Dr. Sussman is editor of Primary Psychiatry as well as Associate Dean for Post-Graduate Programs and professor of psychiatry at the New York University School of Medicine in New York City.

Dr. Sussman reports no affiliation with or financial interest in any organization that may pose a conflict of interest.

Email questions or comments to ns@mblcommunications.com


Selecting the best strategy to optimize antidepressant response is a major ongoing clinical challenge. The need for more effective approaches for producing remission has been made clear by recent evidence that confirms treatment with any single antidepressant drug produces remission in only ~33% of patients, and that when antidepressants do work, they are of most benefit to those with more severe depressive symptoms. Patients with moderate levels of depression who seek care because they are either distressed or impaired by their symptoms may, paradoxically, be more difficult to bring into remission than those with a more pronounced disorder. An abundance of studies have shown that numerous augmentation or switching strategies may be effective for some patients, but no body of evidence demonstrates consistent superiority of any. In summarizing lessons learned from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial, the most ambitious attempt to date to address the question of antidepressant enhancement options, Rush wrote that “the gap between what we do in practice and what we know is very large.”1 In the near future, another study should be published that looks at whether it is better to start treatment with a combination of antidepressants rather than monotherapy. In anticipation of that article, I want to review the STAR*D trial and its major finding and describe the Combining Medication to Enhance Depression Outcomes (CO-MED), which looks at whether it is better to start treatment with two drugs instead of one.



STAR*D focused on non-psychotic major depressive disorder (MDD) in adult outpatients. The primary purpose of this research study was to determine which treatments work best if the first treatment with medication does not produce an acceptable response. All participants at first received the selective serotonin reuptake inhibitor (SSRI) citalopram (open label). If symptoms remained after 8–12 weeks of treatment, up to four other levels of treatment were offered, including cognitive therapy and other medications (Table 1). There was no placebo treatment option.

The study involved a highly representative clinical sample of depressed outpatients. In that regard, the STAR*D population was different than the highly selective cohort usually enrolled in industry-sponsored clinical trials.

At each level change, participants were asked to indicate the unacceptability of the potential treatment strategies (eg, to augment or to switch medications). Participants were then be eligible for random assignment the next treatment options.

Level 2

Participants who either did not have an adequate response to or could not tolerate citalopram are eligible for Level 2. The Level 2 treatment strategies were:


i) Medication and Psychotherapy Switch: switch to sertraline, venlafaxine extended release (XR), bupropion sustained release (SR), or cognitive therapy (CT).
ii) Medication and Psychotherapy Augmentation: add to citalopram either a) buspirone, b) bupropion SR, or c) CT.
iii) Medication Only Switch or Medication Only Augmentation: options were available for participants for whom CT is
iv) Psychotherapy Only Switch or Psychotherapy Only Augmentation: options were available for participants for whom additional medication is unacceptable at this point in the study (participants must be willing to continue citalopram)


Level 2A

Participants without a satisfactory response to their Level 2 treatment were eligible for random assignment to additional treatment at Level 2A. Level 2A was included so that all participants entering Level 3 had an opportunity to respond to at least two medications. Level 2A consisted of medication switch to one of two antidepressants (venlafaxine XR or bupropion SR).


Level 3

Participants without satisfactory response to Level 2 and, if appropriate Level 2A, were eligible for random assignment to one of the following treatments:
i) Medication Switch to: a) mirtazapine or b) nortriptyline, a tricyclic antidepressant.
ii) Medication Augmentation: add (to current Level 2 or Level 2A medication) either: a) lithium or b) thyroid hormone (T3).


Level 4

Participants without an adequate response to Level 3 were eligible for random assignment to Level 4 treatment. Level 4 includes two medication switch options: to tranylcypromine (a monoamine oxidase inhibitor), or to mirtazapine plus venlafaxine XR.



The study, which cost $35 million, failed to find any significant differences between drugs at each step in terms of the primary outcome measure, which was remission of depression. While there have been other significant findings from the study, the data did inform practitioners about “next step” management of patients with who fail on initial therapy.

CO-MED, like the STAR*D trial, was National Institute of Mental Health sponsored.2 Completed in late 2009, the results of this research have not been published. In contrast to STAR*D, this study compared whether a combination of antidepressants is better than one antidepressant alone when administered as initial treatment for people with chronic or recurrent MDD. CO-MED was designed to test whether two different medications when given in combination as the first treatment step, compared to one medication, enhances remission rates, increases speed of remission, is well tolerated, and provides better sustained benefits in the longer term. There were two arms to the study.

In Arm A, one of the following were given along with placebo: bupropion, escitalopram, mirtazapine, or venlafaxine.

In Arm B, two of the following drugs were given in combination: bupropion, escitalopram, mirtazapine or venlafaxine (Table 2).

Hopefully, the results of CO-MED will prove less nihilistic than those of the STAR*D trial with respect to answering the major question: Which treatment works best? One of the more disappointing aspects of both studies is that neither one looked at the use of a second-generation antipsychotic as an add-on treatment. Given that we now have increasing use of these drugs to augment antidepressants, it would be reassuring to have comparative data on both the safety and effectiveness of this approach.



Perhaps the answers we are looking for in terms of predicting treatment response may not come from large comparative clinical trials, but from molecular psychiatry research.

I want to thank David A. Mrazek, MD, FRCPsych, for serving as guest editor for this issue. Pharmacogenomic testing, he observes, may soon become standard practice based on the patient-specific evidence base that already exists. The four articles in this issue that address progress in individualized molecular psychiatry hint at the possibility, he notes, that we will be able to abandon our traditional trial and error approach to medication selection and begin providing our patients safer and more effective individualized psychopharmacologic treatments.

I also direct your attention to an article by Racha Nazir, MD, and colleagues regarding advice on starting the outpatient clinic. It touches on practical issues as office design, charting, knowledge of pharmacotherapy and psychotherapy, and individualization of patient care.

This issue marks the introduction of a new bi-monthly column titled “Clinical Updates in Child & Adolescent Psychiatry” by Margaret D. Weiss, PhD. Dr. Weiss is the head of the Provincial ADHD Program and clinical professor at the University of British Columbia Children’s & Women’s Health Centre in Vancouver, Canada. The column will highlight the clinical approaches, science, and new developments in child psychiatry. I look forward to her contributions and hope our reader-practitioners find the information useful.  PP



1. Rush AJ. STAR*D: what have we learned? Am J Psychiatry. 2007;164(2):201-204
2. Combining Medications to Enhance Depression Outcomes (CO-MED). Available at: http://clinicaltrials.gov/ct2/show/NCT00590863. Accessed April 19, 2010.


Researchers Analyze Prescription Rates for Psychiatric Medications

Tami K. Mark, PhD, and colleagues analyzed data from the 2005 National Disease and Therapeutic Index (NDTI) in order to examine which disease states psychiatric medications were being prescribed for. The NDTI is a continuing survey of over 4,000 office-based United States-based physicians. These physicians provide quarterly reports detailing their contact with patients and recording patient demographics, diagnosis, and therapies.

Via an e-mail interview, Dr. Mark stated their reasoning for conducting this research: “As part of an ongoing SAMHSA study to document how much is spent on mental health care in the US, we regularly conduct focused studies to better understand how specific types of mental health services are provided. In the area of psychotopic medications, we were frequently being asked whether most spending was for psychiatric illnesses, or whether it was often for medical illnesses, some of which may be off-label. We thus set out to better document the reasons why physicians were prescribing psychiatric medications.”

Mark and colleagues found that ~93% of antidepressants were prescribed for psychiatric conditions. Mood disorders accounted for 65.3% of mentions and anxiety disorders accounted for 16.4%. They also found that ~67% of anti-anxiety medications were prescribed for psychiatric conditions, with anxiety disorders accounted for ~40% of mentions and mood disorders accounted for ~19%.

They also found that ~99% of antipsychotics were prescribed for psychiatric conditions. Mood disorders, such as depression and bipolar disorder, accounted for 39% of mentions and schizophrenia or other psychiatric disorders accounted for 34.5% of mentions. Delirium, dementia, amnestic or other cognitive disorders accounted for 7.4% of drug mentions. Attention-deficit/hyperactivity disorder (ADHD) accounted for 5.7% of mentions and anxiety disorders accounted for 5.5%. Disorders diagnosed in infancy/childhood/adolescence, such as autism, accounted for 2.3% of mentions. Whether or not the prescription was on- or off-label was not part of the analysis.

“We were somewhat surprised at the small amount of non-psychiatric use of antidepressants (only ~7%) because some prior smaller studies found higher uses for medical purposes such as headache and chronic pain. The fact that ~33% of anti-anxiety medications were not prescribed for psychiatric diagnoses was also interesting. Approximately 6% of prescriptions were indicated as prescribed for a ‘medication examination/evaluation,’ thus presumably to relieve anxiety associated with the interventions.

“There has been considerable discussion in the scientific literature about the widening use of antipsychotics for a variety of psychiatric conditions and this study systematically documents this phenomenon. We found that the most common use for antipsychotics was not schizophrenia, but mood disorders, and that use for ADHD and dementia were common, despite being off-label,” Dr. Mark wrote.

The researchers hope that this analysis will be able to serve as a guide for future research, policy, and education about psychiatric medications, as well as their benefits, risks, and uses.

Funding for this research was provided by the Substance Abuse and Mental Health Services Administration to Thomson Reuters. (CNS Drugs. 2010;24(4):319-326). –CN

Rapid Cycling More Likely in Patients With Bipolar Disorder and Comorbid Substance Abuse

A recent study provided new evidence regarding specific characteristics that differentiate patients with bipolar disorder and comorbid substance use disorders (SUDs) from those who do not have comorbid SUDs.

Data were derived from the largest study on the treatment of bipolar disorder, the Systemic Treatment Enhancement Program, in which 2,154 patients with a diagnosis of bipolar I or II disorder who experienced a new-onset depressive episode were analyzed. Approximately 44% of patients had current or prior alcohol use, and 30% had a past or current drug use disorder. It was found that the likelihood of switching did not differ significantly between patients with prior SUDs and those with current SUDs. Therefore, the risk for direct switch in these patients was not induced or worsened by ongoing substance use.

An unexpected finding was that patients’ recovery time from a major depressive episode was not affected by whether patients had comorbid SUDs. Neither current nor prior substance use was thought to delay recovery from a depressive episode; therefore, patients did not suffer longer depressive episodes than patients without SUDs.

Lead researcher, Michael Ostacher, MD, MPH, of Massachusetts General Hospital and Harvard Medical School stated: “The results from this study suggest that treating patients with bipolar disorder for depression, even if they have a drug or alcohol problem, is no less successful than if they have no substance problem. This means that the standard guidelines for the treatment of bipolar disorder can be used for patients regardless of drug or alcohol problems.”

Defined as ≥4 mood episodes in the previous year, rapid cycling was more common in patients with prior or current alcohol use disorders, but had no significant correlation with prior or current drug use disorders. Based on these findings, the authors propose that patients with concomitant bipolar disorder and SUDs may have a set of inherent characteristics different from those of patients with bipolar disorder and no substance abuse.

“Patients with bipolar disorder and concomitant SUDs tend to be more ill. They are more likely to have attempted suicide, have more prior episodes, do not appear to function as well, are less likely to adhere to treatment, and are more likely to be violent,” explained Dr. Ostacher.

Regarding treatment of patients with SUDs, Dr. Ostacher added: “First, patients should be counseled to moderate or stop their use. Motivational interviewing techniques should be used to engage patients in a process of behavioral change, and referral for specialized treatment should be made. Treatments that are approved for drug or alcohol dependence should be used, especially considering the absence of data showing their ineffectiveness in comorbid bipolar disorder.”

Funding for this study was provided by the National Institute of Mental Health. (Am J Psychiatry. March 15, 2010 [Epub ahead of print]) –JV

Interpersonal Psychotherapy for Adolescent Girls at Risk for Adult Obesity

A recent study suggests that interpersonal psychotherapy (IPT) may help prevent weight gain and binge eating in adolescent girls at risk for adult obesity.

Marian Tanofsky-Kraff, PhD, at the Uniformed Services University of the Health Sciences in Maryland, and colleagues, evaluated the 1-year outcomes of IPT compared to general health education. Thirty-eight adolescent girls (12–17 years of age) at risk for adult obesity (body mass index in the 75th-97th percentile) were randomized to IPT or a health education group. Twenty of the 38 girls had out of control eating patterns at baseline.

According to previous studies, IPT can effectively reduce binge-eating behavior in obese adults and help stabilize the weight gain associated with binge eating. One goal of IPT is to demonstrate to patients the influences of social interaction, and especially negative social interaction. In this study, patients in the IPT group were encouraged to appreciate how their own spoken communication and, for example, body language, affects interaction with others. By moving toward more frequent positive social interactions, the goal was to lessen, or eliminate, any number of negative stimuli that might cause the patients to respond by eating.

Thirty-five patients returned to 1-year follow-up. Patients with out of control eating, who were in the IPT group, had greater reductions in those behaviors than those in the health education group (P=.036). Regardless of out of control eating status, IPT patients also showed greater weight stabilization at 1-year follow-up.

Funding for this study was provided by the National Institutes of Health and the Uniformed Services University of the Health Sciences. (Int J Eat Disord. Oct 30, 2009 [epub ahead of print]). –LS

Psychiatric dispatches is written by Christopher Naccari, Lonnie Stoltzfoos, and Jennifer Verlangieri.


Dr. Nazir is post-doctoral fellow and Dr. Sedky is associate professor of psychiatry at the Hershey Medical Center in Pennsylvania. Dr. Paladugu is an observer and Dr. Lippmann is professor of psychiatry at the University of Louisville School of Medicine in Kentucky.

Disclosure: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Karim Sedky, MD, Department of Psychiatry, Hershey Medical Center, 500 University Drive, Mail Code H073, Hershey, PA 17033; Tel: 717-782-2180; Fax: 717-782-2190; E-mail: sedky66@hotmail.com.


Residents benefit by being prepared for their outpatient rotation. Coming to the clinic with an understanding of the procedures, challenges, and how to meet educational objectives should promote confidence and a better educational experience. Learning how to adjust to this setting, arrange their office, get supervision, and provide good clinical service are important steps in the resident’s training. Assuring access to faculty guidance at pharmacotherapy and psychotherapy facilitates expertise and safety for the patient and trainee. Understanding administrative and practical aspects of psychiatric care in this setting fosters a good clinical approach and education in a supervised, productive manner.

Focus Points

• Office design is important and includes a focus on safety.
• Charting is important for clinical, insurance, and medico-legal reasons.
• Missed appointments are frequently encountered in outpatient settings.
• It is important to learn pharmacotherapy and psychotherapy.
• Patient care is individualized to specific patient needs.



The outpatient clinic is one of the principal sites for training psychiatry residents. The Accreditation Council of Graduate Medical Education for psychiatry requires at least 1 year of outpatient experience for trainees.1

Most residencies start psychiatric training on inpatient services in the first postgraduate year. There, the resident acquires an understanding about psychopathology. Risk assessment, diagnostic evaluation, and formulating a differential diagnosis are mastered during this phase of training. It also offers an opportunity for prescribing medication under supervision and learning about aftercare options.

Residency may vary with respect to when residents begin to see outpatients. Before starting, it is important to learn about the clinic policies. Ambulatory patients exhibit a wide range of exposures. Certain conditions, such as obsessive-compulsive disorder (OCD), are seen in this setting more often than in a hospital service. Having residents continue clinic work as long as possible improves patient and physician satisfaction through a longer-term relationship. Therapeutic alliances are enhanced and it affords the resident an opportunity to observe the course of mental illness over time.2

Residents typically have at least one outpatient supervisor. Especially during the adjustment phase, supervisors provide orientation to the clinic. They offer professional advice, clinical guidance, and other assistance throughout the rotation. Discussion may include guidance on study of appropriate educational materials; prescribing pharmacotherapies; and help in handling referrals, complaints, and so forth. Residents also meet with their supervisors to review psychotherapeutic techniques and alternatives. Self-educational reading and attending lectures or conferences is usually required.


What About Your Office?

For safety reasons, the clinician’s chair should ideally be nearer to the door than is the patient’s chair. Some clinics place an emergency alarm button at the desk or some other alert system to call for help, if protection is needed. Extra seating is made available for family. A box of tissues should always be available.

The room should be well illuminated. There is controversy about whether to display pictures of one’s family. From a psychoanalytic point, this may not be advisable. Pictures on the wall should have a calmative theme. Plants beautify the room and promote a pleasant atmosphere, as long as they are healthy.



Clinics differ in respect to scheduling of team meetings where referrals, clerical issues, and other problems are discussed. These meetings often review clinically difficult cases and administrative issues.

In cases of conjoint treatment with a psychotherapist, frequent contact between both clinicians is expected for information sharing. Billing is usually new to residents, but it is essential to learn the coding system for intakes, medication checks, psychotherapy sessions, and other patient contacts.


How To Chart

Legible documentation is important. Typing is clearer than handwriting, and printed clinical recording sheets for patient data also can simplify charting. Maintain appropriate eye contact with the patient when recording information. Note the date and time of each session, including the start and ending time and the duration of the visit. Document general content of the session, complaints, concerns, and therapy utilized. Include details about patient progress, efficacy of pharmacotherapy, and any side effects. Clinical data should support the type of session noted on the billing forms.

The chart should reflect a discussion of safety concerns and decisions about management. Safety includes suicidal or homicidal thoughts, inability to take care of oneself, abuse, or noncompliance with medical treatment. In these situations, consultation with the supervisor is advised and documented before ending the appointment. Child Protective Services must be notified whenever there is possible abuse to a minor. Adult Protective Services are informed if an adult is unable to care for him- or herself or is being abused.


About Tarasoff

It is important to be familiar with the Tarasoff ruling. In cases of expressed dangerous threats to others, clinicians have the duty to protect the potential victim by a direct warning to that individual and to the police; this can often be done without compromising the therapeutic relationship.3 When a patient refuses to reveal information about the possible victim, inform the local police department. These facts must always be documented in the chart.


First Appointment

Clinics differ with respect to who schedules the initial appointments, provides the clinic’s address and phone number, and answer questions, such as how to access parking. The first 1-hour session is dedicated to evaluating the patient with a history and mental status examination, followed by discussion of treatment plans. Laboratory tests may be ordered as needed. Therapeutic decisions are postponed in complex cases until the required information is obtained and reviewed with the supervisor. Collateral information from family members or a previous treatment team might be beneficial. Some patients may require more intensive treatment with referral to specialty clinics, as for persons with dangerous self-mutilation or substance abuse.

