Ms. Cascade is Vice President, Quintiles Inc./iGuard, Falls Church, Virginia; Dr. Kalali is Vice President, Global Therapeutic Group Leader CNS, Quintiles Inc., San Diego, California, and Professor of Psychiatry, University of California, San Diego; and Dr. Findling is Professor of Psychiatry and Pediatrics
Case Western Reserve University, Cleveland, Ohio.

Psychiatry (Edgemont) 2009;6(6):21–23

Financial Disclosure

Dr. Findling receives or has received research support, acted as a consultant, and/or served on a speaker’s bureau for Abbott, Addrenex, AstraZeneca, Biovail, Bristol-Myers Squibb, Forest, GlaxoSmithKline, Johnson and Johnson, KemPharm Lilly, Lundbeck, Neuropharm, Novartis, Organon, Otsuka, Pfizer, Sanofi-Aventis, Sepracore, Shire, Solvay, Supernus Pharmaceuticals, Validus, and Wyeth.

Abstract

Over the 2004 through 2008 period, total second-generation antipsychotic prescriptions grew 33 percent from 6.9 million to 9.2 million; second-generation antipsychotic prescriptions for patients under age 18 also increased, but at a slightly slower rate: 24-percent increase from 1.0 million to 1.2 million prescriptions. One-third of patients under age 18 who are prescribed second-generation antipsychotics use them for the treatment of affective psychoses, primarily bipolar disorder (34%). Other common uses for second-generation antipsychotics include hyperkinetic syndrome (12%), pervasive developmental disorders (10%), emotional disorders of children/adolescents (10%), and conduct disturbance (7%). A discussion of the data is provided.

Key Words

Children, adolescents, second-generation antipsychotics, bipolar disorder, hyperkinetic syndrome, pervasive developmental disorders, conduct disorder, emotional disorder

Introduction

Although second-generation antipsychotics are being studied for an increasing number of indications, questions regarding the safe use of antipsychotics in children and adolescents remain. In this article, we examine trends in prescriptions of second-generation antipsychotics overall and in pediatrics specifically.

Methods

We examined quarterly retail pharmacy prescription data from SDI/Verispan from January 2004 through December 2008. The data capture more than 1.4 billion patient-centric prescriptions per year, nearly half of all prescription activity in the US. We also obtained data on reasons for product use from SDI/Verispan’s Prescription Drug and Diagnosis Audit (PDDA) database for patients taking second-generation antipsychotics in 2004 through 2008. PDDA captures data on disease state and associated therapy from 3,100 office-based physicians representing 29 specialties across the United States.

Results

Figure 1 displays quarterly growth trends for the overall market and for prescriptions in patients under age 18. Over the 2004 through 2008 period, total second-generation antipsychotic prescriptions grew 33 percent from 6.9 million to 9.2 million. Second-generation antipsychotic prescriptions for patients under age 18 also increased, but at a slightly slower rate: 24-percent increase from 1.0 million to 1.2 million. Reasons for the use of second-generation antipsychotics in patients under the age of 18 are shown in Figure 2. As seen in Figure 2, one-third of patients under age 18 use second-generation antipsychotics for the treatment of affective psychoses, primarily bipolar disorder (34%). Other uses for second-generation antipsychotics include hyperkinetic syndrome (12%), pervasive developmental disorders (10%), emotional disorder of children/ adolescents (10%), conduct disturbance (7%), and schizophrenia ( 3%). Although total prescriptions for second-generation antipsychotics have increased steadily over the past few years, the reasons for use did not change between 2004 and 2008.

Expert Commentary
by Robert Findling, MD

The observation that second-generation antipsychotics are being prescribed to youths at increasing rates is an important one. This may be due, in part, to the fact that there is a growing body of evidence from clinical trials that has described that many of these agents have acute efficacy in youngsters suffering from a variety of conditions. However, because these medications may be associated with substantive side effects, it is important to know more about the young patients that are having these agents prescribed to them. It is also very relevant to characterize the effects, both salutary and detrimental, that these drugs are having on young people in real-world settings.

The reasons for use that are described in this article begin to provide some information about the diagnoses given to youths who are prescribed these medications. However, it is important to point out the potential limitations of diagnostic data obtained from such sources. For example, only diagnoses for which insurance coverage is available may be listed. As a result, some secondary or comorbid “uncovered” diagnoses may not be listed. Therefore, the primary reason for which the antipsychotic is being prescribed may not be available. Similarly, treatment history is not always readily forthcoming from such data sources. It might be important to know whether or not these patients have been prescribed second-generation antipsychotics as first-line treatment, or whether they have failed other interventions (both pharmacological and nonpharmacological). Another issue of note is that a substantive number of these young people have been given the diagnosis of bipolar disorder. Considering the large increase with which this diagnosis is being applied to youths, diagnostic accuracy may also be an important empiric question.

Regardless of the limitations of these data, it appears reasonably clear that youngsters are indeed being prescribed second-generation antipsychotics in real-world settings at higher rates. Due to the putative risks associated with these agents as well as the limitations of the extant data pertaining to these compounds, more needs to be learned about who is receiving these agents. In addition, a thorough characterization of the treatment outcomes and risks associated with these drugs could provide much-needed data. With such information, prescribers, youths, and their families will have available to them important facts that could assist them in making treatment decisions regarding second-generation antipsychotics as a treatment option.

Professor of Psychiatry, SUNY Upstate Medical University, Syracuse, New York; and Clinical Professor of Psychiatry, Tufts University School of Medicine, Boston, Massachussetts
Psychiatry (Edgemont) 2009;6(6):29–37

Financial Disclosure

Dr. Pies reports no relevant conflicts of interest or commercial ties with respect to this material.

Abstract

There is neurobiologically based, theoretical support for the use of antipsychotic medications in the treatment of anxiety, and two first-generation neuroleptics are approved by the United States Food and Drug Administration for the treatment of nonpsychotic anxiety. However, neuroleptics are associated with a large side effect burden, which has limited their utility in the treatment of nonpsychotic disorders. Because of their somewhat improved safety profile, atypical antipsychotics are increasingly used for the treatment of nonpsychotic anxiety. The published literature describing the efficacy of atypical antipsychotics in randomized, controlled trials involving patients with anxiety disorders is briefly reviewed, and the safety of atypical antipsychotics in nonpsychotic disorders is discussed. There is moderately strong controlled evidence supporting the use of some atypical antipsychotics, either as adjunctive treatment or monotherapy, in the treatment of nonpsychotic anxiety; however, the side effect burden of some atypical antipsychotics probably outweighs their benefits for most patients with anxiety disorders. The evidence to date does not warrant the use of atypical antipsychotics as first-line monotherapy or as first- or second-line adjunctive therapy in the treatment of anxiety disorders. Rigorous, independently funded, long-term studies are needed to support the off-label use of atypical antipsychotics in the treatment of anxiety disorders. Nevertheless, some patients with highly refractory anxiety disorders may benefit from the judicious and carefully monitored use of adjunctive atypical antipsychotics. A careful risk-benefit assessment must be undertaken by the physician, on a case-by-case basis, with appropriate informed consent.

Key Words

atypical antipsychotic, anxiety disorder, posttraumatic stress disorder, obsessive-compulsive disorder, generalized anxiety disorder, social anxiety disorder, off label, tardive dyskinesia, neuroleptic malignant syndrome, extrapyramidal side effects

Introduction

Consider the case of Ms. B, a 37-year-old mother of two with a 20-year history of severe generalized anxiety disorder (GAD) diagnosed by current Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. She saw four different psychotherapists since her condition began and received both cognitive-behavioral and psychodynamically oriented psychotherapy. In addition, Ms. B was prescribed adequate courses of three different benzodiazepines, two tricyclic antidepressants, and three selective serotonin reuptake inhibitors (SSRIs) over the past decade. The most effective pharmacologic treatment in Ms. B’s history was a very brief course of thioridazine (50mg/day) in the late 1980s, which was discontinued owing to complaints of dry mouth, constipation, and severe dizziness.  Although she experienced modest improvement on a number of the other medication regimens, Ms. B remained “…wound up all the time, like my muscles are in knots…” and experienced restlessness, fatigue, difficulty concentrating, irritability, and difficulty falling asleep. Ms. B added, “I know it’s neurotic, but I’m always waiting for the next shoe to drop—like something bad is going to happen to me or the kids, even though life is great.” There was no evidence of a frank psychotic or delusional disorder, and Ms. B did not fit DSM-IV criteria for dysthymia or major depression. All laboratory and medical investigations turned up no abnormalities, and there was no history of drug or alcohol misuse. Ms. B said she “…saw on the internet that these new atypicals” were useful for anxiety and wanted to know if she could begin taking one.

Is it reasonable to try one of the atypical antipsychotics for a patient like Ms. B? What theoretical and empirical justification is there for using an antipsychotic for a nonpsychotic condition? What do the controlled data show, with respect to the efficacy of atypical antipsychotics (AAPs) for anxiety disorders, either as adjunctive treatment or monotherapy? What are the medical risks of using AAPs off label in such cases? These questions are the focus of the present commentary.

This article is not a comprehensive review of pharmacologic or nonpharmacologic treatment of anxiety; rather, it represents the author’s synthesis and recommendations regarding the use of AAPs for specific anxiety disorders. For a more fine-grained analysis of the research data, two recent comprehensive reviews are referenced.[1,2]

Historical Perspective

Recently graduated residents in psychiatry may not be aware that two pharmacologic “dinosaurs”—both conventional neuroleptics—have US Food and Drug Administration (FDA)-approved labeling for the treatment of anxiety. Trifluoperazine is approved for short-term treatment of generalized, nonpsychotic anxiety, though not as “initial therapy;” and perphenazine (in combination with the tricyclic antidepressant amitriptyline Triavil) is approved for “treatment of depression and anxiety.” Though a review of “typical” antipsychotics (neuroleptics) is beyond the scope of this commentary, it is noteworthy that 15 years elapsed between the landmark 1986 study by Mendels et al of trifluoperazine[3] and the FDA-approved labeling of this agent for short-term treatment of GAD in 2001.2 One wonders whether this reflected some ambivalence on the part of the FDA reviewers, but this author was unable to discover any explanation for the delay (K. Gao MD, personal communication, 3/09/09).

The Mendels study was a large (n=415), randomized, double-blind, placebo-controlled trial of trifluoperazine (2–6mg/day). The active drug was superior to placebo on all outcome measures, including the Hamilton Anxiety Scale. The Mendels study avoided many methodological problems with similar studies done in the early 1980s[2] and encouraged the view that at least some antipsychotics have significant anxiolytic properties. However, the Mendels study followed patients for only four weeks; and, to this day, there are few, if any, long-term safety data on the use of standard neuroleptics as anxiolytics. Indeed, the FDA’s own caveats for trifluoperazine suggested potential problems with long-term use of typical antipsychotics as anxiolytics. The labeling information states that “Stelazine is not the first drug to be used in therapy for most patients with nonpsychotic anxiety because certain risks associated with its use are not shared by common alternative treatments (i.e., benzodiazepines).”[4]

As we shall see, these risks are not necessarily eliminated when AAPs are considered (see “Medical Risks”). Indeed, despite encouraging—but as yet unpublished[5–8]—controlled data supporting the use of quetiapine for nonpsychotic anxiety, no AAP has FDA-approved labeling for any anxiety disorder, as of this writing. In April 2009, the FDA Psychopharmacologic Drugs Advisory Committee (PDAC) conducted a review of supplemental new drug applications (sNDAs) for AstraZeneca’s Seroquel XR (quetiapine fumarate extended-release tablets). The sNDAs were proposed for the treatment of major depressive disorder (MDD) and GAD. Essentially, the PDAC concluded that Seroquel XR was effective in MDD as both monotherapy and adjunctive therapy; and also effective in GAD as monotherapy. But whereas the PDAC found the drug acceptably safe as an adjunctive treatment for MDD, the committee did not find Seroquel XR acceptably safe as monotherapy for “broad treatment” of MDD, nor acceptably safe as monotherapy for the treatment of GAD. While a detailed discussion of the PDAC’s deliberations are beyond the scope of this review, specific concerns as to the safety of Seroquel XR in GAD may be found at: http://www.fda.gov/ohrms/dockets/ac/09/transcripts/2009-4424t2-part1.pdf

Theoretical Foundation for AAP Use in Nonpsychotic Anxiety

Anxiety is a complex human phenomenon, with multiple biological, psychological, and sociocultural components. From a medical standpoint, the complexity of anxiety is aptly summarized by Tefera and Tomao,[9] as such: “Anxiety is a complex feeling of apprehension, fear, and worry often accompanied by pulmonary, cardiac, and other physical sensations. It is a common condition that can be a self-limited physiologic response to a stressor, or it can persist and result in debilitating emotions. When pathologic, it can exist as a primary disorder, or it can be associated with a medical illness or other primary psychiatric illnesses (e.g., depression, psychosis).”

It would be naïve to suggest that we fully understand the pathophysiology of severe anxiety states, much less that all the DSM-IV anxiety disorders arise from the same biochemical aberration or abnormality. The neurobiological basis of anxiety is comprehensively reviewed by Charney and Drevets.[10]

Notwithstanding anxiety’s diverse origins, there appears to be pathophysiological derangements that accompany many types of severe anxiety and which bear on the relevance of AAPs as anxiolytics. Thus, there is ample evidence that aberrant g-aminobutyric-acid (GABA) circuits are integrally involved in anxiety disorders.[11] In crude terms, there appears to be reduced GABAergic function in some severe anxiety states. But the situation is far more complex. For example, as Charney and Drevets[10] show, neuropeptide Y, substance P, the monoaminergic neurotransmitters (norepinephrine, serotonin, dopamine), and glutamate are almost certainly involved in the pathophysiology of anxiety. Most likely, there are important differences among the various anxiety disorders with respect to the relative contributions of these neurochemicals. For example, there is little evidence that dopaminergic dysfunction plays a primary role in most anxiety disorders, including panic disorder.[10] However, there is some evidence of reduced dopamine-receptor binding in social phobia.[12] And in combat-related posttraumatic stress disorder (PTSD), there is preliminary evidence that susceptibility is associated with a polymorphism in the DRD2 gene—the gene that encodes the D2 type of dopamine receptor.[13]

In any case, because the AAPs have very broad pharmacodynamic effects, there are many ways in which the AAPs could influence anxiety—and not necessarily or reliably in a favorable direction. Thus, AAPs appear to have complex and perhaps regionally specific effects on GABA in the brain, based on in-vitro and animal models. For example, clozapine appears to antagonize GABAA receptors in cultured neurons,14 which would not point to anxiolytic properties, all other things being equal. On the other hand, some evidence suggests that olanzapine counteracts stress-induced, anxiety-like behavior in rats15 via an indirect effect on the GABAergic system. This seems to be mediated by olanzapine’s effects on allopregnanolone, a neuroactive steroid that activates the GABAA receptor complex.

The AAPs have complex effects on dopamine and dopamine receptors, depending on the specific drug. Thus, risperidone binds “tightly” and chronically to D2 receptors, whereas quetiapine and olanzapine appear to have a “fast-off” action at D2 receptors, thus mitigating their D2 antagonism.[16] This may partly account for the reduced likelihood of extrapyramidal side effects and akathisia with quetiapine or olanzapine use, compared with risperidone or conventional neuroleptics—though these findings are variable and dose related. As we shall see, akathisia may be a cause of severe anxiety or agitation. Finally, the AAPs also have histamine receptor antagonist properties to varying degrees, and both animal and human data suggest that the histaminergic system is implicated in anxiety states.[17]

Aripiprazole is unusual among the AAPs in having partial agonism at the D2 receptor, suggesting that its effects may vary with ambient dopamine levels. Aripiprazole shares with the other AAPs antagonist effects at the serotonin 2A (5-HT2A) receptor; however, aripiprazole also has partial agonist activity at the 5-HT1A receptor,[18] which is known to be involved in anxiolysis. For example, the approved anxiolytic buspirone probably exerts some of its effects by acting as a 5-HT1A partial agonist.[19]

What is the upshot of all these complex neurochemical nuances? In the author’s view, the possible interactions between AAPs and the neurochemicals that mediate anxiety are too complex to predict the effect of AAPs on anxiety. It is even more hazardous to predict an AAP’s effect on any given anxiety disorder, since the pathophysiology probably varies among these disorders. There is also no reason to assume that the AAPs have consistent “class effects” on anxiety, as each agent has a distinct pharmacodynamic profile. Thus, we will need empirical investigations of specific AAPs in specific anxiety disorders to learn which agents are useful in treating which disorders. That said, there are theoretical reasons to hypothesize that some AAPs may have beneficial effects on some types of anxiety, with the caveat that AAPs might actually worsen anxiety in some cases—for example, by inducing akathisia.

Synopsis of Published Controlled Studies of AAPs in Anxiety Disorders

Investigations of AAPs as anxiolytics consist mainly of adjunctive therapy studies, with only a few studies of AAP monotherapy. This commentary will focus on randomized, double-blind, placebo-controlled trials [RCTs] of specific anxiety disorders—not on anxiety as a symptom in the context of other diagnoses. Since most data are derived from studies of GAD, refractory obsessive-compulsive disorder (OCD), PTSD, and social anxiety disorder (SAD), we will focus on published studies of these conditions. More detailed reviews are provided by Bandelow et al[1] and Gao et al.[2] Nonpublished presentations or abstracts are also briefly discussed.

