Pharmacological Treatment of Bipolar Depression: Qualitative Systematic Review of Double-Blind Randomized Clinical Trials

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1 Psychiatr Q (2012) 83: DOI /s ORIGINAL PAPER Pharmacological Treatment of Bipolar Depression: Qualitative Systematic Review of Double-Blind Randomized Clinical Trials Lucas Spanemberg Raffael Massuda Lucas Lovato Leonardo Paim Edgar Arrua Vares Neusa Sica da Rocha Keila Maria Mendes Ceresér Published online: 17 September 2011 Ó Springer Science+Business Media, LLC 2011 Abstract Randomized clinical trial (RCT) is the best study design for treatment-related issues, yet these studies may present a number of biases and limitations. The objective of this study is to carry out a qualitative analysis of RCT methodology in the treatment of bipolar depression (BD). A systematic review covering the last 20 years was performed on PubMed selecting double-blind RCTs for BD. The identification items of the articles, their design, methodology, outcome and grant-related issues were all analyzed. Thirty articles were included, all of which had been published in journals with an impact factor[3. While almost half studies (46.7%) used less than 50 patients as a sample, 70% did not describe or did not perform sample size calculation. The Last Observation Carried Forward (LOCF) method was used in 2/3 of the articles and 53.4% of the studies had high sample losses ([20%). Almost half the items were sponsored by the pharmaceutical industry and 33.3% were sponsored by institutions or research foundations. Articles on the pharmacological L. Spanemberg R. Massuda L. Lovato L. Paim E. A. Vares N. Sica da Rocha K. M. M. Ceresér Post-Graduation Program in Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil rmassuda@gmail.com L. Lovato medicolucaslovato@gmail.com L. Paim leonardopaim.com@gmail.com E. A. Vares edgarvares@ig.com.br N. Sica da Rocha neusa-rocha@via-rs.com.br K. M. M. Ceresér keila.cereser@uol.com.br L. Spanemberg (&) Department of Psychiatry, Hospital São Lucas Pontifícia Universidade Católica do Rio Grande do Sul (HSL/PUCRS), 6 andar Sul Internação Psiquiátrica Av. Ipiranga, 6690, Porto Alegre, RS CEP , Brazil lspanemberg@yahoo.com.br

2 162 Psychiatr Q (2012) 83: treatment of BD have several limitations which hinder the extrapolation of the data to clinical practice. Methodological errors and biases are common and statistical simplifications compromise the consistency of the findings. Keywords Systematic review Bipolar depression Clinical trials Pharmacotherapy Introduction Bipolar Disorder (BD) is a severe, chronic, and dysfunctional psychiatric disorder which affects 1 to 3% of the world population [1]. Although manic symptoms are the most evident sign of BD, major depressive episodes and residual depressive symptoms are probably more conspicuous and harmful to the patients along their lives [2, 3]. Current data demonstrate that patients with a diagnosis of BD can spend threefold more time depressed than in a manic phase [4]. Hence, an adequate treatment of the depressive phase of BD has become fundamental, aiming at the remission of symptoms rather than at simply obtaining a response to treatment [5]. Seeking an improved functional state for the patient also targets a reduction in the rates of suicide attempts, suicide completions and further depressive episodes [6, 7]. Specific guidelines for the treatment of bipolar depression have become necessary, given that there is no evidence to suggest that the course of action that suits unipolar depression is equally adequate for bipolar patients. In some cases, such actions may even be harmful, by, for instance, triggering a manic switch. [8] However, the existing literature on bipolar depression is relatively smaller in comparison with that found on unipolar depression. Besides, Randomized Clinical Trials (RCT), which are better designed to provide answers concerning treatments, are subject to a series of biases and limitations which are not always clarified in the studies published [9]. Systematic reviews have demonstrated that RCT for bipolar depression may present significant limitations [10]. Over the past years, several initiatives have been proposed and implemented so as to improve the quality of RCTs. One such example is the Consolidated Standards of Reporting Trials (CONSORT) [11, 12], which has been published in several major journals and is recognized internationally. However, it is not yet clear whether the improvements made to the description of RCTs also reflect methodological improvements and a decrease in bias [9]. In this present study, a qualitative analysis of RCT methodology was made regarding treatment for depression in BD I and II patients. Methods A systematic review was carried out on PubMed, using the Mesh function, and Bipolar Disorder as the descriptor, followed by drug effects OR drug therapy, limited to Randomized Controlled Trials, [18 years and excluding the term mania. The search was limited to articles written in English and published over the last 20 years (from 1990 to June, 2010). 294 abstracts were found. For the selection of the articles, 2 researchers read each abstract independently using the following inclusion criteria:

