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Background: Twice weekly sessions of cognitive behavioral therapy (CBT) and interpersonal psychotherapy (IPT) for major depressive disorder (MDD) lead to less drop-out and quicker and better response compared to once weekly sessions at posttreatment, but it is unclear whether these effects hold over the long run., Aims: Compare the effects of twice weekly v. weekly sessions of CBT and IPT for depression up to 24 months since the start of treatment., Methods: Using a 2 × 2 factorial design, this multicentre study randomized 200 adults with MDD to once or twice weekly sessions of CBT or IPT over 16-24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II and the Longitudinal Interval Follow-up Evaluation. Intention-to-treat analyses were conducted., Results: Compared with patients who received once weekly sessions, patients who received twice weekly sessions showed a significant decrease in depressive symptoms up through month 9, but this effect was no longer apparent at month 24. Patients who received CBT showed a significantly larger decrease in depressive symptoms up to month 24 compared to patients who received IPT, but the between-group effect size at month 24 was small. No differential effects between session frequencies or treatment modalities were found in response or relapse rates., Conclusions: Although a higher session frequency leads to better outcomes in the acute phase of treatment, the difference in depression severity dissipated over time and there was no significant difference in relapse.

Background: Cost-effective treatments are needed to reduce the burden of depression. One way to improve the cost-effectiveness of psychotherapy might be to increase session frequency, but keep the total number of sessions constant., Aim: To evaluate the cost-effectiveness of twice-weekly compared with once-weekly psychotherapy sessions after 12 months, from a societal perspective., Method: An economic evaluation was conducted alongside a randomised controlled trial comparing twice-weekly versus once-weekly sessions of psychotherapy (cognitive-behavioural therapy or interpersonal psychotherapy) for depression. Missing data were handled by multiple imputation. Statistical uncertainty was estimated with bootstrapping and presented with cost-effectiveness acceptability curves., Results: Differences between the two groups in depressive symptoms, physical and social functioning, and quality-adjusted life-years (QALY) at 12-month follow-up were small and not statistically significant. Total societal costs in the twice-weekly session group were higher, albeit not statistically significantly so, than in the once-weekly session group (mean difference €2065, 95% CI -686 to 5146). The probability that twice-weekly sessions are cost-effective compared with once-weekly sessions was 0.40 at a ceiling ratio of €1000 per point improvement in Beck Depression Inventory-II score, 0.32 at a ceiling ratio of €50 000 per QALY gained, 0.23 at a ceiling ratio of €1000 per point improvement in physical functioning score and 0.62 at a ceiling ratio of €1000 per point improvement in social functioning score., Conclusions: Based on the current results, twice-weekly sessions of psychotherapy for depression are not cost-effective over the long term compared with once-weekly sessions.

Efficacious treatments are available for major depressive disorder (MDD), but treatment dropout is common and decreases their effectiveness. However, knowledge about prevalence of treatment dropout and its risk factors in routine care is limited. The objective of this study was to determine the prevalence of and risk factors for dropout in a large outpatient sample. In this retrospective cohort analysis, routinely collected data from 2235 outpatients with MDD who had a diagnostic work-up between 2014 and 2016 were examined. Dropout was defined as treatment termination without achieving remission before the fourth session within six months after its start. Total and item scores on the Dutch Measure for Quantification of Treatment Resistance in Depression (DM-TRD) at baseline, and demographic variables were analyzed for their association with dropout using logistic regression and elastic net analyses. Data of 987 subjects who started routine outpatient depression treatment were included in the analyses of which 143 (14.5%) dropped out. Higher DM-TRD-scores were predictive for lower dropout odds [OR = 0.78, 95% CI = (0.70-0.86), p < 0.001]. The elastic net analysis revealed several clinical variables predictive for dropout. Higher SES, higher depression severity, comorbid personality pathology and a comorbid anxiety disorder were significantly associated with less dropout in the sample. In this observational study, treatment dropout was relatively low. The DM-TRD, an easy-to-use clinical instrument, revealed several variables associated with less dropout. When applied in daily practice and combined with demographical information, this instrument may help to reduce dropout and increase treatment effectiveness., (© 2022. The Author(s).)