The general findings of the present review are summarized in Table 1 Table 1b. Many of these studies have small sample sizes (n=7–70) and must therefore be considered preliminary findings. Since there are no “head-to-head” comparisons of AAPs, it is also premature to conclude that any particular AAP is a “drug of choice” for the adjunctive treatment of anxiety disorders. In gross numerical terms—and with the caveat that we are lumping together heterogeneous studies—the number of studies favoring drug over placebo is as follows: quetiapine, 2 of 5; olanzapine, 4 of 6; and risperidone, 8 of 10. While this tally might suggest that risperidone has more robust anxiolytic effects than the other agents studied, RCTs using a head-to-head design are needed to confirm this preliminary impression. Moreover, risperidone may be less useful in GAD than in either refractory OCD or PTSD. To the author’s knowledge, there are no published RCTs using aripiprazole or ziprasidone in specific anxiety disorders, though aripiprazole appears to be effective adjunctively in patients with major depression presenting with anxious features.[20]

Medical Risks of Using AAPs Off Label for Anxiety

In recent years, several reports have emerged involving pharmaceutical company promotion of unsupported off-label use of AAPs and other psychotropics.[42] This is troubling from a clinical, ethical, and legal perspective. While there is nothing wrong with judicious off-label prescribing under certain carefully defined conditions, the use of AAPs for anxiety disorders raises a number of concerns. First, as the foregoing review suggests, there are only preliminary published data supporting the use of AAPs in anxiety disorders. Of the RCTs reviewed, one third (7 of 21) yielded no significant benefit of the AAP compared with placebo.

It should be noted that in data from several randomized, controlled—but unpubished—studies submitted to the FDA (see http://www.fda.gov/ohrms/dockets/AC/09/briefing/2009-4424b2-03-AstraZeneca.pdf) quetiapine fumarate extended-release tablets showed similar efficacy (i.e., small to moderate effect size) compared with other anxiolytic agents (personal communication, K. Gao MD, 5/15/09); quetiapine also appeared generally well-tolerated.  Nevertheless, there are substantial medical risks associated with the use of antipsychotic medications, including the so-called atypical agents. (Some clinicians, noting more pharmacodynamic similarities than differences between older neuroleptics and AAPs, have urged the abandonment of the term atypical antipsychotic.) Some of these risks are also associated with substantial medicolegal liability.

Posternak has recently reviewed the medical risks associated with AAPs.[43] Contrary to the impression of some clinicians, AAPs have not eliminated serious risks commonly associated with older neuroleptics, including tardive dyskinesia (TD) and neuroleptic malignant syndrome (NMS). Although TD rates are lower with AAPs than with most first-generation neuroleptics—the annual incidence rates in adults are roughly 0.8% and 5.4%, respectively—a psychiatrist treating 100 patients with AAPs could still expect to see one case of AAP-related TD per year—and rates are likely higher in elderly patients.[43,44]

Most data showing AAP-associated extrapyramidal side effects (EPS) and TD rates are derived from patients with schizophrenia. There is no reason to assume that these relatively low rates will hold true for patients with anxiety (or affective) disorders. Recently, for example, Gao et al[45] found that patients with bipolar depression are more vulnerable to acute EPS than those with bipolar mania or schizophrenia during antipsychotic treatments.
Equally worrisome, and much more common than TD or NMS, are metabolic complications associated with the AAPs, such as weight gain or glycemic and lipid abnormalities.[46] Metabolic syndrome (usually defined in terms of weight gain, hypertension, fasting hyperglycemia, and dyslipidemia) may occur in as many as 25 percent of patients treated with olanzapine or risperidone, depending on criteria used.[47] Distinctions among the AAPs should be noted, however. For example, Newcomer’s review[46] concluded that “…clozapine and olanzapine treatment are associated with the greatest risk of clinically significant weight gain,” whereas there is “…no evidence at this time to suggest that ziprasidone and aripiprazole treatment are associated with an increase in risk for diabetes, dyslipidemia or other adverse effects on glucose or lipid metabolism.” It appears likely that risperidone and quetiapine pose an intermediate level of overall metabolic risk,[46] but there is a paucity of prospective, head-to-head (comparative) data on this point.

Recently, the cardiac side effects of the AAPs have been described, including increased risk of arrhythmia and sudden cardiac death; however, this risk is apparently at least as high with older neuroleptics.[43,48] The tendency of most AAPs to increase the QTc interval—albeit in a small proportion of patients49—may be clinically significant in a subgroup of patients with pre-existing long QTc, or those taking concomitant drugs that inhibit metabolism of the AAP. Finally, the risk of medication abuse and dependence, although rarely associated with antipsychotic medications, has become a concern with several AAPs, particularly olanzapine50 and quetiapine.[51] Once again, prospective, head-to-head comparisons are needed to detect genuine differences in abuse liability among the AAPs.
In short, the medical risks of AAPs among patients with psychotic disorders are far from rare or trivial.  We may not be able to infer rates of AAP side effects in patients with anxiety disorders based on such reports, but a conservative operating assumption would hold that comparable risks exist for patients with anxiety disorders.

Conclusions and Recommendations

Based on a review of published RCTs, there is moderately strong evidence that several atypical antipsychotic agents may have significant anti-anxiety effects, when used as adjunctive treatment in some anxiety disorders. The evidence from published studies appears to be most robust for adjunctive risperidone in the treatment of refractory OCD and PTSD, but further RCTs using a head-to-head design are needed. If unpublished data on quetiapine fumarate are confirmed in independently funded RCTs, this agent could hold promise in the treatment of refractory GAD.

Nonetheless, in this reviewer’s opinion, the evidence to date does not warrant the use of AAPs as monotherapy in the treatment of anxiety disorders. Neither do the studies reviewed support the use of AAPs as either first- or even second-line agents in the adjunctive treatment of anxiety disorders. There are, in the first place, many effective agents (including SSRIs, SNRIs, benzodiazepines, and buspirone) that already have FDA-approved labeling for the treatment of anxiety disorders and which have a more favorable risk-benefit ratio, compared with AAPs. The medical risks associated with AAPs may vary from agent to agent and disorder to disorder in unpredictable ways. For example, in the only study of bipolar disorder and co-occuring panic disorder or GAD, Sheehan et al[26] found not only that risperidone was not superior to placebo in reducing anxiety symptoms, but also that it actually worsened anxiety in some patients with panic disorder.

In the absence of frank psychotic symptoms, refractory anxiety disorders should be treated by means of drug substitution within a given class of agents, such as switching to a different SSRI or SNRI or with combinations of agents already approved for treatment of anxiety disorders, such as combined SSRI/benzodiazepine treatment. Forms of psychotherapy known to be effective in anxiety disorders—such as cognitive-behavioral therapy—should also be offered to the patient prior to considering an AAP.1 In the author’s opinion, AAPs should be reserved as “third-line” agents for patients who do not respond to already-approved anxiolytics and/or psychotherapy or who are poor candidates for approved and validated treatments. For example, Ms. B—who had poor results from adequate courses of three different benzodiazepines, two tricyclic antidepressants, and three SSRIs—would be an appropriate candidate for an AAP trial, assuming she had no medical contraindications. (An EKG to rule out a long QTc would probably be prudent). Other appropriate candidates for an AAP trial could include markedly anxious patients who refuse psychotherapy or who have relative contraindications to SSRIs, buspirone, or benzodiazpines (e.g., patients with histories of alcohol or other substance abuse would generally not be good candidates for benzodiazepine treatment.) The physician must weigh such factors on a case-by-case basis, calculating as carefully as possible the overall risk-benefit ratio of the proposed treatment.

Informed consent is particularly important when AAPs are prescribed off label, especially given rare but serious risks, such as NMS or TD. Medicolegal risks of such off-label prescribing should also be considered. More common problems, such as weight gain, metabolic dysfunction, and cardiac abnormalities, must be carefully considered, with appropriate clinical and laboratory monitoring for such effects. Nonetheless, with careful assessment, close monitoring, and appropriate informed consent, some patients with refractory anxiety disorders are likely to benefit from adjunctive treatment with AAPs.

Acknowledgments

The author wishes to thank Dr. Keming Gao and Dr. David Osser for their helpful comments on earlier drafts of this manuscript and Ms. Chantelle Marshall for her assistance with editing. The views expressed here are solely those of the author.

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48.    Ray WA, Chung CP, Murray KT, et al. Atypical antipsychotic drugs and the risk of sudden cardiac death. N Engl J Med. 2009;36:225–235.
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Drs. Moturi and Ivanenko are from the Division of Child and Adolescent Psychiatry, Children’s Memorial Hospital, Chicago, Illinois. Dr. Ivanenko is also from the Children’s Memorial at Central DuPage Hospital, Winfield, Illinois.

Psychiatry (Edgemont) 2009;6(6):38–44

Funding

There are no sources of financial support for preparation of this manuscript.

Financial disclosure

The authors report no relevant conflicts of interest or commercial ties with respect to this material.

Abstract

Narcolepsy is an uncommon chronic, neurological disorder characterized by abnormal manifestations of rapid eye movement sleep and perturbations in the sleep-wake cycle. Accurate diagnosis of psychotic symptoms in a person with narcolepsy could be difficult due to side effects of stimulant treatment (e.g., hallucinations) as well as primary symptoms of narcolepsy (e.g., sleep paralysis and hypnagogic and/or hypnapompic hallucinations). Pertinent articles from peer-reviewed journals were identified to help understand the complex phenomenology of psychotic symptoms in patients with narcolepsy. In this ensuing review and discussion, we present an overview of narcolepsy and outline diagnostic and management approaches for psychotic symptoms in patients with narcolepsy.

Key Words

psychosis, narcolepsy, comorbidity, stimulants, antipsychotics

Overview of Narcolepsy

Individual who experience rapid eye movement (REM) phenomena, such as hallucinations, associated with narcolepsy may be misdiagnosed as having schizophrenia,[1] and such misdiagnosis tends to occur even in childhood.[2] Treatment of narcoleptic symptoms, such as excessive daytime sleepiness (EDS), with stimulant medications (e.g., amphetamine and methylphenidate) may result in new-onset psychotic symptoms related to initiation (or dose escalation) of such medications.

In children, emotional reactions to frightening hallucinatory phenomena (and to sleep paralysis) can be misconstrued as sleep terrors, nightmares, or panic attacks.[3] Children may resist going to bed or falling asleep due to prior frightening hallucinatory experiences (negative associations), and parents could perceive this as oppositional behavior. Children and adolescents with narcolepsy report embarrassment, academic decline, loss of self worth, and avoidance of social situations that might precipitate cataplexy or draw attention to the patient’s somnolence.[3]

Narcolepsy may be misdiagnosed as epilepsy due to the presence of sleep attacks and/or unresponsiveness during periods of hypersomnolence or cataplexy.[4] In adults, diagnostic confusion may exist between attention deficit hyperactivity disorder (ADHD) and hypersomnias of central origin (idiopathic hypersomnia and narcolepsy), especially when the conditions co-occur and self-report questionnaires are used.[5]

When underlying narcolepsy remains undiagnosed and the patient presents with vivid hallucinations, the patient may experience legal consequences (e.g., false accusations, work-place conflicts) due to impaired reality testing.[6] Family and friends may misconstrue patients with narcolepsy as being emotionally unstable, lazy, and irresponsible,[7] often leading to feelings of guilt and anger in the patient as well as poor self esteem.

Clinicians should be aware that perceptual disturbances like hypnic hallucinations restricted to awakening and falling asleep are not sufficient to diagnose the patient with a psychotic disorder. A detailed sleep history with focus on timing and relationship of such hallucinations to sleep can provide a clue to the true nature of these symptoms. Furthermore, a primary psychotic disorder, such as schizophrenia, can occur comorbidly with narcolepsy, leading to a diagnostic and therapeutic challenge for clinicians.

Narcolepsy and psychosis

Narcolepsy is an uncommon chronic, neurological disorder characterized by chronic sleepiness, markedly disorganized sleep-wake behaviors, and abnormal manifestations of REM sleep.[8] Incidence of narcolepsy usually peaks in adolescence or early adulthood, and prevalence in the general population appears to vary with ethnicity and familial risk. The estimated prevalence is as low as 0.002 percent in the Israeli population, as high as 0.02 percent in the Japanese population, and up to five percent in families with significant genetic predisposition.[9] The age of onset varies from early childhood to the 50s, with two peaks: a larger peak that occurs at around 15 years of age and a smaller peak at approximately 36 years of age.[10]

The pathophysiology of narcolepsy appears to be related to deficiency of hypocretin neurons in the hypothalamus secondary to a degenerative process like gliosis.[11] According to the International Classification of Sleep Disorders (ICSD) criteria,[12] narcolepsy is usually diagnosed by the following classic tetrad of symptoms: EDS, inability to move after awakening in conscious state (sleep paralysis), sudden loss of muscle tone (cataplexy), and REM phenomena (e.g., hypnagogic and hypnapompic hallucinations).

Hypnagogic hallucinations occur during the “falling asleep” phase (more common) and hypnapompic hallucinations occur during the “awakening from sleep” phase (less common). Diagnosis of narcolepsy without cataplexy can be made in the presence of EDS if one of the associated symptoms (hypnagogic hallucinations, automatic behaviors, sleep paralysis, and/or disrupted sleep) is present together with the following polysomnographic abnormalities: average sleep latency less than eight minutes or presence of two sleep-onset REM periods (SOREMPs) during the multiple sleep latency test (MSLT).

The regular MSLT consists of five naps at two-hour intervals, usually scheduled after six hours of sleep the night prior to MSLT. SOREMPs are associated with onset of REM sleep within 15 minutes after sleep onset. Human leukocyte antigen (HLA) typing showing the association with HLA DQB1*0602 is supportive of the diagnosis, but the specificity of DQB1*0602 positivity is low for narcolepsy. Low CSF hypocretin levels (110pg/mL; one-third of mean control value) can often aid in diagnosis, especially if cataplexy is present.[13] Most low levels of CSF hypocretin tend to correlate with narcolepsy associated with cataplexy and HLA DQB1*0602 positivity.[14]

Multiple case reports describe the difficulties of diagnosing psychotic symptoms in presence of narcolepsy.[15–17] Psychotic symptoms in patients with narcolepsy have the following three possible explanations: co-occurring primary psychotic illness (e.g., schizophrenia),[15-20] an iatrogenic occurrence due to treatment with stimulants,[16] or a narcoleptic psychosis viewed as delusional elaboration of hypnic hallucinations.[1,17] Patients with narcolepsy who experience prominent REM phenomena, such as hypnic hallucinations, may attach significance to a particular vivid hallucination, often followed by attempts to explain the hallucination. This could lead to delusional explanations of such hallucinatory experiences. Such patients may exhibit bizarre and disorganized behaviors suggestive of a primary psychotic illness. Patients with episodes of sleep paralysis in narcolepsy have described such episodes as “electricity shooting through the body” and described vivid visual hallucinations (e.g., “aliens standing next to my bed”). These episodes were associated with ensuing patient narratives, such as being “abducted by aliens.” It appears that these narratives have significant cultural influences.[21] A specific example of this is in patients who experience breathing difficulties and sleep paralysis. These events have been described by patients as a person sitting on their chests (vivid hallucination). The specific description of who is “sitting” on the patient’s chest within the narrative may vary from culture to culture (e.g., an old hag or witch may be described by a patient in Newfoundland or the US while “kanashibari,” a term related to supernatural powers, may be described by a patient in Japan).[22]

It has been suggested that about seven percent of patients with a diagnosis of schizophrenia actually have a psychotic variant of narcolepsy;[1] however, larger studies to confirm these findings are lacking. Although an earlier study showed that patients with schizophrenia were four times as likely to have narcolepsy-associated antigens, such as HLA DR15 and DQ6, compared to normal controls,[23] there appears to be insufficient evidence at this time to suggest any shared pathology between narcolepsy and psychotic illnesses. In this regard, studies into rare genetic syndromes, such as succinic semialdehyde dehydrogenase deficiency (g-hydroxybutyric aciduria), which present with neurological deficits (e.g., hypotonia, seizures, impaired language development, psychotic symptoms in adolescence and late-adulthood, and sleep difficulties consistent with narcolepsy) may help provide further insights into possible neurobiological interactions between psychosis and narcolepsy.[24] However, Walterfang et al25 argue against a specific narcoleptic form of psychosis in an extensive review. They point out that the following pathological mechanisms are largely absent in primary psychotic disorders compared to narcolepsy: significant REM sleep phenomena, associations with HLA antigens like HLA DR15, DQ6 and DQB1*0602 (an allele of DQ1), TNF-alpha gene polymorphisms, and evidence of hypocretin neuron disruption.[25]

Thus, the key diagnostic challenges in co-occurring narcolepsy and psychosis would be the following: A) to distinguish the psychosis-like symptoms of narcolepsy (REM sleep-related hallucinations) from positive symptoms of schizophrenia, and/or B) to establish a temporal relationship between initiation of stimulant medications and onset and continuation of psychotic symptoms or, conversely, reduction in psychotic symptoms upon cessation of stimulants.