3 Psychiatr Q (2012) 83: Randomized Clinical Trials; 2. Pharmacological interventions; 3. Articles in English. Every abstract was also assessed by two researchers using the following exclusion criteria: 1. The improvement of depression outcome was not assessed; 2. Study randomized non-bipolar patients, bipolar patients who were not in a depressive episode or patients from special populations (e.g.: having substance use/abuse-related disorders as an inclusion criterion); 3. Articles using the same sample as another citation (e.g.: analysis of outcomes secondary to a main study using the same sample); 4. Interventions with non-standardized drugs (e.g.: herbal extracts, intravenous hormones, etc.). Once all the abstracts had been analyzed, the reports for each abstract were compared: the analyses were deemed reliable when both reports of a given abstract were in agreement regarding inclusion and exclusion criteria. When there was disagreement between the reports (report by rater 1 = report by rater 2), the abstract was read and assessed by the entire group of authors. Figure 1 summarizes the article selection process. Fig. 1 Article selection for qualitative analysis

4 164 Psychiatr Q (2012) 83: As shown in Fig. 1, out of the 294 abstracts found in the initial selection in phase 1, 194 were excluded. Out of the remaining 100 abstracts, 55 were selected to be read jointly by the team of authors. In addition to those, another 45 abstracts were given similar reports by both assessors and were therefore selected to be read in full. In the end, 57 articles were selected to be read in full. Twenty-seven articles were excluded after having been read thoroughly. This phase also aimed at excluding articles which were doubtful or whose abstracts lacked data. The same inclusion and exclusion criteria were used, which led to a final analysis to be carried out on 30 articles. The variables analyzed were: 1. identification items of the articles (publishing year, journal, impact factor of the journal, drugs used); 2. Methodology and design items (follow-up time, exclusion criteria, instruments utilized, placebo use, origin of the patients, diagnostic assessment, washout period, number of patients, sample size calculation, statistical analyses, etc.); 3. Outcome items (advantage of a given intervention towards the improvement of depression outcome, remission, manic switch, losses, etc.); 4. Type of grant. The variables were analyzed in terms of frequency percentage. Microsoft Excel was used to table the data and the Statistical Package for the Social Sciences (SPSS) 18 was used for the frequency reports. Results Table 1 shows the list of 30 articles included in the final analysis [8, 13 41]. All the articles were published in journals with a high impact factor (IF [ 3), where most, i.e. 19 (or 63.3%) were published in journals with IF [ 5. Sixteen articles (or 53.3%) were published within the last 6 years and only 5 (16.66%) articles were published prior to Table 2 shows items related to the methodology and design of the studies. Most of the articles (66%) used structured instruments to establish the bipolar disorder diagnosis, mainly assessing out-patients (63.3%) and patients with concomitant type I and II BD while defining entry criteria according to a cutoff point on a scale of severity of depression (90%). Most did not include a washout period (60%), 2/3 used group placebo and almost half of all studies (46.7%) used a small final sample (\ 50 patients). Some (40%) described the sample size calculation and 2/3 only used the intention-to-treat statistical analysis using Last Observation Carried Forward (LOCF). Only 2 articles (6.7%) reported also only having used in the final analysis those patients who completed the study, besides the LOCF. Table 3 shows some outcome items of the studies. Almost half the studies (46.7%) failed to find advantages regarding a given intervention in the improvement of depression outcome, whereas another 40% found that an active drug had an advantage over placebo. In only 4 studies (25%) was an active intervention found to be superior to another. Most studies (56.7%) did not assess remission in the improvement of depression outcome and 53.3% found dropout rate above 20% at the end of follow-up. 80% of the studies did not report any differences in the manic switch outcome and the other 20% either failed to report it or did not assess it. Table 4 presents results regarding study grants. Approximately half the studies (46.7%) were sponsored by the pharmaceutical industry, 33.3% were sponsored by public