Background: Long-term untreated major depressive disorder (MDD) is associated with a less favorable clinical course. Waiting time, defined as the interval between diagnostic workup and treatment initiation, may be clinically relevant given the prolongation of the pre-existing duration of untreated MDD. However, it is currently unknown whether and to what extent waiting time affects treatment course in routine outpatient care., Methods: Retrospectively extracted data from 715 outpatients with MDD who received naturalistic outpatient MDD treatment were examined. Treatment outcome was defined as the difference in depression severity at the start of treatment and six months thereafter. Clinical course during waiting time was defined by the difference in severity at diagnostic workup and at treatment initiation. We analyzed the association between waiting time and treatment outcome and between waiting time and clinical course during this waiting time using multivariable regression analyses. We adjusted for severity and suicidality as potential confounders., Results: An increased duration of the waiting time was associated with a less favorable treatment outcome (B = 0.049, SE = 0.019, p = 0.01). This association persisted after adjustment for potential confounders (B = 0.053, SE = 0.02, p = 0.01). No association was found between length of waiting time and clinical course during waiting time., Limitations: Strict definitions resulted in smaller sample sizes for the final analyses. The uncontrolled design may be questionable to definitively establish the impact of waiting time on treatment outcome., Conclusions: A prolonged waiting time is significantly associated with less favorable treatment outcome. Reduction of waiting time deserves priority in depression treatment planning to improve clinical outcomes., Competing Interests: Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Psychopathic traits come with high levels of anger and aggression. Since previous studies showed that compassion can mitigate both anger and aggression, the current research puts compassion forward as a possible target to alleviate psychopathy's destructive patterns. Specifically, the present study explored the influence of subclinical psychopathic traits-as well as their three subcomponents egocentricity, callousness, and antisociality-on the efficacy of experimentally induced self-compassion (SC) and other-compassion (OC). This manuscript is part of a larger study in which student and community participants ( N = 230, M age = 27.41, 65.2% female) completed a psychopathic trait questionnaire to assess their dimensional level of psychopathy, filled out state SC and OC questionnaires, and were randomized to participate in an experimental self- or other-compassion induction. It was expected that psychopathic traits would positively relate to increases in SC but negatively relate to increases in OC. Baseline levels of both SC and OC negatively related to psychopathy. Overall, as expected, the results on change scores show that subclinical psychopathic traits positively related to a stronger increase in SC, irrespective of the type of compassion induction. This positive relation between a stronger increase in SC and psychopathy total and callousness was more pronounced after the SC induction, rather than after the OC induction. Psychopathic traits did not differentially influence changes in OC. One implication of this study is that high psychopathic and callousness traits predispose to profit extra from targeting SC. Furthermore, psychopathic traits do not hinder increasing compassion for others. These findings suggest that compassion is a promising intervention to improve the wellbeing of people with elevated subclinical psychopathic traits and those around them. Although further research is needed to assess the impact of compassion on anger and aggression specifically, and on clinical psychopathy, the current study suggests that both SC and OC may be useful intervention targets in case of elevated psychopathic traits., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lobbestael, Freund, Geschwind, Meesters and Peeters.)

Objective Psychotherapies for depression are similarly effective, but the processes through which these therapies work have not been identified. We focus on psychological process changes during therapy as predictors of long-term depression outcome in treatment responders. Method: Secondary analysis of a randomized trial comparing cognitive therapy (CT) and interpersonal psychotherapy (IPT) that focuses on 85 treatment responders. Using mixed-effects models, changes during therapy (0-7 months) on nine process variables were associated with depression severity (BDI-II) at follow-up (7-24 months). Results: A decrease in dysfunctional attitudes was associated with a decrease in depression scores over time. Improved self-esteem was associated with less depression at follow-up (borderline significant). More improvement in both work and social functioning and interpersonal problems was associated with better depression outcomes in IPT relative to CT, while less improvement in work and social functioning and interpersonal problems was associated with better outcomes in CT relative to IPT. Conclusions: Less negative thinking during therapy is associated with lower depression severity in time, while changes during therapy in work and social functioning and interpersonal problems appear to predict different long-term outcomes in CT vs. IPT. If replicated, these findings can be used to guide clinical decision-making during psychotherapy.

Objective: The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care., Methods: Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models., Results: Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders., Conclusions: Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients.

