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Personalized Pharmacotherapy for Bipolar Disorder: How to Tailor Findings From Randomized Trials to Individual Patient-Level Outcomes

Abstract

The quest for “personalized medicine” in psychiatry has focused mainly on pursuing potential biomarkers such as pharmacogenetic predictors of drug response. However, the collective randomized trial database across phases of bipolar disorder allows one to identify clinical characteristics that inform the likelihood of desired treatment outcomes. In turn, those characteristics, termed moderatorsand mediators of drug response, enable those who administer treatment to construct clinical profiles that can help them tailor pharmacotherapies to the features of a given patient rather than simply to an overall diagnosis. Bipolar disorder typically involves more heterogeneous than uniform clinical presentations, partly because of its highly prevalent psychiatric and medical comorbid conditions. Further clinical diversity arises from characteristics such as bipolar I versus II disorder subtype, rapid cycling, mixed versus pure affective episodes, psychosis, anxiety, chronicity, cognitive dysfunction, and suicidality, among other distinguishing features. By coupling such profiles with an awareness of the psychotropic breadth of spectrum held by particular medications, clinicians can devise strategic combination therapy regimens, capitalizing on synergies and using drugs that exert multiple relevant effects, addressing comorbid conditions, incorporating medications that could offset adverse effects of other agents, and avoiding or deprescribing medication options that lack known evidence to target symptoms within the clinical profile of a given patient.

Bipolar disorder represents one of the most heterogeneous known forms of psychopathology. Although mood and affective disturbances are, by definition, core elements of the condition, more nuanced endophenotypic studies have placed increasing nosologic importance on related dimensions, such as changes in energy or motor activity (1), attentional and executive dysfunction (2), impulsivity and aggression (3, 4), anxiety (5), psychosis proneness (6), sleep-wake cycle dysregulation (7), susceptibility to formal thought disorder (8), and affective vulnerability to chronobiological and social rhythm disruptions (9). Moreover, given that two thirds of bipolar disorder patients have at least one distinctly comorbid psychiatric or substance use diagnosis (10), the clinical target profile for treatment of any given patient becomes far more complex than simply choosing a medication based solely on the overarching diagnosis. Consequently, asking what the best treatment is for mania or for bipolar depression becomes as nonspecific and oversimplified a question as if one were to ask how best to treat cancer or infections, or even heart disease.

Bipolar disorder involves diverse and protean features with varied dimensions of psychopathology, expressed to greater or lesser degrees at different points in time. Optimal pharmacotherapy therefore requires devising individualized treatments suited to the unique characteristics of a given patient, following a model of personalized medicine. Hence, the main objective of this article is to describe symptom contexts and patterns of presentations that best align with evidence-based findings from randomized controlled trials (RCTs).

Translating Randomized Trials to Individualized Care

RCTs yield information about treatment outcomes for diagnostic or subdiagnostic groups as a unit, but the practitioner almost always must extrapolate such findings to the unique clinical circumstances of a given patient. A key concept in this regard involves the notion of enrichment of patient groups enrolled in clinical trials, meaning that study participation may be restricted to individuals only with certain characteristics—such as those who responded acutely to a particular medication before entering a relapse prevention trial—or study participation may be confined to a specific age range, or to patients with bipolar disorder without rapid cycling or active suicidal features, active substance misuse, or psychiatric comorbid conditions. Ironically, most patients treated for bipolar disorder in routine practice are ultimately deemed ineligible to participate in RCTs. Screen failure rates for intervention trials for bipolar mania range from 55% to 96% (11)—most often because of active substance misuse or psychiatric comorbid conditions, suicidality, poor adherence, or failure to meet full diagnostic criteria; this suggests that most individuals identified as having bipolar disorder in the community differ in fundamental phenomenological ways from their RCT-participant counterparts. Practitioners and investigators alike then wonder why “real-world” patient outcomes often differ markedly from those that might otherwise be expected from the evidence-based literature.

One way in which clinicians and readers of the literature can better distinguish similarities and differences between RCT participants and their own clinical populations—and thereby anticipate how much extrapolation may be needed from the study group to the individual—is to understand and recognize clinical and biological characteristics that increase the likelihood of a favorable treatment response for a given patient. In conducting clinical trials, investigators have begun to recognize the need to distinguish individual from group treatment responses and are increasingly using refined data-analytic approaches that pool patient data to allow for participant-level analyses (12). Such studies usefully reveal factors about an overall study population that may increase or decrease the likelihood of individual participants to respond to an intervention. For example, one such analysis of olanzapine for the treatment of bipolar mania found especially robust separation between drug and placebo among patients with high baseline symptom severity (13). Hopefully, the concept of “personalized medicine” in psychopharmacology will validate possible biomarkers (e.g., gene expression products and proteomics, pharmacogenetics, and inflammatory cytokines) as well as clinical characteristics associated with drug responsivity for a given patient. At present, clinical features can be identified and clustered to devise risk profiles that may favor drug response or that parsimoniously target heterogeneous phenotypes (e.g., one drug targeting multiple effects). Clinicians who follow the empirical literature can formulate their own hypotheses about tailoring a treatment regimen that best matches the unique profile of a given bipolar patient on the basis of their own experience relative to findings from RCTs.