5 Psychiatr Q (2012) 83: Table 1 Articles included in the analysis Title Authors Year Interventions Journal Impact factor 1. A double-blind, placebo-controlled study of quetiapine and lithium monotherapy in adults in the acute phase of bipolar depression. (EMBOLDEN I) [13] 2. A double-blind, placebo-controlled study of quetiapine and paroxetine as monotherapy in adults with bipolar depression. (EMBOLDEN II) [14] 3. Effectiveness of the extended release formulation of quetiapine as monotherapy for the treatment of acute bipolar depression. [15] 4. Efficacy and safety of lamotrigine as add-on treatment to lithium in bipolar depression: a multicenter, doubleblind, placebocontrolled trial. [16] 5. Decreased glutamate/ glutamine levels may mediate cytidine s efficacy in treating bipolar depression: a longitudinal proton magnetic resonance spectroscopy study. [17] 6. A placebo-controlled evaluation of adjunctive modafinil in the treatment of bipolar depression. [18] 7. Effectiveness of adjunctive antidepressant treatment for bipolar depression. [8] 8. Efficacy of quetiapine monotherapy in bipolar I and II depression: a double-blind, placebocontrolled study (The BOLDER II Study). [19] Young 2010 Quetiapine vs. Lithium vs. McElroy 2010 Quetiapine vs. Paroxetine vs. Suppes 2010 Quetiapine vs. van der Loss 2009 Lamotrigine/ Lithium vs. Yoon 2009 Cytidine vs. Frye 2007 Modafinil vs. Sachs 2007 Paroxetine/EH vs. Bupropion/EH vs. /EH Thase 2006 Quetiapine vs. J Clin Psychiatry 5.21 J Clin Psychiatry 5.21 J Affect Disord 3.27 J Clin Psychiatry 5.21 Neuropsychopharmacol 6.83 Am J Psychiatry NEJM J Clin Psychopharmacol 4.37

6 166 Psychiatr Q (2012) 83: Table 1 continued Title Authors Year Interventions Journal Impact factor 9. A 7-week, randomized, double-blind trial of olanzapine/fluoxetine combination versus lamotrigine in the treatment of bipolar I depression. [20] 10. Mood switch in bipolar depression: comparison of adjunctive venlafaxine, bupropion and sertraline. [21] 11. Randomized, doubleblind pilot trial comparing lamotrigine versus citalopram for the treatment of bipolar depression. [22] 12. Inositol augmentation of lithium or valproate for bipolar depression. [23] 13. Efficacy of ethyleicosapentaenoic acid in bipolar depression: randomised doubleblind placebocontrolled study. [24] 14. A randomized, double-blind, placebocontrolled trial of quetiapine in the treatment of bipolar I or II depression. [25] 15. Comparison of fluoxetine, olanzapine, and combined fluoxetine plus olanzapine initial therapy of bipolar type I and type II major depression lack of maniac induction. [26] 16. Divalproex in the treatment of bipolar depression: a placebocontrolled study. [27] 17. Risperidone and paroxetine given singly and in combination for bipolar depression. [28] Brown 2006 Olanzapine/ fluoxetine vs. Lamotrigine Post 2006 Bupropion/EH vs. Sertraline/EH vs. Venlafaxine/EH Schaffer 2006 Lamotrigine/EH vs. Citalopram/ EH Eden Evins 2006 Inositol/EH vs. /EH J Clin Psychiatry 5.21 Br J Psychiatry 5.07 J Affect Disorders 3.27 Bipol Disorders 3.95 Frangou 2006 EPA vs. Br J Psychiatry 5.07 Calabrese Amsterdam and Shultz 2005 Quetiapine vs. placebo 2005 Fluoxetine/ Olanzapine vs. Fluoxetine vs. Olanzapine vs. Davis 2005 Divalproex vs. Shelton and Stahl 2004 Risperidone vs. Paroxetine vs. Risperidone/ Paroxetine Am J Psychiatry J Affect Disorders 3.27 J Affect Disorders 3.27 J Clin Psychiatry 5.21

