Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (Jan 2021)

Uniform data set language measures for bvFTD and PPA diagnosis and monitoring

  • Adam M. Staffaroni,
  • Sandra Weintraub,
  • Katya Rascovsky,
  • Katherine P. Rankin,
  • Jack Taylor,
  • Julie A. Fields,
  • Kaitlin B. Casaletto,
  • Argye E. Hillis,
  • Sladjana Lukic,
  • Maria Luisa Gorno‐Tempini,
  • Hilary Heuer,
  • Merilee A. Teylan,
  • Walter A. Kukull,
  • Bruce L. Miller,
  • Bradley F. Boeve,
  • Howard J. Rosen,
  • Adam L. Boxer,
  • Joel H. Kramer

DOI
https://doi.org/10.1002/dad2.12148
Journal volume & issue
Vol. 13, no. 1
pp. n/a – n/a

Abstract

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Abstract Introduction The Frontotemporal Lobar Degeneration Module (FTLD‐MOD) includes a neuropsychological battery designed to assess the clinical features of FTLD, although much is unknown about its utility. We investigated FTLD‐MOD and Uniform Data Set 3.0 (UDS) language tests for differential diagnosis and disease monitoring. Methods Linear regressions compared baseline performances in 1655 National Alzheimer's Coordinating Center participants (behavioral variant frontotemporal dementia (bvFTD, n = 612), semantic variant primary progressive aphasia (svPPA, n = 185), non‐fluent/agrammatic variant PPA (nfvPPA, n = 168), logopenic variant PPA (lvPPA, n = 109), and controls (n = 581)). Sample sizes to detect treatment effects were estimated using longitudinal data. Results Among PPAs, the FTLD‐MOD language tasks and UDS Multilingual Naming Test accurately discriminated svPPA. Number Span Forward best discriminated lvPPA; Phonemic:Semantic Fluency ratio was excellent for nfvPPA classification. UDS fluency and naming measures required the smallest sample size to detect meaningful change. Discussion The FTLD‐MOD and UDS differentiated among PPA subtypes. UDS 3.0 measures performed best for longitudinal monitoring.

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