Latent classes of symptom trajectories among major depressive disorder patients in China

Abstract

ObjectiveThis study aimed to understand the long-term symptom trajectories of Chinese patients with major depressive disorder (MDD) using piecewise latent growth modeling and growth mixture modeling. The investigation also aimed to identify the baseline characteristics indicative of poorer treatment outcomes. MethodsA total of 558 outpatients with MDD were assessed using a sequence of surveys. The Hamilton Rating Scale for Depression (HRSD), Hamilton Anxiety Rating Scale (HAMA), and Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) were used to evaluate baseline depression, anxiety, and cognitive function. Depression symptom severity was subsequently measured at the 1-month, 2-month, 6-month, 1-year, and 2-year follow-ups. ResultsResults indicated three depressive symptomology trajectories, including (a) severe, improving class (12.72 %), (b) partially responding, later deteriorating class (6.09 %), and (c) moderate, improving class (81.18 %). Logistic regression analyses showed that a history of cardiovascular disease (CVD) increased the odds of belonging to the partially responding, later deteriorating class, whereas higher baseline depression increased the odds of belonging to the severe, improving class compared to the moderate, improving class. Patients who experienced less depression relief during the first month of treatment had a lower probability of belonging to the moderate, improving class. LimitationsParticipant attrition in this study may have inflated the estimated rate of treatment-resistant patients. ConclusionsThe burden of CVD and poorer initial treatment response are plausible risk factors for poorer treatment outcomes, highlighting targets for intervention in Chinese MDD patients.