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Journal of Affective Disorders 259 (2019) 164–172
Contents lists available at ScienceDirect
Journal of Affective Disorders
journal homepage: www.elsevier.com/locate/jad
Research paper
Bipolar depression and suicidal ideation: Moderators and mediators of a
complex relationship
T
Masoud Kamalia,b,c, , Noreen A. Reilly-Harringtona,b, Weilynn C. Changa, Melvin McInnisc, Susan L.
McElroyd, Terence A. Kettere, Richard C. Sheltonf, Thilo Deckersbacha,b, Mauricio Toheng, James H.
Kocsish, Joseph R. Calabresei, Keming Gaoi, Michael E. Thasej, Charles L. Bowdenk, Gustavo Kinrysa,b,
William V. Bobol, Benjamin D. Brodyh, Louisa G. Sylviaa,b, Dustin J. Rabideaum, Andrew A.
Nierenberga,b
a
Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
b
Harvard Medical School, Boston, MA, United States
Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
c
d
Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati OH and Lindner Center of HOPE, Mason, OH, United
States
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
e
f
Department of Psychiatry, University of Alabama at Birmingham, Birmingham, AL, United States
Department of Psychiatry, University of New Mexico Health Science Center, Albuquerque, NM, United States
Department of Psychiatry, Weill Cornell Medical College, New York, NY, United States
i
Department of Psychiatry, Case Western Reserve University, Cleveland, OH, United States
j
Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
k
Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States
l
Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
g
h
m
Department of Biostatistics, Massachusetts General Hospital, Boston, MA, United States
ARTICLE INFO
ABSTRACT
Keywords:
Bipolar disorder
Depression
Suicidal ideation
Lithium
Quetiapine
Introduction: Not all patients with bipolar depression have suicidal ideation (SI). This study examines some factors that link
bipolar depression to SI.
Methods: 482 individuals with bipolar I or II were randomized to either lithium or quetiapine plus adjunctive personalized
therapy in a 24 week comparative effectiveness trial. Severity of depression and SI were assessed with the Bipolar Inventory
of Symptoms Scale (BISS). We examined potential moderators (age, gender, age of illness onset, bipolar type, comorbid
anxiety, substance use, past suicide attempts, childhood abuse and treat-ment arm) and mediators (severity of anxiety, mania,
irritability, impairment in functioning (LIFE-RIFT) and satisfaction and enjoyment of life (Q-LES-Q)) of the effect of
depression on SI. Statistical analyses were con-ducted using generalized estimating equations with repeated measures.
Results: Bipolar type and past suicide attempts moderated the effect of depression on SI. Life satisfaction mediated the effect
of depression and SI. The relationship between anxiety, depression and SI was complex due to the high level of correlation.
Treatment with lithium or quetiapine did not moderate the effect of depression on SI.
Limitations: Suicide assessment was only done using an item on BISS. Patient population was not specifically chosen for high
suicide risk.
Discussion: Individuals with Bipolar II experienced more SI with lower levels of depression severity. A history of suicide
predisposed patients to higher levels of SI given the same severity of depression. Reduced life satisfaction mediates the effect
of depression on SI and may be a target for therapeutic interventions.
This work was supported by the Agency for Healthcare Research and Quality (AHRQ: 1R01HS019371) and the Dauten Family Center for Bipolar Treatment Innovation.
Corresponding author at: Dauten Family Center for Bipolar Treatment Innovation, Massachusetts General Hospital, 50 Staniford Street, Suite 580, Boston, MA 02114, United States.
E-mail address: [email protected] (M. Kamali).
https://doi.org/10.1016/j.jad.2019.08.032
Received 5 August 2018; Received in revised form 27 July 2019; Accepted 17 August 2019
Available online 19 August 2019
0165-0327/ © 2019 Published by Elsevier B.V.
Journal of Affective Disorders 259 (2019) 164–172
M. Kamali, et al.
1. Introduction
concurrent symptoms and stressors would account for a significant portion of
the association between SI and depression.
Bipolar disorder has high rates of suicidal ideation, suicide attempts and
deaths from suicide (López et al., 2001; Slama et al., 2004; Tondo et al.,
2003; Valtonen et al., 2005). In clinical studies of bipolar dis-order, 20 to
30% of the participants report suicidal ideation at time of study entry
(Goldberg et al., 2005; Suppes et al., 2001). Depressive episodes are common
in bipolar disorder, and suicidal ideation (SI) is closely related to depression
and one of the diagnostic criteria for a major depressive episode. However,
not all patients who are depressed experience suicidal ideation.
2. Methods
The Bipolar CHOICE study (Comparative Effectiveness of a SecondGeneration Antipsychotic Mood Stabilizer and a Classic Mood Stabilizer for
Bipolar Disorder) is a 24 week, multi-site, randomized pragmatic clinical trial
comparing lithium to quetiapine. Study rationale, design, methods, and results
have been reported elsewhere (Nierenberg et al., 2016, 2014). Briefly, the
study enrolled 482 in-dividuals aged 18–70 years, between 2011 and 2012
across 11 sites (Nierenberg et al., 2016). Participants were required to have a
DSM-IV-TR diagnosis of bipolar I or II disorder (determined using an
electronic version of the Extended Mini-International Neuropsychiatric
Interview [MINI]) (Sheehan et al., 1998) and to be at least mildly
symptomatic (defined as a Clinical Global Impression Severity Scale for
Bipolar Disorder [CGI-S-BP] ≥3) (Spearing et al., 1997). Demographic data
such as age of onset of bipolar disorder, history of suicide attempts and
history of childhood abuse were collected at baseline. Participants were
randomized to lithium or quetiapine plus adjunctive personalized therapy
(APT). This included any additional medications needed for management of
symptoms, consistent with guidelines used to treat bi-polar disorder and
personalized to the clinical needs of the patient (Suppes et al., 2005). There
were few restrictions on treatment options per study protocol other than the
lithium arm could not receive anti-psychotics and the quetiapine arm could
not receive lithium or other antipsychotics. All other clinically appropriate
medication choices for bipolar disorder, including other mood stabilizers such
as Valproic acid, Carbamazepine or benzodiazepines were allowed.
