Validity of three risk prediction models for dementia or cognitive impairment in Australia

Abstract

Abstract Background no studies have compared the predictive validity of different dementia risk prediction models in Australia. Objectives (i) to investigate the predictive validity of the Australian National University-Alzheimer’s Disease Risk Index (ANU-ADRI), LIfestyle for BRAin Health (LIBRA) Index and cardiovascular risk factors, ageing and dementia study (CAIDE) models for predicting probable dementia/cognitive impairment in an Australian cohort. (ii) To develop and assess the predictive validity of a new hybrid model combining variables from the three models. Methods the Hunter Community Study (HCS) included 3,306 adults aged 55–85 years with a median follow-up of 7.1 years. Probable dementia/cognitive impairment was defined using Admitted Patient Data Collection, dispensing of cholinesterase inhibitors or memantine, or a cognitive test. Model validity was assessed by calibration and discrimination. A hybrid model was developed using deep neural network analysis, a machine learning method. Results 120 (3.6%) participants developed probable dementia/cognitive impairment. Mean calibration by ANU-ADRI, LIBRA, CAIDE and the hybrid model was 19, 0.5, 4.7 and 3.4%, respectively. The discrimination of the models was 0.65 (95% CI 0.60–0.70), 0.65 (95% CI 0.60–0.71), 0.54 (95% CI 0.49–0.58) and 0.80 (95% CI 0.78–0.83), respectively. Conclusion ANU-ADRI and LIBRA were better dementia prediction tools than CAIDE for identification of high-risk individuals in this cohort. ANU-ADRI overestimated and LIBRA underestimated the risk. The new hybrid model had a higher predictive performance than the other models but it needs to be validated independently in longitudinal studies.