The SIST-M Predictive Validity of a Brief Structured Clinical Dementia Rating Interview
ABSTRACT We have previously established the reliability and cross-sectional validity of the SIST-M (Structured Interview and Scoring Tool-Massachusetts Alzheimer's Disease Research Center), a shortened version of an instrument shown to predict progression to Alzheimer disease (AD), even among persons with very mild cognitive impairment (vMCI).
To test the predictive validity of the SIST-M.
Participants were 342 community-dwelling, nondemented older adults in a longitudinal study. Baseline Clinical Dementia Rating (CDR) ratings were determined by either (1) clinician interviews or (2) a previously developed computer algorithm based on 60 questions (of a possible 131) extracted from clinician interviews. We developed age+sex+education-adjusted Cox proportional hazards models using CDR-sum-of-boxes (CDR-SB) as the predictor, where CDR-SB was determined by either a clinician interview or an algorithm; models were run for the full sample (n = 342) and among those jointly classified as vMCI using clinician-based and algorithm-based CDR ratings (n = 156). We directly compared predictive accuracy using time-dependent receiver operating characteristic (ROC) curves.
AD hazard ratios (HRs) were similar for clinician-based and algorithm-based CDR-SB: for a 1-point increment in CDR-SB, the respective HRs [95% confidence interval (CI)] were 3.1 (2.5, 3.9) and 2.8 (2.2, 3.5); among those with vMCI, the respective HRs (95% CI) were 2.2 (1.6, 3.2) and 2.1 (1.5, 3.0). Similarly high predictive accuracy was achieved: the concordance probability (weighted average of the area-under-the-ROC curves) over follow-up was 0.78 versus 0.76 using clinician-based versus algorithm-based CDR-SB.
CDR scores based on items from this shortened interview had high predictive ability for AD-comparable to that using a lengthy clinical interview.
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ABSTRACT: Activities of daily living (ADL) impairment is a hallmark of Alzheimer's disease (AD) dementia, but impairment in instrumental ADL (IADL) has been reported in mild cognitive impairment (MCI). The Structured Interview and Scoring Tool-Massachusetts Alzheimer's Disease Research Center (MADRC)-Informant Report (SIST-MIR) includes 60 graded items that assist in scoring the Clinical Dementia Rating; it assesses the spectrum of cognitive and ADL changes relevant to early AD. Of the 60 SIST-M-IR items, 41 address IADL; we aimed to determine which of these best discriminate individuals with MCI from clinically normal (CN) elderly.Current Alzheimer Research 09/2014; 11(8):785-91. DOI:10.1016/j.jalz.2013.05.1591 · 3.80 Impact Factor
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ABSTRACT: Background: Impairment in instrumental activities of daily living (IADL) starts as individuals with amnestic mild cognitive impairment (MCI) transition to Alzheimer's disease (AD) dementia. However, most IADL scales have not shown IADL alterations in clinically normal (CN) elderly. The objective of this study was to determine which of the IADL-related Everyday Cognition (ECog) scale items are most sensitive for detection of early functional changes. Methods: We assessed 290 CN and 495 MCI participants from the Alzheimer's Disease Neuroimaging Initiative. We performed logistic regression analyses predicting the probability of CN vs. MCI diagnosis using only the 17 participant-based and 17 informant-based ECog items related to IADL. We then performed Cox regression analyses to predict progression from CN to MCI. All analyses were adjusted for demographic characteristics. Results: We found that worse performance on "remembering a few shopping items" (participant and informant-based p<0.0001), "remembering appointments" (participant and informant-based p<0.0001), "developing a schedule in advance of anticipated events" (participant-based p=0.007), "balancing checkbook" (participant-based p=0.02), and "keeping mail and papers organized" (informant-based p=0.002) best discriminated MCI from CN. We found that worse performance on "keeping mail and papers organized" (participant-based Hazard Ratio (HR)=2.27, p=0.07) marginally predicted greater hazard of progressing from CN to MCI. Conclusions: Our results indicate that a few simple questions targeting early functional changes, addressed either to the individual or informant, can effectively distinguish between CN elderly and individuals with MCI. Additionally, one of the above questions related to organization suggested which CN individuals are likely to progress to MCI.Current Alzheimer Research 10/2014; 11(9). DOI:10.2174/1567205011666141001120903 · 3.80 Impact Factor
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ABSTRACT: To determine whether the addition of data derived from magnetic resonance imaging (MRI) of the brain to a model incorporating conventional risk variables improves prediction of dementia over 10 years of follow-up. Population based cohort study of individuals aged ≥65. The Dijon magnetic resonance imaging study cohort from the Three-City Study, France. 1721 people without dementia who underwent an MRI scan at baseline and with known dementia status over 10 years' follow-up. Incident dementia (all cause and Alzheimer's disease). During 10 years of follow-up, there were 119 confirmed cases of dementia, 84 of which were Alzheimer's disease. The conventional risk model incorporated age, sex, education, cognition, physical function, lifestyle (smoking, alcohol use), health (cardiovascular disease, diabetes, systolic blood pressure), and the apolipoprotein genotype (C statistic for discrimination performance was 0.77, 95% confidence interval 0.71 to 0.82). No significant differences were observed in the discrimination performance of the conventional risk model compared with models incorporating data from MRI including white matter lesion volume (C statistic 0.77, 95% confidence interval 0.72 to 0.82; P=0.48 for difference of C statistics), brain volume (0.77, 0.72 to 0.82; P=0.60), hippocampal volume (0.79, 0.74 to 0.84; P=0.07), or all three variables combined (0.79, 0.75 to 0.84; P=0.05). Inclusion of hippocampal volume or all three MRI variables combined in the conventional model did, however, lead to significant improvement in reclassification measured by using the integrated discrimination improvement index (P=0.03 and P=0.04) and showed increased net benefit in decision curve analysis. Similar results were observed when the outcome was restricted to Alzheimer's disease. Data from MRI do not significantly improve discrimination performance in prediction of all cause dementia beyond a model incorporating demographic, cognitive, health, lifestyle, physical function, and genetic data. There were, however, statistical improvements in reclassification, prognostic separation, and some evidence of clinical utility. © Stephan et al 2015.BMJ (online) 06/2015; 350:h2863. DOI:10.1136/bmj.h2863 · 16.38 Impact Factor