Elsevier

Journal of Psychiatric Research

Volume 95, December 2017, Pages 19-27
Journal of Psychiatric Research

A comprehensive model of predictors of persistence and recurrence in adults with major depression: Results from a national 3-year prospective study

https://doi.org/10.1016/j.jpsychires.2017.07.022Get rights and content

Highlights

  • We developed a comprehensive model of the 3-year risk of MDE persistence and recurrence.

  • We used structural equation modeling in a nationally representative sample.

  • We found 4 main independent predictive factors at baseline.

  • These factors include severity of depression and comorbidities, quality of life, and failure to seek treatment for MDE.

  • This model highlights strategies that may improve the course of MDE.

Abstract

Identifying predictors of persistence and recurrence of depression in individuals with a major depressive episode (MDE) poses a critical challenge for clinicians and researchers. We develop using a nationally representative sample, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N = 34,653), a comprehensive model of the 3-year risk of persistence and recurrence in individuals with MDE at baseline. We used structural equation modeling to examine simultaneously the effects of four broad groups of clinical factors on the risk of MDE persistence and recurrence: 1) severity of depressive illness, 2) severity of mental and physical comorbidity, 3) sociodemographic characteristics and 4) treatment-seeking behavior. Approximately 16% and 21% of the 2587 participants with an MDE at baseline had a persistent MDE and a new MDE during the 3-year follow-up period, respectively. Most independent predictors were common for both persistence and recurrence and included markers for the severity of the depressive illness at baseline (as measured by higher levels on the general depressive symptom dimension, lower mental component summary scores, prior suicide attempts, younger age at onset of depression and greater number of MDEs), the severity of comorbidities (as measured by higher levels on dimensions of psychopathology and lower physical component summary scores) and a failure to seek treatment for MDE at baseline. This population-based model highlights strategies that may improve the course of MDE, including the need to develop interventions that target multiple psychiatric disorders and promotion of treatment seeking to increase access to timely mental health care.

Introduction

Major depression is a leading source of disease burden (Hollon et al., 2005, Lopez et al., 2006) characterized by complex patterns of recurrence and persistence (Hasin et al., 2005, Kessler et al., 2003, Mueller et al., 1999, Solomon et al., 1997). Persistence and recurrence are common among patients with major depression (Frank et al., 1990, Keller et al., 1983, Mueller et al., 1999). Persistence may be defined by a prolonged time to recovery from an index episode and recurrence by the occurrence of a new episode in a remitted case (Skodol et al., 2011). Identifying predictors of persistence and recurrence in patients with a major depressive episode (MDE) is an important challenge for clinicians and researchers.

Prior research has implicated several risk factors for MDE persistence or recurrence. They include severity of major depression (Sargeant et al., 1990, Skodol et al., 2011, Spijker et al., 2010, Steinert et al., 2014), number of lifetime MDEs (Skodol et al., 2011, Spijker et al., 2010, Steinert et al., 2014), co-occurring Axis I (Hoertel et al., 2013a, Hoertel et al., 2013b, Hoertel et al., 2013c, Keller et al., 1982, Keller et al., 1992, Klein et al., 2006, Manetti et al., 2014, Steinert et al., 2014) and Axis II disorders (Grilo et al., 2005, Skodol et al., 2011), history of suicide attempts (Avery and Winokur, 1978), family history of depression (Patten et al., 2010), concurrent physical health problems and psychosocial difficulties (Lam et al., 2009), early age at onset of first MDE (Hoertel et al., 2013a, Klein et al., 1999), stressful live events (Wang et al., 2012), female gender, older age and being divorced or widowed (Colman et al., 2011, Dowrick et al., 2011, Fava et al., 2007, Gilman et al., 2013, Hardeveld et al., 2013a, Hardeveld et al., 2013b, Kornstein et al., 2000, Lam et al., 2009, Patten et al., 2012, ten Doesschate et al., 2010, Wang et al., 2012).

The diversity of these predictors and their frequent co-occurrence suggest the need to develop more powerful statistical approaches. Several integrative predictive models of MDE persistence or recurrence have been examined (Brugha et al., 1997, Dowrick et al., 2011, ten Doesschate et al., 2010, Wang et al., 2014, Fandiño-Losada et al., 2016). However, most of these models have been based on samples of convenience and used relatively small sample sizes. In addition, because MDE often co-occurs with other mental disorders (Kessler et al., 2003, Kessler et al., 2005, Manetti et al., 2014), recent theories have proposed a meta-structure of psychiatric diagnoses that organizes disorders into broad dimensions of psychopathology (i.e., internalizing and externalizing dimensions) (Blanco et al., 2013, Eaton et al., 2012, Hoertel et al., 2015a, Hoertel et al., 2015b, Kotov et al., 2011, Krueger et al., 1998, Krueger and Markon, 2006). Applying this dimensional approach to model disorder comorbidity in a comprehensive model of MDE persistence or recurrence could help clarify whether broad psychopathological liabilities or individual Axis I or Axis II disorders predict persistence or recurrence of MDE.