Clinical variables such as age (Ösby et al., 2001), gender (Baldassano,
2005), age of onset of illness (Slama et al., 2004), type of bipolar disorder (I
vs. II) (Coryell et al., 1987; Novick et al., 2010; Tondo et al., 2007), history of
childhood abuse (Garno et al., 2005), comorbid substance abuse disorders
(Tondo et al., 1999), anxiety (Simon et al., 2007), mixed mood states (Balázs
et al., 2006), poorer quality of life (Chen et al., 2011; de Abreu et al., 2012),
and functional impairment (Sanchez-Moreno et al., 2009) have been reported
as fac-tors increasing the risk of suicidal behavior. Certain variables such as
gender or type of bipolar disorder may have differential effects on how
depressed mood leads to SI. Likewise, co-occurring symptoms of irrit-ability
or anxiety may mediate the effects of depression on SI. Also, an important
clinical question is if lithium, compared to quetiapine, has an independent
effect on suicidal ideation, above and beyond its effects on mood. Prior
research has suggested that lithium has independent effects on reducing
suicide that are distinct from its effectiveness as a treat-ment for mood
disorders (Ahrens and Müller-Oerlinghausen, 2001; Baldessarini et al., 2006;
Cipriani et al., 2005; Müller-Oerlinghausen et al., 1992).
Understanding how the above clinical factors moderate and mediate the
effect of depression on the development of suicidal ideation is of clinical
importance and can assist in identifying individuals at elevated risk for
suicide and target interventions towards reducing this risk.
The current study includes a group of individuals with bipolar dis-order
types I and II, enrolled in a comparative effectiveness treatment trial of
lithium vs. quetiapine plus adjunctive personalized therapy (Nierenberg et al.,
2014). We examined the relationship between se-verity of depression and SI
measured concurrently, over the 24-week period of the study.
The MINI was also used to assess current and lifetime comorbid
psychiatric disorders (e.g., anxiety disorders and substance use dis-orders).
Exclusion criteria were limited to maximize generalizability, but included a
history of nonresponse or intolerable side effects with lithium or quetiapine,
and active substance dependence within the past 30 days (a history of
substance abuse was not an exclusion criteria). The Institutional Review
Boards of the 11 study sites approved the study protocol. All participants
provided written informed consent.
Mood symptom severity and suicidality were assessed with the Bipolar
Inventory of Symptoms Scale (BISS) at baseline and all sub-sequent
scheduled study visits (weeks 2, 4, 6, 8, 12, 16, 20 and 24-end of study)
(Bowden et al., 2007; Gonzalez et al., 2008). The BISS is a 45-item clinician
rated questionnaire with subscales for depression, mania, irritability, anxiety,
and psychosis. The BISS questionnaire, item 4 asks about suicidal tendencies,
including preoccupation with thoughts of death or suicide. This score was
used in our analysis as a marker of severity of suicidal ideation. In our
calculation of BISS-depression score, the suicidality item was not included to
avoid redundancy. The suicide severity score is from 0 (none at all) and 1
(Slight; e. g. Occasional thoughts of death (without suicidal thoughts), “I
would be better off dead” or “I wish I were dead” with 4 (Severe: e.g. often
thinks of suicide and has thought of a specific plan or has made a suicidal
gesture or attempt) being the highest score. This is different from the PHQ-9
questionnaire that has a single question, “Thoughts that you would be better
off dead or of hurting yourself in some way” and four options for severity (Not
at all, Several days, More than half the days, and Nearly every day).
According to the PHQ-9 the individual can have no actual suicidal intention
and score higher than an individual who has actual suicidal ideation, just not
every day. In the BISS, higher scores indicate more severe suicidal ideation.
Our study had two goals. First, we wanted to understand the dif-ferences
between patients with bipolar disorder who did and who did not experience SI
while depressed. Second, we wanted to understand how the relationship
between depression and SI changed during the course of the comparative
effectiveness trial.
In our first analysis, we examined whether baseline clinical vari-ables
including age, gender, age of illness onset, bipolar subtype (I vs. II), lifetime
comorbid anxiety or substance use disorders, prior suicide attempts, history of
childhood abuse and assignment to treatment with lithium vs. quetiapine
affected the direction or strength of the re-lationship between depression
severity and suicidal ideation during the course of the study (a moderator
effect (Baron, 1986)). Although prior research has identified most of the above
named variables as predictors of suicide risk, our moderator analysis
examined the significance of these effects when both the direct effect of
depressed mood and the interaction of depression and the moderator on SI are
taken into con-sideration.
In the second analysis, a mediator analysis (Baron, 1986), we ex-plored if
symptoms of mania and irritability (which are associated with mixed
episodes), anxiety and measures of quality of life and impairment in
functioning (all of which have been found to be associated with SI), when
collected at the same time as measures of depression severity and SI, could
account for some of the relationship between depression and SI. Although we
did not expect full mediation (i.e. the relationship between depression and
suicide being completely explained by one of our mediator variables), we
predicted that for some individuals, these
We were not able to identify previous research that has examined the
BISS suicide question as we have. However, multiple other studies have used
item 9 from the PHQ-9 as a measure for suicide risk. (Bauer et al., 2013;
Simon et al., 2016, 2013). The use of the PHQ-9 item 9 has been criticized
(Na et al., 2018) with the PHQ-9 generating more false positive rates than the
C-SSRS (Viguera et al., 2015). There are also
165
Journal of Affective Disorders 259 (2019) 164–172
M. Kamali, et al.
concerns about using a single item from a questionnaire. This is a limitation
of our analysis and any interpretation of our results should take this limitation
into consideration.