Written consents are obtained from patients before information is revealed to a third party, even to family or an insurance company. Special consents are obtained for video or audio taping a session.

Treatment discussions include pharmaceutical options as well as psychotherapy selections. Always tell patients whom to call in case of emergency, during working hours or when the clinic is closed. If there is overt concern for patient safety, involve family for monitoring. Although assessments are more accurate when the supervisor and the trainee conduct concluding parts of the initial interview together, this is usually not done for practical reasons.4


Follow Up

A follow-up visit is mutually agreed upon by the patient and resident. Some clinics depend on secretaries to schedule appointments, but the doctors must inform staff about their available times and planned visit dates. The clinic phone number, emergency contacts, and physician’s name should be provided to every patient. The next follow-up date and time should be given to the patient in written form.


Missed Visits

Residents should be aware of clinic policy towards individuals who frequently miss appointments. Every outpatient facility has its own way to deal with missed visits. Failure to appear for an appointment is most common among people seen by a resident, in younger patients, and for those individuals with a record of missed visits or living far from the facility.5



Prescribing medications is a frequent part of treatment. There are algorithms available for treatment of different syndromes6 and the American Psychiatric Association offers downloadable guidelines.7 Drug interactions between psychopharmaceuticals and other co-administered medical treatments must always be considered. Avoid polypharmacy when possible.8,9 The physiologic impact of medications must always be considered; for example, avoid lithium during pregnancy, lactation, renal dysfunction, or hypothyroidism.

Residents should know which medications cause weight gain.10 Patients taking antipsychotics should be monitored for the metabolic syndrome according to the current guidelines. Side effects should be discussed and charted.

Always consider the prospect of pregnancy to avoid teratogenicity from pharmaceutical exposure in female patients of child-bearing age. Pharmacotherapy is avoided if possible during pregnancy or lactation. The risk versus benefit of using medications during pregnancy mandates explicit indications and thorough discussion; consultation with a supervisor and an obstetrician is essential. Be aware that efficacy of oral contraceptives in preventing pregnancy is reduced when co-prescribed with hepatic enzyme-inducing drugs, like carbamazepine.

For patients taking benzodiazepines or other controlled substances, continued benefit should be consistently and specifically charted; taper off such medications when possible. Controlled substances, as in treatment for insomnia, should ideally be prescribed only for short periods. For patients with alcohol and/or drug abuse, sobriety is consistently stressed. Alcoholics Anonymous or Narcotics Anonymous are encouraged, buprenorphine administration is considered, and/or other chemical dependency intervention plans are implemented. Some programs offer special training to residents at handling drug abuse cases.11 Any controlled substances in the clinic, like buprenorphine, must be kept in a locked location. Needles and injectable medicines should be stored in secure places, with refrigeration as needed.

Always consider the cost of medication and insurance coverage in planning treatment. Pharmaceutical sales representative visits often inappropriately influence resident prescribing habits. Thus, this practice is now discouraged.12


Individual Versus Conjoint Treatment

Residents can do both medication management and psychotherapy. This allows more time to understand the patient and improves the therapeutic alliance. However, having two people share a case can also be clinically beneficial, and is often the reality.



After the assessment, the clinician and supervisor determine the type of psychotherapy indicated. Consider patient education, motivation, energy, and functional capacity. Availability, times for sessions, and financial aspects should be reviewed.

Supportive therapy is indicated, especially for those recently discharged from the hospital, after an acute relapse, or those with compromised function. Cognitive-behavioral therapy is a frequently chosen treatment that focuses on cognitive distortions and automatic thoughts.13 In cases of phobias, posttraumatic stress disorder, or OCD, exposure with response prevention is a frequent option. If there is a concern about self-harm, dialectical-behavioral therapy might be selected.14 This includes teaching interpersonal effectiveness, stress tolerance, acceptance skills, and emotional regulation.15 Mentalization therapy is an alternative for treating patients with borderline personality disorder by helping them develop stability within a secure attachment relationship.16 Learning psychodynamic psychotherapy is a core training requirement and utilized in selected cases.17 For those who have chemical dependence issues, one can encourage abstinence by motivational enhancement therapy through a guided review of ambivalences.

Other therapeutic options include group approaches, family or marital counseling, hypnotherapy, or other traditional or even less conventional therapies. It can be advantageous when different supervisors suggest alternative approaches, even in the same patient.18 Electroconvulsive therapy may be indicated as a somatic treatment in certain cases. Transcranial magnetic stimulation and vagal nerve stimulation are newer considerations.


Crisis Assesment And Community Treatment Team

During a psychiatric emergency, a crisis team or the regular clinical staff must provide an immediate assessment and/or referral to inpatient hospitalization. For chronically ill, low-functioning individuals, a referral to a community treatment program is appropriate since these agencies have an intense assistance program provided by multidisciplinary professionals.


Forms And Letters

Some patients may have forms for physician signature. Others may ask for social security or insurance papers to be filled out. Excuses for job or school absences are often requested. The same applies to notices about returning to work and clarifying occupational restrictions. Place copies of all forms and similar papers in the chart to document the transaction. An appreciation of disability regulations can be an aid in assisting patients.19



It is important that residents know how to access other services. These may include physician referrals such as securing a psychologist, social worker, nurse practitioner, Meals-on-Wheels, transportation services, or vocational rehabilitation. Knowledge of community resources is expected.20


Laboratory Tests

At the initial evaluation, laboratory screening is considered. This may include a complete blood count, lipid profile, comprehensive serum chemistry profile, urinalysis, or thyroid hormone assays. A serum pregnancy test is conducted in women of childbearing potential. Various tests may be repeated over time, eg, serum glucose or lipid monitoring when metabolic syndrome is a concern. Neuroimaging is requested when brain disease is in the differential. Syphilis or other infectious disease testing is indicated in demented or other selected people. Clozapine prescribing mandates hematologic follow up regularly with special attention to the neutrophil count. Lithium requires attention to serum levels, renal effects, and antithyroid properties as well as pre-treatment testing. Blood counts, liver or renal function tests, hepatic enzyme assays, or electrolytes are monitored regularly in patients taking medications with adverse potential in these areas. The procedures for ordering tests vary from clinic to clinic.

Samples/Returned Medications

It is important to be familiar with the policy for handling medication samples. Many clinics do not allow sampling of pharmaceuticals, but some facilities still do, under tight regulation.

Special Populations

Training residents about cultural differences is important.21-23 For example, African-American populations reportedly are often overdiagnosed with schizophrenia.24 Hispanic populations may have a higher incidence of anxiety disorders.25 Interpreter services are required in cases with a language barrier. Adjustment disorders and non-acceptance by family are frequent complaints by homosexuals.26 Training guidelines exist for women’s issues.27 When treating children or adolescents, family therapy is an integral part of the plan.28-30

Transfering Or Terminating

Sometimes a resident might need to transfer a patient. These situations could include transference or counter-transference issues, concern about physician safety, lack of progress, and always at times when the resident will no longer be available. It is important to explain the reasons for transfers. In long-term therapeutic relationships, discussion focuses on analysis of feelings and future plans. Self-esteem and abandonment issues should be addressed. At the end of the outpatient rotation, detailed discussions should ensue and consider even introducing the patient to the new therapist to avoid feelings of abandonment. A review of the newly arranged follow up is mandatory with names, dates, times, and phone numbers listed on a new appointment card.



The outpatient clinic is an important part of the psychiatric education. Preparing residents before they start the ambulatory rotation reduces anxiety and improves the educational experience. Understanding the practice policies of the clinic helps the resident to be comfortable and productive. Following patients for long duration offers trainees a long-term view of patient pathology, problems, and coping skills. Performing medication management and psychotherapy with expertise are important objectives. Education also focuses on forming therapeutic relationships, monitoring disease progression and/or effectiveness of treatment, and competently handling mental health emergencies. Learning about ambulatory care comes from practical experience in the clinic.  PP


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Dr. Rundell is professor of psychiatry and Dr. Shinozaki has a collaborative research appointment, both in the Department of Psychiatry and Psychology at the Mayo Clinic in Rochester, Minnesota. Dr. Shinozaki is also a psychiatrist at the Sioux Falls Veterans’ Administration Medical Center in South Dakota.

Disclosure: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.



Objective: This article identifies situations wherein an evidence base exists for informing the use of pharmacogenomic testing in treating comorbid medical and psychiatric disorders.
Method: A review of literature was conducted to identify medical conditions with frequent psychiatric comorbidity that had level 1 evidence or meta-analytic studies related to pharmacogenomic factors as they relate to safety, tolerability, efficacy, or cost.
Results: Three situations met inclusion criteria: tamoxifen clinical response, warfarin clinical management, and opioid pain management. Each of these situations is associated with elevated risk of mood or anxiety disorders. For tamoxifen, cancer recurrence risk is the primary indicator for the need for testing. For warfarin, patient safety is paramount. For opioid management, efficacy and tolerability are primary indications for pharmacogenomic testing.
Conclusion: Available clinical data and cost effectiveness data suggest that for tamoxifen patients, pharmacogenomic testing should be routine. In patients treated with warfarin, testing is supported by current safety and clinical evidence in patients who are unable to obtain a stable international normalized ratio level. Testing of analgesic patients is indicated if there is demonstrated treatment non-response or unexpected tolerability. Additional clinical applications of pharmacogenomic testing of patients with comorbid medical-psychiatric illness will be justified by the outcomes of future studies examining effects such as clinical outcome, patient safety, efficacy, and cost.

Focus Points

• Patients with comorbid medical and psychiatric problems often have polypharmacy.
• Polypharmacy increases drug interaction possibilities.
• Specific disease-drug and drug-drug interactions increase morbidity.
• Pharmacogenomic testing can optimize pharmacotherapy in comorbid disorder patients.



Pharmacogenomic testing is increasingly available to physicians to assist with clinical decision making and is probably most useful in cases that involve medication treatment resistance, intolerable adverse effects, or the potential for problematic drug-drug or drug-disease interactions.1-8 Though relatively well studied in psychiatry practice,5,9 the use of pharmacogenomic testing has not been as systematically investigated in patients who are treated for comorbid medical and psychiatric disorders.10 In these patients, additional challenges of medical comorbidities and polypharmacy are more prominent than in general psychiatry or routine primary care practice.11-16 Psychiatric medication polypharmacy is increasing despite concerns regarding multiple medication prescriptions. The percentage of patients being treated with >3 psychiatric medications simultaneously has increased more than 10-fold in the past 30 years.17

Personalized medicine, defined as the implementation of genetic variation to guide prescribing tailored to the individual, is considered to be an inevitable consequence of completion of the Human Genome Project. This is not a new concept, given that genetic factors have been recognized to influence individual responses to medications for >50 years.18 However, many conditions which were mysterious in terms of who was afflicted (eg, malignant hyperthermia) are now demystified because of pharmacogenomic studies.19 A striking failure of modern medical practice is the high morbidity and mortality associated with adverse drug reactions. These reactions are now one of the leading causes of death and illness in the United States. It is estimated that 100,000–200,000 deaths annually are the consequence of an adverse drug reaction.20-22 Adverse drug reactions are reported to account for 7% of all hospital admissions, but this estimate is believed to be low as a consequence of underreporting.20,23 Genetic variations in cytochrome P450 (CYP) enzymes explain some of the variation in patient tolerability and therapeutic response.9,24 However, catastrophic deaths have been the consequence of non-functional enzymes.25

Development of specific applications for the use of pharmacogenomic testing has been rapid in cancer chemotherapy, where associations between specific genetic markers and chemotherapy outcome are well documented.26,27 Similarly, metabolic enzyme genotype variability has been linked with tamoxifen outcome which has resulted in specific recommendations for clinically important genotyping.28 However, for most currently available medications, variability in drug response has been presumed to be the result of a complex interaction of multiple factors. It is relevant to consider the opioid individual response, variations in absorption and distribution, opioid receptor pharmacodynamics, and whether a medication is a prodrug.29 This article identifies clinical situations for which a well-developed evidence base exists to inform the use of pharmacogenomic testing in clinical practice settings which treat patients who are comorbid for medical and psychiatric disorders.



A MEDLINE review of literature was conducted to examine clinical situations in primary care and general medicine where pharmacogenomic clinical data have empirically demonstrated to be of relevance to clinical outcome. Search terms included pharmacogenomic testing, medication safety, medication tolerability, treatment-resistant depression, depressive disorder, drug-induced, treatment resistance, antidepressant treatment, medical-psychiatric comorbidity, antipsychotic treatment, and antipsychotic adverse effects. Meta-analyses and papers with level 1 evidence were included when there was available data about comorbid medical and psychiatric pharmacologic treatments. Over 400 papers were identified in the review; 65 papers meeting these inclusion criteria were reviewed to identify illustrative conditions that inform safety, tolerability, efficacy, or cost.



Three illustrative situations were identified that met the goals of this review and had sufficient scientific evidence to meet the study inclusion criteria. One is a situation where pharmacogenomic insights play a pre-eminent role in determining the outcome of tamoxifen clinical response. The clinical management of patients receiving warfarin and opioid pain management are additional treatments that have become more effective with testing. Treatment of all three situations is often complicated by the need to treat comorbid psychiatric disorders. For example, rates of mood and anxiety disorders are elevated among patients with breast cancer, cardiovascular disease, stroke, and chronic pain.30



Tamoxifen Clinical Response

Tamoxifen is a standard endocrine therapy for the prevention and treatment of estrogen receptor-positive breast cancer. It is a classic pro-drug, requiring metabolic activation to elicit pharmacologic activity. The CYP2D6 enzyme and other CYP isoenzymes catalyze the conversion of tamoxifen into metabolites with significantly greater affinity for the estrogen receptor and greater ability to inhibit cell proliferation than the parent drug.26 For example, 4-hydroxytamoxifen is 30- to 100-fold more potent than tamoxifen in suppressing estrogen-dependent cell proliferation.31

Major tamoxifen metabolites include N-desmethyltamoxifen, 4-hydroxytamoxifen, tamoxifen-N-oxide, a-hydroxytamoxifen, and N-didesmethyltamoxifen, all created by oxidation by CYP isoenzymes.26,32 These tamoxifen metabolites may then undergo secondary metabolism and further biotransformation. This is clinically important because the products of secondary metabolism may have concentrations several times higher than products of primary metabolism.31 One primary tamoxifen metabolite, N-desmethyltamoxifen, is biotransformed to at least four additional secondary metabolites, one of which is 4-hydroxy-N-desmethyl-tamoxifen (endoxifen). Endoxifen may be present in concentrations up to 10-fold higher than the primary metabolite. The transformation of N-desmethyltamoxifen to endoxifen is catalyzed exclusively by CYP2D6.

Since CYP2D6 is a highly polymorphic gene, CYP2D6 genotype can have a marked impact on clinical outcomes when there is exclusive catalysis, as with biotransformation to endoxifen from tamoxifen.28 Women homozygous for the most common allele associated with the CYP2D6 poor metabolizer phenotype (ie, CYP2D6 *4) tend to have worse relapse-free time (hazard ratio, 1.85; P=.176) and disease-free survival time (hazard ratio, 1.86; P=.089) than other tamoxifen patients, even after accounting for lymph node status and tumor size.33 As many as 10% of Caucasian women are CYP2D6 poor metabolizers.9 The relative decrement in biotransformation to endoxifen among women with this genotype was further demonstrated by the finding that none of the women with the poor metabolizer genotype experienced moderate or severe hot flashes, a characteristic tamoxifen adverse effect, compared with 20% of the women with more adequate production of the CYP2D6 enzyme. Most strikingly, for patients with either poor 2D6 metabolism or medication inhibition of CYP2D6, there was significantly higher risk for cancer relapse (hazard ration, 3.12; P=.007), shorter time to cancer recurrence (hazard ratio, 1.91; P=.034), and worse relapse-free survival (hazard ratio, 1.74; P=.017).34

Women with breast cancer often take antidepressants because of the elevated incidence and prevalence of depression.30 Selective serotonin reuptake inhibitors such as paroxetine and fluoxetine, which are strong CYP2D6 inhibitors, reduce plasma endoxifen concentrations.26,31,35 Other antidepressants exhibit varying degrees of CYP2D6 inhibition; until more is known, it may be best to prescribe antidepressants which appear to have little or no capacity for CYP2D6 inhibition. Examples of antidepressants which may avoid CYP2D6 inhibition are escitalopram, fluvoxamine, and desvenlafaxine. The combination of an intermediate CYP2D6 genotype status and CYP2D6 inhibition with medications can cause additive negative impact on survival and recurrence in tamoxifen-treated patients.28 CYP2D6 genotyping is now integrated into many breast cancer clinics and is recommended by expert panels as important in the management of estrogen receptor-positive breast cancer patients.28 The Food and Drug Administration is considering updating the product labeling for tamoxifen with recommendations regarding CYP2D6 genotyping.


Warfarin Clinical Management

Warfarin is a vitamin K antagonist used for >50 years as the most commonly prescribed antithrombotic medication in the US.36 Warfarin therapy presents numerous challenges in clinical practice.37 There are significant risks associated with over- and under-coagulation. Genetic variations account for some of the differences in achieving stable international normalized ratio (INR) levels. Fully 33% of the time the INR in patients receiving warfarin is outside of the target range,38 with 50% of the values being subtherapeutic and 50% being supratherapeutic. Researchers have focused on pharmacogenomic testing to individualize warfarin dosing and improve the safety, efficacy, and cost-effectiveness of warfarin therapy. Testing may be particularly helpful when patients are taking other concurrent medications, including psychotropic medications, which can affect how warfarin is utilized.

Genetic testing has focused on the genes that code for vitamin K epoxide reductase complex subunit 1 (VKORC1) and CYP2C9, which are enzymes involved in the mechanism of action of warfarin and the metabolism of S-warfarin, respectively. VKORC1 is responsible for the conversion of vitamin K epoxide to vitamin K, and is the rate-limiting step in the physiologic process of Vitamin K recycling.39 The CYP2C9 enzyme is largely responsible for metabolism of warfarin. The contribution of VKORC1 polymorphisms to warfarin dose variability has been estimated to be between 15% and 30%.40-42 A single CYP2C9 nucleotide polymorphism accounts for 6% to 18% of the difference in warfarin dose requirements among patients.40-42

Patients who are CYP2C9 intermediate or poor metabolizers have been found to have a lower warfarin dose requirement.40,41 CYP2C9 inhibitors, such as sertraline and fluvoxamine, can prolong bleeding time.43 The combination of being an intermediate metabolizer and taking a medication which inhibits CYP2C9 could potentially have catastrophic consequences. VKORC1 genetic variation is generally felt to have a more significant impact on early response to warfarin anticoagulation, and CYP2C9 a greater impact on achieving steady-state concentrations of warfarin,37,44 because of the different roles these enzymes play in warfarin effects.