Moderators and Mediators of Treatment Outcome

The search for patient features that might influence the chances of a particular result for one patient relative to another involves the statistical concept of moderators and mediators of outcome. As described by the biostatistician Helena Kraemer (14, p. 672), moderators are baseline characteristics that identify “on whom or under what conditions treatment choice differentially affects outcomes” (i.e., who should get the treatment), whereas mediators are factors that suggest “how or why the treatment condition might be preferred to the control condition in the population sampled” (i.e., factors that could either facilitate or jeopardize the best possible treatment outcomes after the treatment has begun). Examples of well-recognized moderators and mediators of pharmacotherapy outcomes in RCTs for treatment of bipolar disorder are summarized in Table 1 and Table 2 (9, 1531).

TABLE 1. Recognized moderators of bipolar disorder treatment outcomes

ModeratorRelevance
Age at onsetEarly onset (prepubertal, adolescent) is one of the more robust correlates of poor outcome, although it sometimes may be a proxy variable for more immediate causes of poor outcome (e.g., social isolation or poorer premorbid functioning).
Baseline severityHigh baseline severity tends to suppress placebo responsivity; it also provides the opportunity for greater variability in severity levels over time than that which occurs with the more restricted range of low baseline severity.
ChronicityLong-standing illness states often respond less well than acute episodes to standard pharmacotherapies and incur higher risk for maladaptation to illness over time (e.g., demoralization, diminished effort, loss of social and economic supports).
Episode numberPatients who have endured multiple episodes may respond less well to lithium than to divalproex (15) and possibly other broader spectrum psychotropics.
Predominant polarityEpisodes predominated by mania more than depression are associated with better responses to lithium, divalproex, and most second-generation antipsychotics; depression predominance more than mania is associated with better response to lamotrigine and quetiapine plus lithium or divalproex (16).
SexDirect effects of sex on treatment outcome have not been described in bipolar pharmacotherapy trials, although indirect effects may bear on longitudinal outcome (e.g., contraindication of divalproex and pregnancy, elevated postpartum risk for mood episodes, and an artifact of higher prevalence of rapid cycling among bipolar women than men [17]). Sex also may interact with mediating factors (e.g., poorer adherence by men [18]).
Rapid cyclingHistorically defined as the most robust predictor of lithium prophylaxis failure (19), rapid cycling has been recognized as a negative predictor of outcomes during antidepressant trials for bipolar depression (20), a likely indication for the need for combinations of mood stabilizers (21) and a poorer prognostic factor in general (22).
Psychiatric comorbid conditionsCommon psychiatric comorbid conditions in bipolar disorder include anxiety disorders (∼56% (23)), personality disorders (∼65% [23]), OCD (∼17% [24]), adult ADHD (∼10% [25]), eating disorders (∼27% [26]), and posttraumatic stress disorder (4%–40% [27]); few studies have formally examined treatment outcomes of comorbid disorders specifically in patients with bipolar disorder, but any psychiatric comorbidity in general worsens prognosis.
Alcohol and substance misuse comorbid conditionsLifetime prevalence of 40%–60% (23) is associated with poorer treatment adherence, higher rates of suicidal behavior, and poorer outcome.
Medical comorbid conditionsMedical comorbidity burden diminished recovery from depression (OR=0.89) in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) (28); overweight and obesity may directly adversely affect treatment outcome in bipolar depression (29).
History of childhood traumaPhysical, sexual, verbal, or emotional abuse or neglect during childhood correlates with psychiatric comorbid conditions and vulnerability to psychosis but also stands as an independent negative predictor of treatment outcome in bipolar disorder (30).
Familiality of drug responseClinicians often presume that psychotropic drug response is a familial trait, yet there has been remarkably little study of this hypothesis. Concordance of lithium response or nonresponse stands as one of the very few evidence-based examples that drug response by a first-degree relative may inform the likelihood of response in a proband (31).
Poor or ultrarapid metabolizer genotypesLess than 10% of most ethnic groups are genetically prone to metabolize substrates of cytochrome P450 2D6, 3A4, or 2C19 either too slowly (“poor metabolizer”) or too rapidly (“ultrarapid metabolizer”), predisposing such individuals to adverse effects or to diminished efficacy or problems hepatically converting some prodrugs to active metabolites, respectively.