Stimulant-induced psychosis

A recent review by the US Food and Drug Administration (FDA) of all pharmaceutical company-sponsored trials reveals that “transient psychotic states” (hallucinosis) occur in 0.25 percent of children on stimulants (1 in 400). These hallucinations tend to wane 3 to 7 days after discontinuation of the stimulant.[26]

A more recent review of manufacturers’ data by the FDA in children at risk of psychosis and/or mania with stimulants showed an average rate of adverse events, such as psychosis and mania, at 1.48 per 100 persons in a year. A total of 865 case reports of psychosis, mania, or similar events were identified in post-marketing surveillance with the most common symptoms of hallucinations related to stimulants being “visual and/or tactile” hallucinations.[27]

Another review found the presence of psychotic symptoms in chronic amphetamine-dependent patients to be as high as 40 percent, mostly at higher doses. One to 15 percent of these patients experienced continued psychotic symptoms even after several days of abstinence.[28]

Psychosis during treatment of narcolepsy with stimulants is dose dependent (i.e., it is less likely at low doses and more likely at high doses and with chronic treatment).[28] However, most patients with narcolepsy treated with high-dose methylphenidate for an extended period of time do not develop psychosis.[29,30]

Chronic use of stimulants results in reduction in dopamine transporter density[31,32] and possibly a persistent hyperdopaminergic state. Although it can be argued that this persistent hyperdopaminergic state could be responsible for evolving psychotic symptoms in patients with narcolepsy and chronic stimulant therapy, vulnerability studies have not established duration criteria that define such a relationship.

Whether emergence of psychosis in patients treated for narcolepsy with licit doses of stimulants might indicate an underlying biological vulnerability to psychosis is largely unknown. A common neurobiological pathway for such a model is unclear, although it is possibly mediated via the dopaminergic system,[33,34] and genetic factors also appear to have a mediating role in emergence of psychotic symptoms during treatment with stimulants.[35]

A systematic review of stimulant psychosis showed that 50 to 70 percent of patients with schizophrenia or history of acute psychosis with stimulants show a worsening in response to a single dose of stimulant, even when such patients have been adherent with an antipsychotic medication. The authors point out that although the long-term effect of stimulants on sensitization is unknown, continued antipsychotic treatment at low doses may prevent the development of chronic, persistent psychosis.[36] This conclusion may thus have therapeutic implications for patients with comorbid narcolepsy and psychotic disorder.

Differentiating core symptoms of psychosis from symptoms of narcolepsy

Criteria for distinguishing whether psychotic symptoms represent hypnic experiences of narcolepsy or a primary psychotic disorder have been elaborated in a study comparing 148 narcoleptic patients to 21 patients with acute schizophrenia and 128 healthy controls.[37] In this study, hallucinations in narcolepsy (compared to hallucinations in schizophrenia) were sleep-related (up to 80% of the experiences) and were associated with other symptoms of narcolepsy; they were posture-dependent (increased in supine position), unlike in schizophrenia wherein hallucinations are not posture-dependent; and the content of hallucinations in narcolepsy was of “visual-kinetic” quality (e.g., “I felt like I was flying or falling,” or “I felt like someone was in the room with me”), whereas in schizophrenia, hallucinations are mostly auditory.

A recent study utilizing schedules for clinical assessment in neuropsychiatry (SCAN 2.1) to compare psychotic symptoms between 60 patients with narcolepsy, 102 patients with schizophrenia, and 120 matched population controls concluded that hallucinations in patients with narcolepsy, compared to patients with schizophrenia, tend to be sleep-related, multimodal or holistic in nature (i.e., combination of visual, auditory, tactile), and were associated with reduced frequency of concurrent delusions.[38] Compared to population controls, patients with narcolepsy were not shown to have increased prevalence of formal psychotic disorders in this study.

Early reports of dream-like or hallucinatory experiences in narcolepsy noted the preponderance of the following descriptions: flying, falling, and skimming or sliding during cataplexy episodes.[39,40] Such visual-kinetic experiences could represent REM sleep intrusion into wakefulness, often accompanied by nonvolitional REM leading to sensations of flying. Such vivid visual-kinetic experiences are rare in patients with schizophrenia.

Diagnostic and treatment complexities

According to the American Academy of Sleep Medicine (AASM), practice parameters for treatment of narcolepsy,[41] modafinil, sodium oxybate, amphetamine, methamphetamine, dextroamphetamine, methylphenidate, and selegiline are effective treatments for excessive sleepiness. The AASM practice parameters recommend tricyclic antidepressants and fluoxetine for cataplexy, sleep paralysis, and hypnagogic hallucinations associated with narcolepsy. Levels of recommendations, however, within these parameters are varied for each of these medications due to differences in published clinical evidence supporting their uses.

In patients presenting with comorbid narcolepsy and psychotic symptoms, diagnosis of narcolepsy should be confirmed using criteria set forth by AASM in the ICSD-2.[12] Once diagnosis of narcolepsy is confirmed, the question remains as to whether the psychotic symptoms are hypnic hallucinations of narcolepsy, stimulant-induced, or ‘chance’ comorbidity of a primary psychotic disorder. A clear temporal relationship between initiation or dose increase of a stimulant and a paranoid hallucinatory state is usually present in stimulant-induced psychosis. Therefore, an initial step to establish a temporal relationship between the onset of psychotic symptoms and dose initiation/escalation of stimulants should be undertaken. If such a relationship is unable to be established after a thorough history, patients should be weaned off of stimulants gradually rather than be stopped abruptly to prevent stimulant rebound. This is particularly relevant in patients with narcolepsy who have an underlying mood disorder, such as bipolar disorder, as stimulants can precipitate/mimic affective disequilibrium,[42] although perhaps to a lesser degree than antidepressants. A careful history should, therefore, be obtained for ascertaining the presence of mood-disordered symptoms, including family history of mood disorder.

After stimulants are gradually discontinued, modafinil can be initiated and titrated to 400mg/day to target symptoms of narcolepsy. The mechanism of action of modafinil is yet to be elucidated although it was proposed that GABA, glutamate, histamine, and hypocretin systems are involved.[43] Recently, modafinil has been shown to occupy catecholamine and dopamine transporters in brain.[44] At least four double-blind, randomized trials of modafinil in narcolepsy have shown improvements in sleepiness symptoms, with continuation of improvement seen in a few open-label extension studies.[43] Caution should be exercised as modafinil was shown to be associated with mania[45,46] and psychosis[47] in case reports. Regular monitoring of symptoms of EDS using Epworth Sleepiness Scale (ESS) as well as clinical monitoring for worsening psychosis and/or affective symptoms can be useful.

Armodafinil is an R-enantiomer of modafinil with a longer half-life and was recently approved by the FDA for improving wakefulness in patients with excessive sleepiness associated with obstructive sleep apnea/hypopnea syndrome (OSAHS), narcolepsy, and shift work sleep disorder. Armodafinil appears to be well tolerated and efficacious in patients with narcolepsy at 150mg and 250mg doses;[48] however, it will not be commercially available until 2010 pending further clinical data.

If psychotic symptoms persist at least 7 to 10 days after cessation of stimulants, initiation of an antipsychotic medication should be considered. Although any antipsychotic medication can be helpful in targeting psychotic symptoms in such a complex clinical situation, aripiprazole might be potentially useful given its unique mechanism of action as a dopamine (D2) partial agonist, serotonin (5-HT1A) partial agonist, and serotonin (5-HT2A) antagonist. Recent evidence suggests that activation of postsynaptic dopamine (D1 or D2) receptors increases wakefulness, and selective stimulation of dopamine D2 autoreceptors or blockade of dopamine D1 or D2 receptors produces sedation. Activation of serotonergic 5-HT1A receptors leads to increased dopamine release in ventral tegmental area (VTA), which in turn may lead to wakefulness; however, effects of serotonergic 5-HT2A receptor activation are still unclear.[49]

In adult studies, the antipsychotics olanzapine and risperidone were shown to increase Stage 2 sleep and Delta sleep and suppress REM sleep; whereas, quetiapine appears to have lesser REM suppressant effects.[50,51] Therefore, abrupt discontinuation of these medications can result in REM rebound and REM-related hallucinations. Effects of aripiprazole on REM sleep architecture are unknown.

Possible utility of aripiprazole in comorbid psychosis and narcolepsy was hypothesized in some reviews,[15,16] but there are no published case reports of aripiprazole’s effectiveness in this clinical scenario. While aripiprazole is considered to be one of the least sedating atypical antipsychotics, caution should be exercised as it may cause sedation and worsen symptoms of narcolepsy. Case reports exist about worsening psychotic symptoms on aripiprazole.[52,53 ]Although antiadrenergic effects of aripiprazole appear to be low compared to clozapine, there is a published report on clozapine-induced cataplexy;[54] therefore, it is reasonable to monitor for worsening narcolepsy symptoms (e.g., cataplexy) in patients on aripiprazole. There are no known drug-drug interactions between modafinil and aripiprazole.

If psychotic symptoms improve but narcoleptic symptoms persist on modafinil therapy, a reasonable choice would be to rechallenge the patient with stimulants after explaining the risks and benefits of such medication. In such cases, monitoring for re-emergence of psychotic symptoms is essential. In one study, psychotic symptoms improved upon initiation of stimulants in some patients with narcolepsy, especially when these patients had worsening of symptoms on antipsychotics. These patients were misdiagnosed as having treatment resistant-schizophrenia when actually they had treatable variants of narcolepsy.[1]

Another choice to consider for narcoleptic symptoms is sodium oxybate, either as monotherapy or in addition to modafinil. Sodium oxybate is a sodium salt of the central nervous system (CNS) depressant gamma-hydroxy butyrate (GHB), and it appears to activate excitatory GHB receptors at low doses, stimulate inhibitory gamma-amino butyric acid (GABA) receptors at higher doses, and possibly cause both dopamine and serotonin release. The recommended starting dose is 4.5g a night divided into two equal doses of 2.25g, which may be adjusted up to a maximum of 9g per night in increments of 1.5g per night at 1- to 2-week intervals.[55]

In cases of narcolepsy where cataplexy presents as the major debilitating symptom in addition to EDS, sodium oxybate has demonstrated statistically significant improvements in both symptoms, either as monotherapy or in combination with modafinil, in clinical trials.[56] Clinicians should, however, note that symptoms of psychosis-like paranoia and hallucinations can be potential and infrequent side effects of sodium oxybate. Therefore, use of sodium oxybate in comorbid narcolepsy and psychosis should be avoided as much as possible. If initiated, monitoring for emergence or worsening of psychotic symptoms during the initiation and dose escalation phases should be undertaken.

GHB has high abuse potential, with notoriety for use in “date rape” and “rave parties” by adolescents and young adults. The FDA has, therefore, currently classified sodium oxybate as a schedule I substance.[57] A history of illicit substance dependence in adolescents or adults with narcolepsy can be a deterrent for initiation of sodium oxybate. However, it has been suggested in animal studies,[58] that patients with narcolepsy, in general, have a lower chance of addiction due to a deficiency in hypocretin (orexin), a hypothalamic neuropeptide that regulates sleep-wake cycle, feeding behaviors, and energy homeostasis, and was recently implicated in reward systems.[59,60] Nevertheless, given the concerns over possible diversion and abuse of sodium oxybate, a restricted drug distribution system called Xyrem Success Program was created. This system incorporates a post-marketing surveillance program that includes centralized distribution and dispensing, maintaining a registry of physicians and patients, provision of educational materials for patients and physicians, involvement of trained staff in pharmacies, and a method to track prescription shipments.[61]

Another concern with use of sodium oxybate appears to be its relatively narrow therapeutic index and risk associated with overdose. A recent review indicated that GHB withdrawal syndrome is associated with emergent delirium and psychotic symptoms that are often persistent.[62] Whether patients previously on stimulants who have experienced psychosis are more prone to delirium with sodium oxybate or GHB still remains unclear.

Conclusions

As a symptom of many psychiatric disorders across the age spectrum, sleep disturbances often complicate the course and treatment of the underlying psychiatric symptoms. Identification of symptoms of narcolepsy assumes importance due to significant implications for diagnosis, treatment, and outcomes. Bizarre descriptions of hypnic hallucinations and sleep paralysis symptoms may lead to diagnostic misinterpretations of patients as psychotic, anxious, and/or depressed. Patients may experience extensive life-threatening medical consequences if REM hallucinations lead to delusional elaboration. When primary psychotic disorders, such as schizophrenia, co-occur with narcolepsy, it can lead to significant diagnostic/therapeutic challenges, as well as worsening in psychosocial impairments (e.g., lack of self care, social withdrawal, and depressed mood). Given such the psychosocial consequences associated with co-occurring narcolepsy and psychosis, clinicians should be mindful of comorbid sleep disorders in psychiatric illnesses and the need for careful attention to routine history taking to prevent misdiagnosis and treatment approaches that may worsen either condition. This discussion regarding diagnosis and treatment of narcolepsy can be useful to monitor both primary psychotic symptoms and psychotic phenomena associated with narcolepsy, when they co-occur.

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34. Chen CK, Lin SK, Sham PC, et al. Pre-morbid characteristics and co-morbidity of methamphetamine users with and without psychosis. Psychol Med. 2003;33(8):1407–1414
35. Berman SM, Kuczenski R, McCracken JT, London ED. Potential adverse effects of amphetamine treatment on brain and behavior: a review. Mol Psychiatry. 2009;14(2):123–142. Epub 2008 Aug 12
36. Curran C, Byrappa N, McBride A. Stimulant psychosis: systematic review. Br J Psychiatry. 2004;185:196–204
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38. Fortuyn HA, Lappenschaar GA, Nienhuis FJ, et al. Psychotic symptoms in narcolepsy: phenomenology and a comparison with schizophrenia. Gen Hosp Psychiatry. 2009;31(2):146–154.
39. Van den Hoed J, Lucas EA, Dement WC. Hallucinatory experiences during cataplexy in patients with narcolepsy. Am J Psychiatry. 1979;136:1210–1211
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41 Morgenthaler TI, Kapur VK, Brown T, et al. Practice parameters for the treatment of narcolepsy and other hypersomnias of central origin. Sleep. 2007;30(12):1705–1711.
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Psychiatry (Edgemont) 2009;6(6):45–48

ABSTRACT

In this edition of The Interface, we review the literature related to sexual boundary violations by physicians. This literature consists of data from both disciplinary boards/agencies and anonymous surveys of physicians. Our findings indicate that disciplinary actions far under-represent the actual prevalence of self-reported physician boundary violations of patients. However, both prevalence rates represent a very small minority of practitioners. According to these findings, most self-reported boundary violations entail male physicians who are predominantly in the areas of family medicine, psychiatry, and obstetrics/gynecology.

Key words

boundaries, sexual relationships, physician/patient relationship

Introduction

In this edition of The Interface, we discuss the uneasy topic of sexual boundary violations by physicians. In our review of the literature, there is relatively scant empirical information in this area. However, in the following article, we present and summarize the available literature.

The Prevalence of Sexual Boundary Violations by Physicians

In the current literature, the available empirical data are based upon either disciplinary actions undertaken by state medical boards/federal agencies or self-report information that was obtained by investigators through anonymous surveys. Note that these sources of information are reliant upon either discovery or disclosure, which is likely to be conditionally determined. Therefore, as is the case with many other types of research, we are likely to be tapping into prevalence rates that may under-represent the genuine prevalence rate.

Disciplinary Reviews by State Medical Boards/Federal Agencies

There are four US studies of disciplinary actions of physicians by state medical boards/federal agencies. These offer some modest indication of the prevalence of sexual boundary violations by physicians. In the first study, Post[1] reviewed the disciplinary actions of the Office of Professional Medical Conduct for the State of New York from 1985 through 1989. During this time period, 68 physicians were disciplined for the sexual violation of patients. Given that the total number of physicians in the state at that time was “more than 40,000,” the rate of sexual boundary violations in this cohort was minimally 0.2 percent.

In the second US study, Enbom and Thomas[2] examined sexual misconduct complaints among 80 licensees who were under the jurisdiction of the Oregon Board of Medical Examiners between the years 1991 and 1995. Of these licensees, 77 were physicians. Given that 4,931 physicians were licensed by the state at that time, the prevalence rate of sexual misconduct complaints in this cohort was 1.6 percent. As for medical specialty, family medicine, psychiatry, and obstetrics/gynecology had the highest proportion of complaints.

In the third US study, Dehlendorf and Wolfe[3] examined a national database of disciplinary actions undertaken by both state medical boards and federal agencies. In this study, a total of 761 physicians were disciplined for sex-related offenses between the years 1981 and 1996; 75 percent of the allegations involved patients. The researchers examined the trends in the frequency of patient complaints and found that during this 15-year time period, the number of disciplined physicians increased. However, this finding may have been affected by a number of variables, including victims’ increasing willingness over the study period to report allegations. According to these data, 1994 was the year with the highest rate of physician disciplines for sex-related offenses, which affected 0.02 percent of all physicians in the country.