Though a great deal of effort is going into the study of how genotyping of VKORC1 and CYP2C9 contribute to safer and more effective warfarin management algorithms,37 there is no single agreed upon recommendation. Numerous factors contribute to the complexity of creating a clinical algorithm.45 First, the interactions between effects of polymorphisms of VKORC1 and CYP2C9 have been difficult to quantify. Second, patients with different ancestry have different frequencies of polymorphisms.46 Third, cost-effective use of genotyping has not yet been demonstrated in terms of time to anticoagulation and improved out-of-range INRs. Fourth, there is some controversy regarding which variants should be included in a testing panel.47 Last, there are non-genetic factors that contribute ~20% to variance in warfarin dose, including age, sex, adherence, and weight.39

Despite the complexities related to pharmacogenomic testing and warfarin therapy, there are advocates who make the case that clinicians should not wait until there is an algorithm that covers all the permutations possible in decision making, or until there is profitability or cost neutrality, to start obtaining pharmacogenomic data when instituting warfarin therapy or when there is a patient on warfarin with unstable INRs.48 Because of the considerable medical risks of under- or over-coagulation, pharmacogenomic testing may make positive individual contributions to safety and efficacy, especially when warfarin is initiated or when medications known to affect CYP2C9 functioning are initiated in a patient receiving warfarin.

Sertraline has an evidence base supporting its use in cardiology patients, making its co-administration with warfarin a clinical event with considerable frequency. Though there is no clear consensus about whether to always order pharmacogenomic testing in a patient on both warfarin and sertraline, it is recommended by some experts, and would be important when there is difficulty with unstable INRs. Other antidepressants that are at least partly metabolized by CYP2C9 inhibition potential include fluoxetine and bupropion. Examples of antidepressants that largely avoid potential problems with CYP2C9 inhibition are citalopram, paroxetine, escitalopram, venlafaxine, and desvenlafaxine. Unfortunately, there are no current guidelines or algorithms that suggest how frequently an INR should be measured in a patient on a medication partly or largely metabolized by CYP2C9; there are too many patient-specific determinants of clinical effect apart from presence or absence of a single medication.


Opioid Pain Management

Many factors influence individual response to opioids. These include individual variations in absorption and distribution, opioid receptor pharmacodynamics, and drug metabolism.29 All these factors may be affected by the co-administration of another medication. Studies of genetic influences on the pharmacodynamic effects of variations in the μ-opioid receptor have been conducted. Factors which influence neurotransmitter pathways include variations in the catechol-O-methyltransferase (COMT) gene and drug transporter proteins.

Genetic polymorphisms that change mu-opioid receptor function result in variability in inter-patient opioid effects.29 COMT gene mutations can affect the perception of pain, as reduced COMT activity results in the up-regulation of opioid receptors.49 Clinical studies of COMT polymorphisms suggest that patients with low COMT activity who have the Met/Met genotype of the Val158Met polymorphism require smaller opioid doses.49 Drug transporter proteins facilitate passage of opioid drugs across biologic membranes such as the liver, kidneys, and intestines, as well as at the blood-brain barrier. Genetic variation in the production of these proteins affects both the efflux and uptake of opiod drugs and contributes to inter-patient variability in response to these drugs.29

Opioid metabolism by CYP enzymes and enzymes that regulate glucuronidation to active metabolites also influence drug concentrations and clinical efficacy. Psychotropic medications are metabolized by many of the same CYP enzymes that metabolize opioid analgesics and their metabolites. The higher incidence and prevalence of mood and anxiety disorders among patients with chronic pain30 creates pharmacologic scenarios that complicate the management of these patients.

The clinical effects of the weaker opioids codeine, hydrocodeine, tramadol, oxycodone, and hydrocodone rely upon formation of their more potent metabolites (eg, morphine, dihydromorphone, and oxymorphone) by a metabolic pathway mediated by CYP2D6.50 A number of in vivo retrospective or case studies51-53 of patients receiving codeine have demonstrated significant differences in plasma morphine concentrations between extensive and poor CYP2D6 metabolizers. Approximately 10% of patients of European ancestry are poor metabolizers and unlikely to gain full benefit from codeine administration, but are just as likely to suffer codeine-related side effects. These findings can be exacerbated when a patient is also on a CYP2D6 inhibitor, including many antidepressants, such as fluoxetine and paroxetine. However, ultrarapid CYP2D6 metabolism is associated with codeine intoxication.54 This phenomenon may extend to breastfeeding neonates of codeine-prescribed mothers who are ultra-rapid metabolizers.55

Tramadol exerts analgesia via the opioid agonist metabolite O-demethyl tramadol and via modulation of noradrenergic and serotonergic monoamine pathways. O-demethylation of tramadol to the opioid agonist O-demethyl tramadol is mediated by CYP2D6; there is lower plasma concentrations in poor metabolizers compared to extensive metabolizers, and there are reduced analgesic effects.56,57 Though the prevalence of CYP2D6 polymorphisms in the population undergoing pain management does not appear to be different from the general population,58 patient care may be improved by genotyping and following therapeutic drug concentrations when there is treatment resistance or poor tolerability.

Other opioid analgesics such as methadone are metabolized by other enzymes, such as the CYP3A4 enzyme. Although genetic polymorphisms occur in the enzyme CYP3A4, unlike CPY2D6, this has not yet been correlated with particular clinical phenotypes.59



The three illustrative clinical management situations reviewed in this paper demonstrate the potential value and complexity of pharmacogenomic testing in the clinical situation where comorbid medical and psychiatric disorders exist. Because of increasing frequency of psychiatric polypharmacy,17 patients with comorbid psychiatric and medical illness represent a growing and unique group of patients where pharmacogenomic testing may improve safety and clinical outcomes. The considerations presented in the three patient categories discussed in this paper highlight how complex the interactive contributions of genetic and non-genetic factors are in determining patient responses.

Available clinical data suggest that for tamoxifen patients, pharmacogenomic testing should be routine. Testing also appears to be clinically indicated when there are difficulties obtaining stable INR levels in patients receiving warfarin and when patients receiving opiate analgesic medications demonstrate treatment non-response or severe tolerability problems. Additional studies of cost effectiveness and clinical utility may identify additional clinical populations who could benefit.27 Studies of cost effectiveness may draw different conclusions over time; the cost of testing varies across laboratories and is currently in a phase of rapid decline. In addition to cost, variability in coverage by insurance providers and turnaround time for results (typically several days) may limit more widespread utilization of pharmacogenomic testing; these factors are likely to change with time.

As the scientific literature identifies clinical situations where pharmacogenomic testing can add value to healthcare, other medical specialists will begin to use this emerging technology. For example, within the field of infectious diseases, the genomes of both the host and the pathogen are relevant to antibiotic efficacy and resistance.60 Examples of host-relevant genetic polymorphisms include genes of antigen recognition molecules, pro-inflammatory cytokines, anti-inflammatory cytokines, and effectors molecules. Genetic mutations for these different factors could define a genetic profile of a high-risk patient for whom a specific treatment should be added urgently. However, co-treatment of the infection and concurrent psychiatric disorders may complicate clinical outcomes and require modifications of treatment algorithms.

Special patient populations may benefit from pharmacogenomic testing. Children and adolescents in particular may have unique considerations related to genomic variations that will translate into childhood-specific genomic testing algorithms. Examples of reported conditions relevant to childhood that are influenced by pharmacogenomic considerations are azathioprine-induced myelosuppression, codeine-induced infant mortality, warfarin-associated anti-phospholipid syndrome, and adverse drug reactions that appear to occur disproportionately in children and adolescents.22 Children are at even greater risk for adverse drug reactions than adults. An estimated 15% of pediatric hospitalizations are a consequence of adverse drug reactions, and 28% of these adverse reactions are severe.61,62 More than 75% of pharmaceuticals licensed in North America have never been tested in pediatric populations and are used without adequate guidelines for safety or efficacy.63

Patient satisfaction surveys indicate that patients are gradually becoming more aware of pharmacogenenomic testing and are beginning to expect their providers to be knowledgeable about the indications for testing.64 Specifically, they expect their providers to be able to interpret test results, provide education about the benefits and limits of testing, and to provide up-front education about cost. As knowledge about benefits of pharmacogenomic testing emerges, an increasing number of situations will be identified where it will prove cost effective and clinically beneficial to employ pharmacogenomic testing early in the course of treatment. Evidence-based pharmacogenomic testing will guide patients and providers in their selection of specific medications, and in implementation of safe and effective dosing strategies.15,65,66 Future development of clinical application of pharmacogenomic testing, in general and in the special setting of comorbid medical-psychiatric illness, will depend on future study outcomes measuring effects of testing on clinical outcome, patient safety, efficacy, and cost.  PP


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Dr. Kung is assistant professor of psychiatry and consultant in psychiatry, and Dr. Li is psychiatry resident, both in the Department of Psychiatry and Psychology at the Mayo Clinic in Rochester, Minnesota.

Disclosures: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Simon Kung, MD, Mayo Clinic, 200 First St SW, Rochester, MN 55905; Tel: 507-255-7184; Fax: 507-284-3933; E-mail: kung.simon@mayo.edu.


Pharmacogenomic testing is clinically available to assist with medication selection in treatment-resistant depression (TRD). Common tests include the cytochrome P450 (CYP) 2D6 and 2C19 enzymes, the serotonin transporter gene, and the serotonin receptor gene. There are practical recommendations of interventions which can be supported from the literature. Identification of a CYP2D6 poor metabolizer would result in recommending a lower dosage of medications metabolized by CYP2D6, or avoiding the use of CYP2D6 medications. Identification of a serotonin transporter gene short/short genotype suggests more adverse effects, less response, or longer time to respond to selective serotonin reuptake inhibitors (SSRIs), and may warrant focusing treatment with non-SSRIs. Numerous other genotypes have been studied but with mixed implications. The use of pharmacogenomic testing can help the clinician rationalize medication selection and reduce the numerous medication combinations used in TRD. Further research and clinical experience will continue to define the clinical utility of this testing.

Focus Points

• Pharmacogenomic testing can be clinically used in guiding medication selection for treatment-resistant depression.
• Cytochrome P450 metabolizer status can guide whether the clinician uses medications metabolized by a specific pathway or uses different dosing ranges.
• The serotonin transporter gene short/short genotype has been associated with adverse reactions and less response to selective serotonin reuptake inhibitors (SSRIs), thus clinicians might choose a non-SSRI for such patients.
• Further research and clinical practice will help define the utility of pharmacogenomic testing.



Treatment-resistant depression (TRD) is a common occurrence in clinical practice. Depending on the operational definitions, studied populations and analytic methods used, prevalence ranges from 15% to 80%.1 Results from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study suggest that ~50% of “real world” patients with psychiatric and medical comorbidity who meet criteria for major depressive disorder (MDD) fail to achieve remission, even after four carefully monitored sequenced treatments.2

The most commonly adopted definition of TRD evolved from >15 historic definitions is “major depression with poor response to two adequate trials with different classes of antidepressants, given in an adequate dose for sufficient time.”3 Staging models of TRD reflect the severity of treatment resistance, factoring in the number of failed trials and intensity or optimization of each trial.4

Numerous strategies are used in TRD, including psychotherapy, pharmacotherapy using augmentation strategies, and brain stimulation techniques such as transcranial magnetic stimulation, vagus nerve stimulation, and electroconvulsive therapy. Deep brain stimulation and magnetic seizure therapy are investigational treatments.5 However, the most common treatment for TRD is the selection of alternative antidepressant trials. Algorithms have been developed to guide pharmacotherapy.6

Given the trial-and-error nature of medication treatment for TRD, a method which could decrease the number of trials needed to achieve remission would be valuable. There has been much research into the use of genotyping to predict drug metabolism (pharmacokinetic) and genotyping to determine serotonin gene variants (pharmacodynamic) associated with drug response. Both strategies provide information that can increase the likelihood that a medication trial will be helpful.

This article reviews our current knowledge of pharmacogenomic testing designed to predict antidepressant adverse effects and response. Clinical implications for the care of patients with MDD and TRD are discussed.



Cytochrome P450 (CYP) enzymes are involved with the metabolism of most medications, including antidepressants. Some medications, such as codeine and tamoxifen, are pro-drugs which require activation by CYP enzyme. Several CYP isoenzymes are involved with antidepressant metabolism, mainly the 2D6 and 2C19, and to a lesser extent, 2C9 and 1A2.7 Polymorphisms in the genes that code for these enzymes result in varying drug levels in an individual. The phenotypes typically range from a “poor” metabolizer (PM) with little or no enzyme activity, to an “intermediate” metabolizer with less than normal activity, to the “extensive” normal type, and to the “ultra-rapid” metabolizer (UM) with greatly increased activity. In patients of European ancestry, the distribution for CYP2D6 is ~10% PMs and 2% to 3% UMs. The phenotype frequencies for patients of European ancestry for CYP2C19 are ~3% PMs and 4% UMs. Drug metabolizing enzyme gene polymorphisms play a role in the interethnic variations in drug metabolism given that up to 20% of patients of Asian ancestry are CYP2C19 PMs.8 Generally, poor metabolizers experience more side effects and ultra-rapid metabolizers are less likely to respond to treatment with an antidepressant that is a substrate of the enzyme.

A clinical laboratory test for CYP2D6 genotyping has been available since 2003. Subsequently, clinical laboratory tests for CYP enzymes 2C19, 2C9, and 1A2 have become available. CYP 3A4 is an important enzyme involved in medication metabolism as well, but does not have many polymorphisms of functional significance.9

A current problem is that there is not a single standard for predicting the phenotype based on genotype. Consequently, different laboratories provide differing phenotype interpretations for the same genotype. This problem is compounded because different laboratories analyze for different sets of alleles. Another less problematic issue is that new alleles continue to be identified.10


Associations with Plasma Concentrations, Adverse Effects, and Treatment Response

The consequence of the CYP genotype on the pharmacokinetics of many antidepressants has been demonstrated. Desipramine,11 venlafaxine,12,13 nortriptyline,14 doxepin,15 imipramine,16 paroxetine,17 fluvoxamine,18 fluoxetine and paroxetine,19 and amitriptyline and nortriptyline20 have significant correlations between CYP2D6 genotypes and their plasma concentrations. However, the implications of these variable serum concentrations are not completely correlated with side effects or therapeutic response.11,13,21-23

CYP2C19 genotypes have been associated with metabolism of imipramine,24 sertraline,25,26 citalopram/escitalopram,27 and clomipramine.28 A study combining genotypes 2D6, 2C19, and 2C9 found significant influence of the 2D6 genotype, minor influence of the 2C19 genotype, and no influence of the 2C9 genotype on plasma concentrations of citalopram, paroxetine, fluvoxamine, and sertraline.29

Many studies show that poor and intermediate 2D6 metabolizers have been associated with more adverse effects to CYP2D6-dependent antidepressants.30-35 However, in some reports the risk for adverse effects have not reached statistical significance.13,36-38 These negative studies have had issues related to comprehensiveness of genotyping and sample size.

There are mixed reports of CYP2D6 genotyping associations with antidepressant response. UMs have been associated with non-response to antidepressants in several studies.17,31,39 However, in a retrospective study40 of 81 responders and 197 non-responders, CYP2D6 metabolizer status was not associated with either response or remission rates.


Practical Recommendations

Pharmacokinetic genotyping provides probabilistic estimates of side effects and efficacy in patients with PM and UM phenotypes. Its usefulness includes guiding certain antidepressant dosage and understanding and avoiding drug-drug interactions (DDIs), especially when 34% of patients in a primary care setting are on an antidepressant and ≥3 medications.41 The current standard clinical practice in using tricyclic antidepressants (TCAs) is to dose until reaching a pre-determined “therapeutic” serum drug level. For newer antidepressants, clinicians sometimes titrate the dose until a patient experiences benefit or uncomfortable side effects. Consequently, patients can be placed on dosages exceeding the manufacturer’s recommended usual dosages. The determination that a patient is an ultra-rapid metabolizer provides a rationale for a patient’s capacity to tolerate higher than recommended doses. Conversely, clinicians should be more cautious with substrate medications if a patient is not able to produce sufficient active enzyme necessary for the metabolism of the drug.

Pharmacokinetic reviews have suggested decreasing by ~50% the dosages of TCAs and risperidone in patients who are CYP2D6 PM, and using higher dosages of a TCA in UM.42-45 More specific dose adjustments have been proposed for the antidepressants imipramine, desipramine, nortriptyline, clomipramine, paroxetine, venlafaxine, amitriptyline, buproprion, citalopram, sertraline, and fluvoxamine, as well as the antipsychotics perphenazine, thioridazine, olanzapine, aripiprazole, haloperidol, and risperidone.44 Another review41 estimates the potential for antidepressants to be the perpetrator of a DDI mediated by effects on CYP2D6 enzymes as substantial (>150%) for paroxetine and fluoxetine; moderate (50% to 150%) for duloxetine; and mild (20% to 50%) for venlafaxine, sertraline, citalopram, and escitalopram.

Fortunately, for the newer antidepressants, clinically significant drug interactions from CYP inhibition are less frequent.46 Psychotropic medications which are not metabolized by CYP2D6 have been developed (eg, desvenlafaxine).

There is one psychotropic medication for which the Food and Drug Administration has made a firm recommendation for genetic testing (HLA-B*1502). Carbamazepine in patients with Asian ancestry with this variant have been shown to be at increased risk of life-threatening skin reactions such as Stevens-Johnson syndrome.47



In addition to CYP enzyme genes, several genes in the serotonin pathway have been studied for their potential role in the susceptibility to depression, adverse effects, and treatment response to psychotropic medications. Commonly studied genes include the 5-HTTLPR promoter region of the serotonin transporter gene (SLC6A4) and the serotonin receptor gene subtypes 5-HT2A and 5-HT2C.


