Table 1.
Search Strategy.
Fig 1.
PRISMA (2009) flow diagram of article selection.
Table 2.
Characteristics of included studies and reported dementia risk prediction models.
Table 3.
Component Variables Used (Either Alone or in Combination) in the Different Risk Prediction Models (Previous and Current Review).
Fig 2.
Comparison of AUC indices in development vs. validation cohorts across different dementia risk prediction models.
Key: BDSI, Brief Dementia Screening Index; CAIDE, Cardiovascualr Risk Factors, Aging and Dementia; CHS, Cardiovascular Health Study; CVHS, Cardiovascular Health Cognition Study; DSDRS, Type-2 Diabetes Specific Dementia Risk Score; FHS, Framingham Heart Study; KP, Kungsholmen Project; KPNC, Kaiser Permanente Medical Care Program of Northern California; MAP, Rush Memory and Aging Project; PS-W, Pathways study cohort from Washington; Pts, Points; SALSA Sacramento Area Latino Study on Aging. References [1] Anstey KJ, Cherbuin N, Herath PM, Qiu C, Kuller LH, Lopez OL, et al. A Self-Report Risk Index to Predict Occurrence of Dementia in Three Independent Cohorts of Older Adults: The ANU-ADRI. PLoS One. 2014;9(1):e86141; [2] Exalto LG QC, Barnes D, Kivipelto M, Biessels GJ, Whitmer RA. Midlife risk score for the prediction of dementia four decades later. Alzheimers Dementia. 2013; [3] Exalto LG, Biessels GJ, Karter AJ, Huang ES, Katon WJ, Minkoff JR, et al. Risk score for prediction of 10 year dementia risk in individuals with type 2 diabetes: a cohort study. The Lancet Diabetes and Endocrinology. 2013; [4] Barnes DE, Beiser AS, Lee A, Langa KM, Koyama A, Preis SR, et al. Development and validation of a brief dementia screening indicator for primary care. Alzheimers Dementia. 2014:S1552-5260. Notes * No development dataset. Rather, model tested in different cohorts.
Table 4.
Optimum features of study design and variables selected for dementia risk prediction models.