In the fourth US study, Morrison and Wickersham[4] examined the causes of physician disciplinary action undertaken by the Medical Board of California during a 19-month study period (October 1995–April 1997). In this study, 37 of the 104,000 physicians (0.04%) in the state underwent some type of action by the board for either inappropriate or actual sexual contact with patients. In comparison with the other types of offenses addressed by the board, those relating to sexual misconduct were fifth in frequency, preceded in order by negligence or incompetence (most common), inappropriate prescribing or drug possession, alcohol or other drug impairment, and fraud.

In addition to these data from US boards/agencies, there is one published British study on the disciplinary actions meted out to physicians. In this study, Donaldson5 examined the prevalence of “serious” disciplinary problems among the medical staff (N=1,274) of a large national health service workforce. Among this cohort, seven physicians (0.5%) were disciplined for “sexual overtones” in dealing with patients as well as staff. Donaldson described these specific physician behaviors as longstanding and repetitive in most cases.

Physician Surveys

In the area of sexual boundary violations by physicians, we encountered in our review of the literature a number of anonymous survey studies. Of these, only three explored such behaviors among physicians in the US. In the first of these studies, Kardener and colleagues examined the prevalence of sexual involvement between patients and four specialty groups of physicians who were members of the California Medical Society—family medicine, internal medicine, obstetrics/gynecology, and surgery.[6] The overall prevalence rate of sexual boundary violations in this 1973 cohort was 7.2 percent, with the highest rate being among family medicine physicians.

In a second US study, Gartrell and colleagues surveyed 10,000 physicians in the fields of family medicine, internal medicine, obstetrics/gynecology, and surgery—all who were members of the American Medical Association.[7] Of the 1,891 individuals who responded (a response rate of less than 20%), 9.3 percent acknowledged sexual contact with one or more patients. Interestingly, in this same sample, 94 percent of respondents opposed sexual contact with current patients, indicating that six percent were not opposed to such contact. Another perspective on these 1992 data is the following: Given a 20-percent response rate and a nine-percent prevalence rate, if the remaining 80 percent of nonrespondents reported no sexual contact with patients, the resulting overall rate would still be two percent.

In a third US study, Bayer, Coverdale, and Chiang[8] surveyed a randomized sample of 1,600 physicians in the American Medical Association in the specialties of internal medicine, family medicine, obstetrics/gynecology, and ophthalmology. Among the 787 respondents, 3.3 percent reported sexual contact with patients. In this 1996 study, there was no difference in prevalence rate among the medical specialties.

In addition to these US studies, several have been conducted in other countries. For example, in a Dutch study, Wilbers et al[9] surveyed over 700 physicians in two national professional societies—gynecology and otolaryngology. The researchers specifically elected otolaryngologists as a comparison group—i.e., a group that would not normally engage in any intimate examination of patients. Somewhat unexpectedly, 3.6 percent and 3.5 percent of gynecologists and otolaryngologists, respectively, reported sexual contact with patients (i.e., there was no statistically significant difference between the study groups).

In a 1995 study from the University of New Zealand, Coverdale et al[10] mailed an anonymous survey to 217 general practitioners. With a response rate of 86 percent (N=186), 3.8 percent of the sample reported having had sexual contact with a current patient.

In a 1996 Israeli study, Rubin and Dror[11] examined and compared the prevalence of sexual boundary violations between psychologists (n=96) and nonpsychiatric physicians (n=72). In exploring sexual contact with a past or current patient or supervisee, the researchers determined that the prevalence rates were 3.4 percent and 14.5 percent for psychologists and nonpsychiatric physicians, respectively.

In a final study from the Netherlands, Leusink and Mokkink[12] mailed anonymous surveys to a randomized sample of 1,250 general practitioners. With 977 respondents, the researchers experienced an 80-percent response rate. Among the respondents in this 2004 study, 32 (3.3%) reported sexual contact with a patient at some time in their careers and 11 of these (34%) acknowledged sexual contact with two or more patients.

Data Comparisons

Prevalence rates. Clearly, there is a notable difference between the percentage of physicians being disciplined by state and federal agencies (1.6% or less) and the self-reported rates of physician sexual contact with their patients (up to 14.5% in the Rubin and Dror study11) (Table 1). This vast divide is potentially wider, given the likelihood that a substantial number of physicians declined to participate in these survey studies because of fears of disclosure of boundary violations.

Another way to analyze these prevalence data is to combine all of the US self-report samples into a single sample. In doing so, a total of 257/3758 physicians reported sexual boundary violations with patients. This represents a prevalence rate of 6.8 percent. This mean prevalence rate is particularly interesting given the survey results of Coverdale et al,[13] who found that less than one percent of US physician respondents believed that sexual contact with patients is appropriate during consultation.[13] In addition, only three percent believed that sexual contact with current patients outside of consultation is appropriate.[13]

Specialty differences. In those studies that compared differences in rates among specialties, physicians most at risk for boundary violations with patients appear to be practitioners in the fields of family medicine, psychiatry, and obstetrics/gynecology,[2,6,7,14] although one study found no differences.[8] Perhaps the heightened risk in these specialties is explained by the patient/physician dyad’s greater likelihood of physical contact and/or psychological intimacy. However, in the study by Wilbers et al,[9] which was designed to explore these very hypothesized elements, the researchers found no differences in the prevalence rate of boundary violations between gynecologists and otolaryngologists.

Gender patterns. Note in Table 1 that the clear majority of boundary offenders are male. This may reflect the continuing male predominance in medicine and/or inherent gender differences in behavior.

Training backgrounds. The study by Enbom and Thomas[2] was the only investigation we encountered that examined the training backgrounds of physicians charged with boundary violations. In this study, osteopathic physicians were four times more likely to be disciplined for boundary violations with patients than allopathic physicians.[2] The veracity of this finding warrants further investigation. If confirmed by future data, what would explain these differences?

Conclusions

These data indicate that 1.6 percent or less of physicians are disciplined for sexual boundary violations with patients, yet on average, according to anonymous self-report surveys, nearly seven percent of respondents report a history of sexual relationships with patients. Most offenders are male (greater than 85%) and are likely to be in the fields of family medicine, psychiatry, and obstetrics/gynecology. While more research is needed, the study of sexual boundary violations by physicians with their patients is likely to remain a murky area. Indeed, such behaviors are clandestine, associated with substantial social stigma, and subject to punishment by licensing agencies. However, continued physician awareness and education will hopefully promote and reinforce appropriate professional boundaries with patients, which the overwhelming majority of physicians seem to manage without difficulty.

References
1. Post J. Medical discipline and licensing in the State of New York: a critical review. Bull N Y Acad Med. 1991;67:66–98.
2. Enbom JA, Thomas CD. Evaluation of sexual misconduct complaints: the Oregon Board of Medical Examiners, 1991-1995. Am J Obstet Gynecol. 1997;176:1340–1346.
3. Dehlendorf CE, Wolfe SM. Physicians disciplined for sex-related offenses. JAMA. 1998;279:1883–1888.
4. Morrison J, Wickersham P. Physicians disciplined by a state medical board. JAMA. 1998;279:1889–1893.
5. Donaldson LJ. Doctors with problems in an NHS workforce. BMJ. 1994;308:1277–1282.
6. Kardener SH, Fuller M, Mensh IN. A survey of physicians’ attitudes and practices regarding erotic and non-erotic contact with patients. Am J Psychiatry. 1973;130:1077–1081.
7. Gartrell NK, Milliken N, Goodson WH 3rd, et al. Physician-patient sexual contact. Prevalence and problems. West J Med. 1992;157:139–143.
8. Bayer T, Coverdale J, Chiang E. A national survey of physicians’ behaviors regarding sexual contact with patients. South Med J. 1996;89:977–982.
9. Wilbers D, Veenstra G, van de Wiel HB, Weijmar Schultz WC. Sexual contact in the doctor-patient relationship in the Netherlands. BMJ. 1992;304:1531–1534.
10. Coverdale JH, Thomson AN, White GE. Social and sexual contact between general practitioners and patients in New Zealand: attitudes and prevalence. Br J Gen Pract. 1995;45:245–247.
11. Rubin SS, Dror O. Professional ethics of psychologists and physicians: morality, confidentiality, and sexuality in Israel. Ethics Behav. 1996;6:213–238.
12. Leusink PM, Mokkink HG. Sexual contact between general practitioner and patient in the Netherlands: prevalence and risk factors. Ned Tijdschr Geneeskd. 2004;148:778–782.
13. Coverdale J, Bayer T, Chiang E, et al. National survey on physicians’ attitudes toward social and sexual contact with patients. South Med J. 1994;87:1067–1071.
14. Enbom JA, Parshley P, Kollath J. A follow-up evaluation of sexual misconduct complaints: the Oregon Board of Medical Examiners, 1988 through 2002. Am J Obstet Gynecol. 2004;190:1642–1650.

Dr. Targum is an executive-in-residence at Oxford BioScience Partners and on the faculty of the Department of Psychiatry at the Massachusetts General Hospital. Dr. Targum is chief medical officer at BrainCells Inc., and chief medical advisor to Prana Biotechnology Ltd. Dr. Targum is on the editorial board of Psychiatry 2009. Dr. Iosifescu is director of Translational Neuroscience in the Depression Clinical and Research Program, site director of the Bipolar Trials Network at Massachusetts General Hospital., and assistant professor of psychiatry at Harvard Medical School.
Psychiatry (Edgemont) 2009;6(6):49–51

Financial Disclosures

Dr. Targum has stock or stock options in BrainCells Inc. and Prana Biotechnology Ltd. In the past year, Dr. Targum has been a consultant to United BioSource Corporation, Dynogen, Epix, DOV Pharmaceuticals, Sepracor, NuPathe, and Memory Pharmaceuticals. Dr. Iosifescu has received research support from Aspect Medical Systems, Forest Laboratories, and Janssen Pharmaceutica; he has been a consultant for Forest Laboratories, Gerson Lehrman Group, and Pfizer, Inc., and he has been a speaker for Cephalon, Inc., Eli Lilly & Co., Forest Laboratories, Pfizer, Inc. and Reed Medical Education (a company working as a logistics collaborator for the MGH Psychiatry Academy). The education programs conducted by the MGH Psychiatry Academy were supported through Independent Medical Education (IME) grants from pharmaceutical companies co-supporting programs along with participant tuition. For 2008, those companies included Astra Zeneca, Eli Lilly, and Janssen Pharmaceuticals.

Introduction

It is well documented that the currently available antidepressants achieve only partial clinical response in many patients with major depressive disorder (MDD) and that approximately 25 to 35 percent of MDD patients actually achieve full remission of symptoms. One reason for the apparent limited clinical efficacy is that different biological-functional deficits may be subsumed under the broad classification of MDD as defined in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Recently, neuroimaging research has focused on the identification of distinct biological subtypes within this broad spectrum of MDD, which might have distinctly different patterns of clinical response as well. In fact, the application of neuroimaging techniques to study MDD has yielded some intriguing possibilities related to differential diagnosis, the prediction of treatment response, and even the prediction of placebo response. In this column, I interviewed Dan V. Iosifescu, MD, MSc, who is Assistant Professor of Psychiatry at the Harvard Medical School, and Director of Translational Neuroscience and Site Director for the Bipolar Trials Network at the Massachusetts General Hospital in Boston, Massachusetts.

What clinical value can Neuroimaging studies offer clinicians who treat mood disorders?

Dr. Iosifescu: I believe that neuroimaging studies may become very valuable in several respects. First, they can offer insights into the neurobiology of mood disorders and reveal reliable pathophysiological markers that may be associated with specific subtypes of mood disorders. These findings could eventually translate into objective diagnostic criteria. Second, specific changes measured with neuroimaging can be associated with treatment response; this could translate into tests that would help the clinical selection of next-step treatment in patients who failed previous antidepressant trials. Moreover, the discovery of disease-specific structural or functional deficits could help our understanding of disease development and thereby guide more accurate clinical diagnoses and even drug development.

But, I need to emphasize that none of these uses of neuroimaging has been sufficiently validated to warrant current application in clinical practice, although the long-term promise of such studies remains extraordinary.

Are there specific brain regions associated with the symptoms of MDD?

Dr. Iosifescu: Yes. Specifically, the limbic and prefrontal cortical regions of the brain are associated with the behavioral and functional deficits seen in MDD patients. These regions are very important for emotional regulation in healthy individuals also. In depressed subjects, there appears to be a functional imbalance in the role and activity between the limbic regions (such as the amygdala and hippocampus that are believed to mediate emotional and stress responses) (Figure 1) and the prefrontal cortical regions like the posterior orbital cortex and anterior cingulate gyrus that modulate emotional expression.[1]  The accumulating evidence from numerous structural and functional imaging studies as well as magnetic resonance spectroscopy (MRS) points to an imbalance in brain circuitry in patients with MDD, where the excessive activity in the limbic system is not adequately modulated and controlled by hypoactive prefrontal areas.

Where have structural brain changes been associated with mood disorders?

Dr. Iosifescu: So far, the neuroanatomical abnormalities associated with MDD include morphological lesions in frontal lobe regions like the anterior cingulate gyrus, the hippocampus, and white matter lesions (WML) as well (Figure 2).[2–4] For instance, reduced hippocampal volume has been reported in first-episode depression and depressed pediatric patients suggesting it is not a drug effect. Furthermore, progressive reductions in hippocampal size have been reported in patients with chronic, untreated depression as well.[5]

What is the clinical significance of the white matter lesions?

Dr. Iosifescu: It is possible that the abnormal white matter connections between the limbic and prefrontal cortical structures may contribute to the imbalance in brain circuitry that I mentioned before. Not surprisingly, these WMLs (which represent areas of demyelination) are more frequently found in elderly depressed patients and have been associated with a distinct subtype of illness called “vascular depression,” which appears to be less responsive to antidepressants compared with MDD patients with no WML. Nonetheless, WML at any age may disrupt brain circuitry patterns and might be predictive of poor treatment response.[4]

What functional neuroimaging techniques have been used to study MDD patients?

Dr. Iosifescu: Researchers have used a variety of functional techniques to study brain activity in depression, including single photon emission computed tomography (SPECT), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI). All of these functional techniques assess changes in cerebral blood flow (CBF) or glucose metabolism, which in turn suggest what brain areas are hyper- or hypoactive. A very exciting part of these studies involve measuring changes in CBF or metabolism actively during specific emotional or cognitive tasks. Compared to healthy controls, MDD patients show different functional patterns when they are exposed to anger induction, emotional faces, or even sad words.

These PET studies have demonstrated abnormally increased or decreased CBF in specific limbic and prefrontal cortical structures. Remarkably, the metabolic abnormalities revealed by these PET studies actually improve with antidepressant treatment.[6] Beyond that, some studies have shown that the metabolic abnormalities do not improve in treatment nonresponders and reveal a different pattern of activation in placebo responders.[7]  Overall, these preliminary studies suggest that it may eventually be possible to predict and to differentiate between true antidepressant response and placebo response in MDD.

Are there clinical applications for Magnetic Resonance Spectroscopy in MDD?

Dr. Iosifescu: MRS is a noninvasive tool for in-vivo chemical analysis, which can be used to compare brain levels of several neurochemicals and specific metabolic pathways. This represents a more refined analysis of metabolism compared to SPECT or PET, which measure CBF or glucose metabolic rates. MRS has been used in psychiatry to measure brain neurotransmitters like GABA and glutamate, structural components like synaptic proteins, and even brain levels of psychotropic drugs.[8]  To date, Proton (1H) MRS studies have reported decreased levels of GABA and glutamate in MDD patients (which seem to be corrected by adequate treatment) and impairment of cellular membrane phospholipid metabolism. Phosphorus (31P) MRS studies have suggested deficits of brain energy metabolism in depression, which may be related to a mitochondrial dysfunction. More recently, we reported that response to antidepressant treatment is associated with a renormalization of bioenergetic metabolism.[9] This metabolic measure can differentiate between responders and nonresponders and may suggest new potential avenues for antidepressant treatment (such as substances which increase mitochondrial activity). In sum, I think that MRS may eventually have practical use in the clinic to target specific chemical markers to predict treatment response for MDD patients.

What is on the horizon for the use of neuroimaging in the evaluation and treatment of MDD patients?

Dr. Iosifescu: As I have mentioned, I believe that structural and functional neuroimaging and MRS techniques will eventually be useful in the clinic for differential diagnosis and selection of appropriate antidepressant treatments. It is possible that these techniques will also identify likely placebo responders who might not need antidepressants at all. These tools will help us to move from mere clinical description to a genuine clinical-neuropathological correlation in our approach to depressed patients.