Adverse Effects of Psychotropic Medications

Several studies reported that 5-HTTLPR L alleles are associated with fewer selective serotonin reuptake inhibitor (SSRI) side effects.48 In a study49 comparing the SSRI paroxetine versus the non-SSRI mirtazapine, patients with 5-HTTLPR S alleles had worse side effects with paroxetine but tolerated mirtazapine better. A possible interaction of 5-HTTLPR L allele and oral contraceptives associated with sexual side effects has also been reported.50 5-HTTLPR S alleles have also been associated with antidepressant-induced mania.51

The serotonin receptor genes 5-HT2A and 5-HT2C have also been associated with psychotropic adverse effects. Paroxetine side-effect severity and discontinuation was associated with the number of 5-HT2A C alleles.38 Various 5-HT2A polymorphisms have also been associated with fewer SSRI side effects including gastrointestinal side effects52 or increased side effects such as sexual side effects.53 An 5-HT2C polymorphism was reported to be protective against significant antipsychotic-induced weight gain54 and associated with tardive dyskinesia, although the association was not significant.55


Response to Treatment

A 2007 meta-analysis of 5-HTTLPR and SSRI treatment reported that the L allele is associated with a better response independent of ethnic differences, and patients with the S/S genotype take >4 weeks to respond and have difficulties reaching remission.56 While there is conflicting data related to the effects of SLC6A4 in patients of African-American or Hispanic ancestry,57,58 an analysis of STAR*D patients restricted to the white non-Hispanic subgroup confirmed an association of SLC6A4 activity level and remission with citalopram.59

Ethnic and gender differences can be seen in various reports. A 2009 study60 of Mexican Americans reported a SLC6A4 haplotype associated with remission using desipramine or fluoxetine. Korean patients with the SLC6A4 S/S genotype responded better to mirtazapine compared to those with the L/L or L/S genotype.61 Chinese patients with the L/L genotype experienced better clinical response to SSRIs compared to serotonin norepinephrine reuptake inhibitors.62 Regarding gender, in women with the SLC6A4 S/S genotype, lower efficacy was reported for SSRIs as well as non-SSRIs.63,64

Other reports of SLC6A4 associations with antidepressant response are interesting. In geriatric patients, SLC6A4 was reported to interact with serum paroxetine levels to influence antidepressant response.65 In a positron emission tomography imaging study, higher serotonin transporter occupancy was associated with clinical improvement with paroxetine in patients with L/L.66 In patients with S/S genotype, antidepressant augmentation with pindolol and lithium was associated with better response.67,68

For 5-HT2A, meta-analysis of antidepressant treatment response showed a contribution to better response with a specific polymorphism, particularly in Asians.52 In the STAR*D data,69 participants who were homozygous for the 5-HT2A A allele of a newly identified variant (rs7997012) had an 18% reduction in absolute risk of having no response to treatment, compared with those homozygous for the other allele. The A allele was over six times more frequent in white than in black participants, and treatment was less effective among black participants.


Practical Recommendations

Pharmacodynamic reviews of SLC6A4 suggest that patients with the S/S genotype do not respond as well to SSRI antidepressants, and may experience more side effects.48,52,70 Thus, a practical approach is to use a non-SSRI in a patient who is SLC6A4 S/S or S/L. A decision analytic model of pre-treatment testing for SLC6A4 concluded that such testing would result in more patients experiencing remission earlier in treatment.71

Knowledge of 5-HT2A alleles might suggest the clinician try citalopram, or if generalization is possible, an SSRI, in patients who are homozygous for the 5-HT2A A allele.69 If a clinician is making a decision whether to augment an antidepressant with an antipsychotic, results of the 5-HT2C might not support an antipsychotic if the patient has the allele associated with increased weight gain with antipsychotics.


Pharmacogenomics in the Perspective of TRD

TRD represents a major public health concern, since it is associated with higher rates of relapse, poorer quality of life, deleterious personal and societal economic ramifications, and increased mortality rates.72,73 In the biopsychosocial model of depression treatment, the biologic standard of care is the medication trial. Numerous algorithms are available for guidance.6,74 Using the example of the Texas Medication Algorithm Project (TMAP), given that each adequate medication trial is ~2 months, and if a patient tries at least 3 SSRIs and 3 non-SSRIs, that would already be 1 year of medication trials. For each antidepressant, augmenting with two different medications such as a mood stabilizer or an antipsychotic for each of the antidepressants tried increases each medication trial by a few more months, and one can appreciate how patients might go through 4 or 5 years of medication trials. By incorporating genotyping results into an algorithm such as TMAP, one should be able to reduce the number of medication trials needed.

Genotyping can also explain some of the adverse events associated with medications. Consider the case example of a 58-year-old Caucasian woman with depression who has not responded to citalopram and bupropion. The clinician selects nortriptyline as the next medication trial, and titrates to a therapeutic dose based on serum level. As her depression is not improving, the clinician adds fluoxetine, noting that the combination of an SSRI and a TCA is listed in Stage 3 of the TMAP. Two weeks later, the patient experiences lethargy and unsteadiness, to the point of falling and sustaining a wrist fracture. A nortriptyline serum level shows it is now in the toxic range, and both medications are held. Two weeks later, the patient returns to her baseline state. Genotyping is obtained, and reveals that the patient is an intermediate metabolizer of CYP2D6. The explanation in this situation is that nortriptyline and fluoxetine are both metabolized by CYP2D6, and additionally, fluoxetine is a strong inhibitor of 2D6. The patient was already an intermediate metabolizer, and by inhibiting that state, effectively converted the patient to a poor metabolizer, which resulted in the nortriptyline toxicity and side effects. Adverse effects are common reasons for switching antidepressants, which leads to more medication trials and a sense of medication “resistance.” Understanding and predicting adverse effects can improve the patient’s experience and compliance with medications, leading to a better outcome.

A patient’s genetic makeup is only one of the many complex factors involved in his or her response to antidepressants. Other factors include diet, caffeine, nicotine, age, medical illness, and concurrent medications. In addition, appropriate attention should be given to the psychological and social stresses aspects of the patients’ illness. Psychotherapies such as cognitive behavioral therapy and acceptance and commitment therapy can be helpful.75,76 Patients with aversive social contexts for their depression also have consistently lower remission rates, indicating the need for social interventions.77



Depression can be difficult to treat, especially with its biopsychosocial contributors. From the biologic perspective, clinicians rely on medication trials which might span several years because of the large number of antidepressants available and the various augmentation strategies. Patients understandably become frustrated with such treatment techniques and look towards methods which might help them identify the optimal medication or combination to treat their depression.

There has been much research into whether pharmacogenomic testing might provide sufficient clinical information to guide psychotropic medication choices and thus decrease the trial and error approach of medication management. With regards to pharmacokinetic testing, specifically CYP2D6 and CYP2C19, identifying poor metabolizers in order to help with medication selection and dosage adjustments can be helpful. In patients presenting with numerous side effects, it can also confirm whether a patient is experiencing side effects because of metabolizer status. From the pharmacodynamic perspective, many genes have been studied, with the most common being the serotonin transporter and serotonin receptor genes. Patients of European ancestry with a serotonin transporter gene S/S or S/L genotype seem to not tolerate or not respond as well to SSRIs compared to patients with the L/L genotype. Various serotonin receptor gene alleles have also been associated with increased or decreased response to SSRIs as well as side effects.

The response of an individual to antidepressant treatment is not only influenced by the limited number of genes that are currently tested. Genome-wide association studies (GWAS) to investigate the entire genome without focus on a specific hypothesis and genomic area represent a new and promising methodologic strategy. A recent GWAS found remission associated with the number of predicted “response” alleles, and supported that antidepressant response emerges from a multitude of genetic variants.78,79 Further research is predicted to reveal additional clinical applications to guide treatment.  PP


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66.    Ruhe HG, Ooteman W, Booij J, et al. Serotonin transporter gene promoter polymorphisms modify the association between paroxetine serotonin transporter occupancy and clinical response in major depressive disorder. Pharmacogenet Genomics. 2009;19(1):67-76.
67.    Zanardi R, Serretti A, Rossini D, et al. Factors affecting fluvoxamine antidepressant activity: influence of pindolol and 5-HTTLPR in delusional and nondelusional depression. Biol Psychiatry. 2001;50(5):323-330.
68.    Stamm TJ, Adli M, Kirchheiner J, et al. Serotonin transporter gene and response to lithium augmentation in depression. Psychiatr Genet. 2008;18(2):92-97.
69.    McMahon FJ, Buervenich S, Charney D, et al. Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am J Hum Genet. 2006;78(5):804-814.
70.    Luddington NS, Mandadapu A, Husk M, El-Mallakh RS. Clinical implications of genetic variation in the serotonin transporter promoter region: a review. Prim Care Companion J Clin Psychiatry. 2009;11(3):93-102.
71.    Smits KM, Smits LJ, Schouten JS, Peeters FP, Prins MH. Does pretreatment testing for serotonin transporter polymorphisms lead to earlier effects of drug treatment in patients with major depression? A decision-analytic model. Clin Ther. 2007;29(4):691-702.
72.    Greden JF. The burden of disease for treatment-resistant depression. J Clin Psychiatry. 2001;62 suppl 16:26-31.
73.    Fekadu A, Wooderson SC, Markopoulo K, Donaldson C, Papadopoulos A, Cleare AJ. What happens to patients with treatment-resistant depression? A systematic review of medium to long term outcome studies. J Affect Disord. 2009;116(1-2):4-11.
74.    TMAP. Texas Medication Algorithm Project. Available at: www.dshs.state.tx.us/mhprograms/disclaimer.shtm. Accessed February 11, 2010.
75.    Markowitz JC. Evidence-based psychotherapies for depression. J Occup Environ Med. 2008;50(4):437-440.
76.    Pull CB. Current empirical status of acceptance and commitment therapy. Curr Opin Psychiatry. 2009;22(1):55-60.
77.    Brown GW, Harris TO, Kendrick T, et al. Antidepressants, social adversity and outcome of depression in general practice. J Affect Disord. 2010;121(3):239-246.
78.    Sabbagh A, Darlu P. Data-mining methods as useful tools for predicting individual drug response: application to CYP2D6 data. Hum Hered. 2006;62(3):119-134.
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Dr. Haq is house officer in the Department of Psychiatry at the University of Michigan in Ann Arbor.

Disclosure: Dr. Haq reports no affiliation with or financial interest in any organization that may pose a conflict of interest.

Off-label disclosure: This article includes discussion of treatments for insomnia and anxiety disorders in patients with chronic alcohol-use disorders which are not approved by the United States Food and Drug Administration.

Acknowledgments: The author would like to thank Kirk Brower, MD, for his valuable editorial assistance; Michelle Riba, MD, Michael Jibson, MD, PhD, and Theadia Carey, MD, for their support; and Edward Jouney, DO, for his inspiration for this article.

Please direct all correspondence to: Aazaz Haq, MD, Department of Psychiatry, University of Michigan, MCHC F6135, 1500 E Medical Center Drive, Ann Arbor, MI 48109; Tel: 734-764-6875; Fax: 734-936-9116; E-mail: ahaq@med.umich.edu.



Insomnia and anxiety are frequently encountered problems in patients with chronic alcohol use disorders. The use of benzodiazepines and benzodiazepine-receptor agonists in post-withdrawal patients is discouraged due to their abuse potential and cross-reactivity with alcohol, and clinicians should be aware of what alternate medications are available. For the treatment of insomnia, trazodone, low-dose tricylic antidepressants, gabapentin, and quetiapine can all be used effectively in this population. For common anxiety disorders (panic disorder, generalized anxiety disorder, social anxiety disorder, and posttraumatic stress disorder), selective serotonin reuptake inhibitors, buspirone, venlafaxine, quetiapine, and gabapentin all have varying levels of evidence of efficacy. These medications have their greatest effect when used in conjunction with continued behavioral and other non-pharmacologic therapy.

Focus Points

• Some antidepressants at low doses (trazodone, tricyclic antidepressants), at least one antiepileptic (gabapentin), and atypical antipsychotics (particularly quetiapine) can all be used to treat insomnia in patients with chronic alcohol use disorders.
• For the treatment of common anxiety disorders in alcohol-dependent patients, there is varying degrees of evidence supporting the use of selective serotonin reuptake inhibitors, venlafaxine, buspirone, quetiapine, and gabapentin.
• Large-scale, placebo-controlled trials assessing the efficacy of common anxiolytics in the treatment of anxiety disorders in alcohol-dependent patients are generally lacking.
• Benzodiazepines and benzodiazepine receptor agonists should be used in patients with alcohol-use disorders only with extreme caution.



Alcohol use disorders are known to be frequently comorbid with insomnia, anxiety, and depression.1,2 While depression can be difficult to treat in alcoholics, the medications used to treat depressive symptoms in this population are no different than those used in the general population.3 In contrast, the treatment of insomnia and anxiety in alcoholic patients is made particularly challenging by the relative contraindication of benzodiazepines in this population due to their abuse liability.4 Clinicians who treat patients with alcohol use disorders should be aware of what options are available to treat insomnia and anxiety.

A significant association between alcohol dependence and insomnia has been shown in several community samples.5,6 Moreover, disturbed sleep has been shown to be a strong predictor of relapse in alcoholics after detoxification,7,8 and alcoholic patients are much more likely to use alcohol to self-medicate for their insomnia.8 During acute withdrawal, alcoholics have short and fragmented sleep with long sleep latencies, very small amounts of delta (stages 3 and 4) sleep, and vivid dreams.9 Sleep continues to be significantly disrupted during the first month of sobriety and slowly improves over the next few months. Some measures of sleep quality remain abnormal at ≥14 months after abstinence, with continued decreased delta-wave sleep, increased rapid eye movement (REM) percentage, and increased REM latency.10

Alcoholism is also frequently comorbid with anxiety disorders. In some patients with a genetic predisposition to an anxiety disorder, ingestion of alcohol can “unmask” anxiety symptoms.11 Other patients with preexisting anxiety disorders frequently use alcohol to self-medicate. The National Comorbidity Study found that in 8,000 respondents with alcohol use disorders in the United States between 15–54 years of age, 37% had at least one anxiety disorder, most commonly social anxiety disorder (18%).12 Independent community studies from Germany and Australia have reported rates of comorbid anxiety disorders among alcoholic patients of 42.3% and 15%, respectively, with the most common disorders being generalized anxiety disorder (GAD) and specific phobia.13,14 Significantly higher degrees of anxiety are found in patients who subsequently relapse within 6 months of initiating abstinence than those who manage to stay sober.15

This article discusses the alternatives to benzodiazepine treatment in the management of insomnia and anxiety in post-withdrawal alcohol-dependent patients. For the treatment of insomnia in these patients, trazodone, tricyclic antidepressants (TCAs), gabapentin, and quetiapine are commonly used. For anxiety disorders, selective serotonin reuptake inhibitors (SSRIs), buspirone, venlafaxine, quetiapine, and gabapentin can all generally be used with efficacy, depending on the specific type of anxiety disorder.




The sedative properties of some antidepressants, typically at low doses, can be used to treat insomnia in alcoholic patients. Trazodone is the second most common medication used by clinicians for insomnia (after zolpidem), despite the relative absence of convincing evidence of its efficacy in non-depressed patients with insomnia.16 It is the agent most commonly used by addiction specialists to treat insomnia in alcoholic patients.17 Trazodone has a relatively benign side-effect profile (most common side effects being drowsiness, dizziness, dry mouth), appears to have few interactions with alcohol,18 and does not have abuse potential.19 Some data suggest that tolerance to the sedative effects of trazodone may develop over long-term use.16 For example, two studies20,21 looking at objective measurements of the sedative effects of trazodone show a slight decrease in the total sleep time in subjects using trazodone after week 3 in one study20 and week 4 in the other.21 However, further studies are needed to clarify this effect.

A small (n=16), double-blind, placebo-controlled study22 assessing the efficacy of trazodone in improving sleep in post-withdrawal alcoholics found that, after 4 weeks, patients receiving nightly trazodone (50 mg/night, titrated up to 200 mg) had significantly increased sleep efficiency, less frequent night-time awakenings, and increased non-REM sleep percentage, than those receiving placebo. A later double-blind, placebo-controlled study19 with a larger sample size (n=173) confirmed that trazodone improves sleep quality and overall mental health during its administration. However, the study19 also found that the patients in the trazodone group had less improvement in the proportion of abstinent days during 3 months of treatment and drank a greater number of drinks per drinking day following the cessation of the medication than the placebo group. Therefore, trazodone was not recommended with confidence for the routine treatment of insomnia in alcohol-dependent patients.

Sedating TCAs can be used at low doses for their anti-histaminergic properties to treat insomnia. For example, doxepin, whose antidepressant effects are typically seen at daily doses of 50–300 mg, has been shown to produce effective hypnotic effects at doses of 1–6 mg/day.23,24 At these low doses, doxepin is selective for blocking only histamine (H)1 receptors and has no effect on serotonin or norepinephrine transporters or muscarininc acetylcholine receptors.25 Selective H1 blockade is not associated with rebound insomnia, loss of hypnotic efficacy over time, or daytime sedation; these undesirable effects of many “antihistamine” medications are largely due to their actions on muscarinic, cholinergic, and adrenergic receptors.25,26 Because muscarinic receptors are not affected at such low doses, the anticholinergic side effects of confusion, dry mouth, blurred vision, constipation, and urinary retention, which are commonly associated with TCAs, are not seen with low dose doxepin. TCAs also have the benefit of not producing euphoria as a side effect, not causing physical tolerance or dependence, and not being controlled substances.23 TCAs should be used with caution in alcohol-dependent patients; even mild overdoses can cause cardiotoxicity or severe orthostatic hypotension and can be fatal, something to be wary of in a population that is at an increased risk for suicide attempts. Moreover, TCAs can lower the seizure threshold, so they should be used with caution in patients undergoing alcohol withdrawal.

SSRIs are generally not used to treat insomnia, as they can frequently worsen sleep and increase the number of nighttime awakenings.24 Nefazodone, an antidepressant with a similar structure to trazodone, has some sleep-promoting properties, but it is rarely used today because of its risk of serious hepatic toxicity.



Gabapentin has recently been gaining favor for the treatment of alcohol dependence and alcohol-related insomnia. Gabapentin is an antiepileptic medication that has a relatively benign side-effect profile, little abuse potential, and does not affect the metabolism or excretion of other medications. Gabapentin has been studied for alcohol-related insomnia during both acute withdrawal and after several weeks of abstinence. During acute withdrawal, gabapentin was shown to be superior to lorazepam in reducing nighttime insomnia and daytime sleepiness among subjects with a history of repeated withdrawal episodes.27 In a preliminary non-blinded, uncontrolled study of post-withdrawal insomnia, Karam-Hage and Brower28 showed that 15 alcohol-dependent patients had improved sleep quality as per the Sleep Problems Questionnaire (SPQ) with an average gabapentin dose of 953 mg/day.

In another non-randomized, non-blinded, uncontrolled study29 (n=50) comparing gabapentin with trazodone for the treatment of post-withdrawal insomnia in patients with alcohol dependence, both medications were shown to improve sleep quality, as per the SPQ, although gabapentin improved sleep quality significantly more than trazodone and was associated with less sedation the next day. However, in a recent double-blind, placebo-controlled pilot trial30 (n=21) of post-withdrawal alcohol-dependent subjects, the same authors found no significant difference in the sleep quality of the gabapentin versus placebo group, as measured by the SPQ, sleep diary parameters, and polysomnography parameters. Of note, gabapentin significantly delayed the onset of relapse to drinking in this study.



