Acta Psychiatr Scand 2014: 130: 354–363 All rights reserved DOI: 10.1111/acps.12305

© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd ACTA PSYCHIATRICA SCANDINAVICA

Review

Staging systems in bipolar disorder: an International Society for Bipolar Disorders Task Force Report Kapczinski F, Magalh~ aes PVS, Balanz a-Martinez V, Dias VV, Frangou S, Gama CS, Gonzalez-Pinto A, Grande I, Ha K, Kauer-Sant’Anna M, Kunz M, Kupka R, Leboyer M, Lopez-Jaramillo C, Post RM, Rybakowski JK, Scott J, Strejilevitch S, Tohen M, Vazquez G, Yatham L, Vieta E, Berk M. Staging systems in bipolar disorder: an International Society for Bipolar Disorders Task Force Report. Objective: We discuss the rationale behind staging systems described specifically for bipolar disorders. Current applications, future directions and research gaps in clinical staging models for bipolar disorders are outlined. Method: We reviewed the literature pertaining to bipolar disorders, focusing on the first episode onwards. We systematically searched data on staging models for bipolar disorders and allied studies that could inform the concept of staging. Results: We report on several dimensions that are relevant to staging concepts in bipolar disorder. We consider whether staging offers a refinement to current diagnoses by reviewing clinical studies of treatment and functioning and the potential utility of neurocognitive, neuroimaging and peripheral biomarkers. Conclusion: Most studies to date indicate that globally defined latestage patients have a worse overall prognosis and poorer response to standard treatment, consistent with patterns for end-stage medical disorders. We believe it is possible at this juncture to speak broadly of ‘early’- and ‘late’-stage bipolar disorder. Next steps require further collaborative efforts to consider the details of preillness onset and intermediary stages, and how many additional stages are optimal.

354

F. Kapczinski1,

P. V. S. Magalh~aes1, V. Balanza-Martinez2, V. V. Dias3, S. Frangou4, C. S. Gama1, A. Gonzalez-Pinto5, I. Grande6, K. Ha7, M. Kauer-Sant’Anna1, M. Kunz1, R. Kupka8, M. Leboyer9, C. Lopez-Jaramillo10, R. M. Post11, J. K. Rybakowski12, J. Scott13,14, S. Strejilevitch15, M. Tohen16, G. Vazquez17, L. Yatham18, E. Vieta6, M. Berk19,20 1 National Institute for Translational Medicine, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil, 2Section of Psychiatry, Department of Medicine, University of Valencia-CIBERSAM and Hospital Universitari Doctor Peset, Valencia, Spain, 3Bipolar Disorder Research Program, Faculty of Medicine, Hospital Santa Maria, University of Lisbon (FMUL), Lisbon, Portugal, 4Section of Neurobiology of Psychosis, Department of Psychosis Studies, Institute of Psychiatry, King’s College London, London, UK, 5Hospital Universitario de Alava (Santiago), University of the Basque Country, CIBERSAM, Vitoria, 6 Bipolar Disorder Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain, 7Department of Psychiatry, Seoul National University, Seoul, Korea, 8 Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands, 9Department of Psychiatry, Universite Paris-Est, Creteil, France, 10 Department of Psychiatry, Mood Disorders Program, School of Medicine, University of Antioquia, Medellin, Colombia, 11Bipolar Collaborative Network, Bethesda, MD, USA, 12Department of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland, 13 Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, 14Centre for Affective Disorders, Institute of Psychiatry, London, UK, 15Bipolar Disorder Program, Neurosciences Institute, Favaloro University, Buenos Aires, Argentina, 16 Department of Psychiatry, University of New Mexico, Albuquerque, NM, USA, 17Department of Neurosciences, University of Palermo, Buenos Aires, Argentina, 18Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada, 19IMPACT Strategic Research Centre, School of Medicine and Barwon Health, Deakin University, Geelong, Vic., and 20 Department of Psychiatry, Florey Institute of

