Long-term response to mood stabilizer treatment and its clinical correlates in patients with bipolar disorders: a retrospective observational study
Ahn et al. Int J Bipolar Disord
Long-term response to mood stabilizer treatment and its clinical correlates in patients with bipolar disorders: a retrospective observational study
Sung Woo Ahn 0
Ji Hyun Baek 0
SoY‑ung Yang 0
Yongkang Kim 2
Youngah Cho 1
Yujin Choi 4
Kounseok Lee 3
Taesung Park 2
Kyung Sue Hong 0
0 Department of Psychiatry, Sunkyunkwan University School of Medicine, Samsung Medical Center , Seoul , Republic of Korea
1 Department of Psychiatry, Seoul National University Bundang Hospital , Seongnam , Republic of Korea
2 Department of Statistics, Seoul National University , Seoul , Republic of Korea
3 Department of Psychiatry, St. Andrew's Hospital , Icheon‐si , Republic of Korea
4 Center for Clinical Research, Samsung Biomedical Research Institute , Seoul , Republic of Korea
Background: The efficacy and utility of long‑ term prophylactic treatment in patients with bipolar disorders (BDs) have not been fully explored. This study aims to estimate the long‑ term clinical response of patients with BDs to mood stabilizer treatment and to identify the clinical factors associated with that response. Methods: The study subjects consisted of 80 patients with bipolar I or bipolar II disorder who had been receiving treatment with lithium and/or valproate for more than 2 years at a single bipolar disorder clinic. The long‑ term response to the best treatment option based on treatment algorithms was evaluated using the Alda scale. Clinical characteristics were evaluated on a lifetime basis. Patients were classified into two response groups based on frequentist mixture analysis using the total Alda scale score. Results: Thirty‑ four percent of the patients were good responders, with a total Alda score of 5 or higher. The treatment response rate did not differ between the lithium and valproate groups, but lithium and valproate combination therapy was associated with poorer response. The number of previous mixed episodes was associated with a worse response (p = 0.026). Of individual symptoms, delusions during manic episodes (p = 0.008) and increased appetite (p = 0.035) during depressive episodes were more common in moderate/poor responders than in good responders. Co‑ morbid anxiety disorders were more frequently observed in the moderate/poor response group (p = 0.008). Conclusions: Psychotic, mixed, and atypical features of BDs were found to be correlated with long‑ term treatment outcomes. Lithium and valproate showed similar efficacy but moderate/poor responders preferred to use polypharmacy.
Bipolar disorders; Treatment response; Alda scale; Lithium; Valproate
Bipolar disorders (BDs) are a group of chronic
psychiatric illnesses with diverse clinical courses composed of
combinations of (hypo)manic and depressive episodes
(Sadock et al. 2014)
. Although a number of guidelines
have been established for the pharmacotherapy of BDs
(Yatham et al. 2013; Jeong et al. 2015; Goodwin 2009)
long-term drug response and its clinical correlates in BD
patients receiving standard clinical care have not been
well explored. Considering the wide variation between
individuals in the manifestation of illness, including
biphasic and recurring courses, difficulties in defining
outcomes should be expected. Another obstacle to the
investigation of long-term response is variability in drug
options and changes in the drugs that are taken during
the course of treatment
(Ghaemi et al. 2006; Baek et al.
The criteria for long-term response have been defined
in various ways. One or a few isolated variables, such
as time to recurrence, reduction of episode frequency,
length, or severity, and reduction of the time spent in the
hospital, have frequently been used in previous studies
(Kleindienst et al. 2005)
. These simple variables, however,
do not reflect the diversity of treatment courses observed
in natural clinical settings. Global assessment of
(American Psychiatric Association 2000)
and the clinical global impressions scale for use in
bipolar illness (CGI-BP)
(Spearing et al. 1997)
have also been
used to evaluate long-term efficacy
Engelsmann 1998; Post et al. 2010)
. However, these scales are
generally only appropriate for assessing a patient’s state
at a single cross-sectional time point. A scale specifically
tailored to the retrospective assessment of
prophylactic lithium response in BDs was introduced by Alda and
colleagues (Grof et al. 2002) (the retrospective criteria
of lithium response in research subjects; the Alda scale),
and has been widely used in genetic studies on lithium
(Grof et al. 2002; Passmore et al. 2003; Hou
et al. 2016; Chen et al. 2014; Squassina et al. 2011)
. As the
scale considers confounding factors, such as
polypharmacy, compliance, and disease course before
administration of medication, it can be adapted to various clinical
cases and settings involving long-term treatment.