References
1.    Fales CL, Barch DM, Rundle MM, et al. Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression. Biol Psychiatry. 2008;63(4):377–384.
2.    Drevets WC. Neuroimaging studies of mood disorders. Biol Psychiatry. 2000;48(8):813–829.
3.    Campbell S, Marriott M, Nahmias C, et al. Lower hippocampal volume in patients suffering from depression: a meta-analysis. Am J Psychiat. 2004;161(4):598–607.
4.    Iosifescu DV, Renshaw PF, Lyoo IK, et al. Brain white-matter hyperintensities and treatment outcome in major depressive disorder. Br J Psychiatry. 2006;188:180–185.
5.    Sheline YI, Gado MH, Kraemer HC. Untreated depression and hippocampal volume loss. Am J Psychiatry. 2003;160 (8):1516–1518.
6.    Kennedy SH, Evan KR, Kruger S, et. al. Changes in regional brain glucose metabolism measured by positron emission tomography after paroxetine treatment of major depression. Am J Psychiatry. 2001;158(6):899–905.
7.    Mayberg HS, Silva JA, Brannan SK, et. al. The functional neuroanatomy of the placebo effect. Am J Psychiatry. 2002;159(5):728-737.
8.    Lyoo IK, Renshaw PF. Magnetic resonance spectroscopy: current and future applications in psychiatric research. Biol Psychiatry. 2002;51(3):195–207.
9.    Iosifescu DV, Bolo NR, Nierenberg AA, et al. Brain bioenergetics and response to T3 augmentation in major depressive disorder. Biol Psychiatry. 2008;63(12):1127–1134.

Drs. Azad, McKinnon, and Faubion are from Wilford Hall Medical Center, Lackland AFB, San Antonio, Texas, and the University of Texas Health Science Center at San Antonio, Texas; Dr. Joshi is from Wilford Hall Medical Center, Lackland AFB, San Antonio, Texas.

Psychiatry (Edgemont) 2009;6(6):52–53

Financial Disclosure

Drs. Azad, McKinnon, Joshi, and Faubion report no competing interests. Nor do they have any potential conflicts of interest and financial support to disclose.

Abstract

United States Air Force psychiatry plays a vital role in Operation Iraqi Freedom and Operation Enduring Freedom (Afghanistan). Outside of the military, little is known about US Air Force psychiatry and the Wilford Hall Medical Center. Wilford Hall Medical Center is the US Air Force’s flagship hospital and premiere psychiatric hospital. This article briefly discusses the history of Wilford Hall Medical Center and its psychiatric contributions to the wars in Iraq and Afghanistan.

Key words

Wilford Hall Medical Center, Air Force psychiatry, military medicine, military psychiatry

At the start of World War II, the military recruited some of the nation’s top medical specialists to serve their country. However, soon after the war ended, many of these physicians left the service when their commitment ended. In 1946, Col. Floyd Wergeland proposed the establishment of military graduate medical education programs (GME) to stimulate recruitment of future physicians. The proposal was subsequently implemented by Col. Raymond Duke in 1947, who was the Director of Education and Training at the Office of the Surgeon General.[1]

The Air Force’s largest Accreditation Council for Graduate Medical Education (ACGME)-accredited general psychiatry residency training program (approved in 1962) is located at Wilford Hall Medical Center on Lackland Air Force Base in San Antonio, Texas.2 WHMC is the flagship medical center of the US Air Force. WHMC was founded on November 16, 1957. It is the US Air Force’s largest medical facility, with a staff of 4,500 and a maximum capacity of more than 1,000 beds.[2] WHMC is one of three level-one trauma centers in San Antonio, serving the local community as well as South Central Texas. Its psychiatry residency program is merged with the University of Texas Health Sciences Center at San Antonio. This psychiatry residency training program offers unique training opportunities not seen in nonmilitary institutions. In addition to the mission of providing mental healthcare to service members, retirees, and their families, US Air Force psychiatrists are trained in occupational (military) psychiatry, such as performing fitness-for-duty evaluations, interpreting appropriate Department of Defense and Air Force directives on mental health issues, and providing mental health services to deployed personnel in austere locations.[3]

WHMC has the larger of two inpatient psychiatry units in the US Air Force.[2] Patient populations hospitalized on the inpatient unit include (but are not limited to) basic trainees (age 18–30) who often develop first-break psychotic symptoms, deployed soldiers medically evacuated from Iraq and Afghanistan for mental health symptoms, and individuals suffering from posttraumatic stress disorder. This facility also has the US Air Force’s largest outpatient mental health clinic and its only inpatient psychiatry consultation-liaison service. The faculty also currently consists of forensic-, child/adolescent-, and geriatric-fellowship–trained psychiatrists.[4] WHMC has the US Air Force’s largest psychology training program, creating a unique collaboration between the disciplines in the arenas of education, research, and patient care. WHMC is often tasked with deployment orders for its psychiatrists. At any one time, 10 to 50 percent of the US Air Force staff psychiatrists stationed at WHMC are deployed in support of military missions to Iraq and Afghanistan. Despite these shortages, GME and patient care missions at WHMC continue uninterrupted.

In a nutshell, US Air Force psychiatry, born out of the necessities of World War II, has evolved to offer a unique blend GME training, patient care, and support to the military mission in Iraq and Afghanistan today.

References
1.     Austerman WR. Mustering out the medics: AMEDD downsizing after WWII. AMEDDJ. 2003;PB 8-03-4/5/6:15–20.
2.     Office of Wing Historian. A History of the Medical Facility at Lackland AFB 1941-1951. Extracted from unpublished Lackland Air Force Base records.
3.     Ritchie EC, Benedek D, Malone R, Carr-Malone R. Psychiatry and the military: an update. Psychiatr Clin North Am. 2006;29(3):695–707.
4.     Establishment of residency training in psychiatry at USAF hospital Lackland. Unpublished letter from Brigadier General Larry A. Smith, Director of Medical Staffing and Education to Air Force Systems Command 27. Dec 1962.

Dr. Aboraya is the chief of psychiatry and clinical professor of psychiatry at William R. Sharpe Jr. Hospital, Weston, West Virginia.


Psychiatry (Edgemont) 2009;6(6):24–28

Abstract

Psychiatry (Edgemont) readers were surveyed about whether or not they use structured interviews in real clinical settings. Forty psychiatrists responded to the survey: six psychiatrists in private practices and 34 faculty psychiatrists. The majority of psychiatrists (72.5%) do not use structured interviews and 27.5 percent use some structured interviews in clinical settings. The three most commonly cited reasons for not using structured interviews were “constraints of time,” “structured interviews are research tools,” and “structured interviews interfere with establishing rapport with patients.” Other reasons why psychiatrists do not use structured interviews are analyzed and discussed.

Key words

structured interview, clinical setting, psychiatry, reliability of diagnosis

Background
In an article published in the July issue of Psychiatry (Edgemont),[1] I opined that psychiatrists do not use structured interviews in real clinical settings for the following three reasons: 1) structured interviews are designed as research tools to be used in research settings and are not designed for psychiatrists to use in real clinical settings; 2) structured interviews are time-consuming; and 3) the rules of structured interviews make it difficult for the psychiatrist to establish rapport with the patient.
To obtain input from practicing psychiatrists, I invited the readers of Psychiatry (Edgemont) to answer the the following questions:
1. Do you use structured interviews (not just a rating scale) in your routine clinical practice, whether inpatient or outpatient?
2. If your answer is no, why not?
3. If your answer is yes, which structured interview do you use? For what percentage of your patients’ load do you use the structured interview routinely?
The purpose of this article is to summarize psychiatrists’ responses to the survey about whether or not they routinely use structured interviews. In addition, reasons cited for not using structured interviews are analyzed and discussed.

Results

Forty psychiatrists responded to the open survey: six psychiatrists in private practice and 34 psychiatrists in faculty positions. Twenty-nine psychiatrists (72.5%) said that they do not use structured interviews in clinical settings; eleven psychiatrists (27.5%) said they use structured interviews in clinical settings; seven psychiatrists (17.5%) said they use structured interviews with all patients; and four psychiatrists (10%) said they use them occasionally with a subset of patients only. Among the six psychiatrists in private practice who use structured interviews, one uses an unpublished tool that he developed and has used in his private practice for 20 years. The study results show that faculty psychiatrists, assumedly by virtue of their academic positions, were more likely to use structured interviews in clinical settings.

Table 1 shows the users and nonusers of structured interviews and the names of the instruments used. Among the users of the structured interviews, the Mini-International Neuropsychiatric Interview (M.I.N.I.) is the most commonly used structured interview by psychiatrists in clinical settings.[2] Three psychiatrists responded that they use the M.I.N.I. with all patients (7.5%), and one psychiatrist uses the M.I.N.I. only with some difficult patients (2.5%). The clinical derivatives of the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) are used by two psychiatrists (5%).3,4 The Affective Disorders Evaluation (ADE)5,6 is used by two psychiatrists (5%); one psychiatrist uses the ADE with all patients and the other uses the ADE with some patients only. One child psychiatrist uses the Autism Diagnostic Observation Schedule (ADOS)7 in patients with autism (2.5%). Two psychiatrists use unpublished instruments.

The majority of psychiatrists (72.5%) responded that they do not use structured interviews in clinical settings. The reasons cited were grouped into the following:
A. Structured interviews are time consuming.
B. Structured interviews are designed for research and not designed for clinical use by psychiatrists. Structured interviews were described as “cumbersome,” “unwieldy,” “inconvenient,” “inflexible,” “user unfriendly,” and “complicated.”
C. Structured interviews interfere with establishing rapport with patients.
D. Psychiatrists do not need to use structured interviews. The following reasons were given:
1. Clinical skills acquired through years of training are sufficient to diagnose mental disorders and superseded any structured interview.
2. Clinical interviews can reveal all the information needed to diagnose and manage patients.
3. Structured interviews are based on well-known criteria.
4. All vital information about the patient is gathered over time.
5. Structured interviews reveal little about the patient’s disposition, behaviors, experiences, and ever-changing personal circumstances that dictate his or her treatment requirements at any given point in time.
6. Understanding the patient is more important than a diagnosis.
E. Structured interviews are based on a flawed classification system.
F. The use of structured interviews yields no financial benefits.
G. Structured interviews do not account for differences among patients (e.g. cultural differences).
H. Structured interviews do not account for patients with disabilities (e.g., patients with mental retardation).
I. Structured interviews restrict the creativity of the interviewer.
J. Structured interviews force psychiatrists to act like programmed computers.
K. Psychiatrists are not trained to use structured interviews.

Table 2 shows the individual responses of the 40 psychiatrists who use and do not use structured interviews and the reasons they cited for not using them. Table 3 summarizes the reasons for not using structured interviews. The most commonly cited reason why psychiatrists do not use structured interviews was, “Structured interviews are time consuming” (19 citations, 30.1% of all citations). “Structured interviews are designed for research and not designed for clinical use,” was the second most commonly cited reason (13 citations, 20.6% of all citations). “Structured interviews interfere with establishing rapport with patients,” was cited 12 times (19.0%). “Psychiatrists do not need to use structured interviews,” was cited 10 times (15.9%). “Structured interviews are based on a flawed classification system.” was cited twice (3.2%). “No financial reimbursement for using structured interviews,” was also cited twice (3.2%). Each of the other reasons (G, H, I, J, K) was cited one time.

Discussion
This open-question survey study has limitations. The number of respondents is small (40 respondents), and the procedures used to solicit the responses from psychiatrists were arbitrary.
Readers of Psychiatry (Edgemont) were solicited to respond through a published invitation in the journal. An e-mailed version of the survey was also sent to the editorial advisory board members of the journal as well as colleagues of the author.

Despite the small number of respondents, the results of the survey can be informative, since there is currently little research on the subject.

I previously hypothesized that three main reasons prevent psychiatrists from using structured interviews in real clinical settings: structured interviews are designed as research tools, they are time-consuming, and they interfere with establishing rapport with the patients.[1] The results of this survey appear to confirm the hypothesis as these three reasons combined accounted for 69.7 percent of the cited reasons why psychiatrist do not use structured interviews in clinical settings. The respondents also identified eight additional reasons for not using structured interviews, and these accounted for 30.3 percent of the cited reasons. An interesting finding is that 15.9 percent of the respondents said that psychiatrists do not need to use any structured interviews to diagnose or manage patients.

In my opinion, psychiatrists do appreciate the proven value of the measurement embedded in structured interviews. However, psychiatrists cannot change their methods of assessment to overcome the inadequacies of the existing structured interviews. Psychiatrists develop their clinical skills over years of training and experience. A seasoned psychiatrist can spend 30 minutes interviewing a new patient, establish a good rapport with the patient, and at the end of the interview, he or she can have a valid provisional diagnosis and initial treatment plan. Most, if not all, psychiatrists will resist utilizing any tool that mechanizes the interview process, prevents them from following the leads created by the patient’s responses, and jeopardizes development of rapport with patients. This major nonuse of structured interviews by psychiatrists can be overcome by developing new clinical tools that accommodate and complement what psychiatrists do in clinical practice. These clinical tools should be efficient, should be designed for clinical use (e.g., measuring significant symptoms of clinical significance), and should not interfere with establishing rapport with patients. It is important to differentiate between patient self-reports and clinical assessment by psychiatrists. Positive symptoms reported by the patients do not necessarily require treatment. On the other hand, psychiatrists should evaluate symptoms of clinical significance that cause distress or impairment of function of the patient.
Finally, it is difficult to conclude from the survey whether or not psychiatrists want to use a tool, such as a structured interview, to aid in patient assessment. Ten psychiatrists (25%) said that they do not need any tool to interview patients, and eleven psychiatrists (27.5 %) use some type of existing structured tool. There is a new and external factor that may play a crucial role in whether or not psychiatirsts use structured interviews, which is the trend toward computerizing all medical records. This factor may act as the catalyst that will force psychiatrists to use or adapt to using some of the existing tools or newly developed tools for psychiatric assessment in clinical settings.

References
1. Aboraya A. Do Psychiatrists use structured interviews in real clinical settings? Psychiatry (Edgemont) 2008;5(7):26–27.
2. Sheehan D, Lecrubier Y, Sheehan KH, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59(Suppl 20):22–33.
3. Nienhuis F, Willige G, Rijnders C, et al. The validity of a short clinical interview for psychiatric diagnosis: the mini-SCAN. Submitted. 2009.
4. Romanoski A, Nestadt G, Chahal R, et al. Interobserver reliability of a “Standardized Psychiatric Examination””(SPE) for case ascertainment (DSM-III). J Nerv Ment Dis. 1988;176(2):63–71.
5. Sachs GS, Thase ME, Otto MW, et al. Rationale, design, and methods of the systematic treatment enhancement program for bipolar disorder (STEP-BD). Biol Psychiatry. 2003;53(11):1028–1042.
6. Sachs GS. Strategies for improving treatment of bipolar disorder: integration of measurement and management. Acta Psychiatr Scand. 2004;422(Suppl):7–17.
7. Lord C, Risi S, Lambrecht L, et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord. 2000;30(3):205–223.

DEAR EDITOR:

In the January 2009 issue of Psychiatry (Edgemont), Khawaja et al[1] provided a masterful and exhaustive elucidation of the bidirectional association between depression and coronary artery disease. The pathways from depression to coronary artery disease are complex and circuitous. They include autonomic dysfunction, hypothalamic-pituitary adrenal axis hyperactivity, platelet activation, and release of proinflammatory cytokines. An emerging body of literature implicates coronary risk factors, such as hypertension, diabetes, dyslipidemia, cigarette smoking, and obesity, in the pathogenesis of “vascular” depression.2 The vascular depression hypothesis initially emerged with the discovery that depression with an onset in late life is commonly associated with subcortical and periventricular brain white matter hyperintensity (WMH) microvascular lesions, visualized on magnetic resonance imaging.[2] A recent longitudinal study of 639 older patients conducted in 11 European centers revealed a correlation between the intensity of WMH lesions and the subsequent development of depression.[3] These subcortical brain lesions appear to interrupt the integrity of vital frontostriatal limbic circuits providing a biological substrate for vascular depression. This is a condition distinguished by apathy, executive function deficits, and resistance to antidepressant treatment.[4] At least one promising study has suggested that lowering blood pressure reduces the progression of WMH lesions.[4] Managing hypertension is known to reduce the risk of stroke. Similarly, lowering blood pressure may prevent late-life vascular depression.

Whereas the vascular depression hypothesis has focused exclusively on depression with an onset in late life, vascular risk factors may be equally relevant in the pathogenesis and course of depression in younger individuals.[5] We recently examined the influence of comorbid vascular factors on treatment outcome. Patients, ranging in age from 18 to 75 years, who were hospitalized with depression on the adult psychiatry unit of a general hospital in mid-Michigan completed a brief cardiovascular risk questionnaire. The cohort of patients referred for electroconvulsive therapy (ECT) following failure to respond to drug treatment was compared to that which responded to antidepressant medications. Forty-three (23%) of the 187 study patients who failed to respond to antidepressants were subsequently referred for ECT. These patients had a disproportionately high prevalence of cardiovascular risk factors. The relative risk of hypertension in drug nonresponders was 1.6, diabetes mellitus 2.4, dyslipidemia 1.8, and obesity 1.6. The presence of any cardiovascular risk factor was associated with a later onset of depression (Pearson correlation coefficient r=0.275, p=0.01). The SADHART and ENRICHD study, cited by Khawaja et al,[1] affirmed that in depression following myocardial infarction (MI), the use of selective serotonin reuptake inhibitor (SSRI) antidepressants is associated with a lower risk of subsequent MI recurrence and death. Is it possible that preventing hypertension, diabetes, and dyslipidemia will prevent depression in some susceptible individuals and improve the outcome of depression treatment in others?

