The SIST-M: Predictive Validity of a Brief Structured Clinical Dementia Rating Interview
Alzheimer Disease and Associated Disorders. 2011 Oct 6;
Okereke OI, Pantoja-Galicia N, Copeland M, Hyman BT, Wanggaard T, Albert MS, Betensky RA, Blacker D
BACKGROUND:: 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). OBJECTIVE:: To test the predictive validity of the SIST-M. METHODS:: 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. RESULTS:: 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. CONCLUSION:: CDR scores based on items from this shortened interview had high predictive ability for AD-comparable to that using a lengthy clinical interview.
PMID: 21986342 [PubMed - as supplied by publisher]