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The Capital Region of Denmark - a part of Copenhagen University Hospital
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Prognostic value of complementary biomarkers of neurodegeneration in a mixed memory clinic cohort

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Background: Biomarkers of neurodegeneration, e.g. MRI brain atrophy and [18F]FDG-PET hypometabolism, are often evaluated in patients suspected of neurodegenerative disease.

Objective: Our primary objective was to investigate prognostic properties of atrophy and hypometabolism.

Methods: From March 2015-June 2016, 149 patients referred to a university hospital memory clinic were included. The primary outcome was progression/stable disease course as assessed by a clinician at 12 months follow-up. Intracohort defined z-scores of baseline MRI automatic quantified volume and [18F]FDG-PET standardized uptake value ratios were calculated for all unilaterally defined brain lobes and dichotomized as pronounced atrophy (+A)/ pronounced hypometabolism (+H) at z-score <0. A logistic regression model with progression status as the outcome was carried out with number of lobes with the patterns +A/-H, -A/+H, +A/+H respectively as predictors. The model was mutually adjusted along with adjustment for age and sex. A sensitivity analysis with a z-score dichotomization at -0.1 and -0.5 and dichotomization regarding number of lobes affected at one and three lobes was done.

Results: Median follow-up time was 420 days [IQR: 387-461 days] and 50 patients progressed. Patients with two or more lobes affected by the pattern +A/+H compared to patients with 0-1 lobes affected had a statistically significant increased risk of progression (odds ratio, 95 % confidence interval: 4.33, 1.90-9.86) in a multivariable model. The model was partially robust to the applied sensitivity analysis.

Conclusion: Combined atrophy and hypometabolism as assessed by MRI and [18F]FDG-PET in patients under suspicion of neurodegenerative disease predicts progression over 1 year.

Original languageEnglish
JournalPeerJ
Volume8
Pages (from-to)e9498
ISSN2167-8359
DOIs
Publication statusPublished - 9 Jul 2020

    Research areas

  • Biomarkers, Neurodegenerative disease, Prognosis, Tau, Positron-emission tomography, Magnetic resonance imaging, Neuroimaging

ID: 61245412