References
1.     Khawaja IS, Westermeyer JJ, Gajwani P, Feinstein RE. Depression and coronary artery disease: the association, mechanisms, and therapeutic implications. Psychiatry (Edgemont). 2009;6(1):38–51.
2.     Alexopoulos GS, Murphy CF, Gunning-Dixon FM, et al. Microstructural white matter abnormalities and remission of geriatric depression. Am J Psychiatry. 2008;165:238–244.
3.     Teodorczuk A, O’Brien JT, Firbank MJ, Pet al. White matter changes and late-life depressive symptoms: Longitudinal study. Br J Psychiatry. 2007;191:212–217.
4.     Schiffrin E. Blood pressure lowering in PROGRESS (Perindopril Protection Against Recurrent Stroke Study) and white matter hyperintensities: should this progress matter to patients? Circulation. 2005;112:1525–1526.
5.     Iosifescu DV, Renshaw PF, Lyoo IK, et al. Brain white-matter hyperintensities and treatment outcome in major depressive disorder. Br J Psychiatry. 2006;188:180–185.

With regards,
Dale A. D’Mello, MD
Associate Professor, Department of Psychiatry, Michigan State University, East Lansing, Michigan

Alric Hawkins, MD
Resident, Department of Psychiatry, Vanderbilt University, Nashville, Tennessee

AUTHOR RESPONSE
We appreciate the comments by D’Mello and Hawkins on our review article published in the January 2009 issue of Psychiatry (Edgemont).[1] They discuss an important issue of the effect of metabolic disorders on depression. One of the reasons why DSM IV removed the category of “organic depression” is that all psychiatric disorders have some “organic” basis to them.

D’Mello and Hawkins discuss the “vascular depression” hypothesis, referencing some studies that point to the relationship of subcortical and periventricular brain white matter hyperintensity (WMH) microvascular lesions as a cause of subsequent depression. The correlation of WMH and development of depression is an important and interesting finding. It is possible that microvascular disease causing these lesions could interrupt the integrity of the frontostriatal limbic circuits, thus making a person more susceptible to depression with distinguished clinical features, such as apathy, executive dysfunction, and treatment resistance to medications. We appreciate the authors sharing their study results, suggesting that the treatment-resistant group had more cardiovascular and metabolic comorbidities than those who are responders to medications. Does this damage cause cell death in certain areas of the brain? Increased neurogenesis in hippocampus has been hypothesized as a mechanism of electroconvulsive therapy (ECT),[2] and it would be interesting to see if the treatment-resistant group shows improvement in their depression with ECT.

We would like to add further to the discussion of metabolic disorder’s effect on vascular health by pointing to the association of sleep disorders with cardiovascular health. In an 18-year follow up of the Wisconsin cohort study,[3] the adjusted hazard risk of cardiovascular mortality of patients with untreated obstructive sleep apnea was 5.2 (1.4–19.2). Intermittent hypoxemia associated with sleep apnea has been linked to endothelial dysfunction causing direct damage to the vascular system.[4] In addition to this, in one study,[5] longer sleep duration was associated with reduced calcification incidence over five years. Pepperell et al6 found a small but significant reduction in daytime blood pressure in a normotensive cohort after four weeks of continuous positive airway pressure (CPAP) therapy, especially for those who had frequent desaturation episodes. We wonder how many of D’Mello’s treatment-resistant patients had sleep apnea.

We agree with the authors that it is plausible that preventing metabolic disorders or treating them effectively could prevent vascular depression. A large, prospective study should be conducted with the population at risk being treated aggressively for metabolic problems and compared to the controls of patients whose metabolic disorders are either uncontrolled or not treated. We encourage such a study to be conducted as it surely would further our understanding of the relationship between coronary artery disease, metabolic disorders, and depression.

References
1.     Khawaja IS, Westermeyer JJ, Gajwani P, Feinstein RE. Depression and coronary artery disease: the association, mechanisms, and therapeutic implications. Psychiatry (Edgemont). 2009;6(1):38–51.
2.     Madsen TM, Treschow A, Bengzon J, et al. Increased neurogenesis in a model of electroconvulsive therapy. Biol Psychiatry. 2000;47:1043–1049.
3.     Young T, Finn L, Peppard P, et al. Sleep disordered breathing and mortality: eighteen year follow-up of the Wisconsin sleep cohort. Sleep. 2008;31(8):1071–1078
4.    Caples SM, Garcia-Touchard A, Somers VK. Sleep disordered breathing and cardiovascular risk. Sleep. 2007;30(3):291–303
5.    King CR, Knutson KL, Tathouz PJ, et al. Short sleep duration and incident coronary artery calcification. JAMA. 2008;300(24):2859–2866.
6.    Pepperell JC, Ramdassight-Dow S, Crosthwaite N, et al. Ambulatory blood pressure after therapeutic and subtherapeutic nasal continuous positive airway pressure for obstructive sleep apnoea: a randomized parallel trial. Lancet. 2002;359:204–210.

With regards,

Imran S. Khawaja, MBBS

Psychiatrist, Sleep Medicine Physician, VA Medical Center Minneapolis, Minnesota; Assistant Professor, Department of Psychiatry, University of Minnesota; Fellow, Sleep Medicine, Mayo Clinic, Rochester, Minnesota

Joseph W. Westermeyer, MD, PhD

Professor of Psychiatry, Department of Psychiatry, University of Minnesota School of Medicine, Minneapolis, Minnesota; VA Medical Center, Minneapolis, Minnesota

Prashant Gajwani, MD

Hoffman-La Roche, Inc., Nutley, New Jersey

Robert E. Feinstein, MD

Professor of Psychiatry, Department of Psychiatry, University of Colorado, Denver, Colorado

Trauma appears to be a specific psychosocial variable that potentially heightens an individual’s emotional response to the external environment. Although not everyone develops this syndrome in the aftermath of childhood trauma, perhaps the best example of this phenomenon is posttraumatic stress disorder (PTSD) and the subsequent clinical finding of hyperarousal.[1] Another example might be multiple chemical sensitivities (MCS), a controversial syndrome in which individuals experience adverse physical reactions to low levels of common chemicals.[2] Magill and Suruda[3] state that, “there are marked similarities between MCS and posttraumatic stress disorder.” In an effort to expand upon this trauma/hypersensitivity paradigm, we hypothesized that medications may represent an environmental element and that there might be a relationship between histories of childhood trauma (e.g., sexual, physical, and/or emotional abuses; witnessing violence; and physical neglect) and the number of patient-reported drug allergies. Indeed, in an earlier study, we determined that outpatients with borderline personality disorder, in which trauma is a contributory substrate, evidenced a marginal statistically significant relationship with the number of self-reported drug allergies.[4] However, in this latter study, we did not explore histories of trauma.

In the present study, participants consisted of 117 chronic noncancer pain patients (response rate: 94.4%; 43 men, 73 women) who were referred to a pain-management specialist by physicians predominantly in the areas of physical medicine and rehabilitation, orthopedics, and primary care. All participants were insured, and in this practice setting, 37 percent of patients are covered through workers compensation and 63 percent through private insurance (i.e., no Medicare or Medicaid sponsorship). We elected to examine this population because of the anticipated high frequency of childhood trauma. The sample ranged in age from 18 to 69 years (M=44.50, SD=11.50). With regard to race/ethnicity, 105 (89.7%) participants were Caucasian, six (5.7%) were Hispanic, three (2.6%) were African-American, one (0.8%) was Asian, and two (1.7%) were “other.” Sixty of the subjects were married (51.3%), 26 (22.2%) were never married, 26 (22.2%) were divorced, four (3.4%) were separated, and one (0.8%) was widowed. Nine (7.7%) did not graduate high school, 25 (21.4%) graduated high school only, 39 (33.3%) attended some college, 27 (23.1%) had college degrees, and 17 (14.5%) had graduate degrees.

Participants were recruited during their initial clinical evaluations for chronic pain. Each completed a research booklet that explored personal demographics, drug allergies (write-in section), and histories of childhood trauma. The definition of “drug allergy” was not provided. With regard to childhood trauma, participants were asked, “Prior to the age of 12, did you ever experience…” with yes/no response options regarding the following: sexual abuse (“any sexual activity against your will”); physical abuse (“any physical insult against you that would be considered inappropriate by either yourself or others and that left visible signs of damage on your body either temporarily or permanently or caused pain that persisted beyond the ‘punishment’”); emotional abuse (“verbal and nonverbal behaviors by another individual that were purposefully intended to hurt and control you, not kid or tease you”); physical neglect (“not having your basic life needs met”); and witnessing of violence (“the first-hand observation of violence that did not directly involve you”). Beyond face validity, this brief trauma assessment had no determined validity or reliability. We elected the preceding brief inquiry for childhood trauma because of our concerns about the possible negative impact of longer and more detailed surveys among chronic pain patients being seen in a busy clinic setting. The project was approved by an institutional review board and completion of the research booklet was assumed to function as informed consent (i.e., the first page of the booklet clearly stated that the results of this anonymous survey would be used in a study by the authors).

As for results, 33 (28.2%) participants reported having experienced sexual abuse, 35 (29.9%) physical abuse, 58 (49.6%) emotional abuse, 12 (10.3%) physical neglect, and 45 (38.5%) the witnessing of violence. Only 45 (38.5%) denied having experienced any of the five forms of trauma. Most (61; 52.1%) reported having experienced one, two, or three different types of childhood trauma.

All participants reported between 0 and 4 allergies to individual medications, with the exception of one participant who reported eight allergies. (To prevent this unusual outlier from exerting too much statistical influence, this patient’s number of allergies was recoded to 4.) Specifically, 74 participants reported no allergies, 25 one allergy, 12 two, 3 three, and 3 four. The overwhelming majority of allergies were attributed to antibiotics and analgesics. In the resulting analyses, the total number of allergies was positively correlated with the total number of different traumas indicated (r=0.19, p<0.05). In examining the specific types of childhood trauma, the total number of allergies statistically differed between the trauma and no-trauma groups for both witnessing violence and sexual abuse. Specifically, those who witnessed violence in childhood reported more allergies (M=0.84, SD=1.09) compared to those who did not witness violence ([M=0.44, SD=0.84], t[1,115]=-2.24, p<0.03). Similarly, those who experienced sexual abuse in childhood reported more allergies (M=0.91, SD=1.16) compared to those who did not experience sexual abuse ([M=0.48, SD=0.84], t[1,115]=-2.24, p<0.03.)

These data highlight a possible relationship between trauma and environmental sensitivity in the form of allergies to medications. We do not know if these reported allergies are genuine, exaggerated, adverse medication effects, or factitious. However, that specific environmental substances are less tolerated in  traumatized patients tends to reinforce the trauma/hypersensitivity paradigm observed in PTSD and MCS. If these findings are valid, then patients with multiple allergies to medications may be more likely to have histories of trauma with secondary sensitivity or reactivity to the environment in the form of drug allergies—an important finding for both psychiatrists and primary care physicians. In other words, multiple allergies may be a nonspecific clinical indicator of the possible presence of childhood trauma, and thereby alert clinicians to examine the patient’s history for evidence. In addition, such histories may culminate in a number of potential psychiatric and medical syndromes.

The potential limitations of this study include the small sample size, self-report nature of the data, the absence of a definition for “drug allergies” (i.e., a heightened risk of false positives), and the lack of a standardized assessment of childhood trauma. However, this is the first study to our knowledge to explore medication allergies and their specific relationship to childhood trauma in an outpatient, chronic-pain population. Our findings lend support to a trauma/hypersensitivity paradigm.

References
1.    American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC: American Psychiatric Press, Inc., 1994.
2.    US Department of Labor Occupational Safety and Health Administration. Multiple chemical sensitivities. 2008. http://www.osha.gov/SLTC/multiplechemicalsensitivies/index/html. Accessed on November 25, 2008.
3.    Magill MK, Suruda A. Multiple chemical sensitivity syndrome. http://www.aafp.org/afp/980901ap/magill.html. Accessed on November 25, 2008.
4.    Sansone RA, Gentile J, Markert RJ. Drug allergies among patients with borderline personality symptomatology. Gen Hosp Psychiatry. 2000;22:289–293.

With regards,

Randy A. Sansone, MD

Professor, Psychiatry and Internal Medicine, Wright State University School of Medicine, Dayton, Ohio; Director, Psychiatry Education, Kettering Medical Center, Kettering, Ohio

J. David Sinclair, MD, FRCP
private practice, independent consultant for management of chronic non-cancer pain, Seattle, Washington

Michael W. Wiederman, PhD
Professor of Psychology, Department of Human Relations, Columbia College, Columbia, South Carolina

Dr. Sheehan is Distinguished University Health Professor, Professor of Psychiatry, Director, Depression and Anxiety Disorders Research Institute, University of South Florida College of Medicine, Tampa, Florida; Dr. Croft is Medical Director, San Antonio Psychiatric Research Center, San Antonio, Texas; Drs. Gossen, Levitt, Brullé, and Rozova are from Labopharm Inc., Laval, Québec, Canada; and Dr. Bouchard is from Lakeshore General Hospital, Montréal, Québec, Canada.

Psychiatry (Edgemont) 2009;6(5):20–33

Funding: Funding for the development of this manuscript was provided by Labopharm Inc., Laval, Québec, Canada

Trial registry information: Registry name: A Randomized, Double-Blind, Two-Arm Study Comparing the Efficacy and Safety of Trazodone Contramid® OAD and Placebo in the Treatment of Unipolar Major Depressive Disorder, Registration number: NCT00775203, Registration URL: http://www.clinicaltrials.gov/ct2/show/NCT00775203?term=NCT00775203&rank=1

Financial disclosures: Please see end of article for a list of author financial disclosures.

Key Words: Major depressive disorder, trazodone, extended release, antidepressant, serotonin-2 antagonist/reuptake inhibitor (SARI), placebo-controlled trial, Hamilton Depression Rating Scale

Abstract

Objective: To investigate the efficacy, safety, and clinical benefit of a once-daily formulation of trazodone (Trazodone Contramid® OAD) in the treatment of major depressive disorder.
Design/Participants: In this double-blind study, 412 patients with major depressive disorder (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria) were randomized 1:1 to receive either Trazodone Contramid OAD (150 to 375mg) or placebo. Treatment was titrated over two weeks to each individual optimal dose. Patients then continued six weeks of treatment; further dose adjustments were allowed based on efficacy and tolerability.
Measurements: The primary end point was change in the 17-item Hamilton Depression Rating Scale total score from baseline to last study visit. Secondary end points included Hamilton Depression Rating Scale responders/remitters, change in Montgomery-Åsberg Depression Rating Scale, Clinician and Patient Global Improvement Scales, and quality of sleep.
Results: From the end of titration to the end of the six-week treatment period, the mean maximum daily dose of the intent-to-treat population was 310mg for the active group and 355mg for the placebo group. There was a statistically significant difference between trazodone and placebo on the mean HAMD-17 score (-11.4 vs. -9.3, P=0.012). A significant difference was present as early as Week 1 and was maintained at all subsequent study visits. Many secondary end points supported these findings, including improvements in quality of sleep. The most frequent adverse events were the same for both the treatment and placebo groups: headache and somnolence. There were no serious adverse events that were considered related to treatment. There were no clinically significant electrocardiogram or laboratory abnormalities.
Conclusions: The trazodone Contramid formulation was more effective than placebo in major depressive disorder and was well tolerated.

INTRODUCTION

Trazodone is a triazolopyridine-derived antidepressant that acts by means of serotonin-2A and -2C (5HT2A/2C) receptor antagonism and through serotonin reuptake inhibition.[1,2] It belongs to a distinct class of antidepressants referred to as serotonin-2 antagonist/reuptake inhibitors (SARIs). Trazodone has moderate histamine-1 (H1) receptor antagonism and possesses some anxiolytic and hypnotic properties.[3,4]

Since its introduction 40 years ago as an atypical antidepressant with unique pharmacological properties, trazodone’s antidepressant equivalence to other drug classes is demonstrated in several comparative studies, including those with the tricyclic antidepressants amitriptyline and imipramine;[4] the selective serotonin reuptake inhibitors (SSRIs) fluoxetine,[5,6] paroxetine,[7] sertraline,[8] citalopram, and escitalopram;[9] the serotonin-norepinephrine reuptake inhibitors (SNRIs) venlafaxine[10] and mirtazapine;[9] and the norepinephrine and dopamine reuptake inhibitor bupropion.[11]

The sedative effects of immediate-release formulations of trazodone limit its dosing as an antidepressant.[1,10] Immediate-release trazodone is primarily prescribed as a hypnotic at doses ranging from 50 to 200mg.[1,12] At these low doses, immediate-release formulations achieve plasma concentrations that are sufficient to exploit sedating effects secondary to 5HT2A and H1 receptor antagonism, but are not sustained sufficiently to induce an antidepressant effect.[3,13] To achieve an antidepressant effect, higher daily dosages must be maintained if they are to adequately inhibit the 5HT2A and 5HT2C receptors and block the serotonin transporter.[3]

The sedating effects of trazodone may also be beneficial to patients with insomnia associated with MDD. Insomnia is a risk factor for the onset and relapse of MDD and an independent predictor for treatment failure, while its treatment may increase remission rates.[3,14,15] Trazodone administered as a single dose at bedtime may mitigate adverse effects associated with immediate-release trazodone.[16] However, current immediate-release formulations of trazodone recommend administration as divided daily doses.[17] No once-daily, controlled-release formulations exist for trazodone, while most other antidepressants are available as once-daily formulations. It is possible that a formulation that controls the release of trazodone over 24 hours may optimize its antidepressant efficacy while improving sleep in patients with MDD. These factors collectively provide a rationale for examining once-daily formulations of trazodone as a monotherapy for patients with MDD.