A number of previous studies investigated potential
predictors of prophylactic lithium treatment in BDs.
According to a systematic review by Kleindienst and
colleagues (2005), depression-mania episode sequence,
earlier onset of illness, a high number of previous
hospitalizations, and continuous cycling seem to be
associated with poor outcomes. In later studies, psychotic
symptoms, inter-episodic residual symptoms, mixed
episodes, and rapid cycling
(Backlund et al. 2009;
Pfennig et al. 2010; Silva et al. 2016)
were identified as
predictors of poor long-term response to lithium. A positive
correlation of long-term response with hyperthymic
(Rybakowski et al. 2013)
episodic course of illness with earlier onset
(Garnham et al.
were also reported. Comorbid anxiety disorders
and alcohol abuse/dependence were associated with poor
prophylactic efficacy in both early and recent studies
(O’Connell et al. 1991; Young et al. 1993; Kliwicki 2014)
Controversial results were generated regarding bipolar I
disorder (BD-I) vs. bipolar II disorder (BD-II)
(Kleindienst et al. 2005; Garnham et al. 2007; Rybakowski 2014)
and a family history of mood disorders
Mendlewicz et al. 1973; Maj et al. 1985; Misra and Burns
1977; Coryell et al. 2000)
In contrast to the lithium response, studies on
longterm response to the broader category of mood
stabilizers are limited. A recent study evaluating the
prophylactic efficacy of lithium, valproate, and
carbamazepine reported an association between the likelihood
of relapse and a mixed episode and the total number of
manic or depressive symptoms prior to the observational
(Peselow et al. 2015)
. In naturalistic observational
studies of the Stanley Foundation Treatment Outcome
Network that assessed the prospective outcomes of BD
patients receiving various combinations of
pharmacologic treatments, family history of drug abuse, history
of childhood abuse, a greater number of prior episodes,
and comorbid substance abuse were associated with poor
(Post et al. 2010; Nolen et al. 2004)
. To the best
of our knowledge, long-term studies investigating
specific predictors of treatment response to valproate are
lacking (Carvalho and McIntyre 2015).
According to a recent multi-center investigation of
prescription patterns in Korea, valproate is more
commonly used than lithium, and polypharmacy is used in
80.86% of patients
(Baek et al. 2014)
. Also, medication
changes owing to adverse drug effects, lack of response,
and phase changes frequently occur during the course of
treatment for BDs
(Yatham et al. 2013; Baek et al. 2014;
Arvilommi et al. 2010)
. Given the complexity of
pharmacotherapy, the long-term effect of an isolated mood
stabilizer is quite difficult to delineate. In addition, the effects
of a single medication given alone would be hard to
generalize to real-world BD treatment. A more global view
of treatment effects on the long-term outcome of BD is
This study was designed to estimate the clinical
response of individuals with BDs to long-term treatment
with mood stabilizers. In order to reflect the
prescription patterns shown by a recent nationwide survey that
includes data from our clinic
(Baek et al. 2014)
with the most commonly used mood stabilizers, i.e.,
valproate and lithium, was selected as target mood stabilizer
treatment. The overall response rate was retrospectively
assessed using the Alda scale based on observational data
collected over a period of more than 2 years. This study
also aimed to identify the factors associated with
treatment response among all of the comprehensive clinical
Patients and methods
Patients who met the DSM-IV criteria for BD-I or BD-II
and had received treatment with lithium and/or valproate
for more than 2 years between March, 2009 and April,
2015 at the Bipolar Disorder Clinic of the Samsung
Medical Center, a tertiary-care university-affiliated hospital,
were screened for inclusion in the study. The patients’
ages ranged from 18 to 55 years. Those who had evidence
of neurologic disorders or general medical conditions
related to mental symptoms were excluded. A total of
eighty patients who met the above criteria and agreed
to participate in the study were enrolled (Fig. 1). Among
those patients, there were 60 participants who were
involved in other clinical and genetic studies described
(Baek et al. 2011, 2016; Yang et al. 2015)
study was approved by the Institutional Review Board of
the Samsung Medical Center.