Functional impairment was measured with the LIFE-Range of Impaired
Functioning Tool (LIFE-RIFT), a semi-structured interview that measures
impairment in four domains: work, interpersonal re-lationships, satisfaction
and recreation (Leon et al., 2000). Scores of individual subscales range from
1–5, with higher scores indicating more impairment. Life satisfaction was
assessed with the self-reported Quality-of-Life Enjoyment and Satisfaction
Questionnaire (Q-LES-Q) (Endicott et al., 1993). This questionnaire measures
level of satisfaction in ten areas (physical health, subjective feelings of wellbeing, work, household duties, school/course work, leisure time activities,
social relationships, general activities, satisfaction with medications and
overall life satisfaction). Higher scores indicate more satisfaction in that area.
The Data for these questionnaires were collected at baseline, and weeks 12
and 24.
0.001). After adding each moderator to the model the coefficient for
depression remained significant (0.022 – 0.031, all p values < 0.001);
moderators with a significant interaction with depression were bipolar type
(−0.005, p = 0.03) and history of suicide attempts (0.008, p = 0.002).
To examine the mediator effects of our variables of interest, we evaluated
several other associations represented in Fig. 1. Depression was significantly
associated with each of the potential mediators (a 1 in Table 3, also Fig. 1model 1) and each of the potential mediators was significantly associated with
suicidal ideation (b1 in Table 3, also Fig. 1-model 2). The direct and mediated
effect of depression scores, illu-strated in Fig. 1- models 3 and 4, are given in
Table 4 (c1 and g1). In a full mediation relationship, g1 would be zero. This
would indicate that all the effect of depression on suicidal ideation was
through the med-iator of interest; however, we did not expect full mediation.
Rather we predicted that the magnitude of c1 would be reduced when the
med-iator was present in the model. Although we cannot calculate α, the
coefficient a1 is an approximation and was highly significant for all variables
(Table 3). Given these criteria, this analysis showed that BISS-anxiety score,
LIFE-RIFT total and satisfaction sub-scores, and the Q-LES-Q subscales,
other than Physical, School and Medications, were significant mediators of
the effect of depression on suicidal ideation. Although the relative coefficient
changes ( %) for Satisfaction with Medications and School/Course work were
significant, these variables were not significantly associated with SI in the
model (as shown by g2) and as such cannot be considered mediators. Mania
or irritability scores were not significant mediators.
2.1. Statistical analyses
Analyses were conducted using generalized estimating equations (GEEs)
with repeated measures utilizing SAS 9.3 statistical software (SAS Institute,
Inc., 2011). We analyzed the BISS item score as a con-tinuous variable (even
though it is an ordinal variable), without any assumptions of normal
distribution and used a GEE model with an identity link (using the robust
standard errors for p-values, CIs). To calculate the moderating effects of the
variables of interest, we fit linear GEE models using suicidality scores as the
dependent variable and depression severity score, each of the possible
moderators, and the depression-by-moderator interaction term as independent
variables. If the interaction term is significant, it indicates that the additional
variable does, indeed, increase or decrease (moderate) the association
between suicidality and depression. To determine whether concurrent
symptoms or stressors account for (mediate) some or all of the observed effect
of depression on suicidality, we fit the linear GEE models re-presented in Fig.
1. To assess mediation, we computed the percent change that occurred in the
depression coefficient when introducing the mediator into the model (i.e.
change between c1 and g1 in models 3 and 4 in Fig. 1). We computed the
4. Discussion
Our study has several important and clinically significant findings.
Lithium or quetiapine did not have different moderating effects on suicidal
ideation. Prior research has suggested that lithium reduces completed and
attempted suicide. These include several meta-analyses of lithium studies
(Baldessarini et al., 2006; Cipriani et al., 2005), which include studies with
both bipolar and major depressive disorder participants. Some compare
lithium to placebo or an anti-depressant or mood stabilizing agent and the
outcomes of interest were completed or attempted suicide. By contrast, our
study was limited to 24 weeks, fo-cused on suicidal ideation and included
only bipolar participants who were not selected based on high suicide risk. It
also included an active comparator with proven effectiveness in bipolar
disorder, and allowed for adjunctive therapies. It is possible and has been
suggested that li-thium's anti-suicidal properties are due to effects on
impulsive and aggressive behavior (Müller-Oerlinghausen et al., 1992) and as
such it should affect attempts more than ideation. An alternative explanation
for the discrepancy in our finding is that the effects on suicide are primarily
through better control of mood, and effective reduction in depression severity
is the main reason for reduction in suicidal risk. In our sample with two
effective treatment options, no difference in SI was detected.
relative change in coefficient c1 as (g1-c1)/c1 and computed its significance
using a bootstrap method. A two-tailed significance threshold of P < 0.05 was
used with no correction for multiple comparisons. For this analysis, we chose
a cross sectional model of mediation rather than a time lagged analysis. Cross
sectional examination of mediation can generate significantly biased estimates
of longitudinal mediation parameters (Maxwell and Cole, 2007). However
with time lag designs, estimates of effects in longitudinal models can change
greatly depending on the chosen time interval (Cole and Maxwell, 2003). The
appropriate time lag to measure a change in de-pression leading to a change in
the variable of interest and then SI is not known. We have thus chosen
concurrent measurements of depression, the mediators, and SI given the close
temporal relationship between mood and anxiety symptoms, quality of life
and impairment measures and SI. However, this is a limitation in our study
and the chosen ana-lysis model and our findings should be interpreted with
caution given this limitation.
