Case Western Reserve University, Center for Health Care Research & Policy, MetroHealth Medical Center, Cleveland, OH, USA.
Case Western Reserve University, Department of Epidemiology and Biostatistics, Cleveland, OH, USA.
Mult Scler Relat Disord. 2016 Sep;9:163-9. doi: 10.1016/j.msard.2016.08.004. Epub 2016 Aug 5.
Trajectories of depression over time may be heterogeneous in Multiple Sclerosis (MS) patients. Describing these trajectories will help clinicians understand better the progression of depression in MS patients to aid in patient care decisions.
Latent class growth analysis (LCGA) was applied to 3507 MS patients using an electronic health records (EHR) data base to identify subgroups of MS patients based on self-reported depression screening (PHQ-9). Latent trajectory classes were used for group comparisons based on baseline clinical characteristics.
Three subgroups were found characterized by high (10.0% [of participants]), wavering above and below moderate (26.2%) and low and variable (63.8%) depression level trajectories. The subpopulation trajectories, respectively, were also characterized by high, moderate and low MS disability at baseline. In contrast, the overall average trajectory was slightly declining and below the moderate depression threshold.
The LCGA approach described in this paper and applied to MS patients provides a template for improved use of an EHR data base for understanding heterogeneous depression screening trajectories. Clinicians may use such information to more closely monitor patients that are expected to maintain high or unstable depression levels.
多发性硬化症 (MS) 患者的抑郁随时间的轨迹可能存在异质性。描述这些轨迹将有助于临床医生更好地了解 MS 患者抑郁的进展，以辅助患者护理决策。
使用电子健康记录 (EHR) 数据库对 3507 名 MS 患者进行潜在类别增长分析 (LCGA)，根据自我报告的抑郁筛查 (PHQ-9) 对 MS 患者进行基于亚组的分组。基于基线临床特征，使用潜在轨迹类别进行组间比较。
发现了三个亚组，分别表现为高（10.0%[参与者]）、中度以上波动（26.2%）和高低波动（63.8%）的抑郁水平轨迹。亚群轨迹在基线时也分别表现出较高、中度和低度的 MS 残疾。相比之下，总体平均轨迹呈略微下降趋势，低于中度抑郁阈值。
本文描述的 LCGA 方法应用于 MS 患者，为更好地利用 EHR 数据库来理解异质的抑郁筛查轨迹提供了模板。临床医生可以使用这些信息来更密切地监测那些预计会保持高或不稳定抑郁水平的患者。