TABLE 1. Recognized moderators of bipolar disorder treatment outcomes

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TABLE 2. Recognized mediators of bipolar disorder treatment outcomes

MediatorRelevance
Treatment adherenceLikely the most obvious and common factor that can adversely affect response to an otherwise efficacious treatment. Prevalence estimates of poor medication adherence in bipolar disorder range from 20% to 60% (18). Poor adherence itself correlates with several moderators of outcome (e.g., illness severity, episode number, and substance use comorbidity [18]), underscoring the complex interplay of treatment moderators and mediators. Nonadherence substantially disrupts judging adequate trials because of inadequate dose or duration.
Drug-drug interactionsThe addition of other pharmacotherapies that alter the bioavailability or metabolism of (or pose pharmacodynamic interactions with) an existing psychotropic drug can obviously alter treatment outcomes. Mental health prescribers are not always aware of changes to pertinent nonpsychotropic drug regimens in this regard, such as hepatic enzyme inducers that can hasten substrate metabolism (e.g., oral contraceptives, omeprazole, phenytoin, and rifampin) or inhibitors that may prolong it (e.g., cimetidine, amiodarone, erythromycin, ketoconazole, allopurinol, nifedipine, quinidine, and ritonavir).
Therapeutic allianceThe working relationship between prescriber and patient is often underappreciated for its mediating effect on pharmacotherapy outcome partly through its indirect impact on fostering drug adherence but also through its more proximal shaping of attitudes and expectations about likely and realistic expectations of what pharmacotherapy can and cannot do.
Stressful life events after treatment has begun (e.g., job loss, deaths, pregnancies)On the one hand, reversals of fortune and interpersonal or other psychosocial stresses (including social rhythm disruptions that may seem benign or beneficial, such as vacations or job promotions) can pose direct triggers for affective relapse (9); on the other hand, optimal treatment should help to foster a sense of resilience in managing unpredictable events or maintaining a sense of emotional equilibrium even in the face of environmental adversity.
Adverse drug effects or nocebo effectsDrug side effects are proximal contributors to adherence and in themselves can influence perceptions of treatment effectiveness (e.g., adverse effects such as somnolence or akathisia can be mistaken for primary undertreated symptoms, and vice versa; or, even if burdensome side effects do not impede adherence, they may diminish overall well-being and patients’ global perceptions of improvement.
Substance misuseAlcohol and illicit substance misuse after treatment initiation can diminish the effectiveness of any pharmacotherapy and exacerbate or perpetuate affective and other symptoms that are themselves the intended targets of treatment.

TABLE 2. Recognized mediators of bipolar disorder treatment outcomes

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Lithium: Gold Standard or Old Standard?

Our field came to appreciate the disparity between treatment outcomes for homogeneously “ideal” patient profiles from the greater heterogeneity (and more variable prognosis) of those in real-world settings through observational studies with lithium in the 1980s. From decades of experience since lithium came into use for bipolar disorder, one can now construct a “profile” of the idealized patient best suited to respond to lithium. Rather than consider lithium to be the gold-standard mood stabilizer, as often described (as if it possessed broad universal properties for most forms of bipolar disorder), one can probably think of it more accurately as a well-studied but narrow spectrum agent. Analogous to penicillin, lithium works best in a definable, narrow subgroup of bipolar patients (<10% by some reports (32)) with a distinctly uncomplicated clinical profile, defined by the following characteristics: pure euphoric more than mixed features (33); positive family history of lithium-responsive bipolar disorder (31); introduction within the first few lifetime episodes (34); absence of rapid cycling (19); better prophylaxis against recurrent mania than depression (35); mania polarity “proneness” (16); episode patterns in which manias precede depressions (36); higher age at illness onset (36); absence of somatic comorbid condition (32); absence of substance use comorbidity (37); hyperthymic temperament (38); absence of psychosis or cognitive disorganization (39); and absence of anxiety (40).

Additionally, lithium may hold a relative advantage over other mood-stabilizing agents in settings where prevention of suicidal behavior is a prominent concern (41), as a countermeasure to leukopenia (e.g., during clozapine therapy), and in patients without psoriasis or other chronic dermatological comorbid conditions.

Anticonvulsants: No Mood-Stabilizing Class Effect

Contrary to early expectations based on studies of divalproex and carbamazepine in the late 1990s, there does not appear to be a “class effect” among anticonvulsant drugs with respect to putative “mood-stabilizing” properties. Indeed, as summarized in Table 3, the mood-specific effects of most newer generation anticonvulsants, as established in RCTs, are narrowly confined to divalproex and carbamazepine (predominantly antimanic>antidepressant) and to lamotrigine (predominantly antidepressant>antimanic and more potent for relapse prevention than the treatment of acute episodes). Check marks in the table indicate robust, well-established efficacy. No positive, large-scale, placebo-controlled trials in any phase of bipolar disorder exist with any of the other anticonvulsants listed in the table. However, anticonvulsant drugs show a diverse range of psychotropic properties; some exert beneficial effects on manic or depressive symptoms, whereas others may cause worsening of affective symptoms (e.g., new-onset depression has been observed in up to 10% of patients with epilepsy taking topiramate (42) or adverse cognitive effects from, notably, topiramate or zonisamide). Other psychotropic effects in addition to those described in Table 3 include the following: established antinocioceptive properties, particularly neuropathic pain (e.g., gabapentin, pregabalin) or trigeminal neuralgia (e.g., carbamazepine); weight loss and appetite suppression (e.g., zonisamide [43]) and reversal of psychotropic-induced weight gain (e.g., zonisamide [44, 45]); treatment of sleep apnea via carbonic anhydrase inhibition (e.g., zonisamide [46]); treatment of insomnia and promoting sleep continuity (e.g., gabapentin prolongs stage 3 sleep); treatment for restless legs syndrome (gabapentin enacarbil); and a possible added benefit of adjunctive topiramate for bipolar disorder with comorbid obsessive-compulsive disorder (OCD [47]).