Staging bipolar disorder Neuroscience and Mental Health and Orygen Youth Health Research Centre, University of Melbourne, Parkville, Vic., Australia Key words: bipolar disorder; clinical aspects; early intervention Flavio Kapczinski, Laboratory of Molecular Psychiatry, Federal University of Rio Grande do Sul – UFRGS, Hospital de Clínicas de Porto Alegre – HCPA, Rua Ramiro Barcelos, 2350 – CPE, Porto Alegre, RS CEP 90035-903, Brasil. E-mail: [email protected]

Accepted for publication May 30, 2014

Summations

• Staging models have the potential of aiding in the selection of stage-specific interventions in bipolar disorder.

• Available data converge to suggest that broadly defining bipolar disorder as early and late stage is heuristically useful.

• The task force suggests specific strategies for advancing the utility of staging, including formal com-

parison between models, employing longitudinal designs and using stage as a stratifications variable in randomized trials.

Considerations

• The preponderance of data is either cross-sectional or secondary in nature. • Studies specifically investigating staging models and their comparative validity are rare. • Collaborative international efforts are needed to validate and confirm the utility of staging for people with bipolar disorder.

Introduction

Prognostic staging has been gaining traction in psychiatry in the past 10 years. This is mainly due to its potential utility, especially in young adults presenting to clinical services for the first time (1). A staging system is a heuristic tool intended to indicate where an individual sits on a succession from ‘at risk’ but asymptomatic to ‘end-stage’ (poor prognosis) illness. In so doing, the clinician is armed with information capable of aiding selection of stage-specific strategies for treatment. Since the original proposals of staging for psychiatric disorders by Fava and Kellner in 1993 (2), McGorry et al. proposed a model for psychosis, with further proposals for models addressing specific disorders – for a recent overview of staging in other disorders such as anxiety, depression, eating disorders and substance use disorders, see Cosci and Fava (3). Within the youth mental health movement, there is also a move toward trans-diagnostic models of staging (4). Proponents of this ‘lumping’ approach argue that the similari-

ties in presentation and lack of specificity of subsyndromal symptoms make a single model of early stages viable (5). However, for the purposes of this manuscript, we wish to review whether there is a place for employing clinical staging in bipolar disorder alongside current diagnostic approaches. There is now consistent evidence that, at least for a significant proportion of people with bipolar disorder, clinical course and outcome are not as benign as initially described (6). The evidence thus far points to relevant differences between early and late stages of bipolar disorders in clinical course of illness, neurobiology, systemic pathology and treatment responsiveness (7). These all suggest that staging is a viable addition to clinical care in bipolar disorder. Aims of the study

The purpose of this report was three-fold. First, we provide a broad overview as an introduction to the concept of clinical staging. Second, we discuss the 355

Kapczinski et al. rationale behind the staging systems proposed specifically for bipolar disorders. Lastly, we outline conclusions regarding current applications, future directions and research gaps.

8 on biomarkers and 7 on neuroimaging). Most excluded reports were reviews or did not explicitly recruit people with bipolar disorder. Clinical staging in psychiatry and bipolar disorder

Material and methods

We systematically reviewed the extant literature pertaining to staging and bipolar disorders. To that end, we searched MEDLINE, PsychInfo and Scopus with the terms ‘bipolar disorder’ and ‘staging’, ‘progression’ or ‘prognosis’ published up to September 2013. We planned to obtain all the available information on staging regarding clinical course of illness, functioning and cognition, differential treatment response, serum biomarkers and neuroimaging relevant for adults with bipolar disorder. Preclinical studies, as well as those involving children and adolescents, were excluded. The reason for the latter is our interest in staging postillness onset for this report, and most cases of bipolar disorder have their onset in early adulthood (8) (Table 1). However, two caveats should be borne in mind: First, the use of the term ‘staging’ is relatively new in psychiatry, and so literature searches were supplemented by references to work undertaken by the authors of this document. In addition, some of the literature on staging models targets preillness onset phases of mental disorders and in many instances examines trans-diagnostic rather than disorder-specific characteristics. As studies of staging are relatively sparse, we examined the literature on several linked issues that can inform the concept of staging, such as evidence regarding illness progression, episode density, functioning and so on. Using this strategy, 4381 references were located, with 14 additional references found manually by task force members. After inspecting the abstracts, 261 papers were read in full. Finally, 58 original articles and meta-analyses were included in the present review (15 on clinical course and outcomes, 28 on functioning and neurocognition, Table 1. Literature search details Inclusion criteria