Trazodone Contramid® once-a day (OAD) is an extended-release, once-daily formulation of trazodone HCl developed by Labopharm Inc. (Laval, Québec, Canada). Trazodone Contramid OAD (TCOAD) is designed to optimize the antidepressant efficacy of trazodone. Contramid is a cross-linked, high-amylose starch excipient that provides controlled release of trazodone over an extended period.[18] TCOAD is available as 150 and 300mg trazodone HCl scored caplets to provide flexibility in dosing, and exhibits linear pharmacokinetics over doses ranging from 75 to 375mg. Administration of 300mg TCOAD provides equivalent steady-state exposure to 100mg immediate-release trazodone administered three times a day, yet with a 42-percent lower mean maximum plasma concentration (1812 vs. 3118ng/mL; Labopharm Inc., data on file).

The objective of this randomized, double-blind, phase III study was to investigate the efficacy and tolerability of TCOAD in patients with MDD.

METHODS

Patient selection. Patients included in this study were men and women, 18 years of age or older, who fulfilled the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for primary MDD, even in the presence of another nonexcluded Axis I disorder. Patients were required to have the current episode of MDD for a minimum of one month, whether diagnosed with a single episode or recurrent episodes. Eligible patients had to have dysphoria for most days over the previous four weeks and a Montgomery-Åsberg Depression Rating Scale (MADRS) total score of at least 26 at screening and baseline. Patients’ MADRS scores were used as an entry criterion rather than the 17-item Hamilton Depression Rating Scale (HAMD-17) score to reduce the potential for investigator bias on the primary end point when evaluating patients for inclusion in the study.

Patients with DSM-IV MDD specifiers, such as catatonic features, postpartum onset, and/or seasonal patterns, were excluded from the study. Other exclusion criteria consisted of patients with generalized anxiety disorder, panic disorder, social phobia, obsessive-compulsive disorder, posttraumatic stress disorder, eating disorder, bipolar disorder, alcohol/substance abuse or dependence (caffeine and nicotine allowed), any psychotic disorder, depression secondary to stroke, cancer, or other severe medical illnesses, psychotherapy at the time of enrollment, or high suicide risk. Patients were also excluded if, within the previous three weeks, they were treated with monoamine oxidase inhibitors or during the study used antipsychotics, protease inhibitors, or any concomitant medications causing QT or PR prolongation.

Study design. This double-blind, randomized, placebo-controlled, two-arm, multicenter study (Labopharm protocol 04ACL3-001) evaluated the efficacy and safety of TCOAD (150, 225, 300, 375mg daily) versus placebo for the treatment of MDD. The study was conducted from May 2007 to November 2007 at 38 active centers in the USA and Canada. The protocol conformed to the International Conference on Harmonisation—Good Clinical Practice (ICH-GCP) guidelines and was conducted in compliance with the Declaration of Helsinki.

During the first screening visit, patients provided informed consent and underwent an initial screening for inclusion (Figure 1). The screening visit included the informed consent procedure and assessment for the DSM-IV criteria for MDD (confirmed by the Mini International Neuropsychiatric Interview), the MADRS, concurrent medications, a medical history, a physical examination, vital signs, hematology and blood chemistry analyses, urinalysis, and a 12-lead electrocardiogram (ECG). ECGs were performed at the study centers and interpreted centrally by an independent bioanalytic firm (Covance Cardiac Safety Services, Reno, Nevada) by a panel of cardiologists blind to the patients’ treatment statuses.

In addition to the medications listed in the exclusion criteria, use of antidepressants other than the study medication (including herbal preparations), sedatives, and hypnotics were not permitted during the study. Patients had to be off all prohibited medications for at least five half lives prior to randomization at baseline. Baseline (Visit 2) assessments included the MADRS, HAMD-17, Clinical Global Impression—Severity of Illness (CGI-S), quality of sleep measures, and vital signs. Patients who met eligibility criteria were then randomized to either the TCOAD or placebo treatment arms.

Each randomized patient was registered into the Fisher Automated Clinical Trial System (FACTS), which tracked patient enrollment status and managed randomization, study medication inventory, resupply, and distribution to each participating site.

Over the first two weeks of the double-blind phase, patients’ doses were titrated every 3 to 4 days by 75mg increments from a starting dose of 150mg to a maximum daily dose of 375mg. At each dosing step, if a dose was not well tolerated after two days, patients had the option to decrease to the previous dose. On Days 4 and 9 of titration, patients were contacted by telephone to assess their progress and to assist in deciding whether to decrease the dose of study medication. Patients were allowed to decrease their dosage only once during the titration period. Once the optimal daily dose was selected, patients remained at that dose until the beginning of the six-week treatment period, after which the dose could be adjusted based on efficacy or tolerability. Rescue medications for the treatment of MDD symptoms were not allowed during the study.

Patients were instructed to take their medication once daily at bedtime. To maintain blinding, the active drug and placebo were identical in appearance.

Study assessments. Efficacy and safety evaluations were done at baseline (Day 0), at Days 7 and 14 (titration period visits), and at Days 21, 28, 42, and 56 (treatment period visits). For each visit to the clinic, a “visit window” of plus or minus three days was allowed, with the exception of the last study visit and evaluations performed following discontinuation, for which a plus or minus one-week visit window was permitted.

The primary end point was the change in the HAMD-17 total score from baseline to the last study visit (Day 56 or following discontinuation). Secondary end points consisted of 13 measures: HAMD-17 responders, defined as patients with a decrease of 50 percent or more from baseline to last visit on the HAMD-17 total score; HAMD-17 remitters, defined as patients who achieved a HAMD-17 total score of 7 or less; change in HAMD-17 depressed mood item from baseline; change in MADRS total score from baseline to the last study visit; Clinical Global Impression—Improvement of Illness (CGI-I) responders, defined as patients assessed by investigators as “much improved” or “very much improved” at the last study visit; Patient Global Impression—Improvement of Illness (PGI-I) responders, defined as patients who reported being “much improved” or “very much improved” at the last study visit; change in CGI-S from baseline; CGI-I at the last study visit; PGI-I at the last study visit; and discontinuations due to lack of efficacy. The final secondary end point assessed quality of sleep across three parameters—overall quality of sleep, trouble falling asleep, and awakening during the night—using patient-rated, four-point Likert scale: overall quality of sleep had the possible response options of “excellent”, “good,” “fair,” and “very poor;” trouble falling asleep and awakening during the night had the possible response options of “never,” “rarely,” “frequently,” and “always.”

At each visit, patients’ concomitant medications and adverse events were recorded. Body weight, hematology, blood chemistry, urinalysis, physical examination, and a standard supine, 12-lead ECG were recorded at the last study visit. All AEs and SAEs were followed to resolution, until the condition stabilized or until the patient was lost to followup.

Statistical analyses. Safety analyses were performed on the safety (intent-to-treat [ITT]) population, which was defined as patients who were randomized to the study medication at baseline. Efficacy analyses were performed on the modified ITT population and per protocol (PP) populations. The modified ITT population was defined as all randomized patients who received at least one dosage of the double-blinded study medication, and at least one post-baseline HAMD-17 assessment. The PP population was defined as all randomized patients who completed the study, had no major protocol violations, and had a HAMD-17 rating at the end of the study. End-of-study scores for post-randomization missing data in the modified ITT population were derived using the last observation carried forward (LOCF) data imputation. The observed cases (OC) dataset included only the observations that occurred within the allowed visit window.

The primary efficacy end point (change in HAMD-17 from baseline) was compared between the treatment groups using an analysis of covariance (ANCOVA), with treatment, study center, and baseline as covariates. A mixed-model repeated-measures (MMRM) analysis using an unstructured covariance matrix was used as a sensitivity analysis to support the primary efficacy end point LOCF analysis results. The overall difference over time between the two treatment groups for the primary efficacy end point was tested using a mixed linear model for repeated measures with treatment and study center as factors, study week as the time point, and baseline HAMD-17 total score as a covariate. Only assessments from the treatment period were incorporated into the repeated measurement model.

To achieve 90 percent power to detect a 3.0 unit absolute mean change in the HAMD-17 total score from baseline, a sample size of 133 patients in each treatment group was needed to complete the study; this assumed a common standard deviation of 7.5 with a two-group, two-tailed t test with significance set at P=0.05. Assuming a discontinuation rate of 30 percent, an enrollment of 190 patients in each treatment group was required.

For the categorical secondary end points—responders and remitters in HAMD-17, CGI-I, and PGI-I scores—a Cochran-Mantel-Haenszel test, adjusted for site, was used to test for statistically significant differences between treatment groups. A Fisher’s exact test was used to test for statistically significant differences between groups for the percentage of patients who discontinued due to lack of efficacy and for significant differences in the distribution of responses for each of the three quality of sleep Likert-type items at each visit. For the continuous secondary end points, change from baseline in the HAMD-17 depressed mood item (item 1), change from baseline in MADRS, and CGI-S, a two-way (treatment, time), repeated-measures ANCOVA was used to assess whether the mean response profile over the treatment period differed significantly between the two groups.

RESULTS

Patient characteristics. Of 574 patients screened, a total of 412 patients were randomized to receive either TCOAD (n=206) or placebo (n=206). There were no remarkable differences between the treatment groups with respect to gender, age, or ethnicity. One hundred and five of 412 patients (25.5%; TCOAD, n=62; placebo, n=43) prematurely discontinued the study (Figure 2); six patients (1.5%) discontinued without receiving at least one dose of study medication. Of the 406 patients who received at least one dose of study medication (202 patients in the TCOAD group; 204 patients in the placebo group), the most frequent reasons for discontinuation were AEs (TCOAD, n=25; placebo, n=6), patients lost to followup (TCOAD, n=11; placebo, n=15), and patient requests (TCOAD, n=11; placebo, n=9). The modified ITT population contained all 406 patients that comprised the safety population. The PP population contained a total of 298 patients (TCOAD, n=136; placebo, n=162).

Baseline characteristics are presented in Table 1. The mean age of the modified ITT population was 43.9 (SD: 13.1) years; 260 of 406 (64.0%) were female, and 279 of 406 (68.7%) were Caucasian. There were no remarkable differences between treatment groups with respect to demographics, depression history, baseline depression parameters (HAMD-17, MADRS, and CGI-S) or baseline quality of sleep parameters (overall quality of sleep, trouble falling asleep, awakening during the night). On average, randomized patients had one (SD: 1.1) previous depressive episode over the 24 months prior to study entry (Table 2); the overall mean duration of the current episode was 14.7 (SD: 31.0) months.

In total, 88 of 406 of the randomized patients (21.7%) took medication within the 30 days prior to taking the study medication. The most commonly used medications, regardless of treatment group, were antidepressants (TCOAD: 11/202, 5.4%; placebo: 18/204, 8.8%). Other medications taken by patients in the safety population in the 30 days prior to the study included anxiolytics (14/406 patients, 3.4%), nonsteroidal anti-inflammatory drugs (8 patients, 2.0%), hypnotics and sedatives (13 patients, 3.2%), opioids (8 patients, 2.0%) and other analgesics and antipyretics (14 patients, 3.4%).

Dosing and exposure. At the end of the two-week titration period, 108 of 177 patients (61.0%) in the TCOAD group and 168 of 194 patients (86.6%) receiving placebo required the highest available dosage of 375mg once-daily (dose level IV, Figure 1). The mean maximum daily dosage of the safety population from the end of titration to the end of the six-week treatment period was 310mg (SD: 81mg) for the TCOAD group and 355mg (SD: 50mg) for patients on placebo. Over the total course of the study (titration and treatment period combined), the mean number of days of therapy was 51.6 (SD: 12.8) days for the active treatment and 46.8 (SD: 17.6) days for placebo. The distribution of daily dosages for patients at the end of titration is summarized in Table 3.

Antidepressant efficacy. The mean HAMD-17 total scores at baseline were 23.2 (SD: 4.2) and 22.4 (SD: 4.4) for patients randomized to TCOAD and placebo, respectively (Table 1). The corresponding mean scores at the last study visit (LOCF) were 11.8 (SD: 8.0) for the active treatment group and 13.2 (SD: 8.1) for placebo. Consequently, the primary end point of this study—the change in the HAMD-17 total score from baseline to the last study visit—decreased by an average of 11.4 (SD: 8.2) in the TCOAD group versus 9.3 (SD: 7.9) in the placebo group. This difference was found to be statistically significant in favor of the TCOAD group (P=0.012, Table 4a Table 4b Table 4c). The corresponding percentage of change in the HAMD-17 total score was 49 percent in the TCOAD group and 41 percent in the placebo group. The statistical significance achieved with the LOCF analyses were confirmed by the MMRM sensitivity analysis, which also achieved statistical significance (P=0.006, Table 4a Table 4b Table 4c).

The antidepressant efficacy of the active treatment group was further supported by the change from baseline in the HAMD-17 total score at each post-randomized visit; these results demonstrated a significantly greater improvement in the mean HAMD-17 total score in the TCOAD group compared with placebo by the first week of the double-blind phase (Day 7 of titration, mean [SD]: 5.6 [5.2] vs. 3.9 [4.8], respectively; P=0.005, LOCF). The significantly greater differences were maintained throughout the study (Figures 3a-c). To assess the average antidepressant efficacy throughout treatment, an ANCOVA of the time-weighted average (TWA) of the HAMD-17 total scores at each study visit during the six week treatment period was performed. These results demonstrated a significantly greater decrease in absolute mean improvement in the HAMD-17 total score from baseline for the TCOAD compared with placebo (11.0 [SD: 7.2] vs. 8.6 [SD: 6.8], respectively; P=0.002). A summary of the primary and secondary efficacy results is presented in Table 4a Table 4b Table 4c.

The majority of the secondary efficacy end points at the last study visit (Day 56) showed statistically significant better outcomes for patients receiving TCOAD than those receiving placebo, which held across both the modified ITT and PP populations (Table 4a Table 4b Table 4c). There was a higher percentage of HAMD-17 responders and a greater decrease in the change from baseline in the HAMD-17 depressed mood item (item 1), CGI-S, and MADRS total score. The results of the HAMD-17 responder analysis demonstrated that there were more responders in the active treatment group than in placebo by the end of the titration period (P=0.008, LOCF). The significantly greater number of HAMD-17 responders was maintained until the end of the treatment period (Figure 3b Figures 3a-c).

At the last study visit, the number of HAMD-17 remitters and percentages of CGI-I and PGI-I responders in patients receiving TCOAD were not statistically different (LOCF) compared with placebo. However, the mean percentages of HAMD-17 remitters in the modified ITT and PP populations were significantly higher for patients in the TCOAD group than placebo during all other treatment period assessment days (Figure 3c Figures 3a-c). Moreover, the PGI-I responders in the active treatment group were significantly different from placebo for the PP population (P=0.033): 76 of 133 patients (57.1%) receiving TCOAD reported their improvement of illness as “very much improved” or “much improved” compared with 77 of 160 (48.1%) receiving placebo.

Quality of sleep. At the end of the study, the patients from the modified ITT/ LOCF dataset in the TCOAD group had statistically significant improvements compared with placebo in all quality of sleep parameters; the differences in the quality of sleep questionnaire response distributions also achieved statistical significance in the PP population, except for overall quality of sleep. Improvements in quality of sleep were quantified by assessing the proportion of patients with more favorable responses on the Likert scales at the end of the study. To illustrate, 121 of 201 patients (60.2%) in the modified ITT population receiving TCOAD reported having either “excellent” or “good” overall quality of sleep compared with 92 of 204 patients (45.1%) receiving placebo; 150 of 201 patients (74.6%) receiving active treatment also reported “never” or “rarely” awakening during the night compared with 122 of 204 patients (59.8%) receiving placebo. Likewise, 140 of 201 patients (69.7%) in the active treatment group reported “never” or “rarely” awakening during the night compared with 111 of 204 (54.4%) in the placebo group.
The response distributions for all quality of sleep parameters throughout the study are illustrated in Figures 4a-c. Specifically, there was a trend toward a greater proportion of patients receiving TCOAD reporting “excellent” or “good” overall quality of sleep (Figure 4a Figures 4a-c), “never” or “rarely” trouble falling asleep (Figure 4b Figures 4a-c), and “never” or “rarely” experiencing awakening during the night (Figure 4c Figures 4a-c). Moreover, some of the improvements in the quality of sleep were associated with a rapid onset: the overall quality of sleep (Figure 4a Figures 4a-c) and awakening during the night (Figure 4c Figures 4a-c) response distributions showed statistically significant shifts to better responses in patients receiving TCOAD by Day 7 of the titration phase. These significant differences were maintained throughout most days of the treatment period.