TABLE 3. Varied “niche” psychotropic roles of anticonvulsant drugsa

AgentManiaDepressionAnxietyBinge eatingAlcohol dependencePTSD
Carbamazepine1 (+), 2 (−) placebo-controlled trials (48)1 (−) placebo-controlled trial in panic disorder (48)No data1 (+) placebo-controlled trial (49)Case reports, small open trials
Divalproex3 small (+) placebo-controlled trials (48)2 (+) placebo-controlled trials (48)bNo data1 (+) placebo-controlled trial (50)2 (−) placebo-controlled trials (51, 52)
Lamotrigine2 (−) trials (53)4 negative acute monotherapy trials (54), 2 (+) augmentation trials (55, 56), and 2 (+) relapse prevention trials (57)cNo data1 (−) placebo-controlled trial (58)No data1 (+) placebo-controlled trial (59)
Gabapentin2 (−) trials (53)1 (−) placebo-controlled trial (53)No data2 (+) (60, 61) and 1 (−) placebo-controlled trials (62)Case reports
PregabalinNo dataNo dataNo dataSmall open trials1 (+) placebo-controlled trial (63)
Topiramate4 (−) trials (53)No dataNo data2 (+) placebo-controlled trials (64, 65)1 (+) (66) and 2 (−) placebo-controlled trials (67, 68)
Oxcarbazepine1 (−) trial (youth only) (69)No dataCase reportsNo dataCase reportsCase reports
Zonisamide1 (−) placebo-controlled trial (70)1 (−) placebo-controlled trial (71)No data1 (+) placebo-controlled trial (72)1 (+) placebo-controlled trial (73)No data

aSummaries are based only on data from randomized placebo-controlled trials.

bSignificant reduction in Hamilton Anxiety Scale scores was a reported secondary outcome in two of the small acute bipolar depression RCTs of divalproex.

cLamotrigine relapse prevention trials include patients with past-year rapid cycling, for whom outcomes were better than with placebo.

TABLE 3. Varied “niche” psychotropic roles of anticonvulsant drugsa

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One could readily envision crafting a tailored pharmacotherapy regimen for a given patient with bipolar disorder that incorporates certain anticonvulsants meant to target specific illness characteristics or comorbid conditions such as those described in Table 3 (4873)—without conflating such “ancillary” effects with the core targeting of affective symptoms. Illustrative examples are provided at the end of this article.

Second-Generation Antipsychotics

Second-generation antipsychotics (SGAs) have gained increasing attention over the past 2 decades as having psychotropic effects independent of their antipsychotic properties, including various degrees of antimanic; antidepressant; anxiolytic; and, possibly, procognitive effects in patients with bipolar disorder. All SGAs that have been studied in patients with acute mania in combination with lithium or divalproex have shown greater efficacy than those seen with mood stabilizer monotherapy. Additionally, secondary analyses of RCTs for treatment of acute mania with virtually all SGAs show greater efficacy than those with placebo, regardless of the presence or absence of rapid cycling. RCTs have demonstrated several additional psychotropic effects of certain SGAs, including the following: a beneficial effect for global cognitive functioning (74); possible weight loss effects with adjunctive ziprasidone (75); adjunctive use of aripiprazole for comorbid bipolar disorder and OCD (76); the superiority of aripiprazole over placebo in treating depression, anxiety, and aggression in people with borderline personality disorder (77); and the use of D2 and D3 partial agonists (notably, aripiprazole) to counteract antipsychotic-associated hyperprolactinemia.

The full summary is provided in Table 4 (7899).

TABLE 4. Breadth of psychotropic properties of second-generation antipsychoticsa

AgentAcute maniaMania preventionAcute depressionDepression preventionAnxietyPTSD
Aripiprazole2 (−) placebo-controlled trials (78)2 (−) placebo-controlled trials (79, 80)bSmall open trials1 (−) small placebo-controlled trial (81)
AsenapineNo dataNo dataSmall open trials
BrexpiprazoleNo dataNo dataNo dataNo dataEfficacy in MDD trials with or without anxious distress (82)No data
CariprazineNo dataNo dataNo dataNo data
LurasidoneNo datacNo dataNo dataNo data
Olanzapine2 (+) placebo-controlled trials (83)1 small (+) placebo-controlled trial (84)
Quetiapine1 (+) placebo-controlled trial (85)
RisperidonedNo data1 (−) placebo-controlled trial (86)b,d1 (−) placebo-controlled trial for anxiety symptoms in bipolar patients with comorbid panic or GAD (87)1 (+) (88), 4 (−) placebo-controlled trials as adjuncts to SSRIs in (nonbipolar) military (8991) or civilian (92) PTSD
Ziprasidonec2 (−) placebo-controlled trials (93)1 (−) placebo-controlled trial (94)b,e1 (−) placebo-controlled trial in bipolar disorder with comorbid panic disorder or GAD (95)2 (−) placebo- controlled trials (96, 97)