Exclusion criteria

Search terms

356

Manuscript includes participants with bipolar disorder The study deals with a relevant aspect of staging, such as course of illness or biomarkers, or specifically investigates staging models Areas of interest: clinical studies on course of illness, functioning or cognition; studies on biomarkers or neuroimaging Focus on other psychiatric disorders or mixed samples of patients Studies conducted in children or adolescents Early intervention studies of ultra-high-risk patients Animal models of bipolar disorder (‘Bipolar disorder’ or ‘mania’) AND (‘staging’ or ‘prognosis’ or ‘progression’)

Although the concept of clinical staging had been previously noted in psychiatry (2), McGorry et al. (1, 9, 10) comprehensively discussed its implications and benefits. Clinical staging, as they proposed in these early publications, can be useful in any disease that is likely to show progression over time. This makes it valuable for many psychiatric disorders, where the reliability of diagnostic categories is not matched by predictive validity (11). This approach promotes two key notions for clinical staging. The first is that early-stage disease has a better response to treatment than later stages. The second is that early treatment may be more effective and less hazardous than treatments needed for late-stage disorders. This suggests that treatments with a higher risk or lower benefit are often needed later (12). In the framework suggested by McGorry, any disorder that tends to progress is amenable to staging (1, 9, 10). There is a long-standing debate on whether bipolar disorder is a generally progressive illness (6), but the possibility that a substantial proportion, perhaps between 40% and 50% (13), of patients present a progressive course makes clinical staging relevant. In bipolar disorder, specific models of staging have been put forward. Thus far, most empirical studies have used either the model proposed by Berk et al. (14, 15) and Kapczinski et al. (16). Berk’s system more obviously reflects the style of McGorry’s original formulation for psychosis, and other authors followed, basically in the same vein (1, 17, 18). It proposes a latency of ‘stage 0’ that identifies individuals who are putatively at higher than average risk of a disorder, but who are currently asymptomatic. It then progresses to subthreshold, then to threshold syndromes, then to multiple bipolar episode relapses and finally to an end stage of persistent and unremitting illness. It fundamentally uses episode recurrence as a proxy measure of disease progression. Postproposes a model similarly put together, harboring a few more stages, going from vulnerability to end stage (19, 20). Cosci and Fava’s (3) recent revision proposes a hybrid between using recurrences and residual symptoms. These proposals are displayed in Table 2. The starting point in Kapczinski’s model is also an at-risk state, but it then moves to a stage defined by the absence of impairment during euthymia, then to marked impairment and finally

Staging bipolar disorder Table 2. Current proposals for staging in bipolar disorder Stage

Berk et al. (14, 15)

Kapczinski et al. (16)

0

Increased risk of mood disorder

1a

Mild or non-specific symptom

At risk, positive family history, mood or anxiety symptoms Well-defined periods of euthymia without symptoms

1b 2

Prodromal features (ultra-high risk) First threshold episode

3a

Recurrence of subthreshold mood symptoms First threshold relapse Multiple relapses Persistent unremitting illness

3b 3c 4

Post (19)

Cosci and Fava (3)

Vulnerability

Mild or non-specific symptoms/prodromal phase

Interepisodic symptoms related to comorbidities Marked impairment in cognition or functioning