Among the other moderators examined, only bipolar type and past suicide
attempts were significant. Age, gender, age of illness onset, comorbid anxiety,
comorbid substance use and childhood abuse were neither individually
predictive of suicide when depression severity was included in the model, nor
did they moderate the effects of depression. This emphasizes the importance
of depression severity in the develop-ment of suicidal ideation in patients with
bipolar disorder (Umamaheswari et al., 2014). Past suicide attempt did not independently predict current suicidal ideation above and beyond the effects of
depression. However, a history of suicide moderated the effect of depression
on suicidal ideation, meaning those with past suicide attempts were prone to
having higher SI with similar levels of depres-sion compared to those without
past suicide attempts. We also found that bipolar I and II individuals show
different levels of SI depending on the severity of depression. The interaction
effect for bipolar type
3. Results
482 participants with bipolar I or II were randomized to either li-thium
with APT or quetiapine with APT. The mean (SD) on the BISS suicidality
item for the lithium and quetiapine groups were 0.7 (0.98) and 0.7 (1.02)
respectively. The mean (SD) number of visits per parti-cipant was 7.51 (2.38).
Demographics of participants are summarized in Table 1.
The results of the moderator analysis are summarized in Table 2. The unmoderated coefficient for depression on SI was 0.023 (p <
166
M. Kamali, et al.
Journal of Affective Disorders 259 (2019) 164–172
Fig. 1. Description of models in the mediator analysis. D=Depression, M=Mediator, SI=Suicidal Ideation.
indicates that with less severe depression (BISS depression scores less than
25), individuals with bipolar II have more severe suicidal ideation (compared
to bipolar I individuals) while if the scores of BISS depres-sion increase over
25, individuals with bipolar I report more severe suicidal ideation. Some
studies comparing suicidal risk in bipolar I and
II have not shown significant differences in suicide attempts or risk between
the two groups (Novick et al., 2010; Valtonen et al., 2005), while others show
increased risk with bipolar I (Bobo et al., 2018). Our findings are suggestive
that bipolar I and II individuals may have dif-ferent risks for developing SI.
This variability in risk may be due to difference in comorbidities, severity of
illness or study population, but our study is not fully able to explain the
reason for this observation. Further research into the differences in suicide risk
between bipolar I and II are warranted.
2001). Our study not only shows that life satisfaction affects SI, but also
suggests that some of the effect of depression on SI is mediated through life
satisfaction. Depression leads to lower life satisfaction, which itself leads to
more SI.
Co-occurring mania, irritability and anxiety symptoms showed ef-fects
that were in contrast to our initial predictions. Mania and irrit-ability, which
are prominent features of mixed states were not in-dependently predictive of
SI, even though in bivariate models, they were strongly predictive of SI
(Table 3). Similar to reports by Fiedorowicz et al. (2019) in our sample the
higher levels of SI seen in mixed states are better explained by the presence of
more severe de-pression in these individuals. In bivariate models, anxiety had
a positive correlation with SI (Table 3) but in the mediated model, the
direction of the association reversed and anxiety had a negative correlation
with SI and the mediated coefficient for depression actually increased (from
0.0236 to 0.0374, a statistically significant change; p = 0.00136). This may
indicate that the mediating relationship is in the opposite direc-tion, with
depression mediating the effect of anxiety on SI (Thompson et al., 2005). In
the STEP-BD study, although anxiety was found to be closely related to SI,
the relationship was no longer sig-nificant when adjusted for current recovery
status (Simon et al., 2007). Similar findings were reported in the Jorvi Bipolar
Study (Valtonen et al., 2005) where depression and hopelessness were the
strongest predictors of SI in multivariate models, even though multiple other
variables such as anxiety were predictive in bivariate analyses. In our study
population, depression and anxiety scores were highly cor-related (Pearson
correlation coefficient of 0.52, p < 0.0001), and it may be impossible to
separate the effects of the two so this finding should be interpreted with
caution.
Satisfaction with life emerges as an important mediator of the effect of
depression on suicidal ideation. Among the sub-scores of the LIFE-RIFT,
only life satisfaction is a statistically significant mediator. The total score is
also significant, but it appears that the main effect is through the Satisfaction
sub-score. Impairment in work (which includes impairment in employment,
school or household duties), impairment in relationships (which includes
relationship with spouse, children, other relations and friends) or ability to
enjoy recreational activities do not show an independent effect on SI above
and beyond the effects of de-pression. On the other hand, the life satisfaction
sub-score on the LIFE-RIFT and most subscales on the Q-LES-Q which
measure satisfaction and the ability to enjoy different areas of daily life show
a mediating effect on SI. The non-significant scores on the Q-LES-Q include
the Physical Health, School and Medication Satisfaction sub-scores.
Other studies have shown that lower life satisfaction is associated with
higher rates of depression (Heli Koivumaa-Honkanen MD et al., 2004),
suicidal ideation (Heisel and Flett, 2004), suicide attempts (Claassen et al.,
2007; Ponizovsky et al., 2003; Valois et al., 2004) and completed suicide
(Fujino et al., 2005; Koivumaa-Honkanen et al.,
5. Limitations
Our study has several limitations. The study was limited to bipolar I
167
0.8
−−0.0005[0.006,0.005]
0.1
−0.[0.001,0.009]003
0020.
0.[0.003,0.01]008
−0030.[0.002,0.009]
0.1
−0.[0.001,0.004]001
30.
30.
0.9
030.
50.
0.1
0.1
0.5
−020.[0.06, 0.1]
− −0.07[0.1, 0.03]
− −0.06[0.1, 0.02]
−0.[0.04,0.06]03
<0.001
<0.001
<0.001
<0.001
P value
<0.001
<0.001
− −0.003[0.007, 0.000]
−0080.[0.08, 0.1]
a
Moderator as predictor of SI
P value
168
ffiCoecient [95% CI].
a
Interaction between moderatorand b
depression as predictor of SI.