aMDD, major depressive disorder; GAD, generalized anxiety disorder; SSRIs, selective serotonin reuptake inhibitors.

bMaintenance trial following an index manic or mixed episode; sample enrichment likely contributed to a low observed rate of depression relapses in both treatment arms.

cAlthough there are no formal RCTs with lurasidone in acute mania, trials in bipolar depression with mixed features (98) or major depressive disorder with mixed features (99) suggest antimanic efficacy versus placebo.

dBased on studies of risperidone long-acting injectable formulation.

eZiprasidone was administered as an adjunct to lithium or divalproex.

TABLE 4. Breadth of psychotropic properties of second-generation antipsychoticsa

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RCTs have not, as yet, demonstrated the value of SGAs in treating comorbid alcohol abuse and dependence (100) or substance use disorder symptoms, either in general or in people with bipolar disorder (101). Impulsive aggression also has not been demonstrated as an independent dimension of psychopathology that is responsive to SGAs in bipolar disorder, apart from the use of some short-acting injectable SGAs to treat acute agitation in emergency departments or inpatient settings; nor have RCTs shown value for SGAs in the treatment of anorexia nervosa (102).

It should be noted that some of the negative or failed trial findings identified in Table 4 may be artifacts of particular study designs. For example, in the negative findings of two RCTs, aripiprazole monotherapy (78), in the treatment of acute bipolar depression, ultimately failed to separate from placebo at the end of each study, not because of a weak drug effect but because of an unexpected improvement among placebo recipients near the conclusion of each trial. The relapse prevention trials of aripiprazole oral (79) or long-acting injectable (80) formulations, or of risperidone long-acting injectable (86) formulations, each began after index episodes of manic or mixed episodes, thereby enriching the samples for a higher propensity toward mania than toward depression relapse. In other words, the study designs used in these trials may have failed to reveal the fullest potential of these agents for preventing bipolar depressive episodes that might have provided more evidence using different study designs (with enrollment following index-depressive rather than solely manic or mixed episodes).

Known Combination Therapy Regimens

Clinicians sometimes combine medications without necessarily knowing whether there exists an evidence base to support the value of some combinations other others. Table 5 summarizes known pairings of psychotropic drugs in which combination therapies were superior to monotherapies plus placebo, across various illness states in bipolar disorder (103108).

TABLE 5. Evidence-based combination versus monotherapy therapy regimens for bipolar disorder treatment

RegimenIllness stateOutcome
Lithium + lamotrigine versus lithium + placebo over 8 weeksAcute bipolar depressionCombination>lithium monotherapy (55)
Quetiapine + lamotrigine versus quetiapine + placebo over 12 weeksAcute bipolar depressionCombinationa>quetiapine + placebo (56)
Lithium or divalproex + lurasidone versus lithium + placebo over 6 weeksAcute bipolar depressionCombination>lithium or divalproex monotherapy (103)
Mood stabilizer or antipsychotic + lisdexamfetamine versus mood stabilizer or antipsychotic alone over 8 weeksAcute bipolar depressionCombination>mood stabilizer or antipsychotic alone (104)
Divalproex + celecoxib versus divalproex + placebo over 6 weeksAcute bipolar maniaCombination>divalproex monotherapy (105)
Treatment as usual + divalproex versus Treatment as usual + placebo over 24 weeksBipolar disorder with active alcohol abuse or dependenceCombination>treatment as usual (50)
Treatment as usual + memantine versus Treatment as usual + placebo over 16 weeksBipolar disorder with OCDCombination> treatment as usual (106)
Treatment as usual + withania somnifera versus Treatment as usual + placebo over 8 weeksCognitive dysfunction in bipolar disorderCombination> treatment as usual (107)
Treatment as usual + lurasidone versus Treatment as usual (randomized open label) over 6 weeksCognitive dysfunction in bipolar disorderCombination> treatment as usual (74)
Lithium + divalproex versus either monotherapy over 20 monthsRapid cyclingCombination>either monotherapy (21)
Lithium + divalproex versus either monotherapy over 24 monthsBipolar relapse preventionCombination>divalproex monotherapy (108)

aThe addition of oral supplemental folic acid diminished the efficacy of lamotrigine.