Objective: The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care., Methods: Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models., Results: Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders., Conclusions: Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients., Competing Interests: Dr. Ruhé has received speaking fees from Janssen and Lundbeck and grants from ZonMW, Horizon 2020, and Hersenstichting. The other authors report no financial relationships with commercial interests.

Background: Research on which therapy processes are crucial for whom is necessary to optimize treatment outcomes for major depressive disorder (MDD) but may be impeded by a lack of variation in therapy quality and because of individual differences in therapy response. The present study used a dataset with large variation in therapy quality to investigate the impact of therapy quality on change in therapy processes and outcome. Machine-learning techniques were used to explore individual differences in these relationships., Method: Data come from a multicenter trial that randomized patients with MDD into weekly versus twice weekly sessions of cognitive behavioral therapy (CBT) or interpersonal psychotherapy (IPT). Correlations between quality of therapy, change in therapy processes and depressive symptoms were calculated. Using elastic net regression, a prognostic model was developed that investigated individual differences., Results: There were no significant correlations between therapy quality and change in therapy process variables or between therapy quality and therapy outcome, except between therapy quality and dysfunctional thinking and IPT skills. Improvement in therapy processes played a larger role in patients whose therapy outcome was poorly predicted by their baseline characteristics., Conclusions: In this study, in which therapy quality varied considerably, we found that therapy quality was not related to change in therapy processes or outcome. In addition, this study provides a first demonstration of proposed methods to identify individual responses to change in therapy processes. Results suggested that the importance of certain therapy processes might differ between patients. Future research into the relation between therapy quality, change in therapy processes and outcome should take into account the variation of therapy quality, focus on improved measurement of therapy quality and use a combination of machine learning techniques and experimental lab studies to determine to which extent and for whom therapy quality and change in therapy processes matter., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Optimizing treatment selection is a way to enhance treatment success in major depressive disorder (MDD). In clinical practice, treatment selection heavily depends on clinical judgment. However, research has consistently shown that statistical prediction is as accurate - or more accurate - than predictions based on clinical judgment. In the context of new technological developments, the current aim was to compare the accuracy of clinical judgment versus statistical predictions in selecting cognitive therapy (CT) or interpersonal psychotherapy (IPT) for MDD., Methods: Data came from a randomized trial comparing CT (n=76) with IPT (n=75) for MDD. Prior to randomization, therapists' recommendations were formulated during multidisciplinary staff meetings. Statistical predictions were based on Personalized Advantage Index models. Primary outcomes were post-treatment and 17-month follow-up depression severity. Secondary outcome was treatment dropout., Results: Individuals receiving treatment according to their statistical prediction were less depressed at post-treatment and follow-up compared to those receiving their predicted non-indicated treatment. This difference was not found for recommended versus non-recommended treatments based on clinical judgment. Moreover, for individuals with an IPT recommendation by therapists, higher post-treatment and follow-up depression severity was found for those that actually received IPT compared to those that received CT. Recommendations based on statistical prediction and clinical judgment were not associated with differences in treatment dropout., Limitations: Information on the clinical reasoning behind therapist recommendations was not collected, and statistical predictions were not externally validated., Conclusions: Statistical prediction outperforms clinical judgment in treatment selection for MDD and has the potential to personalize treatment strategies., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: Optimizing treatment selection may improve treatment outcomes in depression. A promising approach is the Personalized Advantage Index (PAI), which predicts the optimal treatment for a given individual. To determine the generalizability of the PAI, models needs to be externally validated, which has rarely been done. Method: PAI models were developed within each of two independent trials, with substantial between-study differences, that both compared CBT and IPT for depression (STEPd: n  = 151 and FreqMech: n  = 200). Subsequently, both PAI models were tested in the other dataset. Results: In the STEPd study, post-treatment depression was significantly different between individuals assigned to their PAI-indicated treatment versus those assigned to their non-indicated treatment ( d  = .57). In the FreqMech study, post-treatment depression was not significantly different between patients receiving their indicated treatment versus those receiving their non-indicated treatment ( d  = .20). Cross-trial predictions indicated that post-treatment depression was not significantly different between those receiving their indicated treatment and those receiving their non-indicated treatment ( d  = .16 and d  = .27). Sensitivity analyses indicated that cross-trial prediction based on only overlapping variables didn't improve the results. Conclusion: External validation of the PAI has modest results and emphasizes between-study differences and many other challenges.

