The importance of transdiagnostic symptom level assessment to understanding prognosis for depressed adults: analysis of data from six randomised control trials.

Publisher: BioMed Central Country of Publication: England NLM ID: 101190723 Publication Model: Electronic Cited Medium: Internet ISSN: 1741-7015 (Electronic) Linking ISSN: 17417015 NLM ISO Abbreviation: BMC Med Subsets: MEDLINE

Original Publication: [London] : BioMed Central, 2003-

Depression*/diagnosis ; Depression*/epidemiology ; Depressive Disorder, Major*; Adult ; Anxiety/diagnosis ; Anxiety/epidemiology ; Anxiety Disorders ; Humans ; Prognosis

Background: Depression is commonly perceived as a single underlying disease with a number of potential treatment options. However, patients with major depression differ dramatically in their symptom presentation and comorbidities, e.g. with anxiety disorders. There are also large variations in treatment outcomes and associations of some anxiety comorbidities with poorer prognoses, but limited understanding as to why, and little information to inform the clinical management of depression. There is a need to improve our understanding of depression, incorporating anxiety comorbidity, and consider the association of a wide range of symptoms with treatment outcomes.
Method: Individual patient data from six RCTs of depressed patients (total n = 2858) were used to estimate the differential impact symptoms have on outcomes at three post intervention time points using individual items and sum scores. Symptom networks (graphical Gaussian model) were estimated to explore the functional relations among symptoms of depression and anxiety and compare networks for treatment remitters and those with persistent symptoms to identify potential prognostic indicators.
Results: Item-level prediction performed similarly to sum scores when predicting outcomes at 3 to 4 months and 6 to 8 months, but outperformed sum scores for 9 to 12 months. Pessimism emerged as the most important predictive symptom (relative to all other symptoms), across these time points. In the network structure at study entry, symptoms clustered into physical symptoms, cognitive symptoms, and anxiety symptoms. Sadness, pessimism, and indecision acted as bridges between communities, with sadness and failure/worthlessness being the most central (i.e. interconnected) symptoms. Connectivity of networks at study entry did not differ for future remitters vs. those with persistent symptoms.
Conclusion: The relative importance of specific symptoms in association with outcomes and the interactions within the network highlight the value of transdiagnostic assessment and formulation of symptoms to both treatment and prognosis. We discuss the potential for complementary statistical approaches to improve our understanding of psychopathology.

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G0200243 United Kingdom MRC_ Medical Research Council; MQDS16/72 United Kingdom MQ_ MQ: Transforming Mental Health; 201292/Z/16/Z United Kingdom WT_ Wellcome Trust

Keywords: Anxiety; Comorbidity; Depression; Item level analysis; Network modelling

Date Created: 20210506 Date Completed: 20211018 Latest Revision: 20231115

20240829

PMC8101158

10.1186/s12916-021-01971-0

33952286