7 Psychiatr Q (2012) 83: Table 1 continued Title Authors Year Interventions Journal Impact factor 18. Pramipexole for Bipolar II depression: a placebo controlled proof of concept study. [29] 19. Preliminary randomized, doubleblind, placebocontrolled trial of Pramipexole added to mood stabilizers for treatment-resistant bipolar depression. [30] 20. Efficacy of olanzapine and olanzapinefluoxetine combination in the treatment of bipolar I depression. [31] 21. Moclobemide vs. Imipramine in bipolar depression: a multicentre double blind clinical trial. [32] 22. Double blind placebocontrolled comparison of imipramine and paroxetine in the treatment of bipolar depression. [33] 23. Inositol as an add-on treatment for bipolar depression. [34] 24. Double-blind comparison of addition of a second mood stabilizer versus an antidepressant to an initial mood stabilizer for treatment of patients with bipolar depression. [35] 25. A double-blind study comparing idazoxan and bupropion in bipolar depressed patients. [36] 26. A double blind placebo-controlled study of lamotrigine monotheraphy in outpatients with bipolar I depression. [37] Zarate 2004 Pramipexole/EH vs. /EH Goldberg 2004 Pramipexole/EH vs. /EH Tohen 2003 Olanzapine vs. Olanzapine/ Fluoxetine vs. Silverston T Moclobemide vs. Imipramine Nemeroff Chengappa 2001 Imipramine/EH vs. Paroxetine/ EH vs / EH 2000 Inositol/EH vs /EH Young 2000 Paroxetine/EH vs. EH/EH Grossman Calabrese 1999 Idaxozan vs. Bupropiona 1999 Lamotrigine vs. Biol Psychiatry 8.67 Am J Psychiatry Arch Gen Psychiatry Acta Psychiatr Scand 3.52 Am J Psychiatry Bipol Disord 3.95 Am J Psychiatry J Affect Disord 3.27 J Clin Psychiatry 5.21

8 168 Psychiatr Q (2012) 83: Table 1 continued Title Authors Year Interventions Journal Impact factor 27. Initial lithium augmentation improves the antidepressant effects of standard TCA treatment in nonresistant depressed patients. [38] 28. A double blind trial of bupropion versus desipramine for bipolar depression. [39] 29. A double-blind study of L-sulpiride versus amitriptiline in lithium maintained bipolar depressives. [40] 30. Tranylcypromine versus imipramine in anergic bipolar depression. [41] Ebert 1995 Lithium vs. Sachs 1994 Bupropion/EH vs. Desipramine/ EH Bocchetta Himmelhoch 1993 L-sulpiride/ Lithium vs. Amitriptiline/ Lithium 1991 Tranylcypromine vs. Imipramine Psychopharmacol 3.67 J Clin Psychiatry 5.21 Acta Psychiatr Scand 3.52 Am J Psychiatry Table 2 Methodological and design items Follow-up time Up to 6 weeks 9 (30%) [6 weeks to 8 weeks 13 (43.3%) [8 weeks 8 (26.7%) use Yes 20 (66.7%) No 10 (33.3%) Origin of the patients Out-patients 19 (63.3%) Out-patients? in-patients 3 (10%) Unclear 8 (26.7%) Diagnostic assessment Structured diagnosis (SCID/MINI) 20 (66.6%) Semi-structured diagnosis 1 (3.3%) Clinical diagnosis only 9 (30%) Washout period Yes 11 (36.7%) No 18 (60%) Not described 1 (3.3%) Inclusion criteria Cutoff score is defined in scales (HAM, MADRS, etc.) 27 (90%) Cutoff score is not defined 3 (10%)

