K.M.L. Huijbregts

A target-driven collaborative care model for Major Depressive Disorder is effective in primary care in the Netherlands. A randomized clinical trial from the depression initiative

BACKGROUNDnPractice variation in the primary care treatment of depression may be considerable in the Netherlands, due to relatively small and unregulated practices. We adapted the collaborative care model for the treatment of Major Depressive Disorder (MDD) to accommodate existing practice variation and tested whether this had added value over Care as Usual (CAU).nnnMETHODSnA cluster randomized controlled trial was conducted to compare an adapted target driven collaborative care model with Care as Usual (CAU). Randomization was at the level of 18 (sub)urban primary care centers. The care manager and GP were supported by a web-based tracking and decision aid system that advised targeted treatment actions to achieve rapid response and if possible remission, and that warned the consultant psychiatrist if such treatment advice was not followed up. Eligible patients had a score of 10 or higher on the PHQ9, and met diagnostic criteria for major depression at the subsequent MINI Neuropsychiatric interview. A total of 93 patients were identified by screening. They received either collaborative care (CC) or CAU. Another 56 patients received collaborative care after identification by the GP. The outcome measures were response to treatment (50% or greater reduction of the PHQ9-total score from baseline) at three, six, nine and twelve months, and remission (a score of 0-4 on the PHQ9 at follow-up).nnnRESULTSnTreatment response and remission in CAU were low. Collaborative care was more effective on achieving treatment response than CAU at three months for the total group of patients who received collaborative care [OR 5.2 ((1.41-16.09), NNT 2] and at nine months [OR 5.6 ((1.40-22.58)), NNT 3]. The effect was not statistically significant at 6 and 12 months.nnnLIMITATIONSnA relatively high percentage of patients (36.5%) did not return one or more follow-up questionnaires. There was no evidence for selective non response.nnnCONCLUSIONSnOur adapted target driven CC was considerably more effective than CAU for MDD in primary care in the Netherlands. The Numbers Needed To Treat (NNT) to achieve response in one additional patient were low (2-3), which suggest that introducing CC at a larger scale may be beneficial. The relatively large effects may be due to our focus on reducing practice variation through the introduction of easy to use web based tracking and decision aids. The findings are highly relevant for the application of the model in areas where practices tend to be small and for mixed healthcare systems such as in many countries in Europe.nnnTRIAL REGISTRATIONnDutch trial register ISRCTN15266438 (http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=820).

Cost-effectiveness of collaborative care including PST and an antidepressant treatment algorithm for the treatment of major depressive disorder in primary care; a randomised clinical trial

BackgroundDepressive disorder is currently one of the most burdensome disorders worldwide. Evidence-based treatments for depressive disorder are already available, but these are used insufficiently, and with less positive results than possible. Earlier research in the USA has shown good results in the treatment of depressive disorder based on a collaborative care approach with Problem Solving Treatment and an antidepressant treatment algorithm, and research in the UK has also shown good results with Problem Solving Treatment. These treatment strategies may also work very well in the Netherlands too, even though health care systems differ between countries.Methods/designThis study is a two-armed randomised clinical trial, with randomization on patient-level. The aim of the trial is to evaluate the treatment of depressive disorder in primary care in the Netherlands by means of an adapted collaborative care framework, including contracting and adherence-improving strategies, combined with Problem Solving Treatment and antidepressant medication according to a treatment algorithm. Forty general practices will be randomised to either the intervention group or the control group. Included will be patients who are diagnosed with moderate to severe depression, based on DSM-IV criteria, and stratified according to comorbid chronic physical illness. Patients in the intervention group will receive treatment based on the collaborative care approach, and patients in the control group will receive care as usual. Baseline measurements and follow up measures (3, 6, 9 and 12 months) are assessed using questionnaires and an interview. The primary outcome measure is severity of depressive symptoms, according to the PHQ9. Secondary outcome measures are remission as measured with the PHQ9 and the IDS-SR, and cost-effectiveness measured with the TiC-P, the EQ-5D and the SF-36.DiscussionIn this study, an American model to enhance care for patients with a depressive disorder, the collaborative care model, will be evaluated for effectiveness in the primary care setting. If effective across the Atlantic and across different health care systems, it is also likely to be an effective strategy to implement in the treatment of major depressive disorder in the Netherlands.