Assessment of the treatment response
The best treatment (including lithium and/or valproate)
was provided to each patient based on treatment
guidelines including the Korean Medication Algorithm for
Bipolar Disorder 2014
(Shin et al. 2013)
(Yatham et al. 2013; Goodwin
, clinicians’ experience, and patients’ special
concern on expected adverse effects. Long-term response
to the treatment was evaluated through retrospective
chart review. When possible, additional information was
directly obtained from the patients during their
outpatient departmental visits. Assessments were performed
using the Alda scale (Grof et al. 2002). The Alda scale
consists of two criteria, i.e., rating of the association
between clinical improvement and treatment
(Criterion A) and rating of the degree of the causal
relationship between clinical improvement and prophylactic
treatment (Criterion B). The total score was obtained by
subtracting the B score from the A score. Two research
psychiatrists (SWA and KSH) and the clinician who saw
each patient (KSH, JHB, YC, S-YY, or SWA)
independently reviewed the hospital records and came to a
consensus on the treatment response.
Fig. 1 Flow diagram of patient enrollment
Assessment of clinical characteristics
For all of the subjects, the current mood state of the
subjects was assessed using the clinical global impressions
scale for use in bipolar illness (CGI-BP)
(Spearing et al.
. Predominant polarity was assessed according to
the criteria proposed by
Colom and colleagues (2006
For 60 subjects (participants in the previous
studies conducted by the authors), comprehensive disease
characteristics had previously been evaluated before the
present assessment of treatment response. The
evaluation was performed through a direct interview using the
revised version of the Korean version of the
Diagnostic Interview for Genetic Studies
(Joo et al. 2004)
is described in detail elsewhere
(Baek et al. 2011, 2016;
Yang et al. 2015)
. The rated variables cover age at onset
and course of mood episodes, manifested symptoms, and
comorbid psychiatric conditions on a lifetime basis.
Patients were classified into good responders and
moderate/poor responders as defined based on frequentist
mixture analysis using the total Alda scale score. The analysis
showed a best-fit theoretical model of two components
(AIC = 374.1; BIC = 383.6) (Additional file 1: Table
S1), and a suggested cut-off point at a total score of 4.5.
Therefore, a total score 5 or higher was defined as a good
response and a score of 4 or lower was defined as a
Comparison of demographic and clinical variables
between the two groups was performed using a
Chisquare test (or Fisher’s exact test) for categorical data,
and a t test for continuous variables. Probability (p)
values less than 0.05 were considered statistically significant.
The same comparisons between good vs. moderate and
poor responders were also applied to the BD-I subgroup.
All statistical analyses were done with IBM SPSS version
Pharmacotherapy and treatment response
Among all 80 subjects, 50 (62.5%) received valproate, 19
(23.8%) received lithium, and 11 (13.8%) received both
lithium and valproate. The mean duration of
medication was 71.7 (SD = 34.1, range: 25–142) months. The
total and A scores of the Alda scale are shown in Fig. 2.
The mean total score was 3.4 (SD = 2.5), and the mean
A score was 6.7 (SD = 1.9). Based on frequentist
mixture analysis of the total score, 27 (33.8%) and 53 (66.2%)
patients were classified into the good response and
moderate/poor response groups, respectively. All of the
subjects had received treatment for 2 or more years and
showed adequate compliance during the observation
period, with more than 80% levels in the therapeutic
range. Patients may have been prescribed multiple drugs,
and quetiapine was the most frequently prescribed
adjunct medication. Additional use of antipsychotics,
antidepressants, and other mood stabilizers at the time
of the current assessment is summarized in Table 1. As
expected, moderate/poor responders received more
adjunctive medicines than did good responders.
Polypharmacy of mood stabilizers including atypical
antipsychotics (except for quetiapine of daily dose of 50 mg or
less which is usually applied for insomnia control) was
popular in both good responders (N = 14, 51.9%) and
moderate/poor responders (N = 43, 81.1%).
Comparison of demographic and disease course characteristics
Table 2 shows the demographic characteristics and
clinical course of good responders and moderate/poor
responders. Sex and age were not significantly different
between the two groups. There were no statistically
significant group differences in the age at onset, subtype
diagnosis (BD-I vs. BD-II), polarity at the first episode,
current smoking status, predominant polarity, number
of depressive/(hypo)manic episodes, and family
history of psychiatric disorders and mood disorders (in
second-degree relatives). Compared to good responders,
moderate/poor responders experienced a greater
number of mixed episodes before taking their current mood
stabilizers (p = 0.026). The type of index mood stabilizer
was not statistically different between groups, but a much
higher rate of combination of lithium and valproate was
observed in the moderate/poor responders compared
to the good responders (18.9 vs. 3.7%). In terms of
efficacy of specific medications, the mean total score of the
Alda scale was not significantly different (t = −1.423,
p = 0.159) between valproate users (4.0 ± 2.4) and
lithium users (3.0 ± 2.7). Lithium and valproate
combination group shows lower mean total score of the Alda
scale (1.45 ± 1.8). In the three-group comparison, an
overall difference (p = 0.008) with a significant difference
between the combination group and valproate group
(p = 0.011, Scheffe’s methods) was observed.