Well-interval

Unable to live autonomously due to impairment

Illness onset

5 6 7 8

to the inability to live autonomously. It is thus a model that emphasizes functioning, especially during euthymia, that is, in the interepisodic interval. These bipolar-specific models converge on the relevance of having an ‘at-risk’ stage and a progression to illness persistence or deterioration. As such, there should be non-trivial overlap between the two models in classifying individual patients. To our knowledge, their relative merits in terms of clinical utility and predictive validity have not been formally tested. Available data, as discussed below, are based on either the Berk or the Kapczinski system. Recently, Reinares et al. (21) employed latent class analysis to derive empirical stages based on functional outcome. In that crosssectional analysis, they defined functioning during remission as the primary outcome measure and identified that in their model, two classes of patients could be identified, best predicted by episode density and residual depressive symptoms, as well as by verbal intelligence and inhibitory control.

Results Evidence supporting the existence of clinical stages in established bipolar disorders

We examine here evidence pertaining to individuals after the first mania or hypomanic episode. This includes studies comparing first episode cases with other groups or indirect evidence for staging from post hoc analyses of recent large-scale randomized clinical trials. Clinical studies. Ideally, a staging system would be supported by prospective follow-up studies that demonstrate that it is possible to prevent or delay

Prodrome

Cyclothymia Acute manifestations of major depression or mania/ hypomania Residual symptoms with cognitive and functional impairment despite treatment

Acute episodes despite treatment

Episode recurrence Illness progression Treatment refractoriness End stage

disease progression or by randomized controlled treatment trials in cases at high risk of bipolar disorder. However, as only a few such studies exist so far for psychosis (22) and definitive studies are not available in bipolar disorder, we focus on studies that have used ‘proxy’ measures of staging (23). With those caveats in mind, we review here studies that address the assumptions behind staging as mentioned earlier, that early treatment is more benign, less complicated, more effective, and carries a better prognosis than later stages. Recently, Magalhaes et al. (24) published an analysis of the STEP-BD (25) database using number of episodes as a proxy of staging. In that large dataset (n = 3345), patients naturalistically treated in specialized facilities followed for up to 2 years were stratified according to the number of previous episodes (fewer than 5, between 5 and 9, 10 or more). Controlling for a host of possible clinical and demographic confounders, they were able to demonstrate that those patients with bipolar disorders with multiple episodes had a worse prognosis on symptom scores and functioning and quality of life. They were generally more impaired at baseline and tended not to improve as much in clinical and functional measures. This analysis was able to demonstrate that a proxy of staging – number of episodes – is able to stratify prospectively clinical and functional outcomes. This study has the advantage of having a very large sample, felt to be representative of those treated for bipolar disorder in the United States and using outcomes that are relevant to bipolar disorder. Also of relevance, Rosa et al. (26) published the analysis of a 1-year follow-up of in-patients with bipolar disorder. Similar to the STEP-BD patients, those with multiple episodes had many significant differences at baseline and also displayed a worse 357

Kapczinski et al. recovery rate at the end of the 1-year follow-up. These data converge with those from the Stanley Foundation Bipolar Collaborative (12, 27) and the Emblem European Study (28). Secondary data from two randomized psychotherapy trials also support the assumption that the patients in earlier stages have a better response to psychotherapy (21, 29). In the first, Scott et al. (29) reported that patients with fewer than 12 previous episodes had a positive response to cognitive behavioural therapy compared with those with twelve or more episodes. In this trial, patients (n = 253) were randomized to CBT or treatment as usual, and only those with fewer than 12 episodes had a lower rate of recurrence on CBT. In another post hoc analysis, a randomized controlled trial of family psychoeducation, Reinares et al. (30) clinically stratified patients with established bipolar disorder (n = 113) into early or late stages according to number of prior illness episodes. Again, they found a positive benefit, in terms of longer time to recurrence, for those in early-stage bipolar disorder. Berk et al. (31) used pooled data from olanzapine trials to evaluate stage-related differences in treatment response. Within this large dataset (12 studies, N = 4346), treatment response was higher in cases with fewer episodes in the acute mania studies, and there was a similar effect in relapse prevention. However, there were no differences in responses in depression studies. Similarly, response to certain agents, such as lithium and olanzapine, appears greater in the early phase of the BD (32, 33). Higher serum lithium levels were also more effective in preventing relapse in patients that had three or more mood episodes in one study (34). Finally, Magalhaes et al. (24) also examined whether there were any differential responses to adjunctive antidepressants within the STEP-BD study (35). However, in the subgroup allocated to antidepressants, no interaction was found between stage and outcomes. A history of rapid cycling can also be used as a proxy for a greater number of prior episodes. Recently, Ghaemi et al. (36) demonstrated that those with rapid cycling had a more adverse response to antidepressant continuation in terms of a greater number of depressive recurrences compared with those discontinuing antidepressants. Psychosocial functioning and neurocognition. The European Mania in Bipolar Longitudinal Evaluation of Medication study (n = 3115) reported that a greater proportion of first episode patients achieve symptomatic and functional recovery compared with those with multiple episodes (28).