.02 [.02, 0.03]
241 (50.2%)
257 (53.3%)Lithium240(49.8%)
Quetiapine
Yes
Treatmentgroup
.02 [.02, 0.02]
173 (36.1%)No224(46.5%)
Yes
PastHistoryofChildhoodAbuse
.02 [.02, 0.02]
300 (62.2%)No306(63.9%)
Yes
PastHistoryofSuicideAttempt
.02 [.01, 0.02]
277 (57.4%)No182(37.8%)
Yes
Lif e ti m e Co m o r b id S u b s tan ce U s e D is o r d er
.02 [.02, 0.02]
205 (42.5%)
Type IINo
Lif etimeComor bidAnxietyDisorder
.02 [.01, 0.03]
.03 [.02, 0.03]
283 (58.7%)15.(±7.78)68
329 (68.2%)
Female
I
BipolarType Type
Ageofillnessonset
.02 [.01, 0.03]
.02 [.02, 0.03]
Table2ff Mo d er ator s of th eeecto f d epr es s ion o n
suicidal ideation.
and II patients treated in an outpatient setting and as such, our fi ndings cannot
be generalized to other diagnoses or other treatment settings. Our sample was
not selected as a high suicide risk sample, and the measure of suicidal
ideation was a single item from the BISS. The BISS suicide question has not
been previously validated for use as a single item and we were unable to find
another study that has used this item the way we have. Also, our follow up
period was 24 weeks and any differences in anti-suicidal effects of lithium and
quetiapine may not be noticeable in this time frame. Although our sample size
was relatively large, it may not have been large enough to detect smaller
effects and the negative findings may not represent a true lack of significance.
However, findings with small effects may not have much clinical significance. Our findings related to anxiety are of interest and in conflict with
our initial hypothesis. Due to the high correlation between de-pression and
anxiety scores in our sample, our ability to examine the effects of each
variable independently is limited. Our mediation ana-lysis was done on cross
sectional data, which can generate significantly biased estimates of
longitudinal mediation parameters. We chose a cross sectional model given
the high variability of suicidal ideation reported in previous research
(Kleiman et al., 2017). We recognize that our model for analysis is not the
only possible explanation for the convergence of symptoms that occur in
bipolar patients. Without un-derstanding the biology of these conditions, any
assumptions of caus-ality in our mediation model are speculative. Our
mediation models make assumptions regarding causality and directionality
that are based on strong cross sectional correlations between symptoms. An
alter-native explanation for this convergence of symptoms is that all variables are caused by a common factor, which is not included in this model.
Our analysis did not find evidence of mediation in our data, other than for life
satisfaction. Interpretation of our finding should
Age 8838. ( ± 12.1)
Gender Male
199 (41.3%)
Abbreviations: BISS (Bipolar Inventory of Symptoms Scale), LIFE-RIFT (Longitudinal
Interval Follow-up Evaluation-Range Impaired Functioning Tool), Q-LES-Q (Qualityof-Life Enjoyment and Satisfaction Questionnaire).
Depression as predictor of SI
a
476
481
481
476
481
Variabl
e
N (%), Or Mean ( ± SD)
14.2 ± 3.3
3.4 ± 0.9
3.4 ± 1.1
3.6 ± 1.3
3.7 ± 1.2
0.1
239
449
67
478
475
478
474
475
− −0.03[0.07, 0.01]
± 21.5
± 21.9
± 22.9
± 22.0
± 19.0
± 17.7
± 40.4
± 24.5
52.1
47.8
45.3
46.0
44.6
44.2
84.0
41.5
482
482
482
482
482
482
<0.001
479
478
−−−0.005[0.0.000]01,
41.5 ± 18.6
45.6 ± 17.8
Age
Age of First Episode
BISS Depression
BISS Mania
BISS Anxiety
BISS Irritability
Q-LES-Q
Physical Health
Subjective Feelings of WellBeing
Work
Household Duties
School/Course Work
Leisure Time Activities
Social Relationships
General Activities
Satisfaction with meds
Overall Life Satisfaction
LIFE-RIFT
Total
Satisfaction
Recreation
Work
Relationships
−−0.0000[0.000,0.000]
479
482
0.2
0030.
173 (36.1%)
257 (53.3%)
M±SD
38.8 ± 12.1
15.6 ± 7.7
17.5 ± 7.3
9.1 ± 6.3
15.9 ± 8.5
16.7 ± 8.5
− −0.003[0.009, 0.003]
0. [0.04, 0.2]1
482
482
482
482
<0.001
<0.001
283 (58.7%)
329 (68.2%)
277 (57.4%)
300 (62.2%)
−−0.002[0.008,0.003]
Female Gender
Bipolar Type I
Lifetime Comorbid Anxiety Disorder
Lifetime Comorbid Substance Use
Disorder
Past History of Suicide Attempt
Past History of Childhood Abuse
−00010.[0.000,0.000]
Total Observations in
Category
050.
80.
N (%)
a
,
b
Variable
ffModeratingeect P value
Table 1
Baseline demographic and clinical characteristics of participants.
20.
Journal of Affective Disorders 259 (2019) 164–172
M. Kamali, et al.
M. Kamali, et al.
Journal of Affective Disorders 259 (2019) 164–172
Table 3
Associations between potential mediators, suicidal ideation and depression.
