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Issue 71, Mar 2018
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Is intranasal esketamine effective for difficult-to-treat depression?

Daly et al. Efficacy and Safety of Intranasal Esketamine Adjunctive to Oral Antidepressant Therapy in Treatment-Resistant Depression: A Randomized Clinical Trial. JAMA Psychiatry. 2018 Feb 1;75(2):139-148. PubMed PMID: 29282469.

Background

About one-third of patients with major depressive disorder don’t respond adequately to antidepressant medications that are currently available.

In recent years, there has been a lot of interest in the use of intravenous ketamine for the treatment of major depressive disorder that has failed to respond to antidepressant medications. But, large-scale use of intravenous ketamine is impractical.

What is esketamine? It is an enantiomer of ketamine. What this means is that ketamine is a mixture of S-ketamine (esketamine) and R-ketamine (arketamine), molecules that are identical in composition but mirror images of each other. S-ketamine has higher affinity for the NMDA receptor than R-ketamine.

Intranasal esketamine is being developed as a potential treatment for major depressive disorder.

This is the first clinical trial of intranasal esketamine for “treatment-resistant depression.”

It aimed to assess the efficacy, safety, and dose-response of intranasal esketamine in these patients.

Methods

This was a phase 2, double-blind, multicenter, randomized, placebo-controlled clinical trial.

Sixty-seven adults with a diagnosis of major depressive disorder and a history of an inadequate response to two or more antidepressant medications were enrolled. But it should be noted that in the current episode an “inadequate response” to only one antidepressant was required to be eligible for participation.

Exclusion criteria included “recent or current suicidal ideation with intent to act.”

Double-blind treatment with intranasal ketamine or placebo was administered for two one-week periods. Then, optional open-label treatment was given for another 60 days.

In the first seven-day treatment period, participants were randomized to receive intranasal esketamine or a matching placebo. Those who received esketamine received 28 mg, 56 mg, or 84 mg twice a week. The 56 mg and 84 mg doses achieve plasma esketamine levels equivalent in effect to giving 0.5 mg/Kg of ketamine intravenously, which is the typical dose of ketamine recommended for persons with major depression.

In the second seven-day treatment period, of those who had received placebo, only those who continued to have moderate-to-severe symptoms were again randomized to either receiving intranasal esketamine (28 mg, 56 mg, or 84 mg twice a week) or to continuing on placebo. Note that this means that those who responded well in the first period were eliminated from continuing in the study, which is advantageous to demonstrating the efficacy of esketamine.

Throughout the study, all participants continued to also take the antidepressant they had been on prior to entering the study.

After the two-week double-blind phase, participants received open-label, intranasal ketamine at a lower frequency—once a week and then once every two weeks.

Results

Sixty-seven participants (38 women, mean age 45 years) were included.

Combining both seven-day periods of double blind treatment, participants receiving any of the three doses of esketamine (28 mg/ 56 mg/ 84 mg twice a week) had a statistically significantly greater reduction in the severity of depression.

The average reduction in the total score on the Montgomery-Asberg Depression Rating Scale total score was 4, 6, and 9 points in the 28 mg, 56 mg, and 84 mg esketamine groups. This dose-response relationship was statistically significant.

When the frequency of dosing was reduced from twice a week to once a week in the open-label phase, the improvement in depression was sustained.

Adverse events are poorly described in the paper but are fully described in the online supplement for the paper. The commonest adverse events that occurred in more than 10% of patients and more often than on placebo in each esketamine treatment group are listed below along with the percentage of patients in the highest dose esketamine group who reported it. 

Dizziness 47%

Headache 18%

Dissociation 24%

Nausea 24%

“Dissociative disorder” 24%

Oral hypoesthesia 12%

The reason that “dissociation” and “dissociative disorder” are listed separately is that depending on the exact words used by the patient, the adverse events were coded as dissociative disorder or dissociative symptoms.

Perceptual changes and/or dissociative symptoms began soon after intranasal ketamine was taken, peaked after about 30 minutes, and resolved within two hours. Also, the perceptual changes/dissociative symptoms became less severe over time as the patients continued to take intranasal ketamine.

Transient increases in blood pressure were also noted in persons who received esketamine.

Conclusions

The antidepressant effect of intranasal ketamine was rapid in onset and dose related.

