Detecting Early Preclinical Alzheimer's Disease via Cognition, Neuropsychiatry, and Neuroimaging: Qualitative Review and Recommendations for Testing

Belleville, Sylvie; Fouquet, Céline; Duchesne, Simon; Collins, D. Louis; Hudon, Carol

doi:10.3233/jad-141470

Cited by 92 publications

(65 citation statements)

References 79 publications

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“…This is consistent with the observation that MCI is mainly characterized by memory deficits [3,5], and that both episodic memory and working memory are impaired early in the disease process and are predictors of conversion from MCI to AD [11,36] (for a review, see [37]) and from healthy aging to MCI [38].…”

Section: Discussionsupporting

confidence: 89%

“…One other crucial difference between the two studies is that we differentiated nonprogressor from progressor MCI. Some studies have indicated that executive functions and inhibition are more impaired in progressors than in non-progressor MCIs [20,21,43,47] and predictive models that are most sensitive and specific often include executive function measures [11] (for a review, see [37]). Our results support this literature as executive functions were found to differ between non-progressor and progressor MCI and only the latter showed increased impairment.…”

Section: Discussionmentioning

confidence: 99%

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O2‐07‐03: Patterns of Cognitive Decline Prior to Dementia in Persons With Mild Cognitive Impairment

Cloutier

Chertkow

Lepage

et al. 2014

Alzheimer's & Dementia

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Abstract. Only a limited number of studies have investigated the decline of discrete cognitive domains as individuals progress from mild cognitive impairment (MCI) to dementia. Thus, the goal of this longitudinal study was to evaluate the cognitive changes underway during the years preceding a diagnosis of probable Alzheimer's disease (AD), and to compare these changes to those found in MCI participants who do not progress to dementia. Participants were compared as a function of whether they later converted to AD (n = 47) or not (n = 74). Cognitive change was assessed prior to the conversion year, using that year as a starting point. A combination of polynomial regression analyses and mixed ANOVAs assessed 1) the trajectory of cognitive decline for each domain and 2) the differences between non-progressors and those who had converted to AD. The different cognitive domains demonstrated very different patterns of decline in the group of MCI progressors. A quadratic function, i.e., many years of stable performance followed by a rapid decline just prior to diagnosis, was observed for delayed recall, working memory, and spatial memory. In contrast, a gradual linear decline was observed for immediate recall, executive function, and visuo-spatial abilities. Finally, language in progressors was impaired on all time periods relative to non-progressors, but there was no further change between the first assessments and conversion to AD. Individuals with MCI who progress to AD show abnormal cognition at least two years prior to their dementia diagnosis. The pattern of symptom change observed appears to depend upon the cognitive domain and thus, clinical studies should not assume similar rate of decline across domains. In contrast and, apart from verbal memory, the non-progressors present a performance similar to that of healthy older adults.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

O2‐07‐03: Patterns of Cognitive Decline Prior to Dementia in Persons With Mild Cognitive Impairment

Cloutier

Chertkow

Lepage

et al. 2014

Alzheimer's & Dementia

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“…A large number of studies have examined the accuracy of cognitive tests to predict progression from MCI to AD, and studies have revealed that a range of episodic memory tests are excellent predictors of future decline. [27] AD is a progressive degenerative disorder of insidious onset, characterized, in its earliest stages, by declarative memory loss. Research diagnostic criteria for AD proposed by an expert consensus group led by Dubois set early and substantial impairment in episodic memory as core diagnostic criteria for AD.…”

Section: Discussionmentioning

confidence: 99%

Macular Ganglion Cell -Inner Plexiform Layer Thickness Is Associated with Clinical Progression in Mild Cognitive Impairment and Alzheimers Disease

2016

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PurposeWe investigated the association of the macular ganglion cell-inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (RNFL) thicknesses with disease progression in mild cognitive impairment (MCI) and Alzheimer’s disease (AD).MethodsWe recruited 42 patients with AD, 26 with MCI, and 66 normal elderly controls. The thicknesses of the RNFL and GCIPL were measured via spectral-domain optic coherent tomography in all participants at baseline. The patients with MCI or AD underwent clinical and neuropsychological tests at baseline and once every year thereafter for 2 years.ResultsThe Clinical Dementia Rating scale-Sum of Boxes (CDR-SB) score exhibited significant negative relationships with the average GCIPL thickness (β = -0.15, p < 0.05) and the GCIPL thickness in the superotemporal, superonasal, and inferonasal sectors. The composite memory score exhibited significant positive associations with the average GCIPL thickness and the GCIPL thickness in the superotemporal, inferonasal, and inferotemporal sectors. The temporal RNFL thickness, the average and minimum GCIPL thicknesses, and the GCIPL thickness in the inferonasal, inferior, and inferotemporal sectors at baseline were significantly reduced in MCI patients who were converted to AD compared to stable MCI patients. The change of CDR-SB from baseline to 2 years exhibited significant negative associations with the average (β = -0.150, p = 0.006) and minimum GCIPL thicknesses as well as GCIPL thickness in the superotemporal, superior, superonasal, and inferonasal sectors at baseline.ConclusionsOur data suggest that macular GCIPL thickness represents a promising biomarker for monitoring the progression of MCI and AD.

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“…Unfortunately, by the time patients meet criteria for dementia, the brain has suffered sufficient damage to severely impact cognition and autonomy. With this in mind, recognizing putative progress to dementia when patients experience only mild cognitive deficits, at a stage of Mild Cognitive Impairment (MCI), is paramount to develop disease-modifying therapies and identifying appropriate therapeutic windows [3–9]. Clinical studies with MCI patients have reported higher risk rates of conversion to dementia (in particularly to AD) than community studies, suggesting these patients as a group of singular interest to follow-up studies and interventions [10, 11].…”

Section: Introductionmentioning

confidence: 99%

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Pereira

Lemos

Cardoso

et al. 2017

BMC Med Inform Decis Mak

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BackgroundPredicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion.MethodsIn the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question “Will a MCI patient convert to dementia somewhere in the future” to the question “Will a MCI patient convert to dementia in a specific time window”.ResultsThe proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set.ConclusionsPrognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-017-0497-2) contains supplementary material, which is available to authorized users.

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Detecting Early Preclinical Alzheimer's Disease via Cognition, Neuropsychiatry, and Neuroimaging: Qualitative Review and Recommendations for Testing

Cited by 92 publications

References 79 publications

O2‐07‐03: Patterns of Cognitive Decline Prior to Dementia in Persons With Mild Cognitive Impairment

O2‐07‐03: Patterns of Cognitive Decline Prior to Dementia in Persons With Mild Cognitive Impairment

Macular Ganglion Cell -Inner Plexiform Layer Thickness Is Associated with Clinical Progression in Mild Cognitive Impairment and Alzheimers Disease

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

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