The identification of cognitive subtypes in Alzheimer's disease dementia using latent class analysis

Scheltens, Nienke M.E.; Galindo-Garré, Francisca; Pijnenburg, Yolande A.L.; Vlies, Annelies E. van der; Smits, Lieke; Koene, Teddy; Teunissen, Charlotte E.; Barkhof, Frederik; Wattjes, Mike P.; Scheltens, Philip; Flier, Wiesje M. van der

doi:10.1136/jnnp-2014-309582

Cited by 98 publications

(115 citation statements)

References 34 publications

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“…In addition, the majority of the instruments used to measure SCD focus on memory (21). However, it might be too restrictive to limit the SCD assessment to memory, in particular for atypical forms of AD, or in the context of non-AD dementias (33). Therefore it is sensible to include other cognitive domains (e.g.…”

Section: Resultsmentioning

confidence: 99%

Implementation of subjective cognitive decline criteria in research studies

Molinuevo

Rabin

Amariglio

et al. 2016

Alzheimer's & Dementia

424

447

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INTRODUCTION Subjective Cognitive Decline (SCD) manifesting prior to clinical impairment could serve as a target population for early intervention trials in Alzheimer’s disease (AD). A working group, the Subjective Cognitive Decline Initiative (SCD-I), published SCD research criteria in the context of preclinical AD. To successfully apply them, a number of issues regarding assessment and implementation of SCD needed to be addressed. METHODS Members of the SCD-I met to identify and agree upon topics relevant to SCD criteria operationalization in research settings. Initial ideas and recommendations were discussed with other SCD-I working group members and modified accordingly. RESULTS Topics included SCD inclusion and exclusion criteria, together with the informant’s role in defining SCD presence and the impact of demographic factors. DISCUSSION Recommendations for the operationalization of SCD in differing research settings, with the aim of harmonization of SCD measurement across studies are proposed, to enhance comparability and generalizability across studies.

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Section: Resultsmentioning

confidence: 99%

Implementation of subjective cognitive decline criteria in research studies

Molinuevo

Rabin

Amariglio

et al. 2016

Alzheimer's & Dementia

424

447

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“…However, even patients who do not display a defined subtype also show a considerable variation in patterns of cognitive impairment. Earlier studies demonstrated the potential to capture cognitive heterogeneity in AD using a data-driven clustering approach [11–14]. Studies differed in sample size, clinical diagnosis of included patients, available neuropsychological (NP) test results, available neurobiological characteristics to compare clusters with, and clustering technique.…”

Section: Introductionmentioning

confidence: 99%

Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts

Scheltens

Tijms

Koene

et al. 2017

Alzheimer's & Dementia

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Introduction Patients with Alzheimer’s disease (AD) show heterogeneity in profile of cognitive impairment. We aimed to identify cognitive subtypes in four large AD cohorts using a data-driven clustering approach. Methods We included probable AD dementia patients from the Amsterdam Dementia Cohort (n = 496), Alzheimer’s Disease Neuroimaging Initiative (n = 376), German Dementia Competence Network (n = 521), and University of California, San Francisco (n = 589). Neuropsychological data were clustered using nonnegative matrix factorization. We explored clinical and neurobiological characteristics of identified clusters. Results In each cohort, a two-clusters solution best fitted the data (cophenetic correlation >0.9): one cluster was memory-impaired and the other relatively memory spared. Pooled analyses showed that the memory-spared clusters (29%–52% of patients) were younger, more often apolipoprotein E (APOE) ε4 negative, and had more severe posterior atrophy compared with the memory-impaired clusters (all P < .05). Conclusions We could identify two robust cognitive clusters in four independent large cohorts with distinct clinical characteristics.

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“…Alzheimer’s disease (AD) is a heterogeneous disease12345. Current diagnostic criteria recognize this heterogeneity in the form of different cognitive presentations678.…”

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confidence: 99%

“…Data-driven approaches using MRI data have largely confirmed these pathologically defined subtypes121415. Other authors have also applied data-driven approaches to cognitive data but the resulting subtypes differ noticeably from study to study351617. However, data-driven approaches rely on group analysis and sophisticated methods that make them difficult to translate into clinical practice at present.…”

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confidence: 99%

Distinct subtypes of Alzheimer’s disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications

Ferreira

Verhagen

Hernández‐Cabrera

et al. 2017

Sci Rep

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239

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Atrophy patterns on MRI can reliably predict three neuropathological subtypes of Alzheimer’s disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to enable their investigation in the clinical routine is still lacking. We aimed to (1) validate the combined use of visual rating scales for identification of AD subtypes; (2) characterise these subtypes at baseline and over two years; and (3) investigate how atrophy patterns and non-memory cognitive domains contribute to memory impairment. AD patients were classified as either typical AD (n = 100), limbic-predominant (n = 33), or hippocampal-sparing (n = 35) by using the Scheltens’ scale for medial temporal lobe atrophy (MTA), the Koedam’s scale for posterior atrophy (PA), and the Pasquier’s global cortical atrophy scale for frontal atrophy (GCA-F). A fourth group with no atrophy was also identified (n = 30). 230 healthy controls were also included. There was great overlap among subtypes in demographic, clinical, and cognitive variables. Memory performance was more dependent on non-memory cognitive functions in hippocampal-sparing and the no atrophy group. Hippocampal-sparing and the no atrophy group showed less aggressive disease progression. Visual rating scales can be used to identify distinct AD subtypes. Recognizing AD heterogeneity is important and visual rating scales may facilitate investigation of AD heterogeneity in clinical routine.

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The identification of cognitive subtypes in Alzheimer's disease dementia using latent class analysis

Abstract: Using LCA, we identified eight distinct cognitive subtypes in a large sample of patients with AD dementia. Cognitive clusters were associated with distinct demographical and neurobiological characteristics.

Cited by 98 publications

References 34 publications

Implementation of subjective cognitive decline criteria in research studies

Implementation of subjective cognitive decline criteria in research studies

Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts

Distinct subtypes of Alzheimer’s disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications

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