Comparison of symptom profiles of mood episodes
Lifetime-based symptom profiles of mood episodes are
described in Additional file 1: Table S2. When
considering the symptoms of (hypo)manic episodes, delusion
was much more frequent in moderate/poor
responders (72.2%) than in good responders (37.5%) (p = 0.008).
At the time of the assessment of treatment response
a Including index medications, atypical antipsychotics, and other mood stabilizers; for quetiapine, daily dose of 50 mg or less which is usually applied for insomnia
control was excluded
Other symptoms including elevated mood, irritability,
grandiosity, decreased sleep need, talkativeness, flight of
idea, distractibility, hyperactivity, excessive involvement
in activity, and hallucination were observed at similar
rates in both groups. Among symptoms of depressive
episodes, only ‘appetite change’ showed a significant
between-group difference (p = 0.035). Increased appetite
was observed only in moderate/poor responders (7
subjects, 19.4%), and appetite loss was more frequent in good
responders (63.6%) than in moderate/poor
responders (36.1%). The other symptoms which we investigated,
i.e., depressed mood, insomnia, hypersomnia, agitation,
retardation, apathy, loss of energy, guilty feeling, low
selfesteem, suicidal ideation, indecisiveness, delusion, and
hallucination did not show any difference between the
Comparison of comorbid psychiatric disorders and conditions
While moderate/poor responders had a lifetime
co-morbidity of any anxiety disorder of 25%, anxiety disorders
were not observed in good responders (p = 0.008)
(Additional file 1: Table S3). The co-morbidity rate of other
psychiatric conditions observed in the current subjects,
including alcohol/substance-related disorders, eating
disorders (anorexia and/or bulimia nervosa), hyperthymic
temperament, premenstrual syndrome, and history of
suicidal attempts, did not show significant
Analyses of possible confounding factors
Considering that the preference for a specific mood
stabilizer (lithium, valproate, or a combination of the two)
given a specific baseline condition might affect the results
of the main analyses, we compared demographic and
clinical variables among the three groups divided by
medication type (Additional file 1: Tables S4, S5). A
betweengroup difference was observed only in subtype diagnosis
(BD-I vs. BD-II). Therefore, we additionally performed
the same analyses only in BD-I (N = 65) patients. A
previous history of mixed episodes (p = 0.015) and delusion
during manic phases (p = 0.003) were again identified as
being associated with a worse response (Additional file 1:
Tables S6, S7).
In this retrospective investigation of the clinical response of
patients with BDs to long-term (2 years or more) treatment
with valproate and/or lithium, one-third of the patients
were good responders, with a total Alda score of 5 or
higher. When our analysis excluded patients receiving both
valproate and lithium, we did not find any significant
differences in the long-term clinical effects between the two
drugs. Previous experience with mixed episodes
(according to DSM-IV criteria), delusions during manic episodes,
appetite increase during depressive episodes, and comorbid
anxiety disorders were related to a worse response.
As the present study does not focus on the effects
and associated factors of a single drug, direct
comparison of clinical response between the current study and
BD-I bipolar I disorder, FE Fisher’s exact test, SD standard deviation
a N = 76
b Equal variance not assumed
c Evaluated in second-degree relatives
d Evaluated in second-degree relatives, including those with major depressive disorders and bipolar disorders
e Clinical global impressions scale for use in bipolar illness
previous studies, most of which investigated the effects
of single mood stabilizers in isolation, would be difficult.
In order to explore long-term response in a naturalistic
clinical setting, we felt it necessary to consider
medication changes and combinations of different mood
stabilizers during the course of treatment. Therefore, we
selected valproate, lithium, and a combination of the two
drugs as a single target treatment. In the current study,
valproate and lithium seemed to be associated with
similar long-term responses. In addition, the
supplementary analysis showed that baseline demographic and
clinical features did not affect selection of one drug over
another, except that there was a preference for valproate
in BD-II. Valproate and lithium are the most frequently
used medications in our clinic and in other mood
disorder clinics in tertiary-care hospitals in Korea
(Baek et al.
. According to a report from the Stanley Foundation
Treatment Outcome Network
(Post et al. 2010)
two drugs are the most frequently prescribed
medications at the time of improvement and have high overall
success rates in outpatients treated for BDs.