Negative association of concomitant physical symptoms with the course of major depressive disorder: A systematic review

OBJECTIVEnThe prognosis of depression greatly varies among patients, and the physical symptoms that often accompany depression may predict treatment resistance and a worse outcome. If so, this may have important clinical implications. The aim of this systematic review was to explore the association of concomitant physical symptoms with the outcome of major depressive disorder (MDD).nnnMETHODSnSystematic review: Medline, Psychinfo, and the Cochrane Library were searched for prospective, cross-sectional, and retrospective studies, and also for open-label trials and randomized controlled trials. The risk of bias assessment and data extraction were performed in duplicate. A qualitative best-evidence synthesis was performed, based on the number of studies reporting on the association between physical symptoms and the course of MDD, the consistency of the results, and the methodological quality. The findings were reported according to the PRISMA guidelines.nnnRESULTSnNine studies met the inclusion criteria. Although the design, outcome measures, and data presentation varied too much to make statistical pooling possible, the best evidence synthesis resulted in strong, consistent evidence for a negative association between physical symptoms and the course of MDD.nnnCONCLUSIONnThis systematic review shows a negative association of concomitant physical symptoms with the course of MDD. The effect might be considerable, but the number of studies addressing this topic is small and there was a wide variation in the study designs and outcome measures. More research is needed.

Adverse effects of multiple physical symptoms on the course of depressive and anxiety symptoms in primary care

389 Harald Baumeister Engelbergerstrasse 41 DE–79085 Freiburg (Germany) Tel. +49 761 203 3044, Fax +49 761 203 3040 E-Mail baumeister @ psychologie.uni-freiburg.de 3 Parker G: Beyond major depression. Psychol Med 2005; 35: 467–474. 4 Parker G, Roy K, Mitchell P, Wilhelm K, Malhi G, Hadzi-Pavlovic D: Atypical depression: a reappraisal. Am J Psychiatry 2002; 159: 1470– 1479. 5 Leventhal AM, Rehm LP: The empirical status of melancholia: implications for psychology. Clin Psychol Rev 2005; 25: 25–44. 6 Thase ME: Atypical depression: useful concept, but it’s time to revise the DSM-IV criteria. Neuropsychopharmacology 2009; 34: 2633–2641. 7 Lurie SJ, Gawinski B, Pierce D, Rousseau SJ: Seasonal affective disorder. Am Fam Physician 2006; 74: 1521–1524. 8 Baumeister H, Kufner K: It is time to adjust the adjustment disorder category. Curr Opin Psychiatry 2009; 22: 409–412. 9 Sneed JR, Roose SP, Sackeim HA: Vascular depression: a distinct diagnostic subtype? Biol Psychiatry 2006; 60: 1295–1298.

Association Between Chronic Physical Conditions and the Effectiveness of Collaborative Care for Depression: An Individual Participant Data Meta-analysis

IMPORTANCEnCollaborative care is an intensive care model involving several health care professionals working together, typically a physician, a case manager, and a mental health professional. Meta-analyses of aggregate data have shown that collaborative care is particularly effective in people with depression and comorbid chronic physical conditions. However, only participant-level analyses can rigorously test whether the treatment effect is influenced by participant characteristics, such as chronic physical conditions.nnnOBJECTIVEnTo assess whether the effectiveness of collaborative care for depression is moderated by the presence, type, and number of chronic physical conditions.nnnDATA SOURCESnData were obtained from MEDLINE, EMBASE, PubMed, PsycINFO, CINAHL Complete, and Cochrane Central Register of Controlled Trials, and references from relevant systematic reviews. The search and collection of eligible studies was ongoing until May 22, 2015.nnnSTUDY SELECTIONnThis was an update to a previous meta-analysis. Two independent reviewers were involved in the study selection process. Randomized clinical trials that compared the effectiveness of collaborative care with usual care in adults with depression and reported measured changes in depression severity symptoms at 4 to 6 months after randomization were included in the analysis. Key search terms included depression, dysthymia, anxiety, panic, phobia, obsession, compulsion, posttraumatic, care management, case management, collaborative care, enhanced care, and managed care.nnnDATA EXTRACTION AND SYNTHESISnIndividual participant data on baseline demographics and chronic physical conditions as well as baseline and follow-up depression severity symptoms were requested from authors of the eligible studies. One-step meta-analysis of individual participant data using appropriate mixed-effects models was performed.nnnMAIN OUTCOMES AND MEASURESnContinuous outcomes of depression severity symptoms measured using self-reported or observer-rated measures.nnnRESULTSnData sets from 31 randomized clinical trials including 36 independent comparisons (Nu2009=u200910u202f962 participants) were analyzed. Individual participant data analyses found no significant interaction effects, indicating that the presence (interaction coefficient, 0.02 [95% CI, -0.10 to 0.13]), numbers (interaction coefficient, 0.01 [95% CI, -0.01 to 0.02]), and types of chronic physical conditions do not influence the treatment effect.nnnCONCLUSIONS AND RELEVANCEnThere is evidence that collaborative care is effective for people with depression alone and also for people with depression and chronic physical conditions. Existing guidance that recommends limiting collaborative care to people with depression and physical comorbidities is not supported by this individual participant data meta-analysis.