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Likewise, a recent 1-year functioning study reported that patients at late stages were significantly more impaired than those at early stage of bipolar disorder in distinct domains of functioning (26). Similar findings have been reported for individuals in the early stages of illness presenting to youth mental health services (18, 37). Significant clinical differences, mainly in terms of severity of depression, suicide attempts and the number of years before receiving a correct diagnosis, have been observed between patients with first and multiple episodes (38). Taken together, these findings suggest that the episode frequency has an impact on patient’s outcome, particularly on psychosocial functioning. Individuals with bipolar disorder often experience persistent neurocognitive deficits and poor psychosocial functioning even when they are euthymic (39–43). Neurocognitive impairment has been related to a worse clinical course and poor psychosocial functioning (44, 45). For instance, in a first episode cohort, verbal learning at baseline was robustly associated with functional outcome at a 6-month follow-up even after controlling for mood symptoms and substance abuse comorbidity (46). More severe neurocognitive deficits are not only associated with illness severity (47, 48), but also associated with cumulative mood episodes (49, 50). For instance, euthymic patients who had at least three manic episodes showed worse overall neurocognitive performance compared with those with only one previous episode of mania (51). In young adults presenting with bipolar depression, Hermens et al. (52) also identify significant neurocognitive deficits in young adults presenting with in the early stages of bipolar disorders. Memory, attention and executive dysfunction have been consistently reported in euthymic patients with bipolar disorder (43, 53, 54), generally in proportion to number of prior episodes (30), with verbal learning and memory impairment being significant predictors of long-term functioning (55). The impact of neurocognitive impairment on functioning led Torrent et al. (56) to develop a functional remediation program specifically for bipolar disorders. This program is especially tailored for people with bipolar disorder who have impairment during euthymia along the progression of the disorder. Functional remediation showed superiority to treatment as usual in improving psychosocial functioning at study endpoint. This study suggests that functional remediation could be more suited to patients in advanced stages, whereas psychoeducation is likely to be more effective in the early stages of illness.

Staging bipolar disorder Peripheral markers. Peripheral biomarkers are pertinent to the theme of staging as they are conceptualized as mediators of allostasis (57–59) and their demonstration in different stages is one of the fundamental hypotheses of neuroprogression (60, 61). Ultimately, they might be useful in selecting staged interventions. For instance, concordant with the allostatic load model, the presence of relevant medical comorbidity is often associated with indications of late-stage bipolar disorder (62). Recently, patients with such comorbidities were shown to have a better response to N-acetyl-cysteine than those without medical conditions (63). If confirmed, these findings would suggest the use of adjunctive antioxidants in those with comorbidities, which could be proxies of higher levels of circulating free radicals. Perhaps, the seminal study on the association of biomarkers with staging was conducted by Kauer-Sant’Anna et al. (64). In that case– control study, the authors were able to demonstrate that patients in a late stage (i.e., a minimum of 10 years after the diagnosis of bipolar disorder and with multiple previous episodes) showed many differences in peripheral inflammation biomarkers when compared to controls, which was not the case in early-stage patients. Furthermore, in the case of tumor necrosis factor a, where both groups of patients had increased circulating levels, patients in late stages had several-fold greater increases (see Table 3). Further exploration of this sample also revealed that glutathione S-transferase and reductase were increased in late-stage patients, although 3-nitrotyrosine was also found increased in early-stage patients (65). These alterations in oxidative biology imply a pro-oxidant pathology in bipolar disorder. Further increases in protein and lipid damage have been reported in patients with bipolar disorder seen at tertiary facilities, which are generally latestage patients (66). However, a recent report of a community-based sample also demonstrated early-stage increases in protein damage (67). Neurotrophins are also relevant to staging as they are pertinent to the kindling hypothesis and other models of illness progression (68, 69). In the study mentioned above, Kauer-Sant’Anna et al. (64) also demonstrated relevant decreases in brainderived neurotrophic factor (BDNF) in late-stage, but not early-stage, patients. A later meta-analysis demonstrated a correlation between the age and length of illness and serum BDNF across seven studies (70). A similar relationship was apparent when a ‘systemic toxicity index’ was examined in late-stage patients compared with people with

