Prognostic Value of Pathological Personality Traits for Treatment Outcome in Anxiety and Depressive Disorders: The Leiden Routine Outcome Monitoring Study.

ABSTRACT: Previous studies have failed to take baseline severity into account when assessing the effects of pathological personality traits (PPT) on treatment outcome. This study assessed the prognostic value of PPT (Dimensional Assessment of Personality Pathology-Short Form) on treatment outcome (Brief Symptom Inventory [BSI-posttreatment]) among patients with depressive and/or anxiety disorders ( N = 5689). Baseline symptom level (BSI-pretreatment) was taken into account as a mediator or moderator variable. Results showed significant effects of PPT on outcome, of which Emotional Dysregulation demonstrated the largest association ( ß = 0.43, p < 0.001). When including baseline BSI score as a mediator variable, a direct effect ( ß = 0.11, p < 0.001) remained approximately one-third of the total effect. The effects of Emotional Dysregulation (interaction effect ß = 0.061, p < 0.001) and Inhibition (interaction effect ß = 0.062, p < 0.001), but not Compulsivity or Dissocial Behavior, were moderated by the baseline symptom level. PPT predicts higher symptom levels, both before and after treatment, but yields relatively small direct effects on symptom decline when the effect of pretreatment severity is taken into account.

Basal and LPS-stimulated inflammatory markers and the course of anxiety symptoms.

A cross-sectional relationship between low-grade inflammation -characterized by increased blood levels of C-reactive protein (CRP) and pro-inflammatory cytokines- and anxiety has been reported, but the potential longitudinal relationship has been less well studied. We aimed to examine whether basal and lipopolysaccharide (LPS-)induced levels of inflammatory markers are associated with anxiety symptom severity over the course of nine years. We tested the association between basal and LPS-induced inflammatory markers with anxiety symptoms (measured with the Beck's Anxiety Inventory; BAI, Fear Questionnaire; FQ and Penn's State Worry Questionnaire; PSWQ) at 5 assessment waves over a period up nine years. We used multivariate-adjusted mixed models in up to 2867 participants of the Netherlands Study of Depression and Anxiety (NESDA). At baseline, 43.6% of the participants had a current anxiety disorder, of which social phobia (18.5%) was most prevalent. Our results demonstrated that baseline inflammatory markers were significantly associated with several outcomes of anxiety at baseline over nine subsequent years. BAI subscale of somatic (arousal) symptoms of anxiety, and FQ subscale of agoraphobia demonstrated the strongest effects with standardized beta-coefficients of up to 0.14. The associations were attenuated by 25%-30% after adjusting for the presence of (comorbid) major depressive disorder (MDD), but remained statistically significant. In conclusion, we found that participants with high levels of inflammatory markers have on average high levels of anxiety consisting of physical arousal and agoraphobia, which tended to persist over a period of nine years, albeit with small effect sizes. These associations were partly driven by co-morbid depression.

Predicting the 9-year course of mood and anxiety disorders with automated machine learning: A comparison between auto-sklearn, naïve Bayes classifier, and traditional logistic regression.

BACKGROUND: Predicting the onset and course of mood and anxiety disorders is of clinical importance but remains difficult. We compared the predictive performances of traditional logistic regression, basic probabilistic machine learning (ML) methods, and automated ML (Auto-sklearn). METHODS: Data were derived from the Netherlands Study of Depression and Anxiety. We compared how well multinomial logistic regression, a naïve Bayes classifier, and Auto-sklearn predicted depression and anxiety diagnoses at a 2-, 4-, 6-, and 9-year follow up, operationalized as binary or categorical variables. Predictor sets included demographic and self-report data, which can be easily collected in clinical practice at two initial time points (baseline and 1-year follow up). RESULTS: At baseline, participants were 42.2 years old, 66.5% were women, and 53.6% had a current mood or anxiety disorder. The three methods were similarly successful in predicting (mental) health status, with correct predictions for up to 79% (95% CI 75-81%). However, Auto-sklearn was superior when assessing a more complex dataset with individual item scores. CONCLUSIONS: Automated ML methods added only limited value, compared to traditional data modelling when predicting the onset and course of depression and anxiety. However, they hold potential for automatization and may be better suited for complex datasets.

