Diagnostic labels varied in nearly 40% of AD study population using different guidelines
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SAN DIEGO — Diagnostic outcomes varied in nearly 40% of a study population when different criteria were used to diagnose Alzheimer’s disease, per a presenter at the Alzheimer’s Association International Conference.
“We quantified the extent at which the differences in diagnostic criteria for Alzheimer’s disease differed in the actual diagnosis,” Andrei Bieger, a PhD candidate at the Federal University of Rio Grande do Sul in Brazil, said during his poster presentation.
Bieger and colleagues sought to clarify how updated guidance from the National Institute on Aging and Alzheimer’s Association (NIA-AA) and the International Working Group (IWG) affect an individual’s diagnostic label by using the following guidelines: NIA-AA 2011, IWG 2016, NIA-AA 2018 and IWG 2021.
Researchers extracted clinical, demographic and biomarker data from 1,215 individuals in the Alzheimer’s Disease Neuroimaging Initiative and used that information to build classification algorithms according to the four diagnostic criteria. Participants were subsequently labeled as not AD (NA), at risk for developing AD (AR) or AD.
Beiger and colleagues compared results according to cognitive stage, cognitively unimpaired (CU) or cognitively impaired (CI) and to a profile based on AD biomarkers. They used Kaplan-Meier curves to evaluate conversion to CI in CU individuals using each diagnostic guideline.
According to results, individuals were diagnosed accordingly using criteria from NIA-AA 2011 (NA = 36.8%, AR = 23.2%, AD = 40%), IWG 2016 (NA = 37.9%, AR = 28.8%, AD = 33.3%), NIA-AA 2018 (NA = 40.5%, AR = 11.1%, AD = 48.4%) and IWG 2021 (NA = 51.3%, AR = 8.7%, AD = 40%).
Data further revealed that diagnoses were variable between criteria in 39.8% of individuals, with 69.4% of those in the A+T– or A–T+ biomarker groups. After conversion from CU to CI, individuals labeled AR compared with NA were NIA-AA 2011 (P < .01), IWG 2016 (P < .01), NIA-AA 2018 (P = 0.24) and IWG 2021 (P < .01).
“We have clinical relevance on the applications of these diagnostic criteria,” Bieger said. “There might also be implications in clinical research, in population enrichment, in population selection for clinical trials.”