Although several studies have investigated the response
to mood stabilizers using the Alda scale, they used
different response criteria. In a previous report by Garnham
and colleagues (2007), which defined the ‘full-responder’
group as those with a total score of 7 or higher, the rate
of full response was 30% in lithium users and 13% in
valproate users. In the ConLiGen study
(Manchia et al.
, which used the same criteria, 33% of
lithiumtreated patients were classified as ‘full responders.’ When
adopting the ConLiGen criteria, the full-responder rate
was just 15.0% in our study (12 out of 80 patients). The
mean total score was also lower in the current study
(3.4 ± 2.5) compared to in the ConLiGen studies, i.e.,
4.4 ± 3.1 in their initial clinical report
(Manchia et al.
, and 4.3 ± 3.3 and 3.9 ± 3.0 in their genome-wide
(Hou et al. 2016)
. However, the mean A
score of the current subjects (6.7 ± 1.9) was higher than
that of the ConLiGen study subjects, which ranged from
6.0 to 6.4
(Hou et al. 2016; Manchia et al. 2013)
indicates a higher B score in the current subjects. The B
score reflects baseline clinical characteristics that could
affect the true causal relationship between treatment and
outcome, including previous mood episodes, treatment
duration, compliance, and additional medication. One
prominent feature of our sample related to B score is a
high rate (76.3%) of psychotic features that could result in
the usage of additional antipsychotic medications.
To identify the clinical factors associated with
longterm mood stabilizer treatment, we investigated a variety
of baseline characteristics, including disease onset and
course, symptoms of episodes, and comorbidities. Worse
treatment response in patients with more previous mixed
episodes, delusions during manic episodes, and appetite
increase during depressive episodes was observed not
only in the main analysis of all subjects but also in the
supplementary analysis of BD-I patients alone. Analysis
of comorbid psychiatric conditions could be performed
only in the overall sample because of the small
sample size of the BD-I group, considering the low rates of
comorbidities. Anxiety disorders were only observed in
the moderate/poor responders. Although study designs
and target drugs differ between studies, the current
results are roughly in agreement with previous reports
of predictors of treatment response to mood
stabilizers. Mixed episodes predicted poor long-term response
in a study on lithium
(Backlund et al. 2009)
and a study
on multiple mood stabilizers
(Peselow et al. 2015)
Psychotic features were also reported as a predictive factor
of a poor response to lithium
(Kleindienst et al. 2005;
Backlund et al. 2009; Pfennig et al. 2010; Silva et al. 2016)
According to the current results, among psychotic
symptoms, delusions during manic episodes were specifically
associated with worse responses. Increase in appetite is a
major symptom of atypical depression, and atypical
features of depression were reported to be associated with
a greater rate of psychiatric comorbidities, increased
distress, suicidal ideation, and disability, all of which
might lead to negative treatment outcomes
(Sadock et al.
2014; Matza et al. 2003)
. To the best of our knowledge,
this is the first study to report on the atypical symptoms
in depressive episodes as a predictor of poor long-term
mood-stabilizer response in BDs. Various comorbid
disorders were expected to occur and are known to be
associated with poor response in BD patients
et al. 2005; Kliwicki 2014; Rybakowski 2014)
, and a
concordant finding was detected only for anxiety disorders in
the current study. In the case of other comorbid
conditions, including eating disorders and
alcohol/substancerelated disorders, the small sample size might have
limited our ability to detect associations. Other reported
predictors of response, i.e., age at onset, a high number of
previous hospitalizations, rapid cycling, and hyperthymic
(Kleindienst et al. 2005; Rybakowski et al.
, did not show a significant association in the
current study, and need to be analyzed in future studies with
larger sample sizes. Regarding the controversial results
of previous studies on BD-I vs. BD-II
(Kleindienst et al.
2005; Garnham et al. 2007; Rybakowski 2014)
current data could not generate any conclusions owing to
the extremely skewed use of valproate in BD-II.
This study has several limitations. First, because of
the relatively small number of subjects, false negative
results are to be expected. The statistical power may be
particularly limited to detect differences in patients
taking lithium vs. valproate. A large number of patients in
the clinic were excluded because they had not taken the
index medications for more than 2 years. Second, as this
is a retrospective study, a conclusive causal relationship
could not be determined between clinical factors and
poor response rates. Third, in this naturalistic
observational study, many uncontrolled confounding variables
might decrease the assay sensitivity. Choice of
medication (valproate vs. lithium) and diagnosis of BD-I vs.
