title: Network analysis of clinical trials on depression: implications for comparative effectiveness research.
abstract: A comprehensive understanding of evidence related to treatments for a disease is critical for planning effective clinical care, and for designing future trials. However, it is often difficult to comprehend the available evidence because of the complex combination of interventions across trials, in addition to the limited search and retrieval tools available in databases such as ClinicalTrials.gov. Here we demonstrate the use of networks to visualize and quantitatively analyze the co-occurrence of drug interventions across trials on depression in ClinicalTrials.gov. The analysis identified general co-occurrence patterns of interventions across all depression trials, and specific co-occurrence patterns related to antidepressants and natural supplements. These results led to insights about the current state of depression trials, and to a graph-theoretic measure to categorize interventions for a disease. We conclude by discussing the opportunities and challenges of generalizing our approach to analyze comparative interventional studies for any disease.
authors.affiliation: Center for Computational Medicine & Bioinformatics.
authors.forename: Suresh K
authors.initials: SK
authors.lastname: Bhavnani
authors.forename: Simona
authors.initials: S
authors.lastname: Carini
authors.forename: Jessica
authors.initials: J
authors.lastname: Ross
authors.forename: Ida
authors.initials: I
authors.lastname: Sim
mesh_terms: D057186:Comparative Effectiveness Research; D003863:Depression; D003866:Depressive Disorder; D006801:Humans