Basal and LPS-stimulated inflammatory markers and the course of individual symptoms of depression.

Multiple studies show an association between inflammatory markers and major depressive disorder (MDD). People with chronic low-grade inflammation may be at an increased risk of MDD, often in the form of sickness behaviors. We hypothesized that inflammation is predictive of the severity and the course of a subset of MDD symptoms, especially symptoms that overlap with sickness behavior, such as anhedonia, anorexia, low concentration, low energy, loss of libido, psychomotor slowness, irritability, and malaise. We tested the association between basal and lipopolysaccharide (LPS)-induced inflammatory markers with individual MDD symptoms (measured using the Inventory of Depressive Symptomatology Self-Report) over a period of up to 9 years using multivariate-adjusted mixed models in 1147-2872 Netherlands Study of Depression and Anxiety (NESDA) participants. At baseline, participants were on average 42.2 years old, 66.5% were women and 53.9% had a current mood or anxiety disorder. We found that basal and LPS-stimulated inflammatory markers were more strongly associated with sickness behavior symptoms at up to 9-year follow-up compared with non-sickness behavior symptoms of depression. However, we also found significant associations with some symptoms that are not typical of sickness behavior (e.g., sympathetic arousal among others). Inflammation was not related to depression as a unified syndrome but rather to the presence and the course of specific MDD symptoms, of which the majority were related to sickness behavior. Anti-inflammatory strategies should be tested in the subgroup of MDD patients who report depressive symptoms related to sickness behavior.

Neuroticism and chronicity as predictors of 9-year course of individual depressive symptoms.

BACKGROUND: The large between-person differences in symptomatology suggest that major depressive disorder (MDD) is a heterogeneous psychiatric disorder. However, symptom-specific prospective studies are scarce. We hypothesized that chronicity (i.e., being depressed for 24 months during a patient's preceding 48 months at baseline) and neuroticism at baseline would predict adverse course trajectories over 9 years of follow up with differential magnitudes for individual depressive symptoms. METHODS: In total, 560 patients with a current MDD were included from the Netherlands Study of Depression and Anxiety (NESDA-cohort). We used a multivariate linear mixed model with repeated measures, with a history of chronicity and neuroticism separately as main independent variables and with Inventory of Depressive Symptomatology self-report (IDS-SR) item scores as outcome variables. For each individual symptom, the model was adjusted for age, gender, and baseline depression severity. RESULTS: Patients were on average 42.7 (SD = 12.1) years old and 64.7% were women. Patients with chronic depression or high levels of neuroticism showed similar absolute rates of decline over time compared to their counterparts. However, because symptoms had higher starting points for mood, cognitive, and somatic/vegetative symptoms (in that order), symptom severity remained higher over time. Chronicity and neuroticism were especially linked to persistent low self-esteem and high interpersonal sensitivity. LIMITATIONS: Neuroticism is partly state dependent and likely affected by depression severity. CONCLUSIONS: Chronicity and neuroticism predict long-term persistence of diverse psychiatric symptoms, in particular low self-esteem and high interpersonal sensitivity.

Testing for response shift in treatment evaluation of change in self-reported psychopathology amongst secondary psychiatric care outpatients.

OBJECTIVES: If patients change their perspective due to treatment, this may alter the way they conceptualize, prioritize, or calibrate questionnaire items. These psychological changes, also called "response shifts," may pose a threat to the measurement of therapeutic change in patients. Therefore, it is important to test the occurrence of response shift in patients across their treatment. METHODS: This study focused on self-reported psychological distress/psychopathology in a naturalistic sample of 206 psychiatric outpatients. Longitudinal measurement invariance tests were computed across treatment in order to detect response shifts. RESULTS: Compared with before treatment, post-treatment psychopathology scores showed an increase in model fit and factor loading, suggesting that symptoms became more coherently interrelated within their psychopathology domains. Reconceptualization (depression/mood) and reprioritization (somatic and cognitive problems) response shift types were found in several items. We found no recalibration response shift. CONCLUSION: This study provides further evidence that response shift can occur in adult psychiatric patients across their mental health treatment. Future research is needed to determine whether response shift implies an unwanted potential bias in treatment evaluation or a desired cognitive change intended by treatment.