Background: Results from previous meta-analyses of the impact of comorbid personality disorders (PD's) on treatment outcomes for depressive disorder are contradictory and biased by methodological differences between included studies., Aim: To investigate the impact of comorbid PD on the outcome of depression treatments, using only studies with controlled treatments and structured measurement instruments (PROSPERO, CRD42019120200)., Method: Studies were searched in PubMed, PsycINFO and Embase, and in reference lists of selected articles and previous meta-analyses. Treatment studies for depression with a subset of individuals with comorbid PD were included. Primary outcome was depression severity change during treatment. Effect sizes were estimated using random effect models, study-level variables were examined with meta-regression. Bias was assessed with the Risk of Bias tool., Results: Six studies involving 942 individuals (447 with PD) were included. There was no significant difference in depression severity reduction between individuals with and without PD (g = 0.03, 95% CI -0.15-0.20, p = 0.27). Heterogeneity and risk of bias were low. The meta-regression did not yield significant results., Conclusion: Findings don't indicate an impact of comorbid PD on the outcome of acute phase treatment for depression. Depressed patients with and without comorbid PD should receive the same evidence-based depression treatments.

Background: Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy., Methods: Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions., Results: One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit., Conclusions: If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.

Background: It is unclear what session frequency is most effective in cognitive-behavioural therapy (CBT) and interpersonal psychotherapy (IPT) for depression., Aims: Compare the effects of once weekly and twice weekly sessions of CBT and IPT for depression., Method: We conducted a multicentre randomised trial from November 2014 through December 2017. We recruited 200 adults with depression across nine specialised mental health centres in the Netherlands. This study used a 2 × 2 factorial design, randomising patients to once or twice weekly sessions of CBT or IPT over 16-24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II at baseline, before session 1, and 2 weeks, 1, 2, 3, 4, 5 and 6 months after start of the intervention. Intention-to-treat analyses were conducted., Results: Compared with patients who received weekly sessions, patients who received twice weekly sessions showed a statistically significant decrease in depressive symptoms (estimated mean difference between weekly and twice weekly sessions at month 6: 3.85 points, difference in effect size d = 0.55), lower attrition rates (n = 16 compared with n = 32) and an increased rate of response (hazard ratio 1.48, 95% CI 1.00-2.18)., Conclusions: In clinical practice settings, delivery of twice weekly sessions of CBT and IPT for depression is a way to improve depression treatment outcomes.

Objective: Although the effectiveness of interpersonal psychotherapy (IPT) and cognitive therapy (CT) for major depression has been established, little is known about how and for whom they work and how they compare in the long term. The latter is especially relevant for IPT because research on its long-term effects has been limited. This overview paper summarizes findings from a Dutch randomized controlled trial on the effects and mechanisms of change of IPT versus CT for major depression., Methods: Adult outpatients with depression (N=182) were randomly assigned to CT (N=76), IPT (N=75), or a 2-month waitlist control group followed by patient's treatment of choice (N=31). The primary outcome was depression severity. Other outcomes were quality of life, social and general psychological functioning, and scores on various mechanism measures. Interventions were compared at the end of treatment and up to 17 months follow-up., Results: On average, IPT and CT were both superior to waitlist, and their outcomes did not differ significantly from one another. However, the pathway through which change occurred appeared to differ. For a majority of participants, one of the interventions was predicted to be more beneficial than the other. No support for the theoretical models of change was found., Conclusions: Outcomes of IPT and CT did not appear to differ significantly. IPT may have an enduring effect not different from that of CT. The field would benefit from further refinement of study methods to disentangle mechanisms of change and from advances in the field of personalized medicine (i.e., person-specific analyses and treatment selection methods).

An adolescent patient with acute abdominal pain and vomiting presented in the emergency room. Bathing in hot water relieved his symptoms. Physical examination, basic laboratory testing and imaging showed no abnormalities. The patient was diagnosed with cannabinoid hyperemesis syndrome, which is characterized by chronic cannabis use, recurrent episodes of intractable vomiting and compulsively hot showering or bathing to relieve the symptoms. Unfamiliarity with the syndrome can easily lead to unnecessary diagnostic testing and inappropriate treatment. The consulting psychiatrist could play a role in the diagnostic process and treatment. Furthermore, early recognition of this syndrome in the emergency room may lead to a proper addiction treatment program.

