Abstract
INTRODUCTION: Chronic depression represents a common and highly disabling disorder. Several randomised controlled trials (RCTs) investigated the effectiveness of psychological, pharmacological and combined treatments for chronic depression. This is the first overarching systematic review and network meta-analysis (NMA) based on aggregated and individual patient data comparing the efficacy and acceptability of various treatment options for all subtypes of chronic depression. Furthermore, individual demographic and clinical characteristics that predict or moderate therapy outcomes will be investigated. METHODS AND ANALYSIS: A systematic literature search of the Cochrane Library, MEDLINE via Ovid, PsycINFO, Web of Science and metapsy databases will be conducted from database inception without language restrictions to include all available samples from RCTs that investigated the efficacy of psychotherapy versus pharmacotherapy, or their combination in adult inpatients or outpatients with a primary diagnosis of chronic depression. Exclusively internet-based treatment studies will be excluded. The main outcome is depression severity measured on a continuous observer-rated scale for depression at 6 months post-treatment (range 3-12 months). Two reviewers will independently screen and select eligible studies based on the predefined inclusion and exclusion criteria. Risk of bias will be assessed using version 2 of the Cochrane risk-of-bias tool for randomised trials (RoB 2). Individual patient data (IPD) will be requested and incorporated in the network when provided, as it is the gold standard of evidence. For studies which do not provide IPD, aggregate data (AD) will be extracted and incorporated in lieu of IPD for the NMA, strengthening the evidence base and leveraging all existing evidence regardless of data availability restrictions. An NMA comparing psychotherapies and a network meta-regression estimating individualised treatment effects of psychotherapy will be implemented assuming a Bayesian framework. All models will be fitted in R with calls to JAGS. Empirical informative prior distributions will be used for model parameters where available, and non-informative priors will be used in cases where empirical priors are not available. ETHICS AND DISSEMINATION: This IPD-NMA requires no ethical approval. All results will be disseminated as peer-reviewed publication in a leading journal in this field and presented at (inter)national scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42024526755.