9 Psychiatr Q (2012) 83: Table 2 continued Number of patients (Total) Up to (46.7%) [50 to (16.7%) [100 to (10%) [200 to (10%) [500 5 (16.7%) Sample size calculation Described 12 (40%) Not described or not performed 18 (60%) BD Subtypes BD Type I 6 (20%) BD Type II 1 (3.3%) Both 18 (60%) Unclear 5 (16.7%) Type of statistical analysis Only LOCF (last observation carried forward) 20 (66.7%) LOCF? OC (observed cases) 2 (6.7%) Other or unclear 8 (26.7%) Table 3 Outcome items a Only 16 studies compared different active interventions Improvement of depression outcome No difference among interventions 14 (46.7%) Medication better than placebo 12 (40%) Medication (or combination) better than other 4 (25%) a medication Assessed remission Yes 13 (43.3%) No 17 (56.7%) Manic switch No difference 24 (80%) Differences found between interventions 3 (10%) Not assessed or not described 3 (10%) Dropouts (follow-up) Up to 20% 13 (43.3%) [20% and under 50% 14 (46.7%) [50% 2 (6.7%) Unclear 1 (3.3%) Table 4 Grants Type of sponsorship for the study Declared sponsorship from the industry 14 (46.7%) Sponsored by institutions/foundations/government 10 (33.3%) Not declared/unclear/unsponsored 6 (20%)

10 170 Psychiatr Q (2012) 83: Fig. 2 Comparison between articles with and without grants from the pharmaceutical industry institutions, foundations and research institutions (e.g.: the Stanley Foundation, NIMH, etc.) and 20% declared not having been granted funding or this information was unclear. Studies funded by the pharmaceutical industry, when placed in comparison with articles without such a grant, had numerically larger sample sizes, greater dropout rate, were more likely to perform sample size calculation and to use LOCF as the only analysis strategy, and tended to have more positive outcomes (e.g.: intervention A better than intervention B). Figure 2 shows some sponsorship-related differences among studies. Discussion Our results have disclosed a series of methodological limitations regarding randomized clinical trials for the treatment of bipolar disorder. Even though 30 RCTs were included in this review, they all had significant limitations. All trials had been published in journals with an impact factor greater than three and 19 of them (63.3%) were published in journals whose impact factor was over 5, yet the impact factor itself was not an inclusion criterion. The trials were published in renowned traditional scientific journals which had large circulation in this field and high impact factors. Even so, most of them (46.7%) were conducted with small sample sizes (under 50 patients), number considered clinically and mathematically insufficient for same authors [42]. Ghaemi, citing the central limit theorem, argues that small samples (\ 50) in RCTs are not sufficient to control confounding