Association Between Chronic Physical Conditions and the Effectiveness of Collaborative Care for Depression

IMPORTANCEnCollaborative care is an intensive care model involving several health care professionals working together, typically a physician, a case manager, and a mental health professional. Meta-analyses of aggregate data have shown that collaborative care is particularly effective in people with depression and comorbid chronic physical conditions. However, only participant-level analyses can rigorously test whether the treatment effect is influenced by participant characteristics, such as chronic physical conditions.nnnOBJECTIVEnTo assess whether the effectiveness of collaborative care for depression is moderated by the presence, type, and number of chronic physical conditions.nnnDATA SOURCESnData were obtained from MEDLINE, EMBASE, PubMed, PsycINFO, CINAHL Complete, and Cochrane Central Register of Controlled Trials, and references from relevant systematic reviews. The search and collection of eligible studies was ongoing until May 22, 2015.nnnSTUDY SELECTIONnThis was an update to a previous meta-analysis. Two independent reviewers were involved in the study selection process. Randomized clinical trials that compared the effectiveness of collaborative care with usual care in adults with depression and reported measured changes in depression severity symptoms at 4 to 6 months after randomization were included in the analysis. Key search terms included depression, dysthymia, anxiety, panic, phobia, obsession, compulsion, posttraumatic, care management, case management, collaborative care, enhanced care, and managed care.nnnDATA EXTRACTION AND SYNTHESISnIndividual participant data on baseline demographics and chronic physical conditions as well as baseline and follow-up depression severity symptoms were requested from authors of the eligible studies. One-step meta-analysis of individual participant data using appropriate mixed-effects models was performed.nnnMAIN OUTCOMES AND MEASURESnContinuous outcomes of depression severity symptoms measured using self-reported or observer-rated measures.nnnRESULTSnData sets from 31 randomized clinical trials including 36 independent comparisons (Nu2009=u200910u202f962 participants) were analyzed. Individual participant data analyses found no significant interaction effects, indicating that the presence (interaction coefficient, 0.02 [95% CI, -0.10 to 0.13]), numbers (interaction coefficient, 0.01 [95% CI, -0.01 to 0.02]), and types of chronic physical conditions do not influence the treatment effect.nnnCONCLUSIONS AND RELEVANCEnThere is evidence that collaborative care is effective for people with depression alone and also for people with depression and chronic physical conditions. Existing guidance that recommends limiting collaborative care to people with depression and physical comorbidities is not supported by this individual participant data meta-analysis.

A high physical symptom count reduces the effectiveness of treatment for depression, independently of chronic medical conditions

AIMnTo assess to what extent a high physical symptom count influences the effect of treatment for major depressive disorder (MDD), and whether or not actual comorbid medical conditions explain this relationship.nnnMETHODnSecondary data-analysis on a cluster-randomized trial in primary care, comparing the effectiveness of collaborative care with care as usual (CAU). MDD was measured using the PHQ-9. The Physical Symptoms Questionnaire (PSQ) was filled out at baseline by 115 patients (77.2% of those who entered the trial). Multilevel logistic regression models were used to test whether a high physical symptom count predicted lack of response to treatment, adding interaction terms to test differential effects on collaborative care versus CAU.nnnRESULTSnA high physical symptom count negatively influenced the effect of both collaborative care and care as usual (no interaction). Specifically, a high physical symptom count predicted lack of response in both conditions at 3 (odds ratio=6.8), 6 (OR=4.1), and 9 months follow-up (OR=6.4). This was not explained by chronic physical illness.nnnCONCLUSIONnIn this RCT, patients with MDD accompanied by a high physical symptom count benefited less from treatment for MDD in primary care, regardless of the type of treatment (either collaborative care or CAU). This was not explained by the presence of comorbid medical conditions. Further research is needed to improve treatment for MDD accompanied by a high physical symptom count, although collaborative care for depression is still more effective than CAU for this group of patients.nnnTRIAL REGISTRATIONnDutch trial register ISRCTN15266438.

