Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China.
Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, People's Republic of China.
Eur J Med Res. 2023 Oct 12;28(1):427. doi: 10.1186/s40001-023-01265-6.
The neuropathological confirmation serves as the gold standard for diagnosing Alzheimer's disease (AD), but it is usually not available to the living individuals. In addition, the gold standard for diagnosing Mild Cognitive Impairment (MCI) remains unclear yet. Neuropsychological testing, such as the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog), is commonly used tests in identifying AD and MCI, offering convenience, affordability, non-invasiveness, and accessibility in clinical settings. We aimed to accurately evaluate the discriminative ability of the three tests administrated at the same visit simultaneously in detecting AD and MCI due to AD in the absence of a gold standard.
A total of 1289 participants aged over 65 were included from the baseline visits of Alzheimer's disease Neuroimaging Initiative. Bayesian latent class models, accounting for conditional dependence between MoCA and MMSE, were conducted to assess the diagnostic accuracy of the three tests for detecting AD and MCI.
In detecting AD, the ADAS-cog had the highest Youden's Index (0.829), followed by the MoCA(0.813) and MMSE(0.796). The ADAS-cog and MoCA showed similar sensitivity (0.922 vs 0.912) and specificity (0.907 vs 0.901), while the MMSE had lower sensitivity (0.874) and higher specificity (0.922). For MCI detection, the ADAS-cog had the highest Youden's Index (0.704) compared to the MoCA (0.614) and MMSE (0.478). The ADAS-cog exhibited the highest sensitivity, closely followed by the MoCA and MMSE (0.869 vs 0.845 vs 0.757), and the ADAS-cog also had good specificity (0.835 vs 0.769 vs 0.721). The estimated true prevalence of AD among individuals aged over 65 was 20.0%, and the estimated true prevalence of MCI due to AD was 24.8%.
The findings suggest that the ADAS-cog and MoCA are reliable tools for detecting AD and MCI, while the MMSE may be less sensitive in detecting these conditions. A large underdiagnosis of the MCI and Alzheimer's population still remains in clinical screening.
神经病理学的确认是诊断阿尔茨海默病(AD)的金标准,但通常无法应用于活体个体。此外,轻度认知障碍(MCI)的金标准仍然不明确。在临床环境中,蒙特利尔认知评估(MoCA)、简易精神状态检查(MMSE)和阿尔茨海默病评估量表-认知子量表(ADAS-cog)等神经心理学测试常用于识别 AD 和 MCI,具有方便、经济、非侵入性和可及性。我们旨在准确评估在缺乏金标准的情况下,同时在同一就诊时进行这三种测试的区分能力,以检测 AD 所致的 AD 和 MCI。
本研究纳入了来自阿尔茨海默病神经影像学倡议基线访视的 1289 名年龄超过 65 岁的参与者。采用贝叶斯潜在类别模型,考虑 MoCA 和 MMSE 之间的条件依赖性,评估这三种测试在检测 AD 和 MCI 中的诊断准确性。
在检测 AD 方面,ADAS-cog 的尤登指数最高(0.829),其次是 MoCA(0.813)和 MMSE(0.796)。ADAS-cog 和 MoCA 的灵敏度相似(0.922 对 0.912),特异性相似(0.907 对 0.901),而 MMSE 的灵敏度较低(0.874),特异性较高(0.922)。对于 MCI 的检测,ADAS-cog 的尤登指数(0.704)最高,其次是 MoCA(0.614)和 MMSE(0.478)。ADAS-cog 的灵敏度最高,其次是 MoCA 和 MMSE(0.869 对 0.845 对 0.757),且 ADAS-cog 的特异性也较好(0.835 对 0.769 对 0.721)。65 岁以上人群中 AD 的估计真实患病率为 20.0%,AD 所致 MCI 的估计真实患病率为 24.8%。
研究结果表明,ADAS-cog 和 MoCA 是检测 AD 和 MCI 的可靠工具,而 MMSE 在检测这些疾病方面可能不太敏感。在临床筛查中,MCI 和阿尔茨海默病人群仍存在大量漏诊。