pharmacoepidemiology).