School of Psychology, University of New South Wales, Kensington, New South Wales, Australia.
Neuroscience Research Australia, Randwick, New South Wales, Australia.
JAMA Netw Open. 2023 Aug 1;6(8):e2331460. doi: 10.1001/jamanetworkopen.2023.31460.
While the Australian National University-Alzheimer Disease Risk Index (ANU-ADRI), Cardiovascular Risk Factors, Aging, and Dementia (CAIDE), and Lifestyle for Brain Health (LIBRA) dementia risk tools have been widely used, a large body of new evidence has emerged since their publication. Recently, Cognitive Health and Dementia Risk Index (CogDrisk) and CogDrisk for Alzheimer disease (CogDrisk-AD) risk tools have been developed for the assessment of dementia and AD risk, respectively, using contemporary evidence; comparison of the relative performance of these risk tools is limited.
To evaluate the performance of CogDrisk, ANU-ADRI, CAIDE, LIBRA, and modified LIBRA (LIBRA with age and sex estimates from ANU-ADRI) in estimating dementia and AD risks (with CogDrisk-AD and ANU-ADRI).
DESIGN, SETTING, AND PARTICIPANTS: This population-based cohort study obtained data from the Rush Memory and Aging Project (MAP), the Cardiovascular Health Study Cognition Study (CHS-CS), and the Health and Retirement Study-Aging, Demographics and Memory Study (HRS-ADAMS). Participants who were free of dementia at baseline were included. The factors were component variables in the risk tools that included self-reported baseline demographics, medical risk factors, and lifestyle habits. The study was conducted between November 2021 and March 2023, and statistical analysis was performed from January to June 2023.
Risk scores were calculated based on available factors in each of these cohorts. Area under the receiver operating characteristic curve (AUC) was calculated to measure the performance of each risk score. Multiple imputation was used to assess whether missing data may have affected estimates for dementia risk.
Among the 6107 participants in 3 validation cohorts included for this study, 2184 participants without dementia at baseline were available from MAP (mean [SD] age, 80.0 [7.6] years; 1606 [73.5%] female), 548 participants without dementia at baseline were available from HRS-ADAMS (mean [SD] age, 79.5 [6.3] years; 288 [52.5%] female), and 3375 participants without dementia at baseline were available from CHS-CS (mean [SD] age, 74.8 [4.9] years; 1994 [59.1%] female). In all 3 cohorts, a similar AUC for dementia was obtained using CogDrisk, ANU-ADRI, and modified LIBRA (MAP cohort: CogDrisk AUC, 0.65 [95% CI, 0.61-0.69]; ANU-ADRI AUC, 0.65 [95% CI, 0.61-0.69]; modified LIBRA AUC, 0.65 [95% CI, 0.61-0.69]; HRS-ADAMS cohort: CogDrisk AUC, 0.75 [95% CI, 0.71-0.79]; ANU-ADRI AUC, 0.74 [95% CI, 0.70-0.78]; modified LIBRA AUC, 0.75 [95% CI, 0.71-0.79]; CHS-CS cohort: CogDrisk AUC, 0.70 [95% CI, 0.67-0.72]; ANU-ADRI AUC, 0.69 [95% CI, 0.66-0.72]; modified LIBRA AUC, 0.70 [95% CI, 0.68-0.73]). The CAIDE and LIBRA also provided similar but lower AUCs than the 3 aforementioned tools (eg, MAP cohort: CAIDE AUC, 0.50 [95% CI, 0.46-0.54]; LIBRA AUC, 0.53 [95% CI, 0.48-0.57]). The performance of CogDrisk-AD and ANU-ADRI in estimating AD risks was also similar.
CogDrisk and CogDrisk-AD performed similarly to ANU-ADRI in estimating dementia and AD risks. These results suggest that CogDrisk and CogDrisk-AD, with a greater range of modifiable risk factors compared with other risk tools in this study, may be more informative for risk reduction.
尽管澳大利亚国立大学-阿尔茨海默病风险指数（ANU-ADRI）、心血管风险因素、衰老和痴呆症（CAIDE）以及大脑健康生活方式（LIBRA）痴呆症风险工具已经被广泛应用，但自这些工具发表以来，已经出现了大量新的证据。最近，认知健康和痴呆症风险指数（CogDrisk）和 CogDrisk 用于阿尔茨海默病（CogDrisk-AD）风险的开发，分别使用了当代证据；这些风险工具的相对性能比较有限。
评估 CogDrisk、ANU-ADRI、CAIDE、LIBRA 和改良 LIBRA（使用 ANU-ADRI 估计年龄和性别后的 LIBRA）在估计痴呆症和 AD 风险（CogDrisk-AD 和 ANU-ADRI）方面的表现。
设计、地点和参与者：本基于人群的队列研究从 Rush 记忆和衰老项目（MAP）、心血管健康研究认知研究（CHS-CS）和健康与退休研究-老龄化、人口统计学和记忆研究（HRS-ADAMS）中获取数据。纳入基线时无痴呆症的参与者。这些因素是风险工具中的组成变量，包括自我报告的基线人口统计学、医疗风险因素和生活方式习惯。研究于 2021 年 11 月至 2023 年 3 月进行，统计分析于 2023 年 1 月至 6 月进行。
根据每个队列中可用的因素计算风险评分。计算接受者操作特征曲线（ROC）下面积（AUC）来衡量每个风险评分的表现。使用多重插补评估缺失数据是否可能影响痴呆症风险的估计。
在本研究纳入的 3 个验证队列的 6107 名参与者中，有 2184 名基线时无痴呆症的参与者来自 MAP（平均[SD]年龄，80.0[7.6]岁；1606[73.5%]为女性），有 548 名基线时无痴呆症的参与者来自 HRS-ADAMS（平均[SD]年龄，79.5[6.3]岁；288[52.5%]为女性），有 3375 名基线时无痴呆症的参与者来自 CHS-CS（平均[SD]年龄，74.8[4.9]岁；1994[59.1%]为女性）。在所有 3 个队列中，使用 CogDrisk、ANU-ADRI 和改良 LIBRA 获得的痴呆症 AUC 相似（MAP 队列：CogDrisk AUC，0.65[95%CI，0.61-0.69]；ANU-ADRI AUC，0.65[95%CI，0.61-0.69]；改良 LIBRA AUC，0.65[95%CI，0.61-0.69]；HRS-ADAMS 队列：CogDrisk AUC，0.75[95%CI，0.71-0.79]；ANU-ADRI AUC，0.74[95%CI，0.70-0.78]；改良 LIBRA AUC，0.75[95%CI，0.71-0.79]；CHS-CS 队列：CogDrisk AUC，0.70[95%CI，0.67-0.72]；ANU-ADRI AUC，0.69[95%CI，0.66-0.72]；改良 LIBRA AUC，0.70[95%CI，0.68-0.73]）。CAIDE 和 LIBRA 提供的 AUC 也低于上述 3 个工具（例如，MAP 队列：CAIDE AUC，0.50[95%CI，0.46-0.54]；LIBRA AUC，0.53[95%CI，0.48-0.57]）。CogDrisk-AD 和 ANU-ADRI 在估计 AD 风险方面的性能也相似。
CogDrisk 和 CogDrisk-AD 在估计痴呆症和 AD 风险方面与 ANU-ADRI 表现相似。这些结果表明，与本研究中其他风险工具相比，CogDrisk 和 CogDrisk-AD 具有更大范围的可改变风险因素，可能对降低风险更有信息价值。
