From the Graduate Program in Biological Sciences: Biochemistry (A.B., W.S.B., M.A.D.B., J.P.F.-S., D.O.S., E.R.Z.), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Wallenberg Centre for Molecular and Translational Medicine (M.S.), University of Gothenburg, Sweden; Pharmacology and Therapeutics Graduate Program (W.V.B.), Universidade Federal do Rio Grande do Sul (UFRGS); Memory Center (W.V.B.), Moinhos de Vento Hospital; Department of Anatomy (W.V.B.), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; The McGill University Research Centre for Studies in Aging (J.T., A.L.B., T.A.P., S.G., P.R.-N., E.R.Z.), McGill University; Douglas Research Institute (J.T., P.R.-N.), Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University; Departments of Neurology and Neurosurgery (J.T., S.G., P.R.-N.) and Psychiatry (J.T., S.G., P.R.-N.), McGill University, Montreal, Canada; Graduate Program in Biological Sciences: Pharmacology and Therapeutics (A.G.M., A.F.S.-S., E.R.Z.), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Department of Psychiatry and Neurochemistry (W.S.B., A.L.B., M.S., H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Sweden; Department of Neurology and Psychiatry (J.P.F.-S., T.A.P.), University of Pittsburgh, PA; Brain Institute of Rio Grande do Sul (J.C.D.C., L.P.S., E.R.Z.), Pontíficia Universidade Católica do Rio Grande do Sul; Department of Biochemistry (D.O.S.), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Neurology Service (R.M.C., A.F.S.-S., M.L.F.C.), Hospital de Clínicas de Porto Alegre; Department of Pharmacology (A.F.S.-S., E.R.Z.), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Department of Neurodegenerative Disease (M.S., H.Z.), Queen Square Institute of Neurology, University College London, United Kingdom; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Gothenburg, Sweden; UK Dementia Research Institute at University College London (H.Z.), United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.).
Neurology. 2024 Sep 10;103(5):e209753. doi: 10.1212/WNL.0000000000209753. Epub 2024 Aug 21.
Updates in Alzheimer disease (AD) diagnostic guidelines by the National Institute on Aging-Alzheimer's Association (NIA-AA) and the International Working Group (IWG) over the past 11 years may affect clinical diagnoses. We assessed how these guidelines affect clinical AD diagnosis in a cohort of cognitively unimpaired (CU) and cognitively impaired (CI) individuals.
We applied clinical and biomarker data in algorithms to classify individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort according to the following diagnostic guidelines for AD: 2011 NIA-AA, 2016 IWG-2, 2018 NIA-AA, and 2021 IWG-3, assigning the following generic diagnostic labels: (1) not AD (nAD), (2) increased risk of developing AD (irAD), and (3) AD. Diagnostic labels were compared according to their frequency, convergence across guidelines, biomarker profiles, and prognostic value. We also evaluated the diagnostic discordance among the criteria.
A total of 1,195 individuals (mean age 73.2 ± 7.2 years, mean education 16.1 ± 2.7, 44.0% female) presented different repartitions of diagnostic labels according to the 2011 NIA-AA (nAD = 37.8%, irAD = 23.0%, AD = 39.2%), 2016 IWG-2 (nAD = 37.7%, irAD = 28.7%, AD = 33.6%), 2018 NIA-AA (nAD = 40.7%, irAD = 9.3%, AD = 50.0%), and 2021 IWG-3 (nAD = 51.2%, irAD = 8.4%, AD = 48.3%) frameworks. Discordant diagnoses across all guidelines were found in 512 participants (42.8%) (138 [91.4%] occurring in only β-amyloid [CU 65.4%, CI 34.6%] and 191 [78.6%] in only tau-positive [CU 71.7%, CI 28.3%] individuals). Differences in predicting cognitive impairment between nAD and irAD groups were observed with the 2011 NIA-AA (hazard ratio [HR] 2.21, 95% CI 1.34-3.65, = 0.002), 2016 IWG-2 (HR 2.81, 95% CI 1.59-4.96, < 0.000), and 2021 IWG-3 (HR 3.61, 95% CI 2.09-6.23, < 0.000), but not with 2018 NIA-AA (HR 1.69, 95% CI 0.87-3.28, = 0.115).
Over 42% of the studied population presented discordant diagnoses when using the different examined AD criteria, mostly in individuals with a single positive biomarker. Except for 2018 NIA-AA, all guidelines identified asymptomatic individuals at risk of cognitive impairment. Our findings highlight important differences between the guidelines, emphasizing the necessity for updated criteria with enhanced staging metrics, considering clinical, research, therapeutic, and trial design aspects.
过去 11 年，美国国家老龄化研究所-阿尔茨海默病协会（NIA-AA）和国际工作组（IWG）对阿尔茨海默病（AD）诊断指南进行了更新，这可能会影响临床诊断。我们评估了这些指南如何影响认知正常（CU）和认知受损（CI）个体的 AD 临床诊断。
我们应用临床和生物标志物数据在算法中，根据以下 AD 诊断指南对来自阿尔茨海默病神经影像学倡议（ADNI）队列的个体进行分类：2011 年 NIA-AA、2016 年 IWG-2、2018 年 NIA-AA 和 2021 年 IWG-3，并分配以下通用诊断标签：（1）非 AD（nAD），（2）AD 发病风险增加（irAD），和（3）AD。根据其频率、指南间的一致性、生物标志物特征和预后价值比较诊断标签。我们还评估了标准之间的诊断差异。
共有 1195 名个体（平均年龄 73.2 ± 7.2 岁，平均受教育年限 16.1 ± 2.7，44.0%为女性）根据 2011 年 NIA-AA（nAD = 37.8%，irAD = 23.0%，AD = 39.2%）、2016 年 IWG-2（nAD = 37.7%，irAD = 28.7%，AD = 33.6%）、2018 年 NIA-AA（nAD = 40.7%，irAD = 9.3%，AD = 50.0%）和 2021 年 IWG-3（nAD = 51.2%，irAD = 8.4%，AD = 48.3%）框架呈现出不同的诊断标签分布。在所有指南中发现了 512 名（42.8%）有诊断差异的参与者（138 [91.4%] 仅在β-淀粉样蛋白阳性[CU 65.4%，CI 34.6%]中出现，191 [78.6%] 仅在 tau 阳性[CU 71.7%，CI 28.3%]中出现）。在 2011 年 NIA-AA（危险比[HR]2.21，95%置信区间[CI]1.34-3.65，<0.000）、2016 年 IWG-2（HR 2.81，95% CI 1.59-4.96，<0.000）和 2021 年 IWG-3（HR 3.61，95% CI 2.09-6.23，<0.000）中观察到 nAD 和 irAD 组预测认知障碍的差异，但在 2018 年 NIA-AA 中未观察到（HR 1.69，95% CI 0.87-3.28，=0.115）。
在使用不同的 AD 标准时，超过 42%的研究人群存在不一致的诊断，主要发生在具有单一阳性生物标志物的个体中。除了 2018 年 NIA-AA 外，所有指南都确定了无症状的认知障碍风险个体。我们的发现强调了指南之间的重要差异，强调了需要更新具有增强分期指标的标准，同时考虑临床、研究、治疗和试验设计方面。
