Chu Chenyin, Wang Yifei, Wang Yihan, Fowler Christopher, Zisis Georgios, Masters Colin L, Doecke James D, Goudey Benjamin, Jin Liang, Pan Yijun
The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.
Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia.
JAMA Netw Open. 2025 Jan 2;8(1):e2453756. doi: 10.1001/jamanetworkopen.2024.53756.
The ability to predict the onset of mild cognitive impairment (MCI) and Alzheimer dementia (AD) could allow older adults and clinicians to make informed decisions about dementia care.
To assess whether the age at onset of MCI and AD can be predicted using a statistical modeling approach.
DESIGN, SETTING, AND PARTICIPANTS: This prognostic study used data from 2 aging and dementia cohort studies-the Australian Imaging, Biomarker and Lifestyle (AIBL) study and the Alzheimer's Disease Neuroimaging Initiative (ADNI)-for model development and validation of the Florey Dementia Index (FDI), a tool used to predict the age at onset of MCI and AD in older adults. Data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer (A4) study were used for a simulated trial. Data were collected from 1665 AIBL participants, 2029 ADNI participants, and 93 A4 participants from October 1, 2004, to March 1, 2023. The data analysis was conducted between January and August 2024.
Predicted age at onset compared with clinically observed age at onset.
Among the 1665 AIBL participants (741 [44.5%] female) and 2029 ADNI participants (925 [45.6%] female), the mean (SD) age at first evaluation was 71.8 (7.1) years and 74.5 (6.7) years, respectively. The FDI achieved mean absolute errors of 2.78 (95% CI, 2.63-2.93) years for predicting MCI onset and 1.48 (95% CI, 1.32-1.65) years for predicting AD onset. In the simulated trial with 93 A4 participants (48 [51.6%] female; mean [SD] age at baseline, 73.4 [5.1] years), the FDI achieved mean absolute errors of 1.57 (95% CI, 1.41-1.71) years for predicting MCI onset and 0.70 (95% CI, 0.53-0.88) years for predicting AD onset.
In this prognostic study, the FDI was developed and validated to predict the onset age of MCI and AD. This tool may be useful in organizing health care for older adults with cognitive decline or dementia and in the future may help prioritize patients for the use of disease-modifying monoclonal antibody drugs.
预测轻度认知障碍（MCI）和阿尔茨海默病性痴呆（AD）发病的能力可使老年人和临床医生就痴呆症护理做出明智决策。
评估是否可以使用统计建模方法预测MCI和AD的发病年龄。
设计、设置和参与者：这项预后研究使用了两项衰老与痴呆队列研究的数据——澳大利亚影像、生物标志物和生活方式（AIBL）研究以及阿尔茨海默病神经影像学倡议（ADNI）——用于弗洛里痴呆指数（FDI）的模型开发和验证，该指数是一种用于预测老年人MCI和AD发病年龄的工具。无症状阿尔茨海默病抗淀粉样蛋白治疗（A4）研究的数据用于模拟试验。数据收集于2004年10月1日至2023年3月1日期间的1665名AIBL参与者、2029名ADNI参与者和93名A4参与者。数据分析于2024年1月至8月进行。
预测的发病年龄与临床观察到的发病年龄进行比较。
在1665名AIBL参与者（741名[44.5%]为女性）和2029名ADNI参与者（925名[45.6%]为女性）中，首次评估时的平均（标准差）年龄分别为71.8（7.1）岁和74.5（6.7）岁。FDI预测MCI发病的平均绝对误差为2.78（95%CI，2.63 - 2.93）岁，预测AD发病的平均绝对误差为1.48（95%CI，1.32 - 1.65）岁。在有93名A4参与者（48名[51.6%]为女性；基线时平均[标准差]年龄为73.4[5.1]岁）的模拟试验中，FDI预测MCI发病的平均绝对误差为1.57（95%CI，1.41 - 1.71）岁，预测AD发病的平均绝对误差为0.70（95%CI，0.53 - 0.88）岁。
在这项预后研究中，开发并验证了FDI以预测MCI和AD的发病年龄。该工具可能有助于为认知功能下降或痴呆的老年人组织医疗保健，并且未来可能有助于确定使用疾病修饰单克隆抗体药物的患者优先级。