Variable
BISS
Mania
Anxiety
Irritability
LIFE-RIFT
Total
Satisfaction
Recreation
Work
Relationships
Q-LES-Q
Physical Health
Subjective Feelings of Well-Being
work
Household Duties
School/Course Work
Leisure Time Activities
Social Relationships
General Activities
Satisfaction with meds
Overall Life Satisfaction
Direct association of mediators with depression (a1)
Association of mediators with suicidal ideation, independent of depression status (b1)
Coefficient
Standard error
P value
Coefficient
Standard error
P value
0.06
0.42
0.34
0.007
0.007
0.010
<0.001
<0.001
<0.001
0.01
0.02
0.02
0.003
0.002
0.002
<0.001
<0.001
<0.001
0.17
0.04
0.05
0.04
0.03
0.005
0.001
0.002
0.002
0.002
<0.001
<0.001
<0.001
<0.001
<0.001
0.07
0.29
0.15
0.14
0.10
0.006
0.02
0.02
0.01
0.02
<0.001
<0.001
<0.001
<0.001
<0.001
−0.76
−0.84
−0.71
−0.63
−0.87
−0.82
−0.86
−0.88
−0.53
−1.13
0.03
0.02
0.05
0.04
0.10
0.04
0.03
0.03
0.07
0.04
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
−0.01
−0.01
−0.009
−0.009
−0.005
−0.01
−0.01
−0.01
−0.002
−0.01
0.001
0.001
0.001
0.001
0.002
0.001
0.001
0.001
0.0009
0.001
<0.001
<0.001
<0.001
<0.001
0.01
<0.001
<0.001
<0.001
0.009
<0.001
Abbreviations: BISS (Bipolar Inventory of Symptoms Scale), LIFE-RIFT (Longitudinal Interval Follow-up Evaluation-Range Impaired Functioning Tool), Q-LES-Q (Quality-of-Life
Enjoyment and Satisfaction Questionnaire).
Table 4
Mediators of the effect of depression on suicidal ideation.
Variable
BISS
Mania
Anxiety
Irritability
LIFE-RIFT
Total
Satisfaction
Recreation
Work
Relationships
Q-LES-Q
Physical Health
Subjective Feelings of Well-Being
work
Household Duties
School/Course Work
Leisure Time Activities
Social Relationships
General Activities
Satisfaction with meds
Overall Life Satisfaction
c1
P value
g1
P value
g2
P value
%
0.02
0.02
0.02
<0.001
<0.001
<0.001
0.02
0.02
0.02
<0.001
<0.001
<0.001
0.002
−0.008
0.002
0.5
0.002
0.1
0.02
0.02
0.02
0.02
0.02
<0.001
<0.001
<0.001
<0.001
<0.001
0.01
0.01
0.02
0.02
0.02
<0.001
<0.001
<0.001
<0.001
<0.001
0.02
0.14
0.01
0.02
0.01
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
0.02
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.02
0.01
<0.001
<0.001
<0.001
<0.001
0.002
<0.001
<0.001
<0.001
<0.001
<0.001
0
−0.007
−0.004
−0.003
−0.001
−0.004
−0.003
−0.007
−0.0008
−0.006
95% Confidence Interval
P value
−0.8
16.1
−04.2
[−2.0, 0.3]
[10.7, 21.4]
[−7.4, −1.0]
0.2
0.001
0.09
0.01
<0.001
0.5
0.1
0.6
−17.3
−29.6
−3.8
−5.5
−2.1
[−25.2, −9.5]
[−36.4, −22.8]
[−9.1, 1.5]
[−9.6, −1.4]
[−5.5, 1.3]
0.01
<0.001
0.2
0.08
0.2
0.9
<0.001
0.01
0.003
0.6
0.005
0.007
<0.001
0.3
<0.001
−1.6
−30.0
−38.1
−11.4
−74.8
−21.0
−16.5
−30.9
−3.8
−30.9
[−6.9, 3.5]
[−36.9, −23.2]
[−48.0, −28.2]
[−15.9, −6.9]
[−96.3, −53.2]
[−25.8, −16.2]
[−22.3, −10.7]
[−38.4, −23.3]
[−5.4, −2.1]
[−38.5, −23.3]
0.3
<0.001
<0.001
0.005
<0.001
<0.001
0.002
<0.001
0.009
<0.001
Abbreviations: BISS (Bipolar Inventory of Symptoms Scale), LIFE-RIFT (Longitudinal Interval Follow-up Evaluation-Range Impaired Functioning Tool), Q-LES-Q (Quality-of-Life
Enjoyment and Satisfaction Questionnaire).
c1: Unmediated coefficient for depression estimating suicidal ideation.
g1: Mediated coefficient for depression estimating suicidal ideation.
g2: Coefficient for mediator estimating suicidal ideation.
%: Percent change in depression coefficient with addition of mediator to the model.
consider these limitations.
In our study, we chose to analyze the BISS item score as a con-tinuous
variable (even though it is an ordinal variable) and used a GEE model with an
identity link (using the robust standard errors for p-values, CIs). GEEs are
semi-parametric and do not make distributional assumptions on the outcome
(only a parametric form for the mean of the outcome), so we do not assume
the outcomes are normally dis-tributed. There has been criticism regarding the
use of parametric tests on Likert scales (Jamieson, 2004). Treating an ordinal
variable as a continuous variable could lead to predicted values outside the
range of
the actual ordinal score and imposes the assumption that each sub-sequent
category is equally distant numerically. For example, the average severity of
SI in this sample was 0.7, which is not a valid score on the BISS. However,
parametric tests are very robust with respect to violations of assumptions and
can be used with Likert scales (Norman, 2010; Sullivan and Artino, 2013) and
though we may not be able to interpret the means, the statistical inference we
make on the coeffi-cients (the betas), is still valid.
Also our choice of moderators and mediators is clearly not ex-haustive.
For example we did not examine the effects of rapid cycling or
169
Journal of Affective Disorders 259 (2019) 164–172
M. Kamali, et al.
sleep. Previous research has shown that sleep disturbances are asso-ciated
with high-lethality suicide attempts across a diverse group of psychiatric
patients (Pompili et al., 2013).
