Summary: A substantial number of false-negative results from common neuroimaging and screening approaches mean many people at increased risk for Alzheimer’s may not receive timely diagnosis or care, according to a new study.
Source: UC San Diego School of Medicine and Veterans Affairs San Diego Healthcare System.
False negatives in routine screening can leave at-risk individuals without needed care or inclusion in research
Mild cognitive impairment (MCI) describes a measurable decline in cognitive abilities—such as trouble remembering names, lists, or recent events—that is greater than expected for a person’s age but not severe enough to severely interfere with daily life. Clinically, a diagnosis of MCI signals an elevated risk for progression to Alzheimer’s disease or another form of dementia, which makes accurate identification important for early intervention, planning, and research recruitment.
In a paper published in the Journal of Alzheimer’s Disease, researchers at the University of California San Diego School of Medicine and the Veterans Affairs San Diego Healthcare System report that commonly used screening procedures for MCI can produce a false-negative error rate exceeding 7 percent. In other words, some individuals who appear cognitively normal under standard screening measures are found to have MCI when evaluated with more comprehensive neuropsychological testing and biomarker assessment.
“There are consequences to misdiagnosis,” said Emily C. Edmonds, PhD, a postdoctoral fellow in neuropsychology in the Department of Psychiatry at UC San Diego School of Medicine and the paper’s first author. “Individuals incorrectly labeled as cognitively normal may miss opportunities for preventive counseling, lifestyle recommendations, or referrals to specialists. Misclassification can also hinder timely planning and support for patients and families.”
Beyond implications for individual care, diagnostic errors affect research quality. Edmonds noted: “When participants are misclassified at enrollment, clinical studies and trials can become less reliable, making it more difficult to develop and evaluate therapies for early Alzheimer’s disease.”
Current conventional diagnostic practices for MCI typically rely on the screened person’s subjective memory complaints, a single impaired test score, and clinician judgment. The authors indicate that this approach is prone to both false-positive and false-negative errors. Their earlier work documented a notable rate of false positives—cases labeled as MCI by standard methods but not confirmed with detailed testing. The new study highlights the complementary problem of false negatives: people who are labeled cognitively normal by routine criteria but who meet more rigorous, actuarial neuropsychological criteria for MCI.
The investigators analyzed data from 520 participants enrolled in the Alzheimer’s Disease Neuroimaging Initiative, a multi-institution study focused on MCI and Alzheimer’s disease. Participants were nearly evenly split by gender and had a mean age of 74.3 years. Each person completed routine MCI screening and a more comprehensive diagnostic evaluation that used multiple standardized memory and learning tests as well as neuropsychological criteria designed to reduce diagnostic error.
The study found that 37 participants—about 7.1 percent—were classified as cognitively normal under standard diagnostic procedures but met the more comprehensive, actuarial criteria for MCI. These individuals not only exhibited mildly impaired cognitive performance on the extended battery, they also showed cerebrospinal fluid biomarkers consistent with increased risk for future dementia. The remaining participants were classified as normal by both methods, resulting in a true-negative rate of 92.9 percent.
The authors conclude that implementing rigorous diagnostic criteria that rely on formal, multi-domain neuropsychological testing rather than a single impaired score and subjective complaint can reduce misclassification. Improved diagnostic accuracy would enhance clinical care by identifying people who would benefit from early counseling and interventions, and strengthen research by ensuring that study cohorts more accurately represent the intended clinical populations.
Authors: Emily C. Edmonds, Lisa Delano-Wood, Amy J. Jak, Douglas R. Galasko, David P. Salmon, and Mark W. Bondi, affiliated with UC San Diego School of Medicine and Veterans Affairs San Diego Healthcare System.
Funding: This research was supported in part by the National Institutes of Health (RO1 AG049810, K24 AG026431, P50 AG05131). Data collection and sharing were supported by the Alzheimer’s Disease Neuroimaging Initiative.
Key takeaway: Conventional screening criteria for mild cognitive impairment may miss a meaningful subset of individuals at risk for dementia. Using comprehensive neuropsychological assessment alongside biomarker evaluation improves detection accuracy, which benefits patient care and the integrity of clinical research and trials targeting prodromal Alzheimer’s disease.
Abstract (summary)
The study “Missed” Mild Cognitive Impairment: High False-Negative Error Rate Based on Conventional Diagnostic Criteria reports that conventional MCI diagnostic methods—relying on subjective complaints, screening measures, clinical judgment, and a single memory score—yield a false-negative error rate of 7.1% when compared to actuarial neuropsychological criteria. Participants reclassified as MCI by the more rigorous approach demonstrated neuropsychological deficits, cerebrospinal fluid biomarker profiles, and rates of decline consistent with true impairment. The authors discuss the implications of missed MCI cases for clinical practice, research studies, and clinical trials of early Alzheimer’s disease.