Safety and tolerability. TCOAD was relatively well tolerated. AEs were the primary reason for withdrawal in patients receiving active treatment. There were 25 of 202 patients (12.4%) in the TCOAD group and six of 204 patients (2.9%) in the placebo group who discontinued due to AEs (Figure 2). The most commonly reported reasons for discontinuations due to AEs in the TCOAD group were dizziness (7 patients), sedation (5 patients), and somnolence (3 patients).

During the course of the study, 345 of 406 patients (85.0%) in the safety population (181 on TCOAD; 164 on placebo) reported at least one AE. AEs reported by five percent or more patients are presented in Table 5. The most common (≥10%) were headache, somnolence, dry mouth, dizziness, nausea, sedation, fatigue, and diarrhea. Overall, the intensity of AEs experienced by patients on TCOAD was mild to moderate in the majority of cases and similar to placebo (TCOAD: 148/202, 73.3%; placebo: 148/204, 72.5%). Only one patient treated with TCOAD reported anxiety during the study compared with five receiving placebo (TCOAD: 1/202, 0.5%; placebo: 5/204, 2.5%). There were no notable changes in vital signs (blood pressure, respiratory rate, pulse) or body weight in either treatment group during the study. No ECG abnormalities occurring during the trial were considered clinically significant. Although some patients exhibited ECG waveforms that fluctuated between normal and abnormal in both groups, the general review of the data did not reveal a consistent signal of repolarization abnormalities associated with trazodone at the doses that were administered in the trial.

Five patients experienced at least one SAE during the study or within 30 days after the last dose (3 patients in the TCOAD group; 2 patients in the placebo group). One patient receiving placebo died; despite appropriate followup, the family did not consent to the release of the autopsy results, and the exact cause of death is unknown. None of the SAEs were judged to be related to the study medication.

The incidence of sexual dysfunction in patients on TCOAD (10/202, 4.9%; placebo: 5/204, 2.5%) was unusually low for an antidepressant. In the TCOAD group, the most common sexual dysfunction was decreased libido, which occurred in three patients; collectively, ejaculation dysfunctions (comprising ejaculation delay, disorder, or failure) occurred in three patients. Table 6 summarizes the incidence of sexual dysfunction in the safety population. No instances of priapism occurred during the study.

The mean time to onset and median duration of the most common AEs are presented in Table 7. The mean time to onset of the most common AEs in patients treated with TCOAD ranged from 6 to 10 days, except for diarrhea (17 days) and back pain (26 days). In the placebo group, the mean time to onset of the most common AEs ranged from 9 to 13 days except for diarrhea (17 days), constipation (17 days), and back pain (23 days). In the TCOAD group, the time to onset for sedation ranged from 1 to 21 days (mean: 6 days); the time to onset for somnolence ranged from 1 to 37 days (mean: 8 days).

Data on duration of AEs were not normally distributed; thus, the median durations are presented. The median duration of the most common AEs (≥10%) in patients receiving TCOAD ranged from 4 to 9 days (Table 7) except for dry mouth (27 days, placebo: 22.5 days), sedation (12.5 days, placebo: 18 days), and fatigue (23 days; placebo: 19 days). Although the duration was prolonged in some patients, this did not generally lead patients to discontinue the study.

DISCUSSION

This is the first large, randomized, double-blind, placebo-controlled trial assessing the efficacy and safety of a once-daily, extended-release formulation of trazodone HCl (TCOAD) in patients with MDD. Following the two-week titration period, patients receiving TCOAD maintained a mean maximum daily dosage of 310mg during the six-week treatment period. Following eight weeks of treatment, the result of primary efficacy end point analyses demonstrated a consistent statistical superiority of TCOAD therapy over placebo. This was accompanied by statistically significant improvements in 7 of 13 secondary efficacy end points in the active treatment group compared with placebo for both the modified ITT and PP populations. TCOAD was also well-tolerated: the majority of AEs were mild to moderate in intensity, occurred during titration, and transient for most patients.

Antidepressant efficacy. Following eight weeks of treatment, there was a statistically significant greater decrease in the mean HAMD-17 total score in the TCOAD group from baseline (-11.4) than placebo (-9.3). The statistical significance achieved by the modified ITT population (P=0.012) was also achieved in the PP population analyses (P=0.009). This outcome was supported by four secondary efficacy outcomes: active treatment demonstrated in a significantly greater decrease from baseline than placebo in the mean HAMD-17 mood item, the mean MADRS score, the mean CGI-S score, and the number of HAMD-17 responders (Table 4a Table 4b Table 4c). These results are consistent with a large body of evidence demonstrating the efficacy of other trazodone formulations in the treatment of MDD.[6–8,10,11,19–21]

A noteworthy supplement to these analyses was the inclusion of an MMRM sensitivity analysis. The MMRM sensitivity analysis imputes missing data with a likelihood-based estimation of patient responses derived from the patient population data. Analyses of covariance using this form of imputation provide lower and more consistent type I error rates than results obtained from analyses with LOCF imputed data.22 The results of the MMRM analysis on the decrease in the HAMD-17 total score from baseline affirmed the statistical significance achieved by the LOCF- and OC-based analyses (P=0.006, Table 4a Table 4b Table 4c), thereby demonstrating a consistent statistically superiority of TCOAD over placebo on the primary efficacy end point.

While all significantly improved secondary end points in the modified ITT population were also demonstrated in the PP population, other secondary end points, such as the PGI-I and CGI-I (Table 4a Table 4b Table 4c), exhibited notable differences. Statistical significance was not achieved for both these end points in the modified ITT population (LOCF), yet the PP population analysis achieved significance for the PGI-I (P=0.033, OC) and approached significance for the CGI-I (P=0.066, OC). With these end points, LOCF imputation may have contributed to decreasing the proportion of patients reporting their improvement of illness (i.e., PGI-I) as “very much improved” and “much improved” (TCOAD: LOCF, 90/176 [51.1%], OC, 76/133 [57.1%]; placebo: LOCF, 80/183 [43.7%]; OC, 77/160 [48.1%]). A similar decrease between the two analyses was also observed for the CGI-I, which had a noticeable effect on the P values (modified ITT population, P=0.22; PP population, P=0.07).

Efficacy during the double-blind phase. The clinical relevance of early improvements in HAMD-17 scores was illustrated in patients with MDD receiving mirtazapine or paroxetine therapy.23 Szegedi et al23 showed that an early improvement in HAMD-17 scores, defined as a reduction of at least 20 percent within two weeks of treatment, was a highly sensitive predictor of a later stable response and remission.23 The improvement in the mean HAMD-17 score observed after the first week of therapy corresponded to a relative decrease of 24 percent from baseline in patients receiving TCOAD versus 18 percent decrease in the placebo group (Figure 3a Figures 3a-c). Early improvements in patients receiving TCOAD—that is, those that occurred within the first two weeks of the double-blind phase—were further characterized by a significantly greater number of HAMD-17 responders than placebo (Figure 3bFigures 3a-c ). While the number of HAMD-17 remitters receiving active treatment (72/202, 35.6%) was not significantly different from placebo at the end of the study (due to an unexpected increase in the percentage of remitters in placebo group from Day 42 to Day 56) there were significantly more remitters in the TCOAD group for all other assessments during the treatment period (Figure 3c Figures 3a-c).

Quality of sleep. TCOAD significantly improves quality of sleep in patients with MDD (Figure 4Figures 4a-c). It is well known that trazodone improves sleep quality in both depressed and nondepressed patients.[24] For example, in a double-blind, four-week, multicenter study with depressed inpatients, Brooks et al[25] demonstrated that 100 to 400mg/day of immediate-release trazodone, given either as a single night-time or thrice daily dosage, significantly improved sleep variables (onset, satisfaction, and duration) compared with placebo. Studies further show that trazodone is more effective than various comparators in improving sleep as assessed by the HAMD sleep disturbance factor.[7,8,10,11,26]

The clinical utility of targeting insomnia in patients with MDD, which is reported in more than 90 percent of patients, in part arises from its predictive association for the onset and relapse of MDD.[4,14,27,28] Indeed, the persistence of insomnia in patients with major depression can serve as a marker of treatment failure in commonly administered treatments such as SSRIs.[14] Moreover, recent evidence suggests treatment of insomnia may contribute to improvement in nonsleep depressive symptoms.[28] In the present study, the prevalence of insomnia at baseline was representative of the overall prevalence of insomnia in patients with MDD. A patient was classified as having insomnia if either his or her baseline HAMD item 4 (early insomnia), item 5 (middle insomnia), or item 6 (insomnia late) scores was 2 or greater or the sum of the three insomnia item scores was 4 or greater. Based on these criteria, 379 of 406 patients (93.3%) in the safety population (TCOAD, 191; placebo, 188) had insomnia at baseline. This corresponded closely with the proportion of patients who report having “fair” or “very poor” overall quality of sleep at baseline (371/406 [91.4%]; Table 1). Patients receiving active treatment demonstrated significant improvements in all three quality of sleep end points, with an improvement by the first week of therapy in “overall quality of sleep” (Figure 4a Figures 4a-c) and “awakening during the night” (Figure 4c Figures 4a-c).

Safety and tolerability. The incidence of the AEs reported in the present study were typical of those found with other formulations of trazodone.[6–8,11,17,21,29,30] Moreover, TCOAD was well tolerated: most AEs were mild to moderate in intensity and led to few discontinuations. Of the 25 patients who discontinued in the active treatment group due to AEs, the most common reasons were dizziness, sedation, and somnolence typically associated with trazodone. When the time course of these AEs was examined in the safety population (Table 7), these effects were found to have an early onset and were transient for most patients. Specifically, dizziness had a mean onset of 6.7 days and a median duration of four days; somnolence, a mean onset of 7.6 days and a median duration of nine days; and sedation, a mean onset of 6.1 days and a median duration of 12.5 days. Although the duration was prolonged in some patients, it did not lead to many discontinuations. In total, 15 of 202 patients (7.4%) discontinued due to these AEs—only eight patients (4.0%) receiving TCOAD discontinued because of sedation or somnolence. The low discontinuation rates combined with the improved quality of sleep in patients receiving active treatment speaks to the notion that the antidepressant efficacy achieved with a mean daily dosage of 310mg of TCOAD was accompanied by beneficial rather than intolerable or unacceptable sedative effects.

AEs of particular concern are those related to weight gain and sexual dysfunction, which are among the most prevalent reasons for discontinuation of antidepressant therapy.[31,32] In this study, there were no significant changes in body weight in either treatment group. While trazodone is not associated with the sexual adverse events observed with SSRIs or SNRIs,[33–35] rare sexual adverse effects have occurred. The occurrence of priapism in men can lead to permanent impairment of erectile function or impotence.[17] However, the incidence of this event in men treated with trazodone is rare (1 in 1,000 to 1 in 10,000)[36] and was not observed in this study. The sexual side effects of trazodone also include increased libido and hypersexual behavior.[37,38] These sexual side effects of trazodone have led to its study as a potential treatment for erectile dysfunction[39,40] and as a treatment for SSRI-related sexual dysfunction.[41] The mean age of our study population (44 years) suggests that the patients were generally sexual active. The low rate of sexual dysfunction reported in patients receiving TCOAD (4.9% vs. 2.5% for placebo, Table 6) combined with its antidepressant efficacy and the purported benefits of some sexual side effects of trazodone suggest TCOAD may be of interest for patients with MDD who have previously experienced sexually related AEs on SSRIs or SNRIs.

CONCLUSION

The results of this large, randomized, double-blind study show that TCOAD—at a mean maximum daily dosage of 310mg—demonstrated a significantly greater improvement in the HAMD-17 primary efficacy end point over placebo. The efficacy was further supported by significant improvements in 7 of 13 secondary end points, including HAMD-17 responders, MADRS score, and quality of sleep. The antidepressant efficacy, improvements in quality of sleep, lack of sexual dysfunction, and the low incidence of anxiety in patients receiving TCOAD may be related to the antagonism of 5HT2A/2C and H1 receptors by trazodone.[3] Although TCOAD was associated with serotonergic and histamine-related AEs typical of those associated with trazodone, this once-daily, extended-release formulation was associated with AEs that were well tolerated and transient for most patients. We conclude that TCOAD at the recommended daily dosage of 300mg appeared to be an appropriate monotherapy for patients with MDD.

Acknowledgment

We wish to convey our deepest thanks to the patients who participated in this clinical study. We also thank INC Research, Inc. for their implementation of the study protocol. Thanks also to Nancy Vermette for her assistance in creating tables and figures for this publication.
We are grateful for the hard work and dedication of the following principal investigators and their staff: Charles Bailey, MD; Roberta Ball, DO; Michael D Banov, MD; Bijan Bastani, MD; Louise Beckett-Thurman, MD; Richard Bergeron, MD; John Carman, MD; Patricia A Daly, MD; Bernadette B D’Souza, MD; Neil S Dubin, MD; Steven J Glass, MD; Michael Greenbaum, MD; Allen Greenspoon, MD; Paul R. Latimer, MD; Michael D Lesem, MD; Raymond Matte, MD; Guiseppe Mazza, MD; Alexander McIntyre, MD; Charles H Merideth, MD; Nicholas J Messina III, MD; P Ryan Moe, MD; Leslie P Moldauer, MD; Marino Molina, MD, CPI; Dennis J Munjack, MD; William M Patterson, MD; John Mark Royce, MD; Angelo Sambunaris, MD; Elias H Sarkis, MD; Ram K Shrivastava, MD; Mary L Stedman, MD; Brock H Summers, MD; Nick G Vatakis, MD; Bradley D Vince, DO; Inna Yuryev-Golger, MD

Financial Disclosures

Dr. Croft is a consultant for, and has receive research grants from GlaxoSmithKline, Labopharm, Forest Laboratories, Boehringer Ingelheim, Eli LIlly and Astra-Zeneca. Drs. Gossen, Levitt, and Rozova are employees of Labopharm Inc. Dr. Bouchard is a consultant in clinical research for Labopharm Inc. Dr. Sheehan has received grant funding support, has been affiliated, or received honoraria and travel expenses related to lectures/presentations or consultant activities from the following organizations: Abbott Laboratories, Ad Hoc Committee, Treatment Drug & Assessment Research Review, Alexa, Alza Pharmaceuticals, Palo Alto, California, American Medical Association, American Psychiatric Association Task Force on Benzodiazepine Dependency, American Psychiatric Association Task Force on Treatments of Psychiatric Disorders, American Psychiatric Association Working Group to revise DSM III Anxiety Disorders Section, Anclote Foundation, Anxiety Disorders Resource Center, Anxiety Drug Efficacy Case, U.S. Food & Drug Administration, Applied health Outcomes/ XCENDA, AstraZeneca, Avera Pharmaceuticals, Boehringer Ingelheim, Boots Pharmaceuticals, Bristol-Myers Squibb, Burroughs Wellcome, Cephalon, Charter Hospitals, Ciba Geigy, Committee (RRC) of N.I.M.H. on Anxiety and Phobic Disorder Projects, Connecticut & Ohio Academies of Family Physicians, Cortex Pharmaceutical, Council on Anxiety Disorders, CPC Coliseum Medical Center, Cypress Bioscience, Dista Products Company3, Division of Drugs & Technology, American Medical Association, EISAI, Eli Lilly, Excerpta Medica Asia, Faxmed, Inc., Forest Laboratories, Glaxo Pharmaceuticals, GlaxoSmithKline, Glaxo-Wellcome, Hospital Corporation of America, Humana, ICI, INC Research, International Clinical Research (ICR), International Society for CNS Drug Development (ISCDD), Janssen Pharmaceutical, Jazz Pharmaceuticals, Kali-Duphar, Labopharm, Layton Bioscience, Lilly Research Laboratories, Lundbeck, Denmark, Marion Merrill Dow, McNeil Pharmaceuticals, Mead Johnson, Medical Outcome Systems, MediciNova, Merck Sharp & Dohme, National Anxiety Awareness Program, National Anxiety Foundation, National Depressive & Manic Depressive Association, National Institute of Drug Abuse, National Institute of Health (NIH), Novartis Pharmaceuticals Corp., Novo Nordisk, Organon, Orion Pharma, Parexel International Corporation, Parke-Davis, Pfizer, Pharmacia, Pharmacia & Upjohn, Philadelphia College of Pharmacy & Science, Pierre Fabre, France, Quintiles, Rhone Laboratories, Rhone-Poulenc Rorer Pharmaceuticals, Roche, Roerig, Sandoz Pharmaceuticals, Sanofi-Aventis, Sanofi-Synthelabo Recherche, Schering Corporation, Sepracor, Shire Laboratories, Inc., SmithKlineBeecham, Solvay Pharmaceuticals, Takeda Pharmaceutical, Tampa General Hosp. University of South Florida Psychiatry Center, University of South Florida College of Medicine. TAP Pharmaceuticals, Targacept, TGH-University Psychiatry Center, Tikvah Therapeutics, Titan Pharmaceuticals, United Bioscience, The Upjohn Company, U.S. Congress-House of Representatives Committee, USF Friends of Research in Psychiatry, Board of Trustees, Warner Chilcott, World Health Organization, Worldwide Clinical Trials, Wyeth-Ayerst, ZARS, Zeneca Pharmaceuticals.

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