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Author statement
Contributors: Drs. Kamali, Reilly-Harrington, McInnis, McElroy, Ketter,
Shelton, Deckersbach, Tohen, Kocsis, Calabrese, Gao, Thase, Bowden,
Kinrys, Bobo, Brody, Sylvia and Nierenberg were investigators in the
CHOICE study and recruited, assessed and treated the original sample. Dr.
Kamali suggested this analysis and wrote the final version of the manuscript.
Mr. Rabideau completed the statistical analysis. Ms. Chang assisted in
literature search and writing the manuscript. All Authors have approved the
final article.
Role of the funding source
Fujino, Y., Mizoue, T., Tokui, N., Yoshimura, T., 2005. Prospective cohort study of stress, life
satisfaction, self‐rated health, insomnia, and suicide death in Japan. Suic. Life-Threat.
Behav. 35, 227–237.
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the clinical course of bipolar disorder. Br. J. Psychiatry 186, 121–125.
Goldberg, J.F., Allen, M.H., Miklowitz, D.A., Bowden, C.L., Endick, C.J., Chessick, C.A.,
Wisniewski, S.R., Miyahara, S., Sagduyu, K., Thase, M.E., Calabrese, J.R., Sachs, G.S.,
2005. Suicidal ideation and pharmacotherapy among step-BD patients. Psychiatr.
Serv. 56, 1534–1540.
Gonzalez, J.M., Bowden, C.L., Katz, M.M., Thompson, P., Singh, V., Prihoda, T.J., Dahl, M.,
2008. Development of the bipolar inventory of symptoms scale: concurrent va-lidity,
discriminant validity and retest reliability. Int. J. Methods Psychiatr. Res. 17, 198–209.
The funding agency had no role in this study design; in the collec-tion,
analysis and interpretation of data; in the writing of this report; and in the
decision to submit this article for publication.
Acknowledgements
The authors thank all the participants that volunteered for this clinical
trial.
Conclusion
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Our study suggests that reported life satisfaction, even more than
functional impairment, is a mediator of the effect of depression on SI. This
has clinical significance, as elements of cognitive therapy that address
cognitive distortions related to life satisfaction may be potential targets to
reduce risk of suicide. Bipolar type and past suicide attempts also moderate
the effects of depression, while most other variables lose significance when
the effects of depression are considered. The most significant predictor of
suicidal ideation in patients with bipolar dis-order remains the severity of
depression. This further emphasizes the importance of treating depressive
episodes to reduce suicide risk in bipolar disorder.
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Terence A. Ketter, MD has received grants from Agency for Healthcare Research and Quality,
during the conduct of the study; personal fees from Acadia Pharmaceuticals, personal fees from
Allergan Pharmaceuticals, personal fees and other from Janssen Pharmaceuticals, personal fees
from Myriad Genetic Laboratories, Inc., personal fees from Navigen, personal fees from Otsuka
Pharmaceuticals, grants and personal fees from Sunovion Pharmaceuticals, personal fees from
Supernus Pharmaceuticals, personal fees from Teva Pharmaceuticals, personal fees from
GlaxoSmithKline, grants from Merck & Co., Inc., personal fees from American Psychiatric
Publishing, Inc., outside the submitted work.
Richard C. Shelton, MD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study; grants and personal fees from Allergan, grants from Assurex
Health, grants from Avanir Pharmaceuticals, grants and personal fees from Cerecor, Inc,
personal fees from Clintara LLC, grants from Genomind, grants and personal fees from Janssen
Pharmaceutica, personal fees from Medtronic, Inc., grants from Novartis, Inc., personal fees
from Pfizer, Inc., grants and personal fees from Otsuka Pharmaceuticals, grants and personal
fees from Acadia Pharmaceuticals, grants from Alkermes, PLC, grants and personal fees from
Takeda Pharmaceuticals, grants from NeuroRx Inc., outside the submitted work.
Thilo Deckersbach, PhD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study; grants from National Institutes of Health, grants from Defense
Advanced Research Projects Agency, grants from Patient Centered Outcomes Research
Institute, grants from Depression and Bipolar Alternative Treatment Foundation, grants and
personal fees from Sunovion Pharmaceuticals, Inc, personal fees from MGH Psychiatry
Acadamy, personal fees from BrainCells, Inc, personal fees from Clintara, Inc., personal fees
from Systems Research and Applications Corporation, per-sonal fees from Boston University,
personal fees from Catalan Agency for Health Technology Assessment and Research, personal
fees from National Association of Social Workers Massachusetts, personal fees from
Massachusetts Medical Society, grants and personal fees from Tufts University, personal fees
from National Institute on Drug Abuse, grants and personal fees from National Institute of
Mental Health, grants from International OCD Foundation, grants from Otsuka
Pharmaceuticals, grants and personal fees from Cogito, Inc., personal fees from Oxford
University Press, grants from Brain and Behavior Foundation, grants from Tourette Syndrome
Association, grants from National Institute on Aging, grants from Janssen Pharmaceuticals,
grants from The Forest Research Institute, grants from Shire Development, Inc., grants from
Medtronic, grants from Cyberonics, grants from Northstar, grants from Takeda, outside the
submitted work.
Mauricio Tohen, MD DrPH. MBA reports grants from Agency for Healthcare Research and
Quality, during the conduct of the study; personal fees from straZeneca, Abbott, BMS, Lilly,
GSK, J&J, Otsuka, Roche, Lundbeck, Elan, Allergan, Alkermes, Merck, Minerva,
Neuroscience, Pamlab, Alexza, Forest, Teva, Sunovion, Gedeon Richter, and Wyeth, outside
the submitted work.
Tondo, L., Isacsson, G., Baldessarini, R.J., 2003. Suicidal behaviour in bipolar disorder.
CNS Drugs 17, 491–511.
Tondo, L., Lepri, B., Baldessarini, R., 2007. Suicidal risks among 2826 Sardinian major
affective disorder patients. Acta Psychiatr. Scand. 116, 419–428.