BD-II were considered as possible confounding factors in
the supplementary analyses, whereas the effects of other
potential confounding variables, such as medication dose
or plasma level, adjunctive medications, and
non-pharmacologic treatment, were not excluded. In the
comparison of long-term response between drugs, there might
be additional confounding variables affecting the
selection of a specific mood stabilizer. Fourth, lack of use of
classical longitudinal illness metrics, e.g., time to
recurrence/recovery is also a limitation of this study
considering difficulties in direct comparison of the current results
with previous studies. Finally, as all of the subjects were
Korean patients, the current results may have limited
generalizability to other populations.
This study also has the following strength. It is a
naturalistic observational study that reflects a real-world
clinical setting. Although retrospective evaluation was
performed, reliable assessment of treatment response is
expected considering the long follow-up period (at least
2 years) at a single institute and the involvement of the
treating clinicians in outcome assessment. In addition,
baseline disease characteristics and clinical variables were
independently assessed in previous studies by the authors
before the current assessment of treatment response.
This study shows an overall outcome and response rate
of BDs to long-term standard treatment using valproate
and/or lithium. This study adds additional evidence that
mixed and psychotic features and comorbid anxiety
disorders are associated with poor treatment response in
patients with BDs. It also identifies specific symptoms
(increased appetite during depressive episodes and
delusions during manic episodes) as novel candidate
predictors of long-term mood stabilizer treatment.
Additional file 1: Table S1. Model fitting evaluation of the total Alda
scale score. Table S2. Comparison of lifetime symptom profiles of mood
episodes between good responders and moderate/poor responders
(N = 60). Table S3. Comparison of the lifetime prevalence of co‑morbid
psychiatric illnesses between good responders and moderate/poor
responders (N = 60). Table S4. Comparison of baseline characteristics
by medication (N = 80). Table S5. Comparison of symptom profiles by
medication (N = 60). Table S6. Comparison of demographic data and
clinical course between good responders and moderate/poor respond‑
ers in patients with bipolar I disorder (N = 65). Table S7. Comparison
of symptom profiles between good responders and moderate/poor
responders (N = 49).
SWA, JHB, YC, SYY, KL, and KSH have contributed to study design, data collec‑
tion, and clinical rating. SWA and KSH wrote the manuscript. YC contributed to
data collection and management, and chart review of the patients. YKK and
TP undertook the statistical analysis. All authors read and approved the final
The authors declare that they have no competing interests. This article is the
authors’ original work, has not received prior publication, and is not under
consideration for publication elsewhere.
Consent for publications
There are no individual person’s data in this article. Not applicable.
Ethics approval and consent to participate
This study was approved by the Institutional Review Board of the Samsung
Medical Center [IRB file No. 2015‑04‑103].
This work was supported by the National Research Foundation of Korea
(NRF) grant funded by the Korea government (MSIP) (2015R1A2A2A01002699).
Springer Nature remains neutral with regard to jurisdictional claims in pub‑
lished maps and institutional affiliations.
American Psychiatric Association , Task Force on D‑I. Diagnostic and statistical manual of mental disorders: DSM‑IV ‑ TR . Washington: American Psychiatric Association; 2000 .
Arvilommi P , Suominen K , Mantere O , Leppamaki S , Valtonen HM , Isometsa E. Maintenance treatment received by patients with bipolar I and II disorders-a naturalistic prospective study . J Affect Disord . 2010 ; 121 ( 1-2 ): 116 - 26 .
Backlund L , Ehnvall A , Hetta J , Isacsson G , Agren H . Identifying predictors for good lithium response-a retrospective analysis of 100 patients with bipolar disorder using a life‑ charting method . Eur Psychiatry . 2009 ; 24 ( 3 ): 171 - 7 .
Baek JH , Ha K , Yatham LN , Chang JS , Ha TH , Jeon HJ , et al. Pattern of pharmacotherapy by episode types for patients with bipolar disorders and its concordance with treatment guidelines . J Clin Psychopharmacol . 2014 ; 34 ( 5 ): 577 - 87 .
Baek JH , Kim JS , Kim MJ , Ryu S , Lee K , Ha K , et al. Lifetime characteristics of evening‑preference and irregular bed‑rise time are associated with lifetime seasonal variation of mood and behavior: comparison between individuals with bipolar disorder and healthy controls . Behav Sleep Med . 2016 ; 14 ( 2 ): 155 - 68 .
