Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
Int Psychogeriatr. 2010 Mar;22(2):281-90. doi: 10.1017/S1041610209991001. Epub 2009 Sep 28.
Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates, have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects.
201 Caucasian subjects with possible or probable Alzheimer's disease (AD) were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept with initial MMSE score, age, gender, education, and APOE 4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included.
AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE 4 was not associated with any trajectory.
Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in AD.
迟发性阿尔茨海默病(LOAD)是一种临床表现异质性的复杂疾病,其特征为进行性认知功能障碍。约半数 LOAD 患者会出现影响认知功能的精神症状,此类精神症状与认知功能下降速度加快相关。然而,LOAD 患者认知轨迹的多样性及其相关因素尚未得到充分明确。因此,我们使用潜在类别建模方法对 AD 患者队列的认知和行为下降轨迹进行了特征描述。
201 名白种人 AD 患者在长达 13.5 年的时间内定期接受认知和精神症状评估。采用简易精神状态检查量表(MMSE)对认知症状进行连续评估,采用 CERAD 行为评定量表(CBRS)对精神症状进行评分。分析采用包含二次轨迹的潜在类别混合模型,包括初始 MMSE 评分、年龄、性别、教育程度和 APOE4 计数作为伴随变量的随机截距。在二次分析中,还纳入了精神病状态。
AD 患者表现出 6 种具有显著不同轨迹和认知下降速度的轨迹。纳入最佳潜在类别轨迹模型的伴随变量包括初始 MMSE 和年龄。精神病症状负担越大,所有年龄和初始 MMSE 组的认知下降速度越快的可能性越大。APOE4 与任何轨迹均无相关性。
对纵向认知和行为数据进行轨迹建模可能会提高 AD 表型变异的分辨率。