Toward Pre-Diagnostic Detection of Dementia in Primary Care

Abstract

Background: Preventing dementia warrants the pragmatic engagement of primary care. Objective: This study predicted conversion to dementia 12 months before diagnosis with indicators that primary care can utilize within the practical constraints of routine practice. Methods: The study analyzed data from the Alzheimer’s Disease Neuroimaging Initiative (Total sample = 645, converting participants = 54). It predicted the conversion from biological (plasma neurofilament light chain), cognitive (Trails Making Test– B), and functional (Functional Activities Questionnaire) measures, in addition to demographic variables (age and education). Results: A Gradient Booster Trees classifier effectively predicted the conversion, based on a Synthetic Minority Oversampling Technique (n = 1,290, F1 Score = 92, AUC = 94, Recall = 87, Precision = 97, Accuracy = 92). Subsequent analysis indicated that the MCI False Positive group (i.e., non-converting participants with cognitive impairment flagged by the model for prospective conversion) scored significantly lower on multiple cognitive tests (Montreal Cognitive Assessment, p < 0.002; ADAS-13, p < 0.0004; Rey Auditory Verbal Learning Test, p < 0.002/0.003) than the MCI True Negative group (i.e., correctly classified non-converting participants with cognitive impairment). These groups also differed in CSF tau levels (p < 0.04), while consistent effect size differences emerged in the all-pairwise comparisons of hippocampal volume and CSF Aβ1 - 42. Conclusion: The model effectively predicted 12-month conversion to dementia and further identified non-converting participants with MCI, in the False Positive group, at relatively higher neurocognitive risk. Future studies may seek to extend these results to earlier prodromal phases. Detection of dementia before diagnosis may be feasible and practical in primary care settings, pending replication of these findings in diverse clinical samples.