11 Psychiatr Q (2012) 83: factors and can not be adequately assessed through some statistical analysis, such as regression models, to reduce confounding bias. He suggests that small sample size RCTs (\ 50) ought to be considered observational studies [42] due to their low inference power. Although statistically significant data can be extracted from small samples, we agree with the viewpoint of Ghaemi. Almost 2/3 of the studies (60%) also failed to perform or describe sample size calculation. Failure to perform this calculation hinders the study in that it cannot determine beta type errors, that is, the probability of not detecting a difference when it actually exists (false-negative) [42]. In our analysis, 53.6% of the articles demonstrated superiority of a pharmacological intervention over another or over placebo. Yet when this analysis is reduced to include only those articles with losses below 20%, this number drops to 16.66%. Only 4 articles (13.3%) demonstrated superiority of a medication or combination in relation to another drug, and only one of them had losses below 20%. This data reveals the paucity of evidence regarding the superiority of active interventions for bipolar depression in higherquality RCTs. Most articles (67.6%) used structured interviews for diagnosis. However, a significant proportion of RCTs (30%) used only a non-instrumental clinical diagnosis, which in turn reduces reliability [43]. Sixty percent of the trials included both bipolar I and II patients. It is important to highlight that there is evidence pointing to the diverse behaviors of these two subgroups as to the treatment of depression. [21] Bipolar II patients have a lower risk of manic episodes [44], and significant implications for treatment. Similarly, some experts recommend different approaches for the treatment of bipolar depression in patients with type I and type II bipolarity, even though they recognize that well-conducted trials in bipolar type II are scarce [3] (in our review, only one RCT involved only bipolar II patients). Nine out of 10 articles defined a cutoff point in scales of depressive symptoms as an inclusion criterion for depressed patients, yet in their results they did not split their samples for the analysis of response according to severity of disease. Although a different response to treatment for different levels of severity in bipolar depression has not been established, it is known that the response to treatment for unipolar depression depends on the initial severity of depressive symptoms [45 47]. Thus, more precise definitions of severity as inclusion criteria and analyses made by level of severity may become necessary. Over 50% of the studies did not assess remission of depression as an outcome, being limited to a response assessment (50% reduction in depressive symptoms). Studies indicate that remission, which is a major deficiency in the existing literature, is the most important clinical outcome to be sought in bipolar depression [48]. Moreover, there are authors who argue that response and remission outcomes are inadequate for sound assessment of RCT results [49]. The units proposed as being the most consistent for the description of results are the number needed to treat (NNT) and the number needed to harm (NNH), which better reflect the effects on treatment for the clinician. In this case, very few studies using these outcome measures for bipolar depression were found. Most studies only used the intention-to-treat (LOCF) analysis as the single statistical strategy for analysis of primary outcome. The LOCF is a statistical strategy to estimate missing values and is deemed simplistic and inadequate by many authors [50, 51]. In LOCF, when a patient leaves the study, the last measured value of the variable studied (e.g. Hamilton scale score) is repeated until the end of the study. This generates conservative data, since it assumes that the patient who left the study showed no improvement after the last evaluation. Therefore, if an intervention has many sample losses, this technique will underestimate the potential for improvement in the group with early dropouts, forging a

12 172 Psychiatr Q (2012) 83: difference that may not exist. This becomes more severe the higher the attrition rate regarding sample loss. Given that most studies had excessive losses, the LOCF may have distorted results. As an alternative to LOCF, some authors suggest probabilistic methods of result estimation, such as multiple imputation or hierarchical linear modeling [50]. Of the 30 trials selected, nearly half had losses over 20% and 6.7% had dropouts above 50%. These losses, when different among groups, may introduce bias, lower the level of RCT evidence [52], while also compromising confidence in the validity of the data [42]. Dropouts greater than 20% also imply even greater problems in the use the LOCF. Fourteen (46.7%) studies were sponsored by the pharmaceutical industry and 33.3% were sponsored by non-pharmaceutical-related institutions or foundations. Those studies which received grants from the industry tended to be larger (all samples found to have over 500 patients were sponsored by the industry), had richer descriptions, but not fewer limitations (70% had dropouts greater than 20% and 93% used LOCF as the main analysis strategy). The industry studies also tended to provide positive outcomes for the sponsored intervention (10/14 studies, or 71.4%), against only 37% (6/16) of non-industry-sponsored studies presenting differences between interventions, despite the similar number of studies with at least two different active interventions (57,1% vs. 50%). This difference in positive outcomes regarding drug-sponsored studies is a well-known phenomenon [53] which could lead to the assumption that some of the limitations of RCTs might intentionally not be minimized so as to reach positive results. This paper has a number of limitations. First of all, as it is a systematic review with many exclusion criteria, not everything in the literature on the treatment of bipolar depression was studied. However, by selecting only double-blind randomized studies we aimed at investigating those articles with a greater scientific soundness. Second, we only assessed studies indexed in PubMed, not extending the search to other sources such as EMBASE and PsychInfo. Third, the assessment of full articles was performed by a single researcher, unlike the initial evaluation of the abstracts. This may have reduced reliability when compared to the first phase of the study. Nevertheless, as they were easy to assess, we believe that this bias was slight. Fourth, we did not use widely used instruments to evaluate the quality of RCT as the items were proposed by the researchers themselves. Many of the items evaluated are similar to those found in CONSORT and some of them (such as the specific assessment of the use of LOCF) were not present in the questionnaires available. Even with methodologies such as CONSORT [11] and GRADE [54], which provide for the use of criteria for the description and evaluation of RCTs, articles concerning the pharmacological treatment of bipolar depression have several limitations that preclude the extrapolation of data to clinical practice, by lacking evidence for treatment. Clinical trials with a more solid design for bipolar depression are necessary to limit the possible existing biases. References 1. Belmaker RH: Bipolar disorder. New England Journal of Medicine 351(5): , Judd LL, : The long-term natural history of the weekly symptomatic status of bipolar I disorder. Archives of General Psychiatry 59(6): , Goodwin FK, Jamison KR, Ghaemi SN: Manic-Depressive Illness: Bipolar Disorders and Recurrent Depression, 2nd edn, New York, NY, Oxford University Press, Kupka RW, : Three times more days depressed than manic or hypomanic in both bipolar I and bipolar II disorder. Bipolar Disorders 9(5): , 2007