Table 3. Selected circulating biomarkers in early- and late-stage bipolar disorder Marker BDNF (76, 82) TNF a (76) IL-6 (76) IL-10 (76) PCC (77–79) TBARS (78) Systemic toxicity (83, 84)

Early stage

Late stage

 ↑ ↑ ↑ ↑  ↑

↓↓ ↑↑ ↑   ↑↑ ↑↑

BDNF, brain-derived neurotrophic factor; TNF-a, tumor necrosis factor a; IL, interleukin; PCC, protein carbonyl content; TBARS, thiobarbituric acid reactive substances.  No change, ↑ modest increase, ↑↑ substantial increase, ↑ mixed results, ↓↓ substantial decrease.

early-stage bipolar disorder from the general population (71, 72). Neuroimaging. Lin et al. (73) recently reviewed neuroimaging evidence for staging in severe mental disorders, including bipolar disorder. They highlight the possibility that structural and functional networks could be differently affected in each illness stage. White matter pathology could be responsible for early-stage dysconnectivity. In first episode patients, for instance, recent meta-analysis shows significant white matter reductions, but not gray matter (74). Another meta-analysis of voxelwise studies also demonstrated fewer alterations in gray matter in first episode patients (75). There was no progression in gray matter loss in patients with severe bipolar disorder during the first 2 years of follow-up, when compared with controls (76). Stage changes were specifically investigated in only a few cross-sectional studies. In one MRI study, the total number of episodes was correlated with the size of the left hippocampus, and only patients with fewer than 10 episodes had a larger hippocampus compared with controls (77). Lagopoulus (78) compared a mixed cohort of people with ‘attenuated syndromes’ (stage 1) with patients with ‘discrete disorders’ (psychosis, bipolar disorder or depression, stages two or three). Patients on stage 2 or 3 had a more widespread pattern of gray matter loss. In a region of interest study, Nery et al. (79) showed similar orbitofrontal cortex gray matter volumes in individuals with bipolar disorder and controls. However, the total number of episodes did not influence significantly the result. A recent systematic review of longitudinal neuroimaging studies notes several caveats and a general dearth of prospective data (80), which mirrors the neurocognitive literature (81). Among structural neuroimaging studies, neuroprogressive changes were more robustly noted in prefrontal, cingulate and subgenual cortices and fusiform gyrus, although total brain volume seems to be stable.

