Major depression, a disorder with early onset and often chronic course, imposes a high individual burden of pain, suffering, and disability. Most depression treatment studies include primarily White and middle-class populations so that little is known about the effectiveness of established treatments for ethnic minority and poor individuals. A frequent characteristic of depression studies is that outcomes over time are subject to considerable between-subject heterogeneity due to the fact that patients often follow different trajectories over time. When comparing the effectiveness of different treatments, it is important to identify and take into account these different trajectories because the effectiveness of an intervention may depend on the trajectory class of the participants. Growth mixture modeling (GMM) allows the analyst to estimate several different trajectories over the course of a study. In this way, GMM may do a better job of capturing between-subject variability because it does not require that all individuals follow the same trajectory over time. In this application, we propose to compare the effectiveness of medication versus cognitive behavioral therapy using data from the WECare study, a longitudinal depression treatment study of low-income mostly minority women with depression. Using GMM we will identify and predict response trajectories over the course of the study.
Our specific aims are (1) Identify subtypes of clinical response trajectories among WECare subjects and then compare the effectiveness of antidepressant medication and cognitive behavioral therapy within these trajectories. (2) Classify subjects in the various response trajectories in terms of their baseline characteristics including socioeconomic and clinical features to identify which patients are more likely to benefit from a given intervention. (3) Extend existing GMM approaches to handle participants who drop out a study. This research has the potential to identify the most effective depression treatments at the individual level.
Project Narrative: This project will estimate the different trajectories that participants follow in response to treatment for depression and the socioeconomic and clinical features associated with these trajectories. The comparative effectiveness of antidepressant medication versus cognitive behavioral therapy will be estimated within trajectories. The overall goal is to contribute to the development of personalized depression interventions for disadvantaged populations.
| Siddique, Juned; Harel, Ofer; Crespi, Catherine M et al. (2014) Binary variable multiple-model multiple imputation to address missing data mechanism uncertainty: application to a smoking cessation trial. Stat Med 33:3013-28 |
| Siddique, Juned; Chung, Joyce Y; Brown, C Hendricks et al. (2012) Comparative effectiveness of medication versus cognitive-behavioral therapy in a randomized controlled trial of low-income young minority women with depression. J Consult Clin Psychol 80:995-1006 |