Using data from 202 patients with depression, the authors conducted a psychometric evaluation of the Dutch translation of the Competencies of Cognitive Therapy Scale-Self-Report and an initial psychometric evaluation of the newly developed Interpersonal Psychotherapy Skills Scale-Self-Report.

Background: The Dutch Measure for Quantification of Treatment Resistance in Depression (DM-TRD) is a promising prediction tool for major depressive disorder (MDD) based on variables associated with treatment outcome. The objective of our study was to examine the association between the DM-TRD and clinical course in a large cohort of MDD outpatients receiving treatment as usual. Furthermore, we examined whether the addition of an item measuring the presence of childhood adversity improved this association., Methods: We included 1115 subjects with MDD (according to the DSM-IV) who were naturalistically treated at seven outpatient departments of a secondary mental healthcare center in the Netherlands. Data on subjects who had a diagnostic work-up between June 2014 and June 2016 were analyzed. Multilevel analyses were performed to examine the association between the DM-TRD score at baseline and clinical course, defined by symptom severity according to scores on the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR) over time. We also investigated whether an extra item measuring childhood adversity improved the model., Results: The model including the DM-TRD and its interaction with time was superior to previous models. The addition of childhood adversity and its interaction with time did not improve the model., Conclusions: In depressed outpatients receiving treatment as usual, the solid longer-term association between higher DM-TRD scores and worse clinical course supports its usefulness in clinical practice. Childhood adversity did not improve the model value indicating that-counterintuitively-this parameter offers no additional predictive power to the variables included., (© 2018 Wiley Periodicals, Inc.)

Background: Major depressive disorder (MDD) has a highly recurrent nature. After successful treatment, it is important to identify individuals who are at risk of an unfavorable long-term course. Despite extensive research, there is no consensus yet on the clinically relevant predictors of long-term outcome in MDD, and no prediction models are implemented in clinical practice. The aim of this study was to create a prognostic index (PI) to estimate long-term depression severity after successful and high quality acute treatment for MDD., Methods: Data come from responders to cognitive therapy (CT) and interpersonal psychotherapy (IPT) in a randomized clinical trial (n = 85; CT = 45, IPT = 40). Primary outcome was depression severity, assessed with the Beck Depression Inventory II, measured throughout a 17-month follow-up phase. We examined 29 variables as potential predictors, using a model-based recursive partitioning method and bootstrap resampling in conjunction with backwards elimination. The selected predictors were combined into a PI. Individual PI scores were estimated using a cross-validation approach., Results: A total of three post-treatment predictors were identified: depression severity, hopelessness, and self-esteem. Cross-validated PI scores evidenced a strong correlation (r = 0.60) with follow-up depression severity., Conclusion: Long-term predictions of MDD are multifactorial, involving a combination of variables that each has a small prognostic effect. If replicated and validated, the PI can be implemented to predict follow-up depression severity for each individual after acute treatment response, and to personalize long-term treatment strategies., (© 2018 The Authors. Depression and Anxiety published by Wiley Periodicals, Inc.)

