Thompson Fintan, Russell Sarah, Quigley Rachel, Sagigi Betty, Miller Gavin, Esterman Adrian, Harriss Linton R, Taylor Sean, McDermott Robyn, Strivens Edward
Australian Institute of Tropical Health and Medicine, College of Public Health, Medical and Veterinary Sciences, James Cook University, Cairns, QLD, Australia.
Queensland Health, Cairns and Hinterland Hospital and Health Service, Cairns, QLD, Australia.
J Alzheimers Dis Rep. 2023 Jun 5;7(1):543-555. doi: 10.3233/ADR-220093. eCollection 2023.
Reducing the burden of dementia in First Nations populations may be addressed through developing population specific methods to quantify future risk of dementia.
To adapt existing dementia risk models to cross-sectional dementia prevalence data from a First Nations population in the Torres Strait region of Australia in preparation for follow-up of participants. To explore the diagnostic utility of these dementia risk models at detecting dementia.
A literature review to identify existing externally validated dementia risk models. Adapting these models to cross-sectional data and assessing their diagnostic utility through area under the receiver operating characteristic curve (AUROC) analyses and calibration using Hosmer-Lemeshow Chi.
Seven risk models could be adapted to the study data. The Aging, Cognition and Dementia (AgeCoDe) study, the Framingham Heart Study (FHS), and the Brief Dementia Screening Indicator (BDSI) had moderate diagnostic utility in identifying dementia (i.e., AUROC >0.70) before and after points for older age were removed.
Seven existing dementia risk models could be adapted to this First Nations population, and three had some cross-sectional diagnostic utility. These models were designed to predict dementia incidence, so their applicability to identify prevalent cases would be limited. The risk scores derived in this study may have prognostic utility as participants are followed up over time. In the interim, this study highlights considerations when transporting and developing dementia risk models for First Nations populations.
通过开发针对特定人群的方法来量化痴呆症的未来风险，可能有助于减轻原住民人群的痴呆症负担。
调整现有的痴呆症风险模型，以适应澳大利亚托雷斯海峡地区原住民人群的横断面痴呆症患病率数据，为参与者的随访做准备。探讨这些痴呆症风险模型在检测痴呆症方面的诊断效用。
进行文献综述以确定现有的经过外部验证的痴呆症风险模型。将这些模型应用于横断面数据，并通过受试者工作特征曲线下面积（AUROC）分析和使用Hosmer-Lemeshow卡方检验进行校准来评估其诊断效用。
七个风险模型可适用于研究数据。在去除老年相关因素前后，衰老、认知与痴呆（AgeCoDe）研究、弗雷明汉心脏研究（FHS）和简易痴呆筛查指标（BDSI）在识别痴呆症方面具有中等诊断效用（即AUROC>0.70）。
七个现有的痴呆症风险模型可适用于该原住民人群，其中三个具有一定的横断面诊断效用。这些模型旨在预测痴呆症发病率，因此它们在识别现患病例方面的适用性将受到限制。随着时间的推移对参与者进行随访时，本研究得出的风险评分可能具有预后效用。在此期间，本研究强调了为原住民人群移植和开发痴呆症风险模型时的注意事项。