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15 Psychiatr Q (2012) 83: Universidade Católica do Rio Grande do Sul (HSL/PUCRS 2007) and currently is Ph.D. student at the Universidade Federal do Rio Grande do Sul (UFRGS). Currently, he is an board-certified psychiatrist at HSL/PUCRS, where he works in the psychiatric unit, supervising residents in psychiatry. Dr. Spanemberg has a private psychiatry practice in Porto Alegre, where works also as a psychotherapist. He is researcher at the Mood Disorder Program of Hospital de Clínicas at the UFRGS. Raffael Maasuda, MD, received his medical degree from Universidade Federal do Paraná (UFPR 2007), did his residency in psychiatry at the Universidade Federal do Rio Grande do Sul (UFRGS 2010) and currently is Ph.D. student at the UFRGS. Currently, he has a private psychiatry practice in Porto Alegre. Lucas Lovato, MD, received his medical degree from Universidade Federal do Rio Grande do Sul (UFRGS 2002), did his residency in psychiatry at UFRGS (2007) and his masters in psychiatry at the UFRGS (2011). Currently, he has a private psychiatry practice in Porto Alegre. Leonardo Paim, MD, received his medical degree from Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS 2003), did his residency in psychiatry at the Universidade Federal do Rio Grande do Sul (UFRGS 2006) and currently is student of masters in psychiatry at the UFRGS. Currently, he has a private psychiatry practice in Porto Alegre. Edgar Arrua Vares, MD, received his medical degree from Universidade Federal do Rio Grande do Sul (UFRGS 2004), did his residency in psychiatry at UFRGS (2009) currently is PhD. student at the UFRGS. Currently, he has a private psychiatry practice in Porto Alegre and works at the Instituto Geral de Perícias do Rio Grande do Sul (IGP-RS). Neusa Sica da Rocha, PhD, received her medical degree from Universidade Federal do Rio Grande do Sul (UFRGS 1996), did her residency in psychiatry at UFRGS (1999), master s degree in psychiatry at the UFRGS (2002) and doctorate in psychiatry at UFRGS and University of Edinburg (2008). Currently she is doing her post-doctorate in psychiatry at the UFRGS and works as a collaborator Professor at Post-graduate Program at the UFRGS. Currently, she has a private psychiatry practice in Porto Alegre. Keila Maria Mendes Ceréser, PhD, received her pharmaceutical degree from Universidade Federal do Rio Grande do Sul (UFRGS 1989), did her master s degree in pharmacy at UFRGS (1993), and doctorate in medical sciences at UFRGS (2005). Currently she is doing her post-doctorate in psychiatry at the UFRGS, works as a researcher at Laboratory of Molecular Psychiatry at Hospital de Clínicas de Porto Alegre (HCPA) and collaborator Professor at Post-graduate Program at the UFRGS.