Background: Anxious depression is an important subtype of Major Depressive Disorder (MDD) defined by both syndromal (anxiety disorders) and dimensional (anxiety symptoms) criteria. A debated question is how anxiety affects MDD treatment. This study examined the impact of comorbid anxiety disorders and symptoms on the effectiveness of and dropout during Cognitive Therapy (CT) and Interpersonal Psychotherapy (IPT) for MDD., Methods: Depressed individuals were randomized to CT (n = 76) or IPT (n = 75). Outcome was depression severity measured with the Beck Depression Inventory-II (BDI-II) at the start of each therapy session, post treatment, and monthly up to five months follow-up. Anxiety disorders were assessed with the Structured Clinical Interview for DSM-IV Axis I disorders, (phobic) anxiety symptoms were assessed with Brief Symptom Inventory subscales., Results: Approximately one third of participants had a comorbid anxiety disorder. Comorbid anxiety disorders and anxiety symptoms were associated with less favorable depression change during IPT as compared to CT in the treatment phase, but not in the trial follow-up phase. Individuals with a comorbid anxiety disorder had significantly higher treatment dropout during both treatments., Limitations: Not all therapists and participants were blind to the assessment of comorbid anxiety disorders and the assessments were performed by one rater., Conclusions: A preference for CT over IPT for MDD is justifiable when comorbid anxiety is present, although long-term differences are not established and replication of this finding is needed. Clinicians should be aware of the risk of dropout for depressed individuals with an anxiety disorder., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: We investigated if the degree of treatment resistance of depression, as measured by the Maudsley Staging Method (MSM), is predictive of a worse depression outcome by using a large naturalistic cohort of depressed patients., Methods: 643 subjects from the general population, primary care, and secondary care who suffered from current depressive disorder were included from the Netherlands Study of Depression and Anxiety baseline assessment. The diagnostic criterion was major depressive disorder (MDD) in the last month, based on the Composite Interview Diagnostic Instrument (CIDI), or a CIDI diagnosis of MDD in the past 6 months with an Inventory of Depressive Symptomatology Self-Report score > 24 at baseline. In these subjects, composite scores of the MSM, based on duration, severity, and treatment history of current episode, were determined retrospectively. We then determined if the MSM score prospectively predicted the 2-year course of depression after baseline. The primary outcomes were percentage of follow-up time spent in a depressive episode and being "mostly depressed" (≥ 50% of the follow-up) between baseline and 2-year follow-up., Results: The MSM predicted "percentage of follow-up time with depression" (P < .001) and was associated with being "mostly depressed" (OR = 1.40; 95% CI, 1.23-1.60; P < .001). These effects were not modified by having received treatment., Conclusions: The current study shows that the MSM is a promising tool to predict worse depression outcomes in depressed patients. In this study that adds to previous work, we show the applicability of MSM in a wider range of primary and secondary care patients with depression., (© Copyright 2018 Physicians Postgraduate Press, Inc.)

Background: Despite extensive research, there is no consensus how Personality Disorders (PD) and PD features affect outcome for Major Depressive Disorder (MDD). The present study evaluated the effects of PD (features) on treatment continuation and effectiveness in Cognitive Therapy (CT) and Interpersonal Psychotherapy (IPT) for MDD., Methods: Depressed outpatients were randomized to CT (n=72) and IPT (n=74). Primary outcome was depression severity measured repeatedly with the Beck Depression Inventory-II (BDI-II) at baseline, three months, at the start of each therapy session, at post-treatment and monthly during five months follow-up., Results: Comorbid PD and PD features did not affect dropout. Multilevel and Cox regression models indicated no negative effect of PD on BDI-II change and remission rates during treatment and follow-up, irrespective of the treatment received. For both therapies, higher dependent PD features predicted overall lower BDI-II scores during treatment, however this effect did not sustain through follow-up. Cluster A PD features moderated treatment outcome during treatment and follow-up: individuals with high cluster A PD features had greater BDI-II reductions over time in CT as compared to IPT., Limitations: Not all therapists and participants were blind to the assessment of PD (features), and assessments were performed by one rater. Further research must investigate the state and trait dependent changes of PD and MDD over time., Conclusions: We found no negative impact of PD on the effectiveness and treatment retention of CT and IPT for MDD during treatment and follow-up. If replicated, cluster A PD features can be used to optimize treatment selection., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: The aim of this study was to investigate the effects of sad mood on default mode network (DMN) resting-state connectivity in persons with chronic major depressive disorder (cMDD)., Methods: Participants with a diagnosis of cMDD (n=18) and age, gender and education level matched participants without a diagnosis of depression (n=18) underwent a resting-state fMRI scan, before and after a sad mood induction. The posterior cingulate cortex (PCC) was used as a seed for DMN functional connectivity across the two resting-state measurements., Results: Mood ratings decreased in both groups following the sad mood induction procedure. PCC connectivity with the parahippocampal gyrus, the superior temporal gyrus and the anterior inferior temporal cortex increased in cMDD patients following the sad mood induction, whereas it decreased in non-patient controls. PCC connectivity with the anterior prefrontal cortex and the precuneus decreased in cMDD patients following the sad mood induction, whereas it increased in non-patient controls., Limitations: Limitations of this study include the relatively small sample size and lack of a clinical control group., Conclusions: These findings are in line with neurobiological models of depression suggesting that the observed changes in DMN connectivity following the sad mood induction might reflect a failure to exert cognitive control over negative memory retrieval in patients with cMDD., (Copyright © 2016 Elsevier B.V. All rights reserved.)