Baek JH , Park DY , Choi J , Kim JS , Choi JS , Ha K , et al. Differences between bipolar I and bipolar II disorders in clinical features, comorbidity, and family history . J Affect Disord . 2011 ; 131 ( 1-3 ): 59 - 67 .
Carvalho AF , McIntyre RS . Treatment‑resistant mood disorders . Oxford: OUP Oxford; 2015 . p. 97 - 110 .
Chen CH , Lee CS , Lee MT , Ouyang WC , Chen CC , Chong MY , et al. Variant GADL1 and response to lithium therapy in bipolar I disorder . N Engl J Med . 2014 ; 370 ( 2 ): 119 - 28 .
Colom F , Vieta E , Daban C , Pacchiarotti I , Sanchez‑Moreno J. Clinical and therapeutic implications of predominant polarity in bipolar disorder . J Affect Disord . 2006 ; 93 ( 1-3 ): 13 - 7 .
Coryell W , Akiskal H , Leon AC , Turvey C , Solomon D , Endicott J . Family history and symptom levels during treatment for bipolar I affective disorder . Biol Psychiat . 2000 ; 47 ( 12 ): 1034 - 42 .
Garnham J , Munro A , Slaney C , Macdougall M , Passmore M , Duffy A , et al. Prophylactic treatment response in bipolar disorder: results of a naturalistic observation study . J Affect Disord . 2007 ; 104 ( 1-3 ): 185 - 90 .
Ghaemi SN , Hsu DJ , Thase ME , Wisniewski SR , Nierenberg AA , Miyahara S , et al. Pharmacological treatment patterns at study entry for the first 500 STEPBD participants . Psychiatr Serv . 2006 ; 57 ( 5 ): 660 - 5 .
Goodwin GM . Evidence‑based guidelines for treating bipolar disorder: revised second edition-recommendations from the British Association for Psychopharmacology . J Psychopharmacol . 2009 ; 23 ( 4 ): 346 - 88 .
Grof P , Duffy A , Cavazzoni P , Grof E , Garnham J , MacDougall M , et al. Is response to prophylactic lithium a familial trait? J Clin Psychiatry . 2002 ; 63 ( 10 ): 942 - 7 .
Hou L , Heilbronner U , Degenhardt F , Adli M , Akiyama K , Akula N , et al. Genetic variants associated with response to lithium treatment in bipolar disorder: a genome‑ wide association study . Lancet . 2016 ; 387 ( 10023 ): 1085 - 93 .
Jeong JH , Lee JG , Kim MD , Sohn I , Shim SH , Wang HR , et al. Korean Medication Algorithm for Bipolar Disorder 2014 : comparisons with other treatment guidelines . Neuropsychiatr Dis Treat . 2015 ; 11 : 1561 - 71 .
Joo EJ , Joo YH , Hong JP , Hwang S , Maeng SJ , Han JH , et al. Korean version of the diagnostic interview for genetic studies: validity and reliability . Compr Psychiatry . 2004 ; 45 ( 3 ): 225 - 9 .
Kleindienst N , Engel R , Greil W. Which clinical factors predict response to prophylactic lithium? A systematic review for bipolar disorders . Bipolar Disord . 2005 ; 7 ( 5 ): 404 - 17 .
Kliwicki SM . Efficacy of long‑term lithium‑treatment in bipolar disorder . Phar ‑ macother Psychiatry Neurol . 2014 ; 30 ( 1 ): 5 - 13 .
Kusalic M , Engelsmann F. Predictors of lithium treatment responsiveness in bipolar patients. A 2‑ year prospective study . Neuropsychobiology . 1998 ; 37 ( 3 ): 146 - 9 .
Maj M , Arena F , Lovero N , Pirozzi R , Kemali D . Factors associated with response to lithium prophylaxis in DSM III major depression and bipolar disorder . Pharmacopsychiatry . 1985 ; 18 ( 5 ): 309 - 13 .
Manchia M , Adli M , Akula N , Ardau R , Aubry JM , Backlund L , et al. Assessment of response to lithium maintenance treatment in bipolar disorder: a Consortium on Lithium Genetics (ConLiGen) report . PLoS ONE . 2013 ; 8 ( 6 ): e65636 .
Matza LS , Revicki DA , Davidson JR , Stewart JW . Depression with atypical features in the National Comorbidity Survey: classification, description, and consequences . Arch Gen Psychiatry . 2003 ; 60 ( 8 ): 817 - 26 .
Mendlewicz J , Fieve RR , Stallone F . Relationship between the effectiveness of lithium therapy and family history . Am J Psychiatry . 1973 ; 130 ( 9 ): 1011 - 3 .