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Kapczinski et al. Discussion

Most of extant evidence relevant to staging models is cross-sectional. This is surely the source of much of the heterogeneity in the biomarker and neuroimaging data. Another source of weakness in the current published literature is the small sample size of the studies, which are mostly pilot studies in nature. Even some of the most carefully designed and strongest research such as the differential changes in peripheral biomarkers according to stage demonstrated by Kauer-Sant’Anna et al. (64) would benefit from independent replication. Transitions from at risk to subsyndromal and then syndromal illness (where the individual meets diagnostic criteria) and between later stages should be studied and validated with relevant clinical endpoints – and possibly biomarker data. This will likely require a multicenter effort, due to the inherent complexity of such endeavors. The current staging models for bipolar disorder should also be formally compared with each other and also with other trans-diagnostic models (3). A staging system should be able to predict disease progression and stratify relevant outcomes in a consistent way. However, this demonstrates an element of the current challenge for psychiatry. Merely predicting future functioning or relapses based on current functioning or previous relapses contains an element of circularity that should be avoided. One attractive option is the use of putative stages as a stratification variable in randomized controlled treatment trials. This has only rarely been performed, but would be clinically useful to confirm previous secondary analyses with rigorous, stage-tailored and hypothesis-driven trials. Alternatively, patients could be randomized to either receive treatment as usual or ‘stage-appropriate’ interventions. Furthermore, there is a need to develop and test the role of stage-specific treatments for at risk and first episode cases: exemplars being the studies led by Miklowitz (82) and by MacNeil (83). With the caveat that most data at present are cross-sectional in nature, based on post hoc analysis or both, the bulk of the preliminary evidence available suggests that staging has promising clinical utility for postillness onset cases of bipolar disorder. Clinically, the early- and late-stage distinction may appear obvious in the sense that such patients have overtly different needs. Clinicians have their own, probably idiosyncratic ways in dealing with this issue (3). Nevertheless, confirming these effects and estimating their magnitude matters. Also of consequence, such different cohorts of 360

patients are usually lumped in clinical trials, which could obscure relevant treatment differences. There is growing consensus that early intervention is valuable in individuals with severe mental disorders (84). Interventions for individuals in late stages have been more problematic and less often studied systematically (85). Most studies to date confirm that globally defined late-stage patients have a worse overall prognosis and poorer response to standard treatment, consistent with patterns known in other medical disorders. Although refinement of staging systems is certainly in need of further study, we believe it is already proper at this juncture to speak broadly of ‘early’ and ‘late’ stages. Early stages are at the first or the first few episodes and are in aggregate associated with better functioning after recovery. Late stages are associated with multiple episodes and tend to have impairment in multiple areas of functioning. In other words, the models proposed by Kapczinski and Berk concur on the importance of ‘early’- or ‘late’-stage disease. The next steps require consideration of the details of intermediary stages and how many additional stages are optimal. The ultimate goal should be linking staging models with optimally tailored therapy. This should be the subject of further local and global collaborative efforts. Declaration of interest Prof. Kapczinski has received grants/research support from AstraZeneca, Eli Lilly, Janssen-Cilag, Servier, CNPq, CAPES, NARSAD and Stanley Medical Research Institute; has been a member of the board of speakers for AstraZeneca, Eli Lilly, Janssen and Servier; and has served as a consultant for Servier. Vasco Videira Dias is consultant for Angelini Pharmaceutical, Portugal, and has received educational grants from Lundbeck, Sanofi-Aventis, AstraZeneca and Bristol-Myers Squibb. Dr. V azquez has served as consultant or speaker for Abbott, AstraZeneca, Gador, Glaxo-SmithKline, Ivax/Teva, Eli Lilly, Lundbeck, Pfizer, Raffo, Servier and Novartis within the last 3 years. Dr. I. Grande has received a research grant Rıo Hortega Contract (CM12/00062), Instituto de Salud Carlos III, Spanish Ministry of Economy and Competiveness, Barcelona, Spain, and has served as a speaker for AstraZeneca. Dr Balanz a-Martınez has received grants and served as consultant, advisor or CME speaker during the last 3 years for the following entities: Angelini, AstraZeneca, Bristol-Myers-Squibb, Janssen, Juste, Lilly, Otsuka, the Spanish Ministry of Science and Innovation (CIBERSAM), and ´Fundaci on Alicia Koplowitz´. Sergio A. Strejilevich has served as consultant or speaker for Glaxo Smith Kline, AstraZeneca, Lilly, Abbott and has received educational grants from Servier. Jan Scott has received funding toward the costs of attending national and international conferences, or fees for talks on psychosocial aspects of bipolar disorders, or advisory board fees from Astra Zeneca, BMS-Otsuka, Eli Lilly, GSK, Jansen-Cilag, Lundbeck, Sanofi-Aventis and Servier. Dr. Vieta has received grants and served as consultant, advisor or CME speaker for the following entities: Adamed, Alexza, Almirall, AstraZeneca, Bial,