Umamaheswari, V., Avasthi, A., Grover, S., 2014. Risk factors for suicidal ideations in
patients with bipolar disorder. Bipolar Disord. 16, 642–651.
Valois, R.F., Zullig, K.J., Huebner, E.S., Drane, J.W., 2004. Life satisfaction and suicide
among high school adolescents. Soc. Indic. Res. 66, 81–105.
Valtonen, H., Suominen, K., Mantere, O., Leppamaki, S., Arvilommi, P., Isometsa, E.T., 2005.
Suicidal ideation and attempts in bipolar I and II disorders. J. Clinic. Psychiatry 66, 1456–
1462.
Viguera, A.C., Milano, N., Laurel, R., Thompson, N.R., Griffith, S.D., Baldessarini, R.J.,
Katzan, I.L., 2015. Comparison of electronic screening for suicidal risk with the pa-tient
health questionnaire item 9 and the Columbia suicide severity rating scale in an outpatient
psychiatric clinic. Psychosomatics. https://doi.org/10.1016/j.psym.2015. 04.005.
James H. Kocsis, MD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study.
Joseph R. Calabrese, MD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study.
Keming Gao, MD reports grants from Agency for Healthcare Research and Quality, during the
conduct of the study; personal fees from Sunovion, personal fees from Otsuka, grants from
Cleveland Foundation, grants from Brian and Behavior Research Foundation, outside the
submitted work.
Michael E. Thase, MD reports grants and personal fees from Alkermes, personal fees from
AstraZeneca, personal fees from Bristol-Myers Squibb Company, grants and personal fees from
Eli Lilly & Co, grants and personal fees from Forest Laboratories, personal fees from Gerson
Lehman Group, personal fees from GlaxoSmithKline, personal fees from Guidepoint Global,
personal fees from H. Lundbeck A/S, personal fees from MedAvante, personal fees from Merck
and Co., personal fees from Neuronetics, Inc., personal fees from Ortho-McNeil
Pharmaceuticals, grants and personal fees from Otsuka, personal fees from Pfizer, personal fees
from Roche, personal fees from Shire US, Inc., personal fees from Sunovion Pharmaceuticals,
Inc., personal fees from Takeda, other from American Psychiatric Foundation, other from
Guilford Publications, other from Herald House, other from W.W. Norton & Company, Inc.,
other from Peloton Advantage, personal fees from Cerecor, Inc., personal fees from Moksha8,
personal fees from Pamlab L.L.C. (Nestle), personal fees from Allergan, personal fees from
Trius Therapeutical, Inc., personal fees from Fabre-Kramer Pharmaceuticals, Inc., grants from
Agency for Healthcare Research and Quality, grants from AssureRx, grants from Avanir, grants
from Forest Pharmaceuticals, grants from Janssen, grants from Intracellular, grants from
National Institutes of Health, grants from Takeda, outside the submitted work.
Masoud Kamali, MD reports grants from Agency for Healthcare Research and Quality, during
the conduct of the study; grants from Janssen Pharmaceutica, grants from Assurex Health,
outside the submitted work.
Noreen A. Reilly-Harrington, PhD reports grants from Agency for Healthcare Research and
Quality, during the conduct of the study; other from Oxford University Press, other from
American Psychological Association, other from New Harbinger, other from United
Biosource/Clintara, outside the submitted work.
Weilynn C. Chang, BS has nothing to disclose.
Melvin McInnis, MD reports grants from Agency for Healthcare Research and Quality, during
the conduct of the study; personal fees from Otsuka Pharmacueticals, personal fees from Takeda
Pharmacueticals, outside the submitted work; In addition, Dr. McInnis has a patent US patent
9685174 B2: Mood Monitoring of Bipolar Disorder using Speech Analysis issued.
Charles L. Bowden, MD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study.
Susan L. McElroy, MD reports grants from Agency for Healthcare Research and Quality,
171
Journal of Affective Disorders 259 (2019) 164–172
M. Kamali, et al.
Dustin J. Rabideau, MS has nothing to disclose.
Gustavo Kinrys, MD reports grants from Agency for Healthcare Research and Quality, during
the conduct of the study.
Andrew A. Nierenberg, MD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study; grants and personal fees from Takeda/Lundbeck, grants and
personal fees from AlfaSigma (formerly Pamlabs), grants from GlaxoSmithKlein, personal fees
from Alkermes, grants from NeuroRx Pharma, personal fees from PAREXEL, personal fees
from Sunovian, personal fees from Naurex, personal fees from Hoffman La Roche/Genentech,
personal fees from Eli Lilly & Company, personal fees from Pfizer, personal fees from SLACK
Publishing, personal fees from Physician's Postgraduate Press, Inc., grants from Marriott
Foundation, grants from National Institute of Health, grants from Brain & Behavior Research
Foundation, grants from Janssen, grants from Patient Centered Outcomes Research Institute,
grants from Intracellular Therapies, other from Appliance Computing, Inc., other from Brain
Cells, Inc., personal fees from Shire, personal fees from Teva, personal fees from Jazz
Pharmaceuticals, outside the submitted work.
William V. Bobo, MD, MPH reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study.
Benjamin Brody, MD reports grants from Agency for Healthcare Research and Quality, during
the conduct of the study, and grant from the Pritzker Neuropsychiatric Disorders Research
Consortium outside the submitted work.
Louisa G. Sylvia, PhD reports grants from Agency for Healthcare Research and Quality,
during the conduct of the study; personal fees from Concordant Rater Systems, personal fees
from United Biosource Corporation, personal fees from Clintara, personal fees from Bracket,
personal fees from Clinical Trials Network and Institute, personal fees from New Harbinger,
outside the submitted work; and she has also received grant/research support from NIMH,
PCORI, AFSP, and Takeda.
172
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