Murley Alexander G, Bowns Lucy, Camacho Marta, Williams-Gray Caroline H, Tsvetanov Kamen A, Rittman Timothy, Barker Roger A, O'Brien John T, Rowe James B
Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Alzheimers Dement. 2025 Jan;21(1):e14377. doi: 10.1002/alz.14377. Epub 2024 Nov 19.
The history from a relative or caregiver is an important tool for differentiating neurodegenerative disease. We characterized patterns of caregiver questionnaire responses, at diagnosis and follow-up, on the Cambridge Behavioural Inventory (CBI).
Data-driven multivariate analysis (n = 4952 questionnaires) was undertaken for participants (n = 2481) with Alzheimer's disease (typical/amnestic n = 543, language n = 50, and posterior cortical n = 50 presentations), Parkinson's disease (n = 740), dementia with Lewy bodies (n = 55), multiple system atrophy (n = 55), progressive supranuclear palsy (n = 422), corticobasal syndrome (n = 176), behavioral variant frontotemporal dementia (n = 218), semantic (n = 125) and non-fluent variant progressive aphasia (n = 88), and motor neuron disease (n = 12).
Item-level support vector machine learning gave high diagnostic accuracy between diseases (area under the curve mean 0.83), despite transdiagnostic changes in memory, behavior, and everyday function. There was progression in CBI subscores over time, which varied by diagnosis.
Our results highlight the differential diagnostic information for a wide range of neurodegenerative diseases contained in a simple, structured collateral history.
We analyzed 4952 questionnaires from caregivers of 2481 participants with neurodegenerative disease. Behavioral and neuropsychiatric manifestations of neurodegenerative disease had overlapping diagnostic boundaries. Simple questionnaire response patterns were sufficient for accurate diagnosis of each disease. We reinforce the value of a collateral history to support a diagnosis of dementia. The Cambridge Behavioural Inventory is sensitive to change over time and suitable as an outcome measure in clinical trials.
亲属或照料者提供的病史是鉴别神经退行性疾病的重要工具。我们对在诊断和随访时照料者关于剑桥行为量表（CBI）的问卷回答模式进行了特征描述。
对患有阿尔茨海默病（典型/遗忘型n = 543、语言型n = 50和后皮质型n = 50表现）、帕金森病（n = 740）、路易体痴呆（n = 55）、多系统萎缩（n = 55）、进行性核上性麻痹（n = 422）、皮质基底节综合征（n = 176）、行为变异型额颞叶痴呆（n = 218）、语义性（n = 125）和非流利变异型进行性失语（n = 88）以及运动神经元病（n = 12）的参与者（n = 2481）进行了数据驱动的多变量分析（n = 4952份问卷）。
尽管在记忆、行为和日常功能方面存在跨诊断变化，但项目级支持向量机学习在疾病之间给出了较高的诊断准确性（曲线下面积平均为0.83）。CBI子分数随时间推移有所进展，且因诊断而异。
我们的结果突出了简单、结构化的旁系病史中包含的针对多种神经退行性疾病的鉴别诊断信息。
我们分析了来自2481名患有神经退行性疾病参与者的照料者的4952份问卷。神经退行性疾病的行为和神经精神表现具有重叠的诊断界限。简单的问卷回答模式足以准确诊断每种疾病。我们强化了旁系病史对支持痴呆诊断的价值。剑桥行为量表对随时间的变化敏感，适合作为临床试验中的一项结局指标。