Of the typical and atypical antipsychotics, quetiapine is the one most commonly used clinically in patients with alcohol use disorders to reduce cravings and promote sleep. A small-scale retrospective review31 of male alcoholic patients at a Veterans Administration (VA) hospital showed that, in patients with difficulty initiating sleep, quetiapine initiated at a dose of 25–50 mg and titrated up to 200 mg increased the total number of days of abstinence and significantly lowered the rate of hospital admissions. The study did not comment on sleep differences between the two groups. Another retrospective chart review32 of data from patients admitted to a 28-day residential rehabilitation program showed significant improvement in insomnia in alcoholic patients given quetiapine. In an open-label pilot trial33 of 28 dually diagnosed alcoholics, quetiapine significantly decreased middle and late insomnia. A randomized control trial34 by the Department of Veterans Affairs to study the use of quetiapine for insomnia during alcohol abstinence is currently recruiting participants. Of note, the use of quetiapine as a drug of abuse has been rising; it is the antipsychotic most commonly implicated in the literature in case reports of antipsychotic abuse.35 It has several street names, such as “quell,” “Susie-Q,” and “baby heroin.”



Any of the common anxiety disorders (panic disorder, GAD, social anxiety disorder, and posttraumatic stress disorder [PTSD]) can be comorbid with alcohol abuse or dependence. Below, evidence regarding treatment will be reviewed by disorder. When assessing these disorders in the context of alcoholism, it is important to distinguish them from transient anxiety states related to alcohol intoxication or withdrawal, as these may improve with abstinence alone. The best way to approach this task is by observation of the patient during a period of abstinence, generally after 3 or 4 weeks of sobriety for patients recovering from chronic alcohol use.36


Panic Disorder

Several types of antidepressants, including SSRIs, TCAs, monoamine oxidase inhibitors (MAOIs), and venlafaxine, have been shown to be effective in the treatment of panic disorders in patients without substance use disorders, but they have not been studied systematically for use in patients with alcohol or other substance use disorders. Given the unfavorable side-effect profiles of TCAs and MAOIs, SSRIs and venlafaxine are logical choices among antidepressants for the treatment of panic disorder in patients in remission from alcohol.11 SSRIs have a relatively benign side-effect profile, are safe in overdose, and have little abuse potential. To avoid increased anxiety with the initial activation associated with SSRIs, they should be started at a low dose and titrated upwards slowly. Patients should be monitored for relapse in the 4-to-6-week window it takes for the SSRIs to have an effect. As these medications are metabolized by the liver, lower doses should be used in chronic alcoholic patients who have compromised liver function.37 Venlafaxine, a serotonin-norepinephrine reuptake inhibitor, is approved by the US Food and Drug Administration for the treatment of panic disorder38; however, trials of its use in alcohol-dependent patients are lacking.

Gabapentin may be a novel alternative to SSRIs in the treatment of severe panic disorder. In a double-blind, placebo-controlled study (n=103), gabapentin (dosed from 600–3,600 mg/day) was not found to be more effective than placebo in reducing scores on the Panic and Agoraphobia Scale (PAS).39 However, in the severely ill subset of patients with baseline PAS≥20, the patients treated with gabapentin showed significant improvement in PAS scores. Gabapentin has not been studied for treatment of panic disorder in alcoholic patients; however, it has a favorable risk-benefit profile and may be a good option for alcoholic patients with severe panic symptoms for whom SSRIs or venlafaxine are not good options or are ineffective.



Diagnosis of GAD in patients with substance abuse disorders is challenging, as many symptoms of intoxication and withdrawal, such as anxiety, restlessness, difficulty concentrating, fatigue, and sleep disturbance, are similar to the symptoms of GAD. Of the anxiolytic medications, buspirone has been studied most extensively for treatment of GAD in alcoholic patients.40 This is a generally well-tolerated medication with a favorable side-effect profile (most common side effects being dizziness, nausea, headache, nervousness, lightheadedness, and insomnia). Patients given buspirone (average daily dose 20 mg/day) in a double-blind, placebo-controlled trial41 (n=50) in outpatients with mild-to-moderate alcohol abuse demonstrated decreased scores on the Hamilton Rating Scale for Anxiety (HAM-A) as well as lower discontinuation rate and decreased cravings. In another trial42 evaluating 51 patients with dual diagnoses of alcohol abuse or dependence and GAD, the buspirone treatment group had decreased overall anxiety, less number of days desiring alcohol, and overall clinical global improvement. However, in a double-blinded, placebo-controlled study43 (n=67) of alcohol-dependent patients with high levels of generalized anxiety in a Veteran’s Administration hospital, there was no significant difference on scores between the treatment and placebo groups on the HAM-A or the Speilberger State Anxiety Scale. Lastly, in a randomized, 12-week, placebo-controlled trial,44 buspirone was found to be associated with reduced anxiety, greater retention rate, a slower return to heavy alcohol consumption, and fewer drinks during the follow-up period compared to placebo. Anxiolytic effects with this medication may only be seen at relatively higher doses (above 30 mg/day) after 2–4 weeks of treatment.45

SSRIs, TCAs, venlafaxine, and some anticonvulsants are also effective in treating symptoms of GAD in the general population. However, trials studying these medications in the treatment of GAD specifically in alcoholic patients are lacking. Based on side effects, metabolic profiles, and data from non-alcoholic patients, buspirone, SSRIs, and venlafaxine are likely the most reasonable choices in alcohol-dependent patients for the treatment of GAD.


Social Anxiety Disorder

Kessler and colleagues46 found the rate of comorbidity of social anxiety and alcohol abuse to be 22%. Patients with social anxiety disorder often use alcohol to self-medicate and ease anxiety in social situations. In the general population, MAOIs (phenelzine, brofaromine, and moclobemide), SSRIs (sertraline and fluvoxamine), benzodiazepines (clonazepam), and one antiepileptic (gabapentin), have been shown to be effective in treating social anxiety in placebo-controlled trials.47 Buspirone is not effective in treating social anxiety.48 Placebo-controlled trials studying these medications in patients with comorbid alcohol use disorders and social anxiety are lacking, with the exception of one study49 examining the use of paroxetine. In this 8-week, double-blind, placebo-controlled trial (n=18), alcohol-dependent patients in the treatment group (paroxetine titrated to 60 mg/day) showed a significant improvement in social anxiety symptoms (as per the Clinical Global Index and the Liebowitz Social Anxiety Scale) by week 6 of the trial. Of note, no significant difference on any of the quantity/frequency measures of alcohol use was seen between the two groups.



PTSD is associated with a greatly increased risk of alcohol dependence.50 SSRIs have been widely shown to be successful in the treatment of PTSD in the non-substance-abusing population. In a preliminary open-label trial of sertraline in patients with comorbid alcohol-dependence and PTSD, PTSD symptom scores (per the Impact of Event Scale) and average number of drinks during the follow-up period decreased, while the number of days of abstinence increased.51 In a follow-up randomized, placebo controlled trial (n=94) of sertraline in PTSD patients with comorbid alcohol-use disorders, the same authors52 found a significant decrease in alcohol use in both the treatment and placebo groups. Of note, in this study, a subgroup of patients with less severe alcohol dependence and early-onset PTSD had significantly fewer drinks per drinking day with sertraline treatment than other groups.

Several atypical antipsychotics, including risperidone,53 olanzapine,54 and quetiapine,55 have been shown to be effective as adjunctive agents to SSRIs in alleviating PTSD symptoms in the general population. However, they have not been studied in patients with co-morbid PTSD and alcohol-use disorders. In a retrospective study31 assessing quetiapine treatment in alcohol-dependent patients in a VA hospital, 90% of whom had PTSD, the authors found a decrease in the number of detoxifications needed per year, increase in the total number of abstinent days, and longer mean time to relapse in patients receiving quetiapine for sleep. These improvements were attributed at least partially to reduction in PTSD symptoms from quetiapine.


Benzodiazepines and Benzodiazepine-Receptor Agonists

The use of benzodiazepines in alcoholic patients merits special discussion. These medications are frequently used to treat anxiety and insomnia in the general population. However, except in the treatment of acute alcohol withdrawal, use of these medications in patients with alcohol use disorders is generally discouraged.4 They share a similar mechanism of action on gamma-aminobutyric acid  receptors to alcohol and have a high abuse potential.56 Even in patients without substance use problems, they are generally recommended only for short-term usage and in conservative dosages.57

Benzodiapzepine receptor antagonists (BzRAs), like zolpidem and zaleplon, present an interesting scenario in the treatment of insomnia in alcoholic patients. These medications are generally well tolerated, and studies have shown that they do not cause tolerance or dependence at physiologic doses over short-term (4-week) nightly use58 or long-term (12-week) non-nightly use.59 A very large percentage of patients who use BzRAs for primary nighttime insomnia do not go on to develop dependence or to abuse the drug in the daytime for non-therapeutic reasons.60 In 2002, a systematic review of all published case studies of BzRA dependence found only 36 cases of zolpidem dependence and 22 cases of zoplicone dependence, almost all of which involved former drug or alcohol abusers or patients with other recognized psychiatric disorders.61 This relatively low number of published cases of dependence was in marked contrast to the much higher incidence of dependence known with benzodiazepines. The authors concluded that zolpidem and zoplicone are relatively safe medications, but “extreme caution” should be utilized when prescribing them to patients with a history of substance abuse, dependence, or other psychiatric illness.

It is worth mentioning that withholding benzodiazepines or BzRAs from all post-withdrawal alcoholic patients as a rule may not be an optimal strategy. According to Lejoyeux and colleagues,4 an anxiolytic agent might help to improve the quality of life and adherence to treatment in patients with severe anxiety. A recent prospective study62 monitoring 545 patients with comorbid anxiety and alcohol-use disorder receiving benzodiazepines over 12 years showed that benzodiazepine usage did not predict recovery or relapse. However, the authors were cautious in generalizing their results to all patients or the set of patients who present for addiction treatment. The judicious use of benzodiazepines in a given patient should be decided on a case-by-case basis after a careful assessment of the alternatives as well as the risks and benefits involved.



The management of insomnia and anxiety in the alcohol-dependent population can be challenging. With the relative contraindication of benzodiazepines and BzRAs, clinicians have to turn to alternative medications to treat these symptoms. It is important to keep in mind that none of the medications discussed above are FDA-approved for treatment of insomnia or anxiety disorders in alcohol-dependent patients. Moreover, they have their greatest effects when used in conjunction with continued behavioral and non-pharmacologic therapy.63 Continued research is needed to further identify the safety and efficacy of these medications in this unique patient population.  PP



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41.    Bruno F. Buspirone in the treatment of alcoholic patients. Psychopathology. 1989;22(suppl 1):49-59.
42.    Tollefson GD, Montague-Clouse J, Tollefson SL. Treatment of comorbid generalized anxiety in a recently detoxified alcoholic population with a selective serotonergic drug (buspirone). J Clin Psychopharmacol. 1992;12(1):19-26.
43.    Malcom R, Anton RF, Randall CL, Johnston A, Brady K, Thevos A. A placebo-controlled trial of buspirone in anxious inpatient alcoholics. Alcoholism Clin Exp Res. 1992;16(6):1007-1013.
44.    Kranzler HR, Burleson JA, DelBoca FK, et al. Buspirone treatment of anxious alcoholics – a placebo-controlled trial. Arch Gen Psychiatry. 1994;51:720-731.
45.    Micromedex Health Care Series. DrugPoint Summary: Buspirone. Thompson Reuters, 2009. Updated February 6, 2009. Available at: www.thomsonhc.com. Accessed February 2, 2010.
46.    Kessler RC, Crum RM, Warner LA, Nelson CB, Schulenberg J, Anthony JC. Lifetime co-ocurrence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry. 1997;54(4):313-321.
47.    Pande AC, Davidson JR, Jefferson JW, et al. Treatment of social phobia with gabapentin: a placebo-controlled study. J Clin Psychopharmacol. 1999;19(4):341-348.
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49.    Randall CL, Johnson MR, Thevos AK, et al. Paroxetine for social anxiety and alcohol use in dual-diagnosed patients. Depress Anxiety. 2001;14(4):255-262.
50.    Pierce JM, Kindbom KA, Waesche MC, Yuscavage AS, Brooner RK. Posttraumatic stress disorder, gender, and problem profiles in substance-dependent patients. Subs Use Misuse. 2008:43(5):596-611.
51.    Brady KT, Sonne SC, Roberts JM. Sertraline treatment of comorbid posttraumatic stress disorder and alcohol dependence. J Clin Psychiatry. 1995;56(11):502-505.
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53.    Monnelly EP, Ciraulo DA, Knapp C, Keane T. Low dose risperidone as adjunctive therapy for irritable aggression in posttraumatic stress disorder. J Clin Psychopharmacol. 2003;23(2):193-196.
54.    Stein MB, Kline NA, Matloff JL. Adjunctive olanzapine for SSRI-resistant combat-related PTSD: a double-blind, placebo-controlled study. Am J Psychiatry. 2002;159(10):1777-1779.
55.    Hamner MB, Deitsche SE, Brodrick PS, Ulmer HG, Lorberbaum JP. Quetiapine treatment in patients with posttraumatic stress disorder: an open trial of adjunctive therapy. J Clin Psychopharmacol. 2003;23(1):15-20.
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This interview took place on November 30, 2009 and was conducted by Norman Sussman, MD.


Dr. Weintraub is Associate Professor of Psychiatry and Fellow at the Institute of Aging at the University of Pennsylvania in Philadelphia. His areas of research interest include the psychiatric and cognitive complications of Parkinson’s disease. Dr. Weintraub recently completed a 5-year Career Development Award from the National Institute of Mental Health titled “Depression Diagnosis and Treatment in Parkinson Disease.” In addition, he was coordinating investigator for a multi-site, international, industry-sponsored study of the frequency and correlates of impulse control disorders in Parkinson’s disease.


What is Parkinson’s Disease and Why Does Dementia with Lewy Bodies (DLB) Tend to get Clustered in with it in Discussions?

Parkinson’s disease is defined by its motor characteristics, whereas DLB is defined primarily by its cognitive and other non-motor deficits.

To meet criteria for idiopathic Parkinson’s disease, a person must have primary motor symptoms, the most common ones being tremor (upper extremity tremor in particular, usually asymmetric at the time of disease onset); bradykinesia, or slowness of movement; stiffness; and, at times, impairments in balance, although that tends to happen later in the course of the illness. Some combination of those types of motor symptoms is what helps patients meet criteria for Parkinson’s disease, often supported by a response to dopamine-replacement therapy.

In contrast, DLB is characterized at disease onset by a dementing illness consisting of impairment in memory and other cognitive abilities. Supporting features include psychotic symptoms, particularly visual hallucinations. Impairments in attention or fluctuations in alertness are also characteristic. Parkinsonism—some of the same features that I mentioned before—is also characteristic of DLB, although the response to dopamine-replacement therapy is typically less in DLB than in Parkinson’s disease.


Would it be confusing for a non-neurologist to distinguish between one or the other?

There is the potential for confusion. One main reason is that a fair number of Parkinson’s disease patients, even at the time of illness onset or diagnosis of motor symptoms, are already demonstrating some level of cognitive impairment.

The two can go hand in hand fairly early in the course of either illness, and therefore there is sometimes a blurring between diagnostic categories. Expert opinion is that if there is an established diagnosis of Parkinson’s disease and at least 1 year has gone by before the patient meets criteria for dementia, then the diagnosis is Parkinson’s disease dementia. If that dementia diagnosis either predates the onset of the motor symptoms or comes within the first year of the parkinsonism, then the patient would meet criteria for DLB.

The reason there seems to be so much overlap is that from a neuropathologic standpoint, the illnesses are very similar. The core neuropathology and even the brain regions that are affected appear to significantly overlap between Parkinson’s disease, Parkinson’s disease dementia, and DLB.


Compared to a decade ago, is there better understanding of the pathophysiology of Parkinson’s disease and DLB?

There has been some evolution in terms of understanding. One change to highlight over the past 10 years is that the neurotransmitter deficits really are beyond dopamine in Parkinson’s disease. The noradrenergic deficits are probably as significant or close to as significant as the dopaminergic deficits. In addition, serotonergic deficits can be prominent in the illness. However, it appears that all of the brain stem monoamines are affected to some degree in Parkinson’s disease, so it really is more than just a dopamine disorder.

Another prominent neurotransmitter deficit is in acetylcholine. The cholinergic deficits in Parkinson’s disease dementia are greater than in Alzheimer’s disease. Even non-demented Parkinson’s disease patients have significant cholinergic loss, so that probably helps explain the high frequency of cognitive impairments in Parkinson’s disease.


Have Anticholinergics been used to treat Parkinson’s Disease?

Yes, and they still are, though less commonly now. They have to be used cautiously in patients who are more likely to suffer the side effects of anticholinergics, which would include older patients or patients with preexisting cognitive impairment. Younger patients who are more intact cognitively still receive those treatments.


How Common are Parkinson’s Disease and DLB?

The primary risk factor for Parkinson’s disease and DLB is increasing age. Accurate prevalence and incidence estimates for Parkinson’s disease are hard to come by. The general estimate of Parkinson’s disease in the United States is anywhere between 500,000 and 1 million people. In Western societies, it is the second most common neurodegenerative disease after Alzheimer’s disease.

Looking at only the dementia end, DLB is thought to be the second most common dementing illness after Alzheimer’s disease. Part of the problems with the prevalence estimates are the overlapping diagnoses of DLB and Parkinson’s disease, so it is sometimes difficult to disentangle those two groups. Still, those are the general prevalence estimates. Increasing age is the main risk factor; however, compared with Alzheimer’s disease, it is not as uncommon for patients in their thirties, forties, or even fifties, to develop Parkinson’s disease, much more common relatively than in Alzheimer’s disease.


When people lose 80% of their neurons they get clinical manifestations of Parkinson’s Disease. Does everybody as they get older lose these neurons? Is it only a matter of time?

Parkinson’s disease is a disorder of aging. It is unclear if the incidence of Parkinson’s disease will peak at a certain age or whether it just continues to go up. All evidence to this point is that it continues to go up with advanced age. A person needs to lose ~80% of the neurons in the substantia nigra before clinically manifesting the motor symptoms of Parkinson’s disease. Another advancement in the past decade has been the work of Professor Heiko Braak and other neuropathologists that have not only staged Alzheimer’s disease, but also showed a staging process for Parkinson’s disease. Clearly, the brain stem changes in the majority of patients occur even before 80% of those neurons are lost in the substantia nigra, which helps explain some of the pre-motor symptoms that can occur. Beyond the substantia nigra in the later stages of the illness, the pathology spreads to cortical areas; by then it really becomes very much a diffuse brain disease.


