Prediction of prolonged treatment course for depressive and anxiety disorders in an outpatient setting: The Leiden routine outcome monitoring study

Highlight

• The BSI can be used, as an indicator of composite symptom severity, to predict prolonged treatment course and to develop an easy to use prediction model.

• A high level of symptoms at 2–6 months of follow-up is a strong predictor for prolonged treatment course.

• Facilitation of early identification of patients at risk of a prolonged course of treatment; in a relatively easy way by a self-assessed symptom severity.

Abstract

Objective

The aim of this study was to improve clinical identification of patients with a prolonged treatment course for depressive and anxiety disorders early in treatment.

Method

We conducted a cohort study in 1.225 adult patients with a depressive or anxiety disorders in psychiatric specialty care setting between 2007 and 2011, with at least two Brief Symptom Inventory (BSI) assessments within 6 months. With logistic regression, we modelled baseline age, gender, ethnicity, education, marital status, housing situation, employment status, psychiatric comorbidity and both baseline and 1st follow-up BSI scores to predict prolonged treatment course (>2 years). Based on the regression coefficients, we present an easy to use risk prediction score.

Results

BSI at 1st follow-up proved to be a strong predictor for both depressive and anxiety disorders (OR = 2.17 (CI95% 1.73–2.74); OR = 2.52 (CI95% 1.86–3.23)). The final risk prediction score included BSI 1st follow-up and comorbid axis II disorder for depressive disorder, for anxiety disorders BSI 1st follow-up and age were included. For depressive disorders, for 28% of the patients with the highest scores, the positive predictive value for a prolonged treatment course was60% (sensitivity 0.38, specificity 0.81). For anxiety disorders, for 35% of the patients with the highest scores, the positive predictive value for a prolonged treatment course was 52% (sensitivity 0.55, specificity 0.75).

Conclusions

A high level of symptoms at 2–6 months of follow-up is a strong predictor for prolonged treatment course. This facilitates early identification of patients at risk of a prolonged course of treatment; in a relatively easy way by a self-assessed symptom severity.

Introduction

Depressive and anxiety disorders are the most common mental disorders (Vos et al., 2010), with an estimated prevalence of respectively 298 and 273 million people worldwide. These disorders are associated with a high burden of disease (Wittchen et al., 2011) and high impact on society (Gustavsson et al., 2011), translating into substantial direct and indirect costs. Direct costs are related to treatment and the use of other health care services, and indirect costs to reduced quality of life, loss of productivity, absenteeism and functional impairment in many other personal and interpersonal areas of life (Donohue and Pincus, 2007, Combs and Markman, 2014).

The course of depressive disorders is variable, with approximately 60% of patients recovering within the first six months after diagnosis and up to 80% within two years (Steinert et al., 2014). Recurrence risk is 15–40% in two years. A persistent course with no major improvement despite treatment over two years or more, has been reported for 5 to 20% of patients, although slow improvements tend to continue over time (Hardeveld et al., 2010, Stegenga et al., 2012, Riihimaki et al., 2014, Steinert et al., 2014). For anxiety disorders the initial course is less favourable, with only 46% of patients recovering within two years and a similar recurrence risk of 15–40%, depending on type of anxiety disorder (Steinert et al. 2013; Penninx et al. 2011; Bruce et al., 2005).

In general, slow and incomplete recovery is associated with longer treatment duration (Riihimaki et al., 2014) and a longer treatment duration is associated with higher healthcare resource utilization (Haller et al., 2014); as for example more (severe) symptoms for patients with a prolonged treatment course, comorbidities, or treatment resistance in patients with a prolonged treatment course (Von Korff et al. 1992; Crown et al., 2002; Richards 2011; Dennehy et al., 2015). The majority of healthcare resources are consumed by a relatively small group of patients with a prolonged treatment course (Rais et al., 2013; Robinson et al., 2016).

Several studies have found that early response to treatment within two to eight weeks partially predicts further recovery (Van et al., 2008a; Van et al. 2008b; van Calker et al., 2009, Tadic et al., 2010, Kim et al., 2011, Baldwin et al., 2012). Identification of patients with an unfavourable initial course of treatment could provide opportunities to target this subgroup with higher intensity treatment and potentially reduce chronicity early in the course of treatment (Trivedi and Baker, 2001, Lutz et al., 2009, Kendrick et al., 2016). Given that only limited data are published to support this, further research is implicated.

The implementation of Routine Outcome Monitoring (ROM) in mental health care provides an opportunity to study treatment course and symptom change, measured by general symptom inventories, such as the Brief Symptom Inventory (BSI) (Lutz et al., 2009; Katon et al., 2010; de Beurs et al. 2011). In the current study, we aimed to improve the clinical prediction of treatment duration for depressive and anxiety disorders in a routine care outpatient setting, and to identify patients with an unfavourable prognosis early in treatment course. Especially, we aimed to assess the role of the BSI, as an indicator of composite symptom severity, to predict prolonged treatment course and to develop an easy to use prediction model.