Time to Diagnosis and Its Predictors in Syndromes Associated With Frontotemporal Lobar Degeneration
- PMID: 38521735
- DOI: 10.1016/j.jagp.2024.03.002
Time to Diagnosis and Its Predictors in Syndromes Associated With Frontotemporal Lobar Degeneration
Abstract
Objectives: Frontotemporal Lobar Degeneration (FTLD) causes a heterogeneous group of neurodegenerative disorders with a wide range of clinical features. This might delay time to diagnosis. The aim of the present study is to establish time to diagnosis and its predictors in patients with FTLD-associated syndromes.
Design: Retrospective study.
Setting: Tertiary referral center.
Participants: A total of 1029 patients with FTLD-associated syndromes (age: 68 [61-73] years, females: 46%) from 1999 to 2023 were included in the present study.
Measurements: Time to diagnosis was operationalized as the time between symptom onset and the diagnosis of a FTLD-associated syndrome. The associations between time to diagnosis and possible predictors (demographic and clinical variables) were investigated through univariate and multivariate linear models.
Results: Median time to diagnosis was 2 [1-3] years. We observed that younger age at onset (β = -0.03, p <0.001), having worked as a professional rather than as a blue (β = 0.52, p = 0.024) or a white (β = 0.46, p = 0.050) collar, and having progressive supranuclear palsy (p <0.05) or the semantic variant of primary progressive aphasia (p <0.05) phenotypes were significantly associated with increased time to diagnosis. No significant changes of time to diagnosis have been observed over 20 years.
Conclusions: The identification of predictors of time to diagnosis might improve current diagnostic algorithms, resulting in a timely initiation of symptomatic treatments, early involvement in clinical trials, and more adequate public health policies for patients and their families.
Keywords: Frontotemporal lobar degeneration; age at onset; frontotemporal dementia; predictors; time to diagnosis.
Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
DISCLOSURES Daniele Altomare received funding by theSwiss National Science Foundation(projectCRSK-3_196354 / 1). Barbara Borroni served as a medical advisor for Alector, Denali, Wave, AviadoBio, Lilly, and UCB. The other authors report no conflicts with any product mentioned or concept discussed in this article.
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