Are there certain non-motor cognitive or psychiatric symptoms in Parkinson’s disease that will present before any movement disturbance is detected?

Yes, there has been significant research conducted in that area in the past decade, both from large European databases where patients are followed prospectively from young adulthood annually, as well as from case-controlled studies. There is now convincing evidence that patients with Parkinson’s disease compared to non-Parkinson patients are more likely to have a lifetime history of either depression or an anxiety disorder in the 5–10-year period, and perhaps even up to 20 years for anxiety, preceding the onset of Parkinson’s disease.

Another common psychiatric or non-motor disorder reported to occur prior to Parkinson’s onset is rapid eye movement behavior disorder, which is a parasomnia where patients are able to verbally or physically act out their dreams. This has been reported to occur up to 20 years prior to the onset of Parkinson’s disease. When most of us dream we are in an atonic state; we cannot physically or verbally act out our dreams. This atonia seems to be lost in a fair percentage of Parkinson’s patients, and apparently may be lost prior to the onset of Parkinson’s disease, which is thought to represent a brain stem dysfunction.

Other non-motor symptoms that have been reported to occur prior to Parkinson’s disease include impaired smell or olfaction, which is very common in Parkinson’s disease; constipation; and altered sympathetic intervention of the heart. All are testable.

What are some of the cognitive symptoms you observe in patients with Parkinson’s disease?

It was taught in the past that Parkinson’s disease patients compared with Alzheimer’s disease patients are less likely to have memory or language deficits and more likely to have deficits in other domains. For patients that have memory deficits, it is less likely to be an encoding deficit, as seen with Alzheimer’s disease, but more of a retrieval deficit, which was thought to reflect more subcortical dysfunction.

However, accumulating research has found that Parkinson’s disease patients can have impairments in a range of cognitive domains, including memory, attention, executive abilities, and visual-spatial abilities. This has been one major shift in the perception of the disease.

The other major shift is the recognition that, whereas cross-sectional studies have demonstrated that ~30% of Parkinson’s disease patients have dementia, more careful longitudinal studies1,2 have shown that the overwhelming majority of patients with Parkinson’s disease do develop dementia if followed long enough. Early stages of these deficits can be detectable often at the time of diagnosis in 20% of patients. If the clinician asks the right questions and uses appropriate assessment instruments, the disease can be detected early.


What kind of visual-spatial disturbances are involved?

A common example would be the judgment of line orientation tests, which is the ability to conceptualize lines in three dimensions, so to speak. However, it can be detectable even at a much simpler level, just with pentagon or clock drawing. Another difficulty for Parkinson’s patients is drawing a cube. The disease can be detected even on simple paper-and-pencil tests.

Are some subtle dysfunctions picked up early and more inevitable ones later on?

Yes. Heterogeneity is the one word that I use more than any to describe all the motor and non-motor features of Parkinson’s disease. There is such a range of presentations of Parkinson’s in patients from both a non-motor and a motor standpoint. This is one area where I think our research has failed us to some extent, in that most studies will present means and averages for patients on a particular score or domain; however, the individual presentation of patients is really lost that way. The means really mean less in Parkinson’s disease than how individual patients present.

Some patients do have cognitive deficits early on, and others do not for 15 years. Somebody may have a primary memory deficit, while another may have impairment in multiple domains. Presentations are all over the board.

Do treatments for psychiatric symptoms and Parkinson’s disease adversely affect each other?

This is a very controversial and complex area. Early in the course of Parkinson’s disease, a de novo case, for example, who has not been treated ever, often would respond with exposure to dopamine-replacement therapies, whether it is levodopa or dopamine agonists. For instance, some patients show improvements in psychomotor speed, attention, and concentration. However, the results are mixed, with some patients or cognitive abilities improving, and others worsening.  Thus, it is difficult to offer a generalization in this regard.

As patients advance in the course of their illness, where they age and the pathology becomes more severe, it seems more likely that the medications, if anything, are not beneficial to cognition. Rather, they may be potentially harmful, particularly with higher dosages when patients can become delirious or psychotic, which certainly has an effect on the cognition, as well.

Deep brain stimulation (DBS), which is increasingly used as a treatment for Parkinson’s disease, is thought to perhaps impair verbal fluency and some aspects of memory. That may be a complicating effect of that specific treatment. The anticholinergics and amantadine are probably the most notorious medications in terms of worsening cognition.

In terms of psychiatric medications, in general the newer antidepressants are thought to be safe and well tolerated from both a motor and cognitive standpoint. Recent studies show benefit for tricyclic antidepressants in Parkinson’s disease.3,4 One concern there, of course, is that with a heavier anticholinergic load, cognition could potentially worsen.

It is unclear from a cognitive standpoint whether antipsychotics have deleterious effects on Parkinson’s disease, but certainly there is concern about them worsening motor symptoms in Parkinson’s patients.

Finally, the last class of psychiatric medications commonly used is benzodiazepines. These medications must be used very cautiously in Parkinson’s disease patients because common side effects include impaired gait, sedation, and worsening cognition.

Are any therapies currently available for Alzheimer’s disease effective in improving cognitive symptoms in patients with Parkinson’s disease and DLB?

The cholinesterase inhibitor rivastigmine actually has Food and Drug Administration approval for the treatment of Parkinson’s disease dementia. This was on the basis of one large European study5 that showed significant, but modest, benefits in the treatment of Parkinson’s disease dementia, similar to what would be present in Alzheimer’s disease patients. A more recent placebo-controlled study6 in patients with both Parkinson’s disease dementia and DLB showed benefit for memantine. Those are really the two large-scale studies that have been positive to date for the treatment of cognitive dysfunction in Parkinson’s disease.

Another common non-motor disturbance in Parkinson’s disease is apathy, often in the context of cognitive impairment, but not always. We really do not have good treatments for apathy in the context of any other disorder. We extrapolate what people use in other populations, including the use of stimulants. Clinicians, myself included, may use methylphenidate and dextroamphetamine as a trial for apathy in particular. Bupropion is also used to some extent because of its stimulant-like properties, the reason being that it has some dopamine-enhancing effects, as well.

Have there been any meaningful advances in the treatment of the motor symptoms of these disorders in recent years?

The one class that was not available 10 years ago that is readily available now and used as a first-line agent in younger patients particularly are the dopamine agonists. The ones being used now are more selective and better tolerated overall than the older ones. This class of medication has been added to the armamentarium, in addition to levodopa, although levodopa still is the most potent in terms of its motor effects.

DBS has been a significant advancement, particularly for patients with more advanced disease, because those patients really had no option previously. Once they developed dyskinesias and other motor fluctuations, they were really at a dead end in terms of treatment. This often can be a successful treatment for patients that enables them to make a significant decrease in their dopamine-replacement therapy. Other fine tuning has been the increased use of catechol-O-methyl transferase inhibitors, that do allow a better management of motor fluctuations in off periods.

That being said, I think treatment has not advanced so significantly. I do think patients are better managed overall. Clinicians are able to go deeper into the course of their illness without significant complications compared with previously.


Does using these other, more indirect interventions delay some of the secondary complications of taking levodopa, such as the dyskinesias?

Yes. A preferred medication choice in this day and age would be to start with a dopamine agonist, or even for milder symptomatic benefit something like an monoamine oxidase-B inhibitor early in the course of the illness, and to delay the introduction of levodopa as long as possible.


Is there anything you would like to add?

One other interesting area for psychiatrists that has come to the forefront recently—and we have been involved in a fair amount of research with this—is impulse control disorders in response to dopamine agonist treatment. Parkinson’s patients can develop compulsive behaviors (the four that have been reported have been gambling, sexual behavior, buying, and eating) in connection with their Parkinson’s treatment. It is quite a problematic disorder, but also an interesting one from a psychiatric standpoint in that the disorder can be essentially induced by these dopaminergic medications. PP



1.    Aarsland D, Andersen K, Larsen JP, Lolk A, Kragh-Sørensen P. Prevalence and characteristics of dementia in Parkinson disease: an 8-year prospective study. Arch Neurol. 2003;60(3):387-392.
2.    Hely MA, Reid WG, Adena MA, Halliday GM, Morris JG. The Sydney multicenter study of Parkinson’s disease: The inevitability of dementia at 20 years. Mov Disord. 2008;23(6):837-844.
3.    Menza M, Dobkin RD, Marin H, et al. A controlled trial of antidepressants in patients with Parkinson’s disease and depression. Neurology. 2009;72(10):886-892.
4.    Devos D, Dujardin K, Poirot I, et al. Comparison of desipramine and citalopram treatments for depression in Parkinson’s disease: a double-blind, randomized, placebo-controlled study. Mov Disord. 2008;23(6):850-857.
5.    Emre M, Aarsland D, Albanese A, et al. Rivastigmine for dementia associated with Parkinson’s disease. N Engl J Med. 2004;351(24):2509-2518.
6.    Aarsland D, Ballard C, Walker Z, et al. Memantine in patients with Parkinson’s disease dementia or dementia with Lewy bodies: a double-blind, placebo-controlled, multicentre trial. Lancet Neurol. 2009;8(7):613-618.

High Rates of Psychiatric Disorders Found in the Wives of Deployed Soldiers

Active military deployment can be a stressful period for both the family member on active deployment as well as family members at home waiting for a safe return. The mental health status of the wives of active military personnel, including those soldiers that are still at home and those that are deployed, has not frequently been studied.

Alyssa Mansfield, PhD, and colleagues reviewed the electronic medical records of >250,000 female spouses of active duty Army personnel receiving outpatient care between 2003 and 2006. Of the wives studied, ~31% had husbands that were currently home, ~34% were stationed overseas between 1–11 months, and 35% were deployed for >12 months.

Mansfield and colleagues found higher rates of mental health diagnosis in the wives of soldiers who were deployed for >12 months compared to those deployed for shorter periods of time or still stationed at home. The Table provides the adjusted analysis of wives whose husbands were not deployed and whose husbands were deployed between 1–11 months compared to the wives whose husbands were deployed for >12 months. When converting the excess cases to potential patients, Mansfield and colleagues found that the 41.3 excess cases would attribute to 3,474 mental health diagnoses and the 60.7 excess cases would attribute 5,370 mental health diagnoses.


Although there are limitations to this study, Mansfield and colleagues believe that this data proves that treatment options and preventive measures not only need to be offered to returning soldiers, but also to all military family members. (N Eng J Med. 2010;362(2):168-170.) –CN


Hypertension, White Matter Brain Lesions, and Dementia Risk in Older Women

Older women with hypertension may be at greater risk for abnormal white matter lesions in the brain that can cause dementia. The relationship between hypertension, blood pressure, and blood pressure control with white matter abnormalities in the Women’s Health Initiative (WHI) Memory Study—MRI Trial was studied by Lewis H. Kuller, MD, PhD, at the University of Pittsburgh.

The study’s sample included 1,403 women, ≥65 years of age, from the WHI study. All participants had no dementia at baseline and received blood pressure, cognitive, and magnetic resonance imaging (MRI) assessments.

According to MRI, women receiving hypertension treatment, with blood pressure ≥140/90 mm Hg, had the greatest number of abnormal white matter lesions. Women receiving no hypertension treatment, with blood pressure ≥140/90 mm Hg, had “intermediate” levels of abnormal white lesions. The white matter lesions were more likely to appear in the frontal lobe, compared to the occipital, parietal, or temporal lobes, and baseline blood pressure was strongly associated with white matter lesion volumes.

Previous evidence, combined with the current study, continues to suggest that maintaining health blood pressure levels consistently and sooner in life is the best preventive measure against dementia.

The WHI program is funded by the National Heart, Lung, and Blood Institute of the National Institutes of Health. (J Clin Hypertens. Epub Dec. 16, 2009) –LS


Sudden Infant Death Syndrome Linked to Lower Levels of Serotonin

Sudden infant death syndrome (SIDS) is the leading cause of postneonatal infant death in the United States. During a critical developmental period, SIDS is speculated to result from abnormalities in brainstem control of autonomic function and breathing. It has been reported that irregularities of serotonin (5-HT) and tryptophan hydroxylase (TPH2) receptor binding in regions of the medulla oblongata have been documented in infant deaths resulting from SIDS.

The hypothesis that SIDS is connected with reductions in tissue levels of 5-HT, TPH2, or both was tested by Jhodie R. Duncan, PhD, and colleagues at the Children’s Hospital Boston and Harvard Medical School in Massachusetts. For biochemical analysis, the study involved 35 infants who had died from SIDS, five infants with acute death from known causes, and five hospitalized infants with chronic hypoxia-ischemia. Through autopsy, tissue samples were obtained and several enzymes, including 5-HT and TPH2, were analyzed and measured.

In the raphé obscurus and the paragigantocellularis lateralis regions of the brain, the researchers found that 5-HT levels were 26% lower in SIDS cases compared with age-adjusted controls. TPH2 levels were 22% lower in the raphé obscurus in the SIDS cases, and 5-HT levels were 55% higher in the raphé obscurus and 126% higher in the paragigantocellularis lateralis in the hospitalized group compared with the SIDS group.

According to the authors, SIDS can be viewed as possibly being caused by a defect in one or more parts of the medullary 5-HT system.

Funding for this research was provided by Children’s Hospital Boston and Harvard Medical School in Massachusetts.  (JAMA. 2010;303(5):430-437). –JV

Psychiatric dispatches is written by Christopher Naccari, Lonnie Stoltzfoos, and Jennifer Verlangieri.


Dr. Goodman is director and assistant professor in the Department of Psychiatry and Behavioral Sciences at Johns Hopkins University School of Medicine in Baltimore, Maryland. Dr. Faraone is a professor in the Department of Psychiatry and Department of Neuroscience and Physiology at SUNY Upstate Medical University in Syracuse, New York. Dr. Adler is a professor in the Department of Psychiatry and Child Adolescent Psychiatry at New York University School of Medicine and Psychiatry Service, and New York VA Harbor Healthcare System in New York City. Dr. Dirks is associate medical director and Mr. Hamdani is associate director at Shire Development Inc. in Wayne, Pennsylvania. Dr. Weisler is an adjunct professor at Duke University Medical Center in Durham, North Carolina and University of North Carolina at Chapel Hill.

Dr. Goodman has been a consultant to Avacat, Clinical Global Advisors, Eli Lilly, Forest, McNeil, New River Pharmaceuticals, Major League Baseball, Novartis, Schering-Plough, Shire, and Thompson Reuters; has received research support from Cephalon, Eli Lilly, Forest Labs, McNeil, New River Pharmaceuticals, and Shire; has received honoraria from Eli Lilly, Forest Labs, McNeil, Shire, and Wyeth; has been on the speaker’s bureaus of the American Professional Society of ADHD and Related Disorders, the Audio-Digest Foundation, CME Inc, Forest Labs, JB Ashton Associates, McNeil, Medscape, Shire, Synermed Communications, Temple University, the Veritas Institute, WebMD, and Wyeth; and receives royalties from MBL Communications. Dr. Faraone is consultant to and is on the advisory boards of Eli Lilly, McNeil, and Shire; and receives research support from Eli Lilly, the National Institutes of Health, Pfizer, and Shire. Dr. Adler is consultant to AstraZeneca, Eli Lilly, Epi-Q, i3 Research, INC Research, Mindsite, Organon/Schering-Plough/Merck, Ortho-McNeil/Janssen/Johnson & Johnson, Otsuka, Shire, United Biosource; receives research support from Bristol-Myers Squibb, Chelsea Therapeutics, Eli Lilly, Organon/Schering-Plough/Merck, Ortho-McNeil/Janssen/Johnson & Johnson; and is on the advisory boards of Eli Lilly, i3 Research, INC Research, Mindsite, Organon/Schering-Plough/Merck, Ortho-McNeil/Janssen/Johnson & Johnson. Dr. Dirks is a full-time Shire employee and has stock and/or stock options from Shire and Johnson & Johnson. Mr. Hamdani is a full-time Shire employee and has stock and/or stock options from Shire. Dr. Weisler has been a consultant to Abbott, Ayerst, Bioavail, Bristol-Myers Squibb, the Centers for Disease Control and Prevention, Corcept, Eli Lilly, Forest Labs, GlaxoSmithKline, Johnson & Johnson, Novartis, Organon, Ostuka America Pharma, Pfizer, Sanofi-Synthelabo, Shire, Solvay, the Agency for Toxic Substances Disease Registry, Validus, and Wyeth; has been on the speaker’s bureaus of Abbott, AstraZeneca, Bioavail, Bristol-Myers Squibb, Cephalon, Eli Lilly, Forest Labs, GlaxoSmithKline, Organon, Pfizer, sanofi-aventis, Shire, Solvay, Validus, and Wyeth Ayerst; has received research support from Abbott, AstraZeneca, Ayerst, Bioavail, Bristol-Myers Squibb, Burroughs Wellcome, Cenerx, Cephalon, Ciba-Geigy, CoMentis, Corcept, Dainnpon-Sumitomo, Eisai, Eli Lilly, Forest Labs, GlaxoSmithKline, Janssen, Johnson & Johnson, Lundbeck, McNeil, MediciNova, Merck, the National Institute of Mental Health, Neurochem, New River Pharmaceuticals, Novartis, Organon, Parke Davis, Pfizer, Pharmacia, Repligen, Saegis, Sandoz, Sanofi-Synthelabo, Schwabe/Ingenix, Sepracor, Shire, SmithKline Beecham, Solvay, Synaptic Pharmaceutical Incorporated, Takeda, TAP Pharmaceutical, UCB Pharma, Upjohn, Vela, and Wyeth; and has been a financial stockholder of Bristol-Myers Squibb, Cortex, Merck, and Pfizer.

Acknowledgments: Supported by funding from Shire Development Inc. Although the study sponsor was involved in the study design as well as collection, analysis, and interpretation of data, the ultimate interpretation of the data was made by the independent authors, as was the writing of this manuscript and the decision to submit it for publication in Primary Psychiatry. Writing assistance was provided by Margaret McLaughlin, PhD, a former employee of Health Learning Systems, and Michael Pucci, PhD, an employee of Health Learning Systems. Editorial assistance in the form of proofreading, copy editing, and fact checking was provided by Health Learning Systems.

Please direct all correspondence to: David Goodman, MD, Johns Hopkins at Green Spring Station, 10751 Falls Rd, Suite 306, Lutherville, MD 21093; Tel: 410-583-2726; Fax: 410-583-2724;
E-mail: dgoodma4@jhmi.edu.