TABLE 5. Evidence-based combination versus monotherapy therapy regimens for bipolar disorder treatment

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Using Antidepressants in Treating Bipolar Disorder: When, Not If

Still a topic of intense debate on which even experts cannot always agree (109), the issue of whether and when to use antidepressants in bipolar disorder plagues psychopharmacologists for three main reasons.

The first reason is questionable efficacy. No large-scale RCT has ever shown that the use of an antimanic drug plus any antidepressant is superior to using an antimanic drug alone for treating acute bipolar depression. As a class, antidepressants have a disturbingly high “number needed to treat” (NNT) of 29 for bipolar depression (110), casting doubt on the reliability with which they might deliver a desired effect.

The second reason is risk for induction of mania or cycle acceleration. Often, this phenomenon, listed in manufacturers’ package inserts for all antidepressants, is presumed by many clinicians to be the greatest hazard posed by antidepressants in the treatment of bipolar disorder. Over the course of its editions, the Diagnostic and Statistical Manual for Mental Disorders (DSM) has varied in its conceptualization of mania or hypomania that arises in the aftermath of antidepressant initiation, as well as the likelihood with which such an outcome represents the unmasking of a bipolar diathesis versus simply an adverse drug effect. In the DSM-5 (111), treatment-emergent mania or hypomania is considered to reflect the unmasking of a bipolar diathesis if the symptoms of mania or hypomania persist at a fully syndromal level after the suspected catalyst has been stopped and its physiological effects are no longer present (e.g., after five elimination half-lives). Although this definition is sensible for differentiating antidepressants as a cause (producing an adverse effect) versus a catalyst, it fails to take into account the reality that clinicians often will intervene with an antimanic pharmacotherapy (rather than wait and observe for the dissipation of mania as simply a drug side effect), and still others may continue an antidepressant despite the emergence of mania symptoms on the basis of the belief that antidepressants are necessary to address concurrent depressive symptoms. In clinical studies, judgments about alleged antidepressant-associated mania are further hampered by inaccuracies in retrospective recall, subjective impressions about whether diagnostic criteria are actually met for a manic or hypomanic syndrome (as contrasted with more nebulous phenomena such as “activation”), and distinguishing the natural course of illness from a true causal association. (On the latter point, some experts consider the possible association of emerging mania-hypomania symptoms with antidepressant exposure-dose increases to be “definite” if within 8 weeks and “likely” or “possible” if within 12 weeks; beyond that time frame, differentiation from the natural course of illness becomes virtually impossible (112).

Across studies, the risk for antidepressant-induced mania in bipolar disorder appears to be much lower than many clinicians assume: about 10%–15%, with a “number needed to harm” (NNH) of about 200 (110), making the anticipated lack of efficacy a greater hazard than the induction of mania for most depressed patients with bipolar disorder who take a traditional antidepressant.

The third reason involves additional limitations about forming hard and fast conclusions about antidepressant safety and efficacy in treating bipolar disorder. These include the following: Most contemporary antidepressants have not been studied in the treatment of bipolar depression, with no existing placebo-controlled studies of serotonin and norepinephrine reuptake inhibitors (SNRIs), vilazodone, vortioxetine, mirtazapine, or escitalopram; no controlled trials exist that examine the safety and efficacy of antidepressants in treating bipolar disorder for purposes other than treating depression (e.g., OCD, specific anxiety disorders, or bulimia); it is largely unknown whether treatment-emergent manic or hypomanic symptoms arise as a dose-dependent or all-or-none phenomenon; and, finally, the value of coadministering an antidepressant with an antimanic mood stabilizer (advocated in many practice guidelines as a safety measure to minimize the risk for induction of mania-hypomania) is largely an unproven hypothesis that has, nevertheless, become widely accepted as if dogmatic.

The existing database of RCTs points to an identifiable clinical profile of individuals with bipolar disorder for whom antidepressant use may be more or less favorable and safe, as summarized in Table 6 (113121). A further consideration, true of psychopharmacology in general, involves an individual patient’s personal history of response to a particular drug. In the world of evidence-based medicine, establishing an unequivocal and sustained response to a specific medication for a given individual is incontrovertible evidence of its effect on that given individual. Someone’s known own favorable response to an antidepressant, even if to an agent that has no established database in the RCT literature, constitutes evidence for that one patient. However, that information cannot generalize or transfer to other individuals on the basis of the experience of one patient alone.