Misra PC , Burns BH . “ Lithium non‑responders” in a lithium clinic . Acta Psychiatr Scand . 1977 ; 55 ( 1 ): 32 - 40 .
Nolen WA , Luckenbaugh DA , Altshuler LL , Suppes T , McElroy SL , Frye MA , et al. Correlates of 1‑ year prospective outcome in bipolar disorder: results from the Stanley Foundation Bipolar Network . Am J Psychiatry . 2004 ; 161 ( 8 ): 1447 - 54 .
O'Connell RA , Mayo JA , Flatow L , Cuthbertson B , O'Brien BE . Outcome of bipolar disorder on long‑term treatment with lithium . Br J Psychiatry . 1991 ; 159 : 123 - 9 .
Passmore MJ , Garnham J , Duffy A , MacDougall M , Munro A , Slaney C , et al. Phenotypic spectra of bipolar disorder in responders to lithium versus lamotrigine . Bipolar Disord . 2003 ; 5 ( 2 ): 110 - 4 .
Peselow ED , Clevenger S , IsHak WW . Prophylactic efficacy of lithium, valproic acid, and carbamazepine in the maintenance phase of bipolar disorder: a naturalistic study . Int Clin Psychopharmacol . 2015 .
Pfennig A , Schlattmann P , Alda M , Grof P , Glenn T , Muller‑ Oerlinghausen B , et al. Influence of atypical features on the quality of prophylactic effectiveness of long‑term lithium treatment in bipolar disorders . Bipolar Disord . 2010 ; 12 ( 4 ): 390 - 6 .
Post RM , Altshuler LL , Frye MA , Suppes T , Keck PE Jr, McElroy SL , et al. Complexity of pharmacologic treatment required for sustained improvement in outpatients with bipolar disorder . J Clin Psychiatry . 2010 ; 71 ( 9 ): 1176 - 86 quiz 252 -3.
Rybakowski JK . Response to lithium in bipolar disorder: clinical and genetic findings . ACS Chem Neurosci . 2014 ; 5 ( 6 ): 413 - 21 .
Rybakowski JK , Dembinska D , Kliwicki S , Akiskal KK , Akiskal HH . TEMPS‑A and long‑term lithium response: positive correlation with hyperthymic temperament . J Affect Disord . 2013 ; 145 ( 2 ): 187 - 9 .
Sadock BJ , Sadock VA , Ruiz P. Kaplan and Sadock's synopsis of psychiatry: behavioral sciences/clinical psychiatry . Philadelphia: Wolters Kluwer Health; 2014 .
Shin YC , Min KJ , Yoon BH , Kim W , Jon DI , Seo JS , et al. Korean medication algorithm for bipolar disorder: second revision . Asia Pac Psychiatry . 2013 ; 5 ( 4 ): 301 - 8 .
Silva LF , Loureiro JC , Franco SCR , Santos MdL , Secolin R , Lopes‑ Cendes I , et al. Assessing treatment response to prophylactic lithium use in patients with bipolar disorder . Jornal Brasileiro de Psiquiatria. 2016 ; 65 : 9 - 16 .
Spearing MK , Post RM , Leverich GS , Brandt D , Nolen W. Modification of the Clinical Global Impressions (CGI) Scale for use in bipolar illness (BP): the CGI‑BP . Psychiatry Res . 1997 ; 73 ( 3 ): 159 - 71 .
Squassina A , Manchia M , Borg J , Congiu D , Costa M , Georgitsi M , et al. Evidence for association of an ACCN1 gene variant with response to lithium treatment in Sardinian patients with bipolar disorder . Pharmacogenomics . 2011 ; 12 ( 11 ): 1559 - 69 .
Yang SY , Huh IS , Baek JH , Cho EY , Choi MJ , Ryu S , et al. Association between ST8SIA2 and the risk of schizophrenia and bipolar I disorder across diagnostic boundaries . PLoS ONE . 2015 ; 10 ( 9 ): e0139413 .
Yatham LN , Kennedy SH , Parikh SV , Schaffer A , Beaulieu S , Alda M , et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) collaborative update of CANMAT guidelines for the management of patients with bipolar disorder: update 2013 . Bipolar Disord . 2013 ; 15 ( 1 ): 1 - 44 .
Young LT , Cooke RG , Robb JC , Levitt AJ , Joffe RT . Anxious and non‑anxious bipolar disorder . J Affect Disord . 1993 ; 29 ( 1 ): 49 - 52 .