Objective: To provide additional understanding of the clinical significance of Attention-Deficit/Hyperactivity Disorder Rating Scale, Version IV (ADHD-RS-IV) total and change scores in relation to Clinical Global Impressions-Severity or -Improvement (CGI-S/-I) levels.
Methods: Using two similarly designed pivotal trials of lisdexamfetamine dimesylate (Vyvanse, Shire US Inc), equipercentile linking was used to identify scores on the ADHD-RS-IV and CGI that have the same percentile rank.
Results: As assessed by CGI-S levels, moderately, markedly, severely, and extremely ill adults had mean (SD) baseline ADHD-RS-IV scores of 36.2 (4.9), 42.1 (6.1), 45.4 (5.1), and 53.0, respectively. A similar relationship was observed in children. At endpoint, children categorized as minimally, much, or very much improved by CGI-I demonstrated mean (SD) ADHD-RS-IV changes from baseline of -9.9 (6.8), -25.5 (7.2), and -33.2 (9.3), respectively. Adults demonstrated a similar relationship between ADHD-RS-IV change scores and CGI-I ratings. Based on equipercentile link function, a change from baseline in ADHD-RS-IV total score of ~10–15 points or 25% to 30% corresponded to a change of 1 level in CGI-I score.
Conclusion: This analysis makes possible the establishment of a clinical impression of severity of illness from total ADHD-RS-IV scores and may facilitate the clinical interpretation of improvement of ADHD-RS-IV change scores.

Focus Points

• Linking the Clinical Global Impressions-Severity (CGI-S) ratings with Attention-Deficit/Hyperactivity Disorder Rating Scale, Version IV (ADHD-RS-IV) scores at baseline, two trials of lisdexamfetamine dimesylate demonstrated that a difference of ~8–10 points in baseline ADHD-RS-IV score is appreciated clinically as a 1-point difference in CGI-S score.
• An improvement in ADHD-RS-IV score of ~50% to 60% is needed to achieve a rating of much improved (2-level improvement) on the CGI-Improvement scale.
• For all three pairs of linkages, the relationship between ADHD-RS-IV scores and CGI levels was consistent across the age groups.



The use of rating scales to quantify subjects’ response to treatment for attention-deficit/hyperactivity disorder (ADHD) is commonplace in clinical trials. These scales are less commonly used in clinical practice and, as such, the clinical implications of total or change scores on these scales may not be readily apparent to clinicians. Additionally, the measures of response used in clinical trials may not mimic the standards used by clinicians in practice.

The ADHD Rating Scale, Version IV (ADHD-RS-IV),1 has been widely used as a measure of efficacy in clinical trials of ADHD treatments in children and adolescents.2,3 Derived from the 18 inattentive and hyperactive/impulsive diagnostic criteria for ADHD from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition,4 the parent and teacher versions of the ADHD-RS-IV have a large base of normative data and have demonstrated reliability and discriminant validity in children and adolescents.1,3 A validated, clinician-administered version of the ADHD-RS-IV using adult prompts was developed at New York University/Massachusetts General Hospital (NYU/MGH) and has been used in adult populations.5-8 Despite extensive use in clinical trials, the meaning of a reduction (ie, improvement) in ADHD-RS-IV scores in response to treatment, with regard to an overall clinical effect, remains unclear.

Global rating scales of disease severity or improvement such as the Clinical Global Impressions-Improvement (CGI-I) and Severity (CGI-S) scales9 are typically more intuitive to clinicians,10 and may better correspond to the global judgments made by clinicians in practice than the item-by-item scores of rating scales. While sometimes adapted for a specific domain of symptoms,11 these scales typically ask clinicians to make a global assessment of function, symptoms, and adverse events (AEs) to rate a patient’s severity of symptoms (ie, CGI-S) and change in symptoms from baseline (ie, CGI-I) based on their experience with the patient population and baseline status, respectively.9 While the psychometric properties of the CGI have not been fully explored, preliminary studies12,13 demonstrate that it is sensitive to differences in treatment responses and possesses good internal consistency and concurrent validity. The CGI scales, however, lack well-defined, consistently applied ADHD-specific anchor points and may not yield consistent results across raters as highlighted by a recent study14 in which clinicians differed considerably in which factors (eg, side effects) they considered when determining a CGI rating.10,14,15

Given the widespread use of the CGI in clinical trials and the potential that such a global assessment of patients may be more contextually applicable and generally understandable to clinicians,10 several analyses have explored the relationship between disorder-specific psychiatric rating scales commonly used in trials (eg, the Positive and Negative Syndrome Scale, the Panic Disorder Severity Scale, and the Brief Psychiatric Rating Scale) and scores on the CGI.16-19 Such analyses typically use the equipercentile linking technique described by Kolen and Brennan.20

The goal of this analysis was to use the equipercentile linking technique to better understand the relationship between scores on the ADHD-RS-IV and scores on the CGI using data from pivotal clinical trials of lisdexamfetamine dimesylate (LDX) in adults and children with ADHD.21,22 LDX is the first long-acting prodrug stimulant and is indicated in the United States for the treatment of ADHD in children 6–12 years of age and in adults. LDX is a therapeutically inactive molecule. After oral ingestion, LDX is converted to l-lysine and active d-amphetamine, which is responsible for the therapeutic effect.23,24



Data Sources

This analysis was conducted using data from two pivotal trials of LDX, one in adults21 and one in children22 with ADHD. Complete descriptions of both studies have been published previously. Briefly, both studies were 4-week, randomized, double-blind, placebo-controlled, forced-dose escalation, parallel-group trials. In the adult trial, subjects were 18–55 years of age, while in the pediatric trial, subjects were 6–12 years of age. In both trials, subjects had to meet DSM-IV-TR25 diagnostic criteria for a primary diagnosis of ADHD and were excluded from the trial if they had a comorbid psychiatric diagnosis with significant symptoms, any medical condition that could interfere with the study or increase risk to the subject, history of seizures (excluding febrile seizures), tic disorder, or Tourette’s disorder. Additional exclusion criteria included any cardiac abnormality that may affect cardiac performance, a clinically significant electrocardiogram or laboratory abnormality, hypertension, pregnancy, lactation, and concomitant use of any medication with central nervous system or blood pressure effects (excluding ADHD treatments, which were washed out). Adults were required to have baseline ADHD-RS-IV total scores of at least 28 assessed using NYU/MGH adult prompts, and children were required to have ADHD-RS-IV total scores of at least 28 at baseline.

Each study began with a screening and washout period during which ADHD medications were discontinued. At the baseline visit, adult subjects were randomized to receive once-daily LDX 30, 50, or 70 mg or placebo for 4 weeks in a 2:2:2:1 ratio. In the pediatric trial, subjects were randomized 1:1:1:1 to placebo or once-daily doses of LDX 30, 50, or 70 mg. Subjects followed a forced-dose titration schedule with those randomized to receive 70 mg/day being titrated to that dose over 2 weeks.



In the pediatric study,22 the primary efficacy measure was the ADHD-RS-IV; in the adult study21 it was the ADHD-RS-IV with adult prompts. In both trials, the ADHD-RS-IV was administered by experienced investigators at each study visit. Whereas the ADHD-RS-IV was originally designed to assess a patient’s behavior over a period of 6 months,1 in these trials it was used to capture behavior over the preceding week. Each item on the 18-item measure is scored on a 4-point scale ranging from 0 (no symptoms) to 3 (severe symptoms), yielding a possible total score of 0–54. Both versions of the scale assess the 18 DSM-IV diagnostic criteria for ADHD, but the individual items are phrased slightly differently. For example, in the pediatric trial, one item asked raters to evaluate if subjects had “difficulty sustaining attention in tasks or play activities.” In the adult trial, the analogous item asked whether the subject had “difficulty sustaining attention in tasks or fun activities.”

The CGI scale was a secondary efficacy measure in both trials. At the baseline visit, clinicians completed the CGI-S and were asked to evaluate the severity of subjects’ illness with respect to ADHD symptoms based on the clinician’s experience with this particular population. Possible scores ranged from 1 (normal, not ill at all) to 7 (among the most extremely ill subjects). At all subsequent study visits, clinicians used the CGI-I to rate the subjects’ total improvement based on comparison with their baseline assessment from 1 (very much improved) to 7 (very much worse).


Statistical Analysis

The procedure for finding corresponding scores on different measurement instruments is called linking.26 Equating procedures, originally described as a method intended to provide interchangeable scores, are the strongest form of linking and can be performed on parallel, yet distinct scales, as in the present analysis. When used in such a manner, the results lead to scores that are not necessarily interchangeable but, rather, are concordant.26,27

The present trial used the equipercentile linking technique detailed by Kolen and Brennan20 at two time points (baseline and endpoint) in each LDX clinical trial to derive percentile rankings of baseline scores on the ADHD-RS-IV and CGI-S ratings as well as endpoint change scores on the ADHD-RS-IV and CGI-I ratings, and to identify scores at each time point in each study that had the same percentile rank. The equipercentile linking technique is not a comparison by subject, where the absolute score on the CGI is compared with the absolute score on the ADHD-RS-IV. Rather, equipercentile linking is a technique that identifies scores on two measures that have the same percentile rank (irrespective of which subjects had particular scores on either measure). So, for every score on one scale, there is a corresponding score on the other scale that has the same percentile rank. Percentile rank functions are calculated for both the ADHD-RS-IV and CGI in the present analysis.

Analyses were performed to compare baseline ADHD-RS-IV scores with CGI-S scores as well as the absolute change and percentage change from baseline in ADHD-RS-IV scores with CGI-I scores. The process of equipercentile linking begins with the calculation of percentile rank function for each variable. A graph is then generated using a score on one measure and the score on the other as the X and Y variables for each point, based on each having the same percentile rank.20 For example, if on Measure 1, 50% of subjects score X or below while on Measure 2, 50% score Y or below; the point X,Y is plotted on a new graph. The X and Y axes are the respective measure scores, not the percentiles. Similar points are generated for each matched percentile ranking, and the resulting line is the equipercentile link function.

Although scores on the CGI scales are discrete, the equipercentile link function is continuous. Therefore, for this analysis, CGI levels are understood to encompass a range. For example, a CGI-S level of markedly ill (a score of 5 on the scale) is equivalent to any score from 4.5–5.5, rather than simply 5. Similarly, CGI-S scores of 2.5–4.5 represent mildly ill (3) to moderately ill (4), 4.5–5.5 represent markedly ill (5), and scores >5.5 represent severely ill (6) to extremely ill (7). On a continuous plot of the CGI-I scale, scores <2.5 represent very much (1) to much (2) improved while scores ranging from 2.5–3.5 represent minimally improved (3), and those >3.5 signify no change (4) or a worsening (5, 6, or 7) compared with the baseline assessment.

Analyses were conducted on the intention-to-treat (ITT) populations of both trials, defined as all subjects randomized to receive treatment who had both a baseline and at least one post randomization ADHD-RS-IV total score available. For all analyses, endpoint was defined as the last post randomization treatment week for which a valid ADHD-RS-IV and CGI-I score was obtained. Only subjects with ADHD-RS-IV scores and CGI-I ratings at endpoint were included in the analysis. Additional analyses by gender were conducted to assess whether there were differences between male and female subjects in link analysis of ADHD-RS-IV scores and CGI ratings.



The demographic and baseline characteristics of the pediatric and adult study populations have been detailed in publications by Biederman and colleagues22 and Adler and colleagues,21 respectively. The treatment groups within each study were generally well matched at baseline. The ITT populations of the trials consisted of 285 children (213 randomized to receive LDX and 72 randomized to receive placebo) and 414 adults (352 randomized to receive LDX and 62 randomized to receive placebo).

As previously reported, significant treatment effects were observed in the primary efficacy measure, the mean change from baseline to endpoint in ADHD-RS-IV total scores compared with placebo for all LDX doses (adult and pediatric studies, P<.0001; Figure 1).21,22 The proportion of subjects with a CGI-I score of 1 (much improved) or 2 (very much improved) at endpoint was significantly higher in all LDX treatment groups compared with the respective placebo groups (adult study P<.01; pediatric study, P<.0001). Among patients receiving LDX, AEs were generally mild or moderate in severity and typical of those observed in trials of other amphetamine-based ADHD treatments. The most common AEs associated with LDX in children included decreased appetite, insomnia, abdominal pain, and irritability, and in adults included dry mouth, decreased appetite, and insomnia.


Linking ADHD-RS-IV Total Scores and CGI-S Levels

The summary statistics for baseline ADHD-RS-IV total scores by baseline CGI-S levels from both studies are presented in Table 1. In the adult study, mean (SD) ADHD-RS-IV scores of 36.2 (4.9), 42.1 (6.1), 45.4 (5.1), and 53.0 corresponded with CGI-S scores of 4 (moderately ill), 5 (markedly ill), 6 (severely ill), and 7 (extremely ill), respectively. It should be noted that these statistics include one subject who had an ADHD-RS-IV total score of 14 (and a CGI-S of markedly ill) at baseline. This subject had an ADHD-RS-IV total score of 35 at screening and 34 after 1 week of treatment. In the pediatric study, mean (SD) ADHD-RS-IV scores of 28.0, 38.7 (6.3), 45.5 (5.8), 48.2 (4.1), and 50.5 (4.0) corresponded with CGI-S scores of 3 (mildly ill), 4 (moderately ill), 5 (markedly ill), 6 (severely ill), and 7 (extremely ill), respectively. Also included in Table 1 are the ADHD-RS-IV quartile scores corresponding to each CGI-S level and the range of ADHD-RS-IV scores corresponding to each CGI-S level that were used in creating the equipercentile link function.


The equipercentile link function for CGI-S and ADHD-RS-IV baseline scores are presented in Figure 2. Data from the adult study demonstrated that a change in the baseline ADHD-RS-IV score of ~8–10 corresponded to a change of 1 in CGI-S level (Figure 2A). Based on the link function from the adult study, baseline ADHD-RS-IV scores ranging from 13.5–37.4 are expected to correspond to CGI-S levels of mildly to moderately ill. Scores ranging from 37.5–48.3 and from 48.4–54.5 corresponded to CGI-S ratings of markedly ill and severely to extremely ill, respectively (Table 2).


Similar to the adult study, the equipercentile link function for CGI-S and ADHD-RS-IV baseline scores derived from the pediatric study also demonstrated that a change in the baseline ADHD-RS-IV score of ~8–10 corresponded to a change of 1 in CGI-S score (Figure 2B). In addition, based on the equipercentile link function, in children a baseline ADHD-RS-IV score of 28.2–41.2 is expected to correspond to a CGI-S level of mildly or moderately ill; an ADHD-RS-IV score of 41.3–50.7 to a CGI-S level of markedly ill; and an ADHD-RS-IV score of 50.8–54.5 corresponded to a CGI-S level of severely to extremely ill (Table 2).


Linking ADHD-RS-IV Total Score Changes From Baseline and CGI-I Levels

The CGI-I levels at endpoint and the corresponding absolute change from baseline to endpoint in ADHD-RS-IV total score are presented in Table 3. In the adult trial, 317 patients were rated improved by CGI-I at endpoint while 97 were rated as no change or worse. Of the 317 adults who improved with treatment, CGI-I scores of 1 (very much improved), 2 (much improved), and 3 (minimally improved) corresponded with mean (SD) changes from baseline in ADHD-RS-IV total scores of -30.4 (7.8), -20.6 (7.2), and -11.2 (5.9), respectively. Adults assessed by CGI-I at endpoint as exhibiting no change demonstrated a mean (SD) change in ADHD-RS-IV total score of -2.1 (3.8).


In the pediatric trial, as assessed by the CGI-I, 217 children showed improvement with treatment while 68 showed no change or worse. Of the children demonstrating improvement, the mean (SD) change from baseline in ADHD-RS-IV scores at endpoint were -33.2 (9.3), -25.5 (7.2), and -9.9 (6.8) for subjects with CGI-I scores of 1 (very much improved), 2 (much improved), and 3 (minimally improved), respectively.

The graph of the equipercentile link function in Figure 3 shows the relationship between CGI-I levels at endpoint and the absolute change from baseline to endpoint in ADHD-RS-IV scores derived from the adult study (Figure 3A) and the pediatric study (Figure 3B). Both graphs indicate that a change from baseline to endpoint in ADHD-RS-IV total score of roughly 10–15 corresponded to a change of 1 in CGI-I score at endpoint.


Based on the above link function, a change from baseline to endpoint in ADHD-RS-IV score of -13.6 to -49.5 corresponded to a CGI-I level at endpoint of much improved or very much improved in adults. Using the link function from the pediatric study, an improvement in ADHD-RS-IV total scores from baseline at endpoint of -17.3 to -50.5 would have been expected to result in a CGI-I score of 2 or 1 (ie, much improved or very much improved) among children. Additional ranges of ADHD-RS-IV scores and their corresponding CGI-I levels are presented in Table 4. In the pivotal trials included in the present analysis, the mean ADHD-RS-IV total score change from baseline at endpoint associated with LDX treatment ranged from -16.2 to -18.6 in the adult study and -21.8 to -26.7 in the pediatric study. According to the link function, these mean scores corresponded to a CGI-I level of much improved.


When the equipercentile link function was carried out for CGI-I scores at endpoint and the percent change from baseline at endpoint in ADHD-RS-IV, CGI-I scores of 1, 2, and 3 (very much improved, much improved, and minimally improved) roughly corresponded to percent changes in ADHD-RS-IV scores of -80% and -80%, -48%, and -52%, and -25% and -27% (adult and pediatric studies, respectively; Figure 4). A percent change from baseline to endpoint in ADHD-RS-IV total score of ~25% to 30% corresponded to a change of 1 in CGI-I score at endpoint. Therefore, an improvement in ADHD-RS-IV score of ~50% to 60% and >75% is needed to achieve a rating of much improved and very much improved, respectively.


Post hoc analyses found no gender differences in linking ADHD-RS-IV and CGI in relation to either baseline severity or change from baseline at endpoint.



In this analysis, the linking between CGI levels and ADHD-RS-IV scores was established using the equipercentile link function and was based on LDX trial data from adults and children with ADHD. To the authors’ knowledge, this is the first time a reliable and valid ADHD-specific rating scale,7,8 the ADHD-RS-IV, has been linked to a clinically meaningful global assessment such as the CGI. This analysis generated three sets of link functions, each containing one linkage for adult subjects and one for pediatric subjects with ADHD. For all three pairs of linkages, the relationship between ADHD-RS-IV scores and CGI levels were consistent across the age groups. This is noteworthy because ADHD symptoms are often variable across the life span and the goals of treatment may be distinct in adults compared with children.28 Such a consistent relationship between the ADHD-RS-IV and CGI across age groups, however, should allow for a valid and consistent means of treatment titration even as children grow into adulthood.

