A Risk Score for the Prediction of Neurocognitive Disorders among Community-Dwelling Chinese Older Adults

Abstract

Background: Several risk scores have been developed for predicting cognitive impairment and dementia, but none have been validated in Asian samples. We aimed to produce a risk score that best predicts incident neurocognitive disorder (NCD) among Chinese elderly and to validate this score against the modified risk score derived from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study. Methods: Data from participants enrolled in the Singapore Longitudinal Ageing Study (SLAS) 1 were analyzed. A total of 957 participants >55 years of age with normal cognition at baseline were included. Incident cases of NCD were measured using the global Clinical Dementia Rating (CDR) and determined by a consensus panel. Results: The best prediction model from SLAS included age, gender, education, depression, heart disease, social and productive activities and Mini-Mental State Examination score. This model predicted the short-term risk of incident NCD in elderly participants moderately well, with a C statistic (area under the curve) of 0.72. Modified CAIDE models applied to our sample had a C statistic of 0.71. Conclusion: Our risk score performs as well as other available risk scores. It is the only risk score formulated for ethnic Chinese, rendering it valuable for clinical use in Asia; at-risk individuals can be identified for early intervention.

Population-based dementia prediction model using Korean public health examination data: A cohort study

“…To our knowledge, we are the first to develop a dementia prediction model for Koreans. Also, this is the first model developed using simple health examination data from Asians, although two other dementia prediction models already exist for Asians [29,30]. One model using data from Japanese adults aged 60–79 years reports risk factors similar to those in our study [30].…”

“…However, the primary goal of this Japanese study was to examine the effect of the APOE allele on dementia onset, which had a very different focus than that of our study. The other model, which was modified from the one developed for non-Asian people, was found to work well for Chinese older adults [29]. However, there is still a lack of studies examining whether dementia prediction models for certain ethnic groups are applicable to other ethnic groups.…”

Models for predicting risk of dementia: a systematic review

“…The Singapore Longitudinal Ageing Study (SLAS) risk score comprising age, gender, education, depression, heart disease, social and productive activities, and MMSE score was developed to predict neurocognitive disorder (NCD) for individuals aged >55 years at baseline 27. This model predicted the risk of incident NCD in elderly participants moderately well in a 5-year follow-up (AUC 0.72).…”

A flexible modeling approach for biomarker‐based computation of absolute risk of Alzheimer's disease dementia

“…Using the dementia incidence models identified for our covariate selection process, we investigated the literature on the association between sex and AD incidence and found it mixed. Of the 29 models that reported and quantified the association between dementia and sex, 3 reported increased risk in women, 4,44,45 5 reported increased risk in men, 37,42,46–48 and 21 found no statistically significant association between sex and dementia 5,40,49–66 …”

“…Of the 29 models that reported and quantified the association between dementia and sex, 3 reported increased risk in women, 4,44,45 5 reported increased risk in men, 37,42,[46][47][48] and 21 found no statistically significant association between sex and dementia. 5,40,[49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66] Overall, the individual models demonstrate good accuracy and discrimination. However, many of our statistical comparisons between the models do not show that adding demographics and biomarkers improve prediction over a model with only age.…”