BACKGROUND: being able to identify individuals at high risk of dementia is important for diagnostics and intervention. Currently, there is no standard approach to assessing cognitive function in older aged individuals to best predict incident dementia. OBJECTIVE: to identify cognitive changes associated with an increased risk of 2-year incident dementia using the Cambridge Cognitive Examination (CAMCOG). DESIGN: longitudinal population representative sample aged 65+ years. METHODS: individuals were from the Medical Research Council Cognitive Function and Ageing Study. Classification and Regression Tree analysis was used to detect the optimal cut-off value for the CAMCOG total, subscales and composite memory and non-memory scores, for predicting dementia. Sensitivity and specificity of each cut-off score were assessed. RESULTS: from the 2,053 individuals without dementia at the first assessment, 137 developed dementia at the 2-year follow-up. The results indicate similar discriminative accuracy for incident dementia based on the CAMCOG total, memory subscale and composite scores. However, sensitivity and specificity of cut-off values were generally moderate. Scores on the non-memory subscales generally had high sensitivity but low specificity. Compared with the CAMCOG total score they had significantly lower discriminative accuracy. CONCLUSION: in a population setting, cut-off scores from the CAMCOG memory subscales predicted dementia with reasonable accuracy. Scores on the non-memory scales have lower accuracy and are not recommend for predicting high-risk cases unless all non-memory subdomain scores are combined. The added value of cognition when assessed using the CAMCOG to other risk factors (e.g. health and genetics) should be tested within a risk prediction framework.
BACKGROUND: being able to identify individuals at high risk of dementia is important for diagnostics and intervention. Currently, there is no standard approach to assessing cognitive function in older aged individuals to best predict incident dementia. OBJECTIVE: to identify cognitive changes associated with an increased risk of 2-year incident dementia using the Cambridge Cognitive Examination (CAMCOG). DESIGN: longitudinal population representative sample aged 65+ years. METHODS: individuals were from the Medical Research Council Cognitive Function and Ageing Study. Classification and Regression Tree analysis was used to detect the optimal cut-off value for the CAMCOG total, subscales and composite memory and non-memory scores, for predicting dementia. Sensitivity and specificity of each cut-off score were assessed. RESULTS: from the 2,053 individuals without dementia at the first assessment, 137 developed dementia at the 2-year follow-up. The results indicate similar discriminative accuracy for incident dementia based on the CAMCOG total, memory subscale and composite scores. However, sensitivity and specificity of cut-off values were generally moderate. Scores on the non-memory subscales generally had high sensitivity but low specificity. Compared with the CAMCOG total score they had significantly lower discriminative accuracy. CONCLUSION: in a population setting, cut-off scores from the CAMCOG memory subscales predicted dementia with reasonable accuracy. Scores on the non-memory scales have lower accuracy and are not recommend for predicting high-risk cases unless all non-memory subdomain scores are combined. The added value of cognition when assessed using the CAMCOG to other risk factors (e.g. health and genetics) should be tested within a risk prediction framework.
Entities:
Keywords:
Cambridge Cognitive Examination (CAMCOG); classification and regression tree (CART) analysis; cognition; dementia risk prediction; older people; predictive accuracy
Authors: Lieke L Smits; Yolande A L Pijnenburg; Esther L G E Koedam; Annelies E van der Vlies; Ilona E W Reuling; Teddy Koene; Charlotte E Teunissen; Philip Scheltens; Wiesje M van der Flier Journal: J Alzheimers Dis Date: 2012 Impact factor: 4.472
Authors: Mary Ganguli; Ching-Wen Lee; Beth E Snitz; Tiffany F Hughes; Eric M McDade; Chung-Chou H Chang Journal: Alzheimer Dis Assoc Disord Date: 2014 Apr-Jun Impact factor: 2.703
Authors: Eugene Y H Tang; Stephanie L Harrison; Linda Errington; Mark F Gordon; Pieter Jelle Visser; Gerald Novak; Carole Dufouil; Carol Brayne; Louise Robinson; Lenore J Launer; Blossom C M Stephan Journal: PLoS One Date: 2015-09-03 Impact factor: 3.240