| 1. |
- Duits, Flora H., et al.
(författare)
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The cerebrospinal fluid "Alzheimer profile": Easily said, but what does it mean?
- 2014
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Ingår i: Alzheimer's & Dementia. - : Elsevier. - 1552-5260 .- 1552-5279. ; 10:6, s. 713-723
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Tidskriftsartikel (refereegranskat)abstract
- Background: We aimed to identify the most useful definition of the "cerebrospinal fluid Alzheimer profile," based on amyloid-beta(1-42) (A beta(42)), total tau, and phosphorylated tau (p-tau), for diagnosis and prognosis of Alzheimers disease (AD). Methods: We constructed eight Alzheimer profiles with previously published combinations, including regression formulas and simple ratios. We compared their diagnostic accuracy and ability to predict dementia due to AD in 1385 patients from the Amsterdam Dementia Cohort. Results were validated in an independent cohort (n = 1442). Results: Combinations outperformed individual biomarkers. Based on the sensitivity of the best performing regression formulas, cutoffs were chosen at 0.52 for the tau/A beta(42) ratio and 0.08 for the p-tau/A beta(42) ratio. Ratios performed similar to formulas (sensitivity, 91%-93%; specificity, 81%-84%). The same combinations best predicted cognitive decline in mild cognitive impairment patients. Validation confirmed these results, especially regarding the tau/A beta(42) ratio. Conclusions: A tau/A beta(42) ratio of greater than0.52 constitutes a robust cerebrospinal fluid Alzheimer profile. We recommend using this ratio to combine biomarkers.
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| 2. |
- Pelak, Victoria S., et al.
(författare)
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Consensus recommendations for clinical assessment tools for the diagnosis of posterior cortical atrophy syndrome from the Atypical AD PIA of ISTAART
- 2023
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Ingår i: Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring. - 2352-8729. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Delay in diagnosis of posterior cortical atrophy (PCA) syndrome is common, and the lack of familiarity with assessment tools for identifying visual cortical dysfunction is a contributing factor. We propose recommendations for the approach to the evaluation of PCA clinical features during the office visit, the neuropsychological evaluation, and the research setting. A recommended screening battery for eye clinics is also proposed. METHODS: Recommendations were developed using results from a web-based survey of members of Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART) Atypical Alzheimer's Disease Professional Interest Area (PIA), literature review, and consensus by the PCA assessment working party of the Atypical Alzheimer's Disease PIA. RESULTS: Survey results revealed robust agreement for assessment tool preferences for PCA features, and many respondents indicated that they reserve assessment tools for use only when PCA is suspected. For some PCA features, curated tools were preferred over validated battery tools, particularly for the office visit. Consensus recommendations superseded survey preferences for two core cognitive features within the 2017 PCA diagnostic criteria. DISCUSSION: These consensus recommendations provide an evaluation framework for PCA clinical features and can facilitate timely and accurate recognition and diagnosis of PCA. Broader use of these tools should be sought, and development and validation of novel PCA clinical outcome assessments are needed to improve our understanding of atypical AD and other dementias and support the inclusion of those with PCA in treatment trials.
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| 3. |
- Ulugut, Hulya, et al.
(författare)
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The natural history of primary progressive aphasia : beyond aphasia
- 2022
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Ingår i: Journal of Neurology. - : Springer Science and Business Media LLC. - 0340-5354 .- 1432-1459. ; 269:3, s. 1375-1385
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Primary progressive aphasia (PPA) is divided into three prototypical subtypes that are all characterized by their single core symptom of aphasia. Although later in their course, other cognitive, behavioral, and motor domains may become involved, little is known about the progression profile of each subtype relative to the other subtypes. Methods: In this longitudinal retrospective cohort study, based on the recent biomarker-supported diagnostic criteria, 24 subjects diagnosed with semantic variant (svPPA), 22 with non-fluent variant (nfvPPA), and 18 with logopenic variant (lvPPA) were collected and followed up for 1–6 years. Symptom distribution, cognitive test and neuropsychiatric inventory scores, and progression into another syndrome were assessed. Results: Over time, lvPPA progressed with broader language problems (PPA-extended) and nfvPPA progressed to mutism, whereas semantic impairment remained the major problem in svPPA. Apart from linguistic problems, svPPA developed pronounced behavioral disturbances, whereas lvPPA exhibited a greater cognitive decline. By contrast, in nfvPPA motor deficits were more common. Furthermore, within 5 years (IQR = 2.5) after clinical onset, 65.6% of the patients additionally fulfilled the clinical criteria for another neurodegenerative syndrome (PPA-plus). Fourteen out of 24 (58%) svPPA patients additionally met the diagnostic criteria of behavioral variant frontotemporal dementia (5.1 years, IQR = 1.1), whereas the clinical features of 15/18 (83%) lvPPA patients were consistent with Alzheimer disease dementia (4.5 years IQR = 3.4). Furthermore, 12/22 (54%) of the subjects with the nfvPPA progressed to meet the diagnostic criteria of corticobasal syndrome, progressive supranuclear palsy, or motor neuron disease (5.1 years IQR = 3.4). Discussion: Despite aphasia being the initial and unique hallmark of the syndrome, our longitudinal results showed that PPA is not a language limited disorder and progression differs widely for each subtype, both with respect to the nature of symptoms and disease duration.
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| 4. |
- van Maurik, Ingrid S., et al.
(författare)
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Biomarker-based prognosis for people with mild cognitive impairment (ABIDE) : a modelling study
- 2019
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Ingår i: Lancet Neurology. - : The Lancet Publishing Group. - 1474-4422 .- 1474-4465. ; 18:11, s. 1034-1044
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia.METHODS: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework.FINDINGS: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76).INTERPRETATION: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour.
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