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- Borland, Emma, et al.
(författare)
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Clinically Relevant Changes for Cognitive Outcomes in Preclinical and Prodromal Cognitive Stages : Implications for Clinical Alzheimer Trials
- 2022
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Ingår i: Neurology. - 0028-3878. ; 99:11, s. 1142-1153
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Tidskriftsartikel (refereegranskat)abstract
- Background and ObjectivesIdentifying a clinically meaningful change in cognitive test score is essential when using cognition as an outcome in clinical trials. This is especially relevant because clinical trials increasingly feature novel composites of cognitive tests. Our primary objective was to establish minimal clinically important differences (MCIDs) for commonly used cognitive tests, using anchor-based and distribution-based methods, and our secondary objective was to investigate a composite cognitive measure that best predicts a minimal change in the Clinical Dementia Rating - Sum of Boxes (CDR-SB).MethodsFrom the Swedish BioFINDER cohort study, we consecutively included cognitively unimpaired (CU) individuals with and without subjective or mild cognitive impairment (MCI). We calculated MCIDs associated with a change of ≥0.5 or ≥1.0 on CDR-SB for Mini-Mental State Examination (MMSE), ADAS-Cog delayed recall 10-word list, Stroop, Letter S Fluency, Animal Fluency, Symbol Digit Modalities Test (SDMT) and Trailmaking Test (TMT) A and B, and triangulated MCIDs for clinical use for CU, MCI, and amyloid-positive CU participants. For investigating cognitive measures that best predict a change in CDR-SB of ≥0.5 or ≥1.0 point, we conducted receiver operating characteristic analyses.ResultsOur study included 451 cognitively unimpaired individuals, 90 with subjective cognitive decline and 361 without symptoms of cognitive decline (pooled mean follow-up time 32.4 months, SD 26.8, range 12-96 months), and 292 people with MCI (pooled mean follow-up time 19.2 months, SD 19.0, range 12-72 months). We identified potential triangulated MCIDs (cognitively unimpaired; MCI) on a range of cognitive test outcomes: MMSE -1.5, -1.7; ADAS delayed recall 1.4, 1.1; Stroop 5.5, 9.3; Animal Fluency: -2.8, -2.9; Letter S Fluency -2.9, -1.8; SDMT: -3.5, -3.8; TMT A 11.7, 13.0; and TMT B 24.4, 20.1. For amyloid-positive CU, we found the best predicting composite cognitive measure included gender and changes in ADAS delayed recall, MMSE, SDMT, and TMT B. This produced an AUC of 0.87 (95% CI 0.79-0.94, sensitivity 75%, specificity 88%).DiscussionOur MCIDs may be applied in clinical practice or clinical trials for identifying whether a clinically relevant change has occurred. The composite measure can be useful as a clinically relevant cognitive test outcome in preclinical AD trials.
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| 3. |
- Borland, Emma, et al.
(författare)
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The age-related effect on cognitive performance in cognitively healthy elderly is mainly caused by underlying AD pathology or cerebrovascular lesions : implications for cutoffs regarding cognitive impairment
- 2020
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Ingår i: Alzheimer's Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: As research in treatments for neurocognitive diseases progresses, there is an increasing need to identify cognitive decline in the earliest stages of disease for initiation of treatment in addition to determining the efficacy of treatment. For early identification, accurate cognitive tests cutoff values for cognitive impairment are essential. METHODS: We conducted a study on 297 cognitively healthy elderly people from the BioFINDER study and created subgroups excluding people with signs of underlying neuropathology, i.e., abnormal cerebrospinal fluid [CSF] β-amyloid or phosphorylated tau, CSF neurofilament light (neurodegeneration), or cerebrovascular pathology. We compared cognitive test results between groups and examined the age effect on cognitive test results. RESULTS: In our subcohort without any measurable pathology (n = 120), participants achieved better test scores and significantly stricter cutoffs for cognitive impairment for almost all the examined tests. The age effect in this subcohort disappeared for all cognitive tests, apart from some attention/executive tests, predominantly explained by the exclusion of cerebrovascular pathology. CONCLUSION: Our study illustrates a new approach to establish normative data that could be useful to identify earlier cognitive changes in preclinical dementias. Future studies need to investigate if there is a genuine effect of healthy aging on cognitive tests or if this age effect is a proxy for higher prevalence of preclinical neurodegenerative diseases.
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| 4. |
- Borland, Emma, et al.
(författare)
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The Montreal Cognitive Assessment : Normative Data from a Large Swedish Population-Based Cohort
- 2017
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Ingår i: Journal of Alzheimer's Disease. - : IOS Press. - 1387-2877 .- 1875-8908. ; 59:3, s. 893-901
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Tidskriftsartikel (refereegranskat)abstract
- Background: The Montreal Cognitive Assessment (MoCA) has a high sensitivity for detecting cognitive dysfunction. Swedish normative data does not exist and international norms are often derived from populations where cognitive impairment has not been screened for and not been thoroughly assessed to exclude subjects with dementia or mild cognitive impairment. Objective: To establish norms for MoCA and develop a regression-based norm calculator based on a large, well-examined cohort. Methods: MoCA was administered on 860 randomly selected elderly people from a population-based cohort from the EPIC study. Cognitive dysfunction was screened for and further assessed at a memory clinic. After excluding cognitively impaired participants, normative data was derived from 758 people, aged 65-85. Results: MoCA cut-offs (-1 to -2 standard deviations) for cognitive impairment ranged from <25 to <21 for the lowest educated and <26 to <24 for the highest educated, depending on age group. Significant predictors for MoCA score were age, sex and level of education. Conclusion: We present detailed normative MoCA data and cut-offs according to the DSM-5 criteria for cognitive impairment based on a large population-based cohort of elderly individuals, screened and thoroughly investigated to rule out cognitive impairment. Level of education, sex, and age should be taken in account when evaluating MoCA score, which is facilitated by our online regression-based calculator that provide percentile and z-score for a subject's MoCA score.
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