This report proposes a comprehensive model of the 3-year risk of persistence or recurrence of MDE using a longitudinal nationally representative study, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). We used structural equation modeling to examine simultaneously the effects of four broad groups of clinical factors previously identified as potential predictors of persistence and recurrence of MDE: 1) severity of depressive illness, 2) severity of mental and physical comorbidity, 3) sociodemographic characteristics and 4) treatment-seeking behavior. With this model, we aimed to ascertain readily identifiable characteristics to help clinicians recognize adults with MDE who are at increased risk for recurrent or chronic MDE.

Section snippets

Sample

Data were drawn from the wave 1 and wave 2 of the NESARC, a nationally representative face-to-face survey of the US adult population, conducted in 2001–2002 (Wave 1) and 2004–2005 (Wave 2) by the National Institute on Alcoholism and Alcohol Abuse (NIAAA) (Grant et al., 2003). The target population included the civilian noninstitutionalized population, aged 18 years and older, residing in the United States. The overall response rate at Wave 1 was 81% and the cumulative response rate at Wave 2

Clinical characteristics assessed at wave 1 and the 3-year risk of MDE persistence and recurrence

Among participants with a 12-month DSM-IV diagnosis of MDE at Wave 1 (n = 2587), 15.7% (SE = 0.8, N = 418) had a chronic MDE and 20.7% (SE = 0.9, n = 526) had a new MDE during a 3-year follow-up period. Binary logistic models showed that increased risk of MDE persistence was significantly associated with all comorbid mental disorders (except for alcohol and drug use disorders and histrionic and antisocial personality disorders), lower mental and physical component summary scores, all symptoms

Discussion

In a large, nationally representative cohort of US adults, we sought to build a comprehensive model of MDE persistence and recurrence that integrates information across a wide range of clinical domains to estimate their relative impact. About 36% of individuals with an MDE at Wave 1 had either a persistent or a recurrent MDE at 3-year follow-up. Risk of persistence or recurrence of MDE was not determined by a single factor, but rather by the combined effects of multiple risk factors. Most

Funding/support

This study was supported by NIH grants MH076051 and MH082773 (Drs. Blanco, Olfson, Oquendo and Wall) and the New York State Psychiatric Institute (Drs. Hoertel, Blanco, Olfson, Oquendo and Wall) and a fellowship grant from Public Health Expertise (Dr. Hoertel). The sponsors had no additional role in the design and conduct of the study; collection, management, analysis and interpretation of the data; and preparation, review or approval of the manuscript.

Role of the funding source

The funding sources had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Additional information

The National Epidemiologic Survey on Alcohol and Related Conditions was sponsored by the National Institute on Alcohol Abuse and Alcoholism and funded, in part, by the Intramural Program, NIAAA, National Institutes of Health. The original data set for the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) is available from the National Institute on Alcohol Abuse and Alcoholism (http://www.niaaa.nih.gov).

Contributors

NH, CB and FL designed the study. NH and MW undertook statistical analyses. NH and CB wrote the first draft of the manuscript. MAO, MW, MO, BF, SF, HP, CL, and FL reviewed the draft. All authors contributed to and have approved the final manuscript.

Conflicts of interest

Dr. Blanco holds stock in Sanofi, Eli Lilly, Inc and General Electric. Dr. Oquendo receives royalties for the commercial use of the C-SSRS and her family owns stock in Bristol Myers Squibb. Dr. Falissard has been consultant for E. Lilly, BMS, Servier, SANOFI, GSK, HRA, Roche, Boeringer Ingelheim, Bayer, Almirall, Allergan, Stallergene, Genzyme, Pierre Fabre, Astrazeneca, Novartis, Janssen, Astellas, Biotronik, Daiichi-Sankyo, Gilead, MSD, Lundbeck, Stallergene, Actelion, UCB, Otsuka, Grunenthal

Disclaimer

The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of any of the sponsoring organizations, agencies, or the US government.

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