TABLE 6. Factors associated with antidepressant responsivity in bipolar disorder

CharacteristicMore favorableLess favorable
Bipolar II (vs. I) disorder√ (113)
Mixed features√ (114, 115)
Rapid cycling√ (20)
History of treatment-emergent mania or hypomania during prior antidepressant therapy√ (116)
Depression or euthymia (but not mania or hypomania) preceding an index-depressive episode)√ (117)
Robust initial response before continuing longer term antidepressant use√ (118)
History of comorbid alcohol or substance use disorder√ (119, 120)
SLC6A4 “s” allele on pharmacogenetics testing√ (121)

TABLE 6. Factors associated with antidepressant responsivity in bipolar disorder

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Adverse Effects Influencing Medication Choice

Practitioners inevitably must strike a reasonable balance between drug benefits and tolerability, but there are instances in which concerns about safety and tolerability may override efficacy or breadth of spectrum when choosing from among pharmacotherapy options. Adverse effects such as weight gain and metabolic dysregulation, sexual dysfunction, sedation, or cognitive dulling can often contribute to treatment nonadherence or otherwise make for situations in which, to paraphrase Sir Francis Bacon, the cure becomes worse than the disease. Well-tolerated but ineffectual treatments make no sense beyond their placebo effect (which, admittedly, contributes in no small part to many treatment outcomes). However, assuming the added value of established pharmacodynamic efficacy (particularly for high-severity mood episodes), clinicians must not disregard high-potency, potentially life-saving interventions (e.g., lithium or clozapine) that may be uniquely beneficial simply in response to concerns about anticipated side effects. By the same token, extensive and “irrational” polypharmacy regimens sometimes arise (alongside the additive accrual of side effects) that may be nonpurposeful and ineffective, in which case streamlining and the pruning of a regimen may be necessary to achieve the best overall patient fit (122).

Other factors that may drive pharmacotherapy decision making may include medical comorbid conditions (e.g., lithium discontinuation in a patient who develops stage 3B chronic kidney disease), a significantly elevated QTc interval on an electrocardiogram for a patient requiring antipsychotic medication, or teratogenicity concerns in a woman taking divalproex who wants to become pregnant (123). Pharmacogenetic test results sometimes influence medication decisions regarding tolerability (e.g., poor metabolizers of cytochrome P450) or possible lack of efficacy (e.g., ultrarapid metabolizers), although the Food and Drug Administration (FDA) issued a consumer warning in November 2018 on the limitations of pharmacogenetic testing (https://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/ucm624725.htm), cautioning practitioners against changing medications solely on the basis of genetic testing results.

Two Case Examples

Case 1

Ben is a 24-year-old data analyst who was diagnosed as having bipolar II disorder after a episode of hypomania during his freshman year in college, with no previous psychiatric history. Since then, he has had brief mixed hypomanic episodes that occur three to five times per year, each lasting no more than a week. He has never been suicidal. He binge drinks alcohol on weekends (and reports no other drug use), is morbidly obese (body mass index [BMI]=41.1) and smokes one pack of cigarettes daily. His current medications include 50 mg of nortriptyline per day for migraine prophylaxis, 20 mg of eletriptan once or twice a week as needed for migraines without aura, 300 mg of lamotrigine per day, and 25 mg quetiapine at bedtime “for sleep.” He currently reports low-grade intermittent depression and anxiety, inner tension, trouble concentrating, distractible thinking, and restless sleep. He thinks he may now have adult-onset attention-deficit hyperactivity disorder (ADHD) and comes for a consultation seeking a psychostimulant trial.

Ben’s case description verges on possible rapid cycling bipolar II disorder with a historical polarity proneness toward mixed episodes. Although he currently complains of depressed mood, one would want to clarify whether, in fact, he currently manifests mixed features (certainly more so than melancholia or anergia) and is misconstruing affectively related distractible thinking and attentional problems with comorbid ADHD. True attention deficit disorder (ADD) or ADHD affects a fairly small minority of bipolar adults (see Table 1), and the apparent absence of childhood ADHD symptoms makes it difficult to attribute his current attentional problems to “adult-onset ADHD” (a controversial, currently unrecognized diagnostic entity). Nortriptyline could be exacerbating the frequency of his affective recurrences and, in any event, does not appear to be helping either his migraines or his depression; nor has high-dose lamotrigine conferred an obvious benefit to improve mood or migraine frequency.

An alternative and more parsimonious drug regimen would be to discontinue successively the nortriptyline and then the lamotrigine for lack of efficacy and replace both with divalproex to target migraine prevention, alcohol binge drinking, and probable rapid cycling with mixed episodes. Tracking his mood, alcohol use, migraine frequency, and cognitive complaints over the subsequent weeks would help shed light on possible interactions among these variables. If his alcohol use declines, does his mood improve, and would his cognitive concerns diminish? Does nortriptyline elimination reduce cycling frequency? If his alcohol use does not decline, one might then add topiramate to the divalproex, lending further evidence-based treatment for Ben’s alcohol binging (62, 63), migraine, and obesity.

Case 2

Elizabeth is a 47-year-old woman diagnosed as having bipolar I disorder whose overdose on lithium during a depressive episode 10 years ago caused acute kidney injury and left her with stage 3 chronic kidney disease (eGFR [estimated glomerular filtration rate]=42 mL/min/1.73 m2). She has had no prior or subsequent suicide attempts but has had three psychiatric hospitalizations in the past 10 years for suicidal ideation during depressive episodes that were without mixed features. There is no substance use comorbidity and no medical comorbidity except hypertension (for which she takes 10 mg enalapril per day); she is obese (BMI=31.2) and at risk for diabetes (hemoglobin A1C of 6.2 and fasting glucose of 105 mg/dL). She is euthyroid. Her mother has been diagnosed as having well-controlled lithium-responsive bipolar I disorder. Currently, Elizabeth is moderately depressed despite taking 200 mg lamotrigine per day plus 20 mg lurasidone per day. Her psychiatrist has steadfastly avoided giving her a monoaminergic antidepressant for fear of inducing mania. What would be a tailored approach to modifying her existing medication regimen?

