Uniform data set language measures for bvFTD and PPA diagnosis and monitoring
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 di...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/dad2.12148 |
| _version_ | 1797975499976212480 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Adam M. Staffaroni |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T04:36:32Z |
| format | Article |
| id | doaj.art-187ece54033d4d8e953d8c37dcbca237 |
| institution | Directory Open Access Journal |
| issn | 2352-8729 |
| language | English |
| last_indexed | 2024-04-11T04:36:32Z |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| spelling | doaj.art-187ece54033d4d8e953d8c37dcbca2372022-12-28T09:12:14ZengWileyAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring2352-87292021-01-01131n/an/a10.1002/dad2.12148Uniform data set language measures for bvFTD and PPA diagnosis and monitoringAdam M. Staffaroni0Sandra Weintraub1Katya Rascovsky2Katherine P. Rankin3Jack Taylor4Julie A. Fields5Kaitlin B. Casaletto6Argye E. Hillis7Sladjana Lukic8Maria Luisa Gorno‐Tempini9Hilary Heuer10Merilee A. Teylan11Walter A. Kukull12Bruce L. Miller13Bradley F. Boeve14Howard J. Rosen15Adam L. Boxer16Joel H. Kramer17Department of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USAMesulam Center for Cognitive Neurology and Alzheimer's Disease and Department of Psychiatry and Behavioral Sciences Feinberg School of Medicine Department of Neurology Northwestern University Chicago Illinois USAPenn Frontotemporal Degeneration Center Department of Neurology Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Psychiatry and Psychology Mayo Clinic Division of Neurocognitive Disorders Rochester Minnesota USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology Johns Hopkins University School of Medicine Baltimore Maryland USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USANational Alzheimer's Coordinating Center Department of Epidemiology University of Washington Seattle Washington USANational Alzheimer's Coordinating Center Department of Epidemiology University of Washington Seattle Washington USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology College of Medicine Mayo Clinic Rochester Minnesota USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USADepartment of Neurology Memory and Aging Center Weill Institute for Neurosciences University of California at San Francisco (UCSF) San Francisco California USAAbstract 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.https://doi.org/10.1002/dad2.12148clinical trialscognitiondifferential diagnosisendpointsfrontotemporal dementia (FTD)FTLD module |
| spellingShingle | 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 Uniform data set language measures for bvFTD and PPA diagnosis and monitoring Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring clinical trials cognition differential diagnosis endpoints frontotemporal dementia (FTD) FTLD module |
| title | Uniform data set language measures for bvFTD and PPA diagnosis and monitoring |
| title_full | Uniform data set language measures for bvFTD and PPA diagnosis and monitoring |
| title_fullStr | Uniform data set language measures for bvFTD and PPA diagnosis and monitoring |
| title_full_unstemmed | Uniform data set language measures for bvFTD and PPA diagnosis and monitoring |
| title_short | Uniform data set language measures for bvFTD and PPA diagnosis and monitoring |
| title_sort | uniform data set language measures for bvftd and ppa diagnosis and monitoring |
| topic | clinical trials cognition differential diagnosis endpoints frontotemporal dementia (FTD) FTLD module |
| url | https://doi.org/10.1002/dad2.12148 |
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