Staging bipolar disorder Bristol-Myers Squibb, Elan, Eli Lilly, Ferrer, Forest Research Institute, Gedeon Richter, Glaxo-Smith-Kline, Janssen-Cilag, Jazz, Johnson & Johnson, Lundbeck, Merck, Novartis, Organon, Otsuka, Pfizer, Pierre-Fabre, Qualigen, Roche, SanofiAventis, Servier, Shering-Plough, Shire, Solvay, Sunovion, Takeda, Teva, the Spanish Ministry of Science and Innovation (CIBERSAM), the Seventh European Framework Programme (ENBREC), the Stanley Medical Research Institute, United Biosource Corporation, and Wyeth. Clarissa S Gama has served as consultant or speaker for Actelion Pharmaceuticals, Eli Lilly, Lundbeck and Roche. Michael Berk has received grant/research support from the NIH, Cooperative Research Centre, Simons Autism Foundation, Cancer Council of Victoria, Stanley Medical Research Foundation, MBF, NHMRC, Beyond Blue, Rotary Health, Geelong Medical Research Foundation, Bristol-Myers Squibb, Eli Lilly, Glaxo SmithKline, Meat and Livestock Board, Organon, Novartis, Mayne Pharma, Servier and Woolworths and has been a speaker for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo SmithKline, Janssen Cilag, Lundbeck, Merck, Pfizer, Sanofi Synthelabo, Servier, Solvay and Wyeth, and served as a consultant to AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo SmithKline, Janssen Cilag, Lundbeck Merck and Servier. Dr. Yatham is on speaker/advisory boards for or has received research grants from: AstraZeneca, Bristol-Myers Squibb, CIHR, CANMAT, Eli Lilly, GlaxoSmithKline, Janssen, Lundbeck, the Michael Smith Foundation for Health Research, Pfizer, Servier, Sunovion and the Stanley Foundation. Janusz K. Rybakowski has acted over the past 2 years as a consultant or as a speaker for the following companies: Bristol-Myers-Squibb, Eli Lilly, Janssen-Cilag, Lundbeck, Sanofi-Aventis and Servier. Marion Leboyer served as a speaker to Servier, AstraZeneca and received research grants from Sanofi and Roche. Prof. Kauer-Sant’Anna has received research grants from NARSAD, SMRI, Universal-CNPq, CNPq/INCT-TM, FIPE-HCPA, and is on the speaker board for Eli-Lilly. Carlos Lopez-Jaramillo has received Grant/Research Support from the Colciencias, Universidad de Antioquia, NIMH, and Abbott, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo SmithKline, Novartis, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo SmithKline, Janssen Cilag, Lundbeck, Pfizer, Sanofi Synthelabo, and served as a consultant/speaker to Abbott, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo SmithKline, Janssen Cilag, Lundbeck, Pfizer and Servier. Dr. Gonzalez-Pinto has received grants and served as consultant, advisor or CME speaker for the following entities: AstraZeneca, Bristol-Myers Squibb, Cephalon, Eli Lilly, Janssen-Cilag, Lundbeck, Merck, Otsuka, Pfizer, Sanofi-Aventis, Servier, the Spanish Ministry of Science and Innovation (CIBERSAM), the Ministry of Science (Carlos III Institute), the Basque Governement, the Stanley Medical Research Institute, and Wyeth. Ralph Kupka received unrestricted research grants from AstraZeneca and served as a speaker for AstraZeneca, Eli-Lilly, Lundbeck and BristolMyersSquibb.

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