Analyzing the progression of Alzheimer's disease (AD) is challenging due to lacking sensitivity in currently available measures. AD stages are typically defined based on cognitive cut-offs, but this results in heterogeneous patient groups. More accurate modeling of the continuous progression of the disease would enable more accurate patient prognosis. To address these issues, we propose a new multivariate continuous-time disease progression (MCDP) model. The model is formulated as a nonlinear mixed-effects model that aligns patients based on their predicted disease progression along a continuous latent disease timeline. The model is evaluated using long-term follow-up data from 2152 participants in the Alzheimer's Disease Neuroimaging Initiative. The MCDP model was used to simultaneously model three cognitive scales; the Alzheimer's Disease Assessment Scale-cognitive subscale, the Mini-Mental State Examination, and the Clinical Dementia Rating scale—sum of boxes. Compared with univariate modeling and previously proposed multivariate disease progression models, the MCDP model showed superior ability to predict future patient trajectories. Finally, based on the multivariate disease timeline estimated using the MCDP model, the sensitivity of the individual items of the cognitive scales along the different stages of disease was analyzed. The analysis showed that delayed memory recall items had the highest sensitivity in the early stages of disease, whereas language and attention items were sensitive later in disease.

中文翻译：

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通过多个认知量表同时模拟阿尔茨海默病的进展

由于目前可用的措施缺乏敏感性，分析阿尔茨海默病 (AD) 的进展具有挑战性。AD 阶段通常是根据认知临界值来定义的，但这会导致患者群体的异质性。对疾病的持续进展进行更准确的建模将使患者预后更准确。为了解决这些问题，我们提出了一种新的多变量连续时间疾病进展 (MCDP) 模型。该模型被制定为非线性混合效应模型，该模型根据患者预测的疾病进展沿连续的潜在疾病时间线排列。该模型使用来自阿尔茨海默病神经影像学计划的 2152 名参与者的长期随访数据进行评估。MCDP 模型用于同时模拟三个认知量表；阿尔茨海默氏症 s 疾病评估量表——认知分量表、简易精神状态检查和临床痴呆评定量表——方框总和。与单变量建模和先前提出的多变量疾病进展模型相比，MCDP 模型显示出预测未来患者轨迹的卓越能力。最后，基于使用MCDP模型估计的多元疾病时间线，分析了认知量表各个项目在疾病不同阶段的敏感性。分析表明，延迟记忆回忆项目在疾病早期的敏感性最高，而语言和注意力项目在疾病晚期敏感。与单变量建模和先前提出的多变量疾病进展模型相比，MCDP 模型显示出预测未来患者轨迹的卓越能力。最后，基于使用MCDP模型估计的多元疾病时间线，分析了认知量表各个项目在疾病不同阶段的敏感性。分析表明，延迟记忆回忆项目在疾病早期的敏感性最高，而语言和注意力项目在疾病晚期敏感。与单变量建模和先前提出的多变量疾病进展模型相比，MCDP 模型显示出预测未来患者轨迹的卓越能力。最后，基于使用MCDP模型估计的多元疾病时间线，分析了认知量表各个项目在疾病不同阶段的敏感性。分析表明，延迟记忆回忆项目在疾病早期的敏感性最高，而语言和注意力项目在疾病晚期敏感。分析了认知量表各个项目在疾病不同阶段的敏感性。分析表明，延迟记忆回忆项目在疾病早期的敏感性最高，而语言和注意力项目在疾病晚期敏感。分析了认知量表各个项目在疾病不同阶段的敏感性。分析表明，延迟记忆回忆项目在疾病早期的敏感性最高，而语言和注意力项目在疾病晚期敏感。