The ability to link ADHD-RS-IV score changes to global improvements as assessed by the CGI-I has several implications for the interpretation of clinical trial results. For example, absolute changes in ADHD-RS-IV scores associated with a given treatment should be interpreted with the understanding that an absolute change of ~10–15 is required to be detected as a change of 1 level on the CGI-I. Clinicians may find such global assessments more clinically useful than reports of mean changes in rating scale scores compared with placebo, the measure usually reported in clinical trials, to understand the likely impact of a treatment on their patients. Furthermore, given that clinicians may not routinely use rating scales such as the ADHD-RS-IV, these results facilitate interpretation of the results of trials of ADHD treatments by healthcare providers and patients because more widely used and readily understood clinical terms may be applied to ADHD-RS-IV scores.

Based on this analysis, a clinically detectable response to treatment, that is, a change in CGI-I score of at least 1 level, requires at least a 25% to 30% change in ADHD-RS-IV score. Historically, clinical trials have often used a 25% to 30% reduction in symptoms as assessed by the ADHD-RS-IV as a threshold for response.29 Interestingly, this threshold has not been fully substantiated by statistical support for the adequacy of this cutoff. Clinical trials have also defined response as a global rating of much or very much improved. The results of this analysis suggest that these two definitions of response are not concordant and that the benchmark of a 25% to 30% reduction in symptoms as a barometer of efficacy, while satisfactory, may not be optimal for future development of useful treatments for ADHD. This also raises the possibility that more stringent criteria, perhaps a 50% reduction in ADHD-RS-IV total score, might be considered as a new standard for response in clinical trials.

The results of the present analysis should be viewed in light of several limitations. Although the results obtained from the adult and pediatric trial were similar, it should be noted that the versions of the ADHD-RS-IV used in these trials were not identical. In the adult study, the ADHD-RS-IV was a semistructured scale and used adult ADHD prompts,5 whereas the pediatric scale was a more structured assessment. In both trials, the scoring of the CGI and ADHD-RS-IV were not independent since they were completed by the same investigator based on behavior observed and reported during the same study visit. Because neither trial included adolescent patients, relationship between ADHD-RS-IV scores and CGI levels in that population remains unknown.

The present analysis contains both potential ceiling and floor effects. The CGI-S was only assessed at baseline, at which point subjects were required to have ADHD-RS-IV scores of ≥28. The lack of CGI-S scores available at endpoint precludes the establishment of a threshold for normalization. Relatively few subjects represented the low and high ends of the ADHD-RS-IV and CGI scales, which likely accounts for the abrupt changes observed in the slopes of the equipercentile link function showing the relationship between ADHD-RS-IV scores at baseline and CGI-S levels (Figures 2A and 2B). For example, only one patient in the adult study had a CGI-S score of 7 and none had a CGI-S score of 3; in the pediatric trial, only one subject was assessed as mildly ill (ie, CGI-S score of 3) and four were assessed as being extremely ill (ie, CGI-S score of 7).

The data from the present analysis originated from two studies with very similar methodologies and included data from ~700 subjects with ADHD. As pivotal trials, both studies had rigorous inclusion and exclusion criteria such as the exclusion of subjects with most medical and psychiatric comorbidities. Such limitations result in a patient population distinct from that seen in clinical practice and may limit generalization of the present results to broader patient populations. Additional analyses using similar methods across other data sets should attempt to confirm and extend these findings, perhaps providing data at the ends of the scales or demonstrating that these findings are similar in other patient populations.



Clinical studies of ADHD often employ rating scales to assess symptom improvement associated with a given treatment. Such measures, while psychometrically sound, are less intuitive and may be assessed by clinicians less frequently than global assessments of improvement since it is often unclear how much of a change in symptom-based scores corresponds to a change that can be observed clinically. In this preliminary analysis, ADHD-RS-IV scores were linked to CGI ratings using the equipercentile linking technique and produced results that were consistent between children and adults. A change of ~10–15 points in ADHD-RS-IV score corresponded to a change of 1 level in CGI-I rating. When analyzed by percent change, each change of ~25% to 30% in ADHD-RS-IV score resulted in a 1 level change in CGI-I. These results may further the clinical understanding of severity levels and change scores on the ADHD-RS-IV and suggest new thresholds for defining clinical response when evaluating ADHD treatments.  PP


1.    DuPaul GJ, Power TJ, Anastopoulos AD, Reid R. ADHD Rating Scale–IV: Checklists, Norms, and Clinical Interpretation. New York, NY; Guilford Press; 1998.
2.    Spencer TJ, Wilens TE, Biederman J, Weisler RH, Read SC, Pratt R. Efficacy and safety of mixed amphetamine salts extended release (Adderall XR) in the management of attention-deficit/hyperactivity disorder in adolescent patients: a 4-week, randomized, double-blind, placebo-controlled, parallel-group study. Clin Ther. 2006;28(2):266-279.
3.    Collett BR, Ohan JL, Myers KM. Ten-year review of rating scales. V: scales assessing attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2003;42(9):1015-1037.
4.    Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
5.    Adler L, Cohen J. Diagnosis and evaluation of adults with attention-deficit/hyperactivity disorder. Psychiatr Clin North Am. 2004;27(2):187-201.
6.    Weisler RH, Biederman J, Spencer TJ, et al. Mixed amphetamine salts extended-release in the treatment of adult ADHD: a randomized, controlled trial. CNS Spectr. 2006;11(8):625-639.
7.    Spencer TJ, Adler LA, Qiao M, et al. Validation of the Adult ADHD Investigator Symptom Rating Scale (AISRS). J Atten Disord. 2009 Sep 30. [Epub ahead of print].
8.    Adler LA, Spencer TJ, Biederman J, et al. The internal consistency and validity of the Attention-Deficit/Hyperactivity Disorder Rating Scale (ADHD-RS) with adult ADHD prompts as assessed during a clinical treatment trial. J ADHD Relate Disord. 2009;1(1):14-24.
9.    Guy W. Clinical global impressions. In: ECDEU Assessment Manual for Psychopharmacology. Rockville, MD: US Department of Health, Education, and Welfare; Public Health Service, Alcohol, Drug Abuse and Mental Health Administration, NIMH Psychopharmacology Research Branch; 1976;218-222.
10.    Nierenberg AA, DeCecco LM. Definitions of antidepressant treatment response, remission, nonresponse, partial response, and other relevant outcomes: a focus on treatment-resistant depression. J Clin Psychiatry. 2001;62(suppl 16):5-9.
11.    Huber CG, Lambert M, Naber D, et al. Validation of a Clinical Global Impression Scale for Aggression (CGI-A) in a sample of 558 psychiatric patients. Schizophr Res. 2008;100(1-3):342-348.
12.    Leon AC, Shear MK, Klerman GL, Portera L, Rosenbaum JF, Goldenberg I. A comparison of symptom determinants of patient and clinician global ratings in patients with panic disorder and depression.
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13.    Leucht S, Engel RR. The relative sensitivity of the Clinical Global Impressions Scale and the Brief Psychiatric Rating Scale in antipsychotic drug trials. Neuropsychopharmacology. 2006;31(2):406-412.
14.    Busner J, Targum SD, Miller DS. The Clinical Global Impressions scale: errors in understanding and use. Compr Psychiatry. 2009;50(3):257-262.
15.    Kadouri A, Corruble E, Falissard B. The improved Clinical Global Impression Scale (iCGI): development and validation in depression. BMC Psychiatry. 2007;7:7.
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19.    Furukawa TA, Shear KM, Barlow DH, et al. Evidence-based guidelines for interpretation of the Panic Disorder Severity Scale. Depress Anxiety. 2009;26(10):922-929.
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d-amphetamine. Poster presented at: the 49th Annual Meeting of the New Clinical Drug Evaluation Unit; June 29-July 2, 2009; Hollywood, FL.
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Dr. Bastiaens is Clinical Associate Professor of Psychiatry at the University of Pittsburgh in Pennsylvania.

Disclosure: Dr. Bastiaens reports no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Leo Bastiaens, MD, Clinical Associate Professor of Psychiatry, University of Pittsburgh, 33 Sunnyhill Drive, Pittsburgh, PA 15228; Tel: 412-343-6871; Fax: 724-335-2867; E-mail: bastiaensl@aol.com.



Introduction: Experts’ recommendations to implement measurement-based treatment in the community raise many questions about the feasibility and effectiveness of this practice.
Methods: This study used a case-controlled retrospective chart review of 60 patients with chronic schizophrenia to investigate the impact of an abbreviated symptom rating scale (Positive and Negative Symptom Scale [PANSS]) on several outcome measures during 1 year.
Results: Compared to treatment-as-usual, the use of the abbreviated PANSS had no impact on numerous outcome measures, such as the number of prescribed medications, number of hospitalizations, or patient’s global level of functioning.
Conclusion: Measurement-based practice in community clinics may not be effective unless accompanied by other changes, such as the ability of psychiatrists to spend more time with their patients.

Focus Points

• Based on large-scale treatment studies, such as the Clinical Antipsychotic Trials for Interventions Effectiveness, experts are recommending the implementation of measurement-based practice in the community.
• This recommendation raises questions about the feasibility and effectiveness of this practice.
• This study used an abbreviated Positive and Negative Symptom Scale in the care of 60 patients with schizophrenia during 1 year.
• The use of the rating scale did not appear to influence outcome measures, such as level of functioning, number of hospitalizations, or number of prescribed medications.
• Measurement-based practice in the community may need to be accompanied by other changes to become effective.



Recently, large-scale treatment studies in depression (Sequenced Treatment Alternatives to Relieve Depression), bipolar disorder (Systematic Treatment Enhancement Program for Bipolar Disorder), and schizophrenia (Clinical Antipsychotic Trials for Interventions Effectiveness) have been completed. Many reports, detailing their results, have been published.1-3 At times, it has been difficult to translate findings from these projects into concrete guidelines for practitioners. However, as the result of these studies, one of the most frequent recommendations made is the need to bring measurement-based practice into the real world.4 Basing treatment decisions on actual symptom rating scales, rather than global impressions, is believed to be more efficient and effective.

A general recommendation to use measurement-based practice in the real world, based upon the above studies, provokes several questions. Are these studies truly representative of the real world? Is it feasible to employ similar instruments in busy community clinics? Is measurement-based practice effective for all the different diseases studied?

Because the answer to these questions is not yet available, it is problematic that some intermediaries, for example insurance companies, have started to put pressure on psychiatrists to use algorithms and rating scales in community clinics,5 without taking the realities of these clinics into account. These include providing care for a large number of severely ill patients, who have significant psychosocial adversity; infrequent 10–15-minute follow-up visits; few support staff; and little time to document encounters. Most importantly, it is not clear if patients are better served with the use of specific symptom rating scales. This article reports on the use of a rating scale during the treatment of patients with schizophrenia in a community clinic.

The largest source of information regarding the implementation of measurements during clinical care of schizophrenia comes from the Texas Medication Algorithm Project.6 The specifics of this state-wide project are well known and are available online.7 Research coordinators, available on site, administered the rating scales and provided feedback to the treating physicians, who followed the antipsychotic algorithm. Published results8 appear to be quite modest; the group of patients with schizophrenia who received the measurement-based practice did not differ on positive and negative symptoms after 12 months, compared to the treatment-as-usual group, although a sustained improvement in cognitive functioning was noted.

Other attempts have been made to introduce evidence-based decisions into routine clinical care.9,10 Clearly, much effort is involved in the realization of these practice improvements.10 While fidelity to the originally developed algorithm is important,11 it is problematic that many algorithms do not discuss very specific guidelines, such as response criteria.12 Thus, for individual practitioners in the community, questions regarding feasibility and effectiveness remain.

The use of a rating scale in the treatment of patients with schizophrenia in a community mental health clinic is documented in this article. It was a quality improvement project in the care of chronic patients. A retrospective case-controlled chart review was used to examine the impact of an abbreviated version of the Positive and Negative Symptom Scale (PANSS)13 on several outcomes, such as the amount of medications used in the treatment, number of hospitalizations, and patient’s level of functioning. If measurement-based practice, that is feasible within the constraints of a community clinic, is effective in schizophrenia, one would expect certain outcomes such as fewer hospitalizations, fewer medications used, and better level of functioning.



Patients with chronic schizophrenia or schizoaffective disorder, who were followed in the same clinic between March 2007 and February 2009, were eligible to be included. Patients were seen by a psychiatrist every 2–3 months, in brief medication management visits. Since March 2008, all patients, during every psychiatric visit, were evaluated with a much abbreviated version of the PANSS. Three positive PANSS items (hallucinatory behavior, delusions, conceptual disorganization) and three negative PANSS items (blunted affect, poor rapport, emotional withdrawal) were rated on a scale from one to seven (1=absent, 2=minimal, 3=mild, 4=moderate, 5=moderately severe, 6=severe, 7=extreme).

The positive items represent the most common positive symptoms in schizophrenia (hallucinations, delusions, and thought disorder). The negative items were chosen based on their observability within the patient-physician encounter.

Pharmacotherapy was based on clinical grounds, incorporating all relevant information provided during the visit by patient, family, and case managers. Since March 2008, the abbreviated PANSS was part of this clinical process. No specific guidelines were used to change the pharmacotherapeutic regimen based on the abbreviated PANSS rating. Rather, the use of the rating scale was meant to provide a more comprehensive assessment of pertinent positive and negative symptoms, compared to a treatment-as-usual situation. Also, no specific medication algorithm was used, since all subjects were chronic patients who had an extensive past history of multiple antipsychotic trials.

The study employed a retrospective chart review and compared, for each patient, the period of March 2007 until February 2008 (year 1) when no PANSS ratings were performed, with the period of March 2008 until February 2009 (year 2) when the abbreviated PANSS ratings were performed during every visit. The following data were extracted from the clinic’s electronic record system: age; gender; race; Global Assessment of Functioning (GAF) scale and number of total psychiatric medications (antipsychotics, antidepressants, benzodiazepines, etc.) in the beginning of year 1 and year 2, and at the end of year 2; number of changes in all psychiatric medications made during the two periods (dose and actual medication changes); number of visits in each period; number of hospitalizations in each period; other treatments added and/or deleted in each period (case management, partial programs, etc); and the abbreviated PANSS scores in the beginning and end of year 2. Students’ t-tests for continuous measures and Chi Square tests for categorical measures were used.



Sixty patients (30 males, 30 females) were included. Fifty-two patients were white and the remaining eight were black. Their average age was 49.2±11.1 years. All patients suffered from schizophrenia or schizoaffective disorder and had been followed for many years in the clinic.

At the beginning of year 1, 16 patients were taking clozapine, 49 were taking another atypical, and 6 patients were taking a typical antipsychotic. Three patients were not taking any antipsychotic, 14 patients were taking a combination of antipsychotics, and six patients were on long-acting injectables. Many patients were taking other psychiatric medications as well.

In the first year, patients had an average of 4.8±2.4 visits. They started out taking an average of 2.8±1.5 psychiatric medications and ended the first year on an average of 2.9±1.6 psychiatric medications. Medications were changed 2.5±3.8 times. An average of 0.17±0.4 other treatments was added, while 0.15±0.4 treatments were deleted. The GAF decreased slightly from 47.4±8.3 to 47±9.4. Four patients were hospitalized during the first year.

In the second year, patients had 4.6±2.2 visits. The amount of prescribed psychiatric medications did not change significantly from 2.9±1.6 to 2.8±1.5 (P=.773). Medication changes happened 2.3±3.0 times in the second year. An average of 0.4±1.4 other treatments was added, while 0.2±0.6 treatments were deleted. The GAF increased slightly from 47.0±9.4 to 49.5±8.3 (P=.133). Six patients were hospitalized in the second year (two patients were admitted twice; P>.5). Antipsychotic poly-pharmacy did not change.

The abbreviated PANSS rating scale decreased from 12.2±5.1 to 9.8±3.4 (P=.003) during the second year.

None of the differences in primary outcomes, level of functioning, number of medications, or hospitalizations between year 1 and year 2 were statistically significant. The Figure visualizes several of the outcome measures.



In this 2-year follow-up of 60 patients with schizophrenia or schizoaffective disorder, the use of a specific rating scale to measure symptomatology, added to the ongoing pre-existing clinical care, did not appear to make a difference in certain outcome measures, such as the number of hospitalizations, intensity of treatment, utilization of pharmacotherapy, or level of functioning.

The results need to be viewed in light of the study’s limitations: small sample size, naturalistic design, abbreviated rating scale, and relatively brief period of follow-up. However, this study is probably representative of the manner in which patients with schizophrenia are treated in the community in the United States.

Some characteristics of the patients and the study may have limited the possibility to find an impact of this measurement-based practice. Patients were relatively stable. This was evidenced by their high GAF score and the low number of medications used in their treatment. Their stability may have limited the impact of measuring their symptomatology to guide changes in their treatment.

The abbreviated rating scale may not have captured enough symptoms or more crucial symptoms to show an impact on patients’ level of functioning. However, longer rating scales may not be feasible on a routine basis in a community clinic. The fact that no guidelines were used on how to adjust medications, based on the score of the rating scale, may have limited the psychiatrist’s ability to intervene appropriately. However, it is not clear what guidelines would be used in a very chronic patient population with multiple past antipsychotic trials.

A major limitation to clinical care and the use of more sophisticated measurements is the limited time available, in community clinics, for psychiatrists to spend with their patients (in the Texas Medication Algorithm Project, physicians were supported by on-site research coordinators). In this regard, the use of an abbreviated measurement may not add any value to the patient’s care since no time is available to adequately investigate the meaning of the changes in the rating scale. Also, follow-up, in terms of frequency and length of psychiatric visits, may not be adequate. This may explain the slight increase in hospitalizations and other treatments in the second year of this study, possibly in response to changes in the abbreviated PANSS, while medications, prescribed by a psychiatrist, did not change.



Thus, it appears that making a recommendation for measurement-based treatment of schizophrenia in the community needs to be preceded by investigations into the necessary changes that need to accompany this practice.14,15 These changes could include training physicians in the use of validated rating scales, recommending specific treatment changes (optimization, switching, augmentation) based upon specific response criteria, developing guidelines for patients who do not fit into existing algorithms (eg, patients who refuse treatment with clozapine, patients on long-acting injectable antipsychotics with insufficient response), and developing regional networks to standardize treatments (so that patients who go from one treatment setting to another receive the same algorithmic treatment). In order for patients to benefit, more frequent visits, longer visits, and higher reimbursement for psychiatric services, may be necessary as well.  PP



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