Cost-utility of collaborative care for major depressive disorder in primary care in the Netherlands

OBJECTIVEnMajor depression is a great burden on society, as it is associated with high disability/costs. The aim of this study was to evaluate the cost-utility of Collaborative Care (CC) for major depressive disorder compared to Care As Usual (CAU) in a primary health care setting from a societal perspective.nnnMETHODSnA cluster randomized controlled trial was conducted, including 93 patients that were identified by screening (45-CC, 48-CAU). Another 57 patients were identified by the GP (56-CC, 1-CAU). The outcome measures were TiC-P, SF-HQL and EQ-5D, respectively measuring health care utilization, production losses and general health related quality of life at baseline three, six, nine and twelve months. A cost-utility analysis was performed for patients included by screening and a sensitivity analysis was done by also including patients identified by the GP.nnnRESULTSnThe average annual total costs was €1131 (95% C.I., €-3158 to €750) lower for CC compared to CAU. The average quality of life years (QALYs) gained was 0.02 (95% C.I., -0.004 to 0.04) higher for CC, so CC was dominant from a societal perspective. Taking a health care perspective, CC was less cost-effective due to higher costs, €1173 (95% C.I., €-216 to €2726), of CC compared to CAU which led to an ICER of 53,717 Euro/QALY. The sensitivity analysis showed dominance of CC.nnnCONCLUSIONnThe cost-utility analysis from a societal perspective showed that CC was dominant to CAU. CC may be a promising treatment for depression in the primary care setting. Further research should explore the cost-effectiveness of long-term CC.nnnTRIAL REGISTRATIONnNetherlands Trial Register ISRCTN15266438.

Agomelatine as a novel treatment option in panic disorder, results from an 8-week open-label trial.

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Risk of relapse after antidepressant discontinuation in anxiety disorders, obsessive-compulsive disorder, and post-traumatic stress disorder: systematic review and meta-analysis of relapse prevention trials

Objectives To examine the risk of relapse and time to relapse after discontinuation of antidepressants in patients with anxiety disorder who responded to antidepressants, and to explore whether relapse risk is related to type of anxiety disorder, type of antidepressant, mode of discontinuation, duration of treatment and follow-up, comorbidity, and allowance of psychotherapy. Design Systematic review and meta-analyses of relapse prevention trials. Data sources PubMed, Cochrane, Embase, and clinical trial registers (from inception to July 2016). Study selection Eligible studies included patients with anxiety disorder who responded to antidepressants, randomised patients double blind to either continuing antidepressants or switching to placebo, and compared relapse rates or time to relapse. Data extraction Two independent raters selected studies and extracted data. Random effect models were used to estimate odds ratios for relapse, hazard ratios for time to relapse, and relapse prevalence per group. The effect of various categorical and continuous variables was explored with subgroup analyses and meta-regression analyses respectively. Bias was assessed using the Cochrane tool. Results The meta-analysis included 28 studies (n=5233) examining relapse with a maximum follow-up of one year. Across studies, risk of bias was considered low. Discontinuation increased the odds of relapse compared with continuing antidepressants (summary odds ratio 3.11, 95% confidence interval 2.48 to 3.89). Subgroup analyses and meta-regression analyses showed no statistical significance. Time to relapse (n=3002) was shorter when antidepressants were discontinued (summary hazard ratio 3.63, 2.58 to 5.10; n=11 studies). Summary relapse prevalences were 36.4% (30.8% to 42.1%; n=28 studies) for the placebo group and 16.4% (12.6% to 20.1%; n=28 studies) for the antidepressant group, but prevalence varied considerably across studies, most likely owing to differences in the length of follow-up. Dropout was higher in the placebo group (summary odds ratio 1.31, 1.06 to 1.63; n=27 studies). Conclusions Up to one year of follow-up, discontinuation of antidepressant treatment results in higher relapse rates among responders compared with treatment continuation. The lack of evidence after a one year period should not be interpreted as explicit advice to discontinue antidepressants after one year. Given the chronicity of anxiety disorders, treatment should be directed by long term considerations, including relapse prevalence, side effects, and patients’ preferences.