This is a tough case, with many facets to consider. First, one wonders whether lithium had originally been helpful to the patient, particularly given her mother’s favorable response, and whether her condition was better stabilized when she previously took it; on the other hand, she attempted suicide despite taking lithium (so much for its antisuicide benefit). Her chronic kidney disease makes her a less-than-ideal candidate to resume lithium, unless the history persuasively showed that its benefits were unique and unequivocally outweighed the risk of further kidney disease. Adding low-dose lithium to an existing, well-chosen psychotropic regimen for bipolar disorder does not necessarily improve overall symptom severity (124), but such observations fail to account for possible moderators of lithium responsivity for a given patient.

Elizabeth currently takes two psychotropic medications with evidence-based antidepressant properties. Her lurasidone dose could be higher (32 mg/day was the mean dose in the flexible monotherapy trial for bipolar depression) (125). Lamotrigine’s efficacy in the view of the FDA is for relapse prevention rather than for the treatment of acute bipolar depression, although there exist at least some acute RCT data supporting higher doses (up to 275 mg/day) in refractory mood disorders (126). Elizabeth’s obesity and prediabetic status lessen enthusiasm for giving her quetiapine, an olanzapine-fluoxetine combination (OFC), or cariprazine as an alternative evidence-based pharmacotherapy for bipolar depression, but these are all obviously options worthy of consideration.

Should a traditional monoaminergic antidepressant be used? On the plus side, there is no known personal history of worsening from a prior antidepressant trial; there are no current or recent mania symptoms, there is no substance use disorder, and she does not meet the DSM-5 definition of rapid cycling. Her diagnosis of bipolar I disorder rather than bipolar II disorder may arouse some hesitation about risk for mood destabilization, but the overall probability of that occurrence is still statistically low (110). The status of her response to a monoaminergic antidepressant is unknown, but her response to more evidence-based treatments for bipolar depression has not been robust. Therefore, an argument can be made for further optimizing the dosing of her current medications versus considering an adjunctive antidepressant (sertraline, fluoxetine, venlafaxine, and bupropion all have at least some randomized data, albeit not placebo controlled); versus replacing lurasidone with quetiapine, OFC, or cariprazine along with close metabolic monitoring; versus adding back low-dose lithium augmentation with its potential to synergize with lamotrigine (55) with close renal monitoring; versus contemplating a more aggressive treatment, such as electroconvulsive therapy (depending on her symptom severity and consequent disability); or versus experimental or novel approaches such as intravenous ketamine (127), midday 7,000-lux bright-light therapy (128), or putative dopamine agonists such as pramipexole, modafinil, or traditional psychostimulants (129). No singular intervention stands above others, and all options have their pros and cons. Whatever course of action is advised, providing a rationale that applies evidence-based findings to Elizabeth’s unique presentation is paramount.

Future Directions

While existing treatments for bipolar disorder can be effective across all phases of illness, many patients still have incomplete remissions or take regimens that are ill suited to the idiosyncrasies of their unique presentations. Future studies must address outcomes related not only to mood but also cognition, impulsivity, psychosis, circadian dysregulations, and anxiety and other comorbid conditions in the hope that both treatment adherence and overall illness burden might improve from targeting all relevant symptom domains. Alongside the search for new drug mechanisms and novel compounds, intervention studies (and practice guidelines) should routinely account for known moderators and mediators of treatment outcome, which, in turn, can help practitioners translate RCT findings in ways that best fit the distinct clinical profile of individual patients.

Conclusions

Bipolar disorder is a phenomenologically heterogeneous condition with multiple symptom targets that extend beyond mood alone. Randomized trials that establish drug efficacy for an overall diagnosis and illness state—such as bipolar mania or depression—can provide a wealth of further information to help practitioners recognize characteristics that may increase the probability of a desired outcome. Clinicians might usefully think of an individual patient’s candidacy for a pharmacotherapy, which is based not solely on the randomized trial evidence for the overall disease entity but, more specifically, on matching recognized treatment moderators and the unique clinical profile of an individual patient beyond the diagnosis alone.

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City.
Send correspondence to Dr. Goldberg ().

Dr. Goldberg received no financial support for this study.

Dr. Goldberg is a consultant for Lundbeck, Neurocrine, Otsuka, Sunovion, and WebMD. He is on the speakers bureaus for Allergan, Neurocrine, Otsuka, Sunovion, and Takeda-Lundbeck. Dr. Goldberg receives royalties from American Psychiatric Association Publishing.

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