The benefit tended to persist even when the frequency of dosing was reduced to once a week.

Clinical Commentary

The term “treatment-resistant depression” is problematic in general and, in my opinion, should not have been used to refer to the participants of this study. In each treatment group, not only a few but the majority of the participants had taken only one antidepressant in the current episode of major depressive disorder. (I also don’t like that this critical information is not given in the paper but only in the online supplement to the paper.) Based on this criterion, a high proportion of patients with major depression would be considered to have “treatment-resistant depression.” The reason I am so concerned about this if this drug gets approved by the FDA, it is likely to be used for “treatment-resistant depression,” so we should be clear what they meant by this term.

Also, the inadequate response to that antidepressant was based on patient self-report and not prospectively determined by giving the patient a trial of an antidepressant as in many other clinical trials. I have been an investigator in clinical trials of treatments for “difficult-to-treat” major depression. Typically, about one-third of participants who say that they did not respond to an antidepressant in the current episode do show a response when another antidepressant is given during the study.

Based on the definition of “treatment-resistant depression” and the exclusion of patients with active suicidal ideation, readers should be clear that this study was using intranasal ketamine to treat a very different population than those treated in the intravenous ketamine studies.

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How to treat apathy in persons with mild Alzheimer's disease

Padala et al. Methylphenidate for Apathy in Community-Dwelling Older Veterans With Mild Alzheimer's Disease: A Double-Blind, Randomized, Placebo-Controlled Trial. Am J Psychiatry. 2018 Feb 1;175(2):159-168.PubMed PMID: 28945120.

Background

Apathy, which means a profound loss of motivation, is the commonest behavioral symptom in persons with Alzheimer's disease.

It includes indifference, disengagement, passivity, and loss of enthusiasm, interest, and empathy.

During follow up over several years, apathy is also one of the most persistent symptoms associated with dementia. This means that if we don’t treat it, it is fairly likely to persist.

Why is apathy important? It is associated with functional impairment, higher service utilization, and higher caregiver burden.

This study aimed to evaluate the effects of methylphenidate on apathy in persons with mild Alzheimer's disease.

Methods

This was a 12-week, double-blind, randomized, placebo-controlled clinical trial.

The participants were veterans with mild Alzheimer’s disease who were living at home.

Apathy was quantified using the Apathy Evaluation Scale-Clinician version. To use this scale, a clinician uses a semi-structured interview to elicit the relevant information from both the patient and a caregiver.

Several other rating scales were used to quantify other clinical variables.

Exclusion criteria included current major depressive disorder.

Methylphenidate was started at 5 mg twice daily and increased after two weeks to 10 mg twice daily.

Results

The participants were 60 men who were 77 years old on average.

Those who received placebo had improvement in apathy during the study. But, those who were randomized to receive methylphenidate had statistically significantly greater improvement in apathy than those who were randomized to the placebo group.

This benefit was noted at the four-week evaluation and was sustained even at the end of the trial, i.e., after 12 weeks of treatment.

The improvement was found in all three domains of the Apathy Evaluation Scale—behavioral, cognitive, and emotional.

Those who were randomized to receive methylphenidate also had greater improvement in cognition, functional status, caregiver burden, Clinical Global Impression scores, and depression than those randomized to receive placebo. But, these benefits were noted only after 12 weeks of treatment.

What about adverse effects?

There was a within-group statistically significant increase in blood pressure at 12 weeks in those who received methylphenidate. But, there was no statistically significant between-group difference in change in pulse, blood pressure, or weight in those who received methylphenidate or placebo.

The frequency of adverse events did not differ between the methylphenidate and placebo groups but it should be noted that one patient who received methylphenidate had a seizure.

Conclusions

Treatment with methylphenidate was associated with improved apathy in a group of community-dwelling veterans with mild Alzheimer's disease.

This treatment was also associated with improvement in cognition, functional status, caregiver burden, Clinical Global Impression scores, and depression.

Clinical Commentary

Considering how prevalent Alzheimer’s disease is, that apathy is the commonest behavioral symptom associated with it, and the significant consequences of apathy, this study has huge practical implications.

We must, of course, make sure that the patient does not have any contraindications to the use of a stimulant.

Since some of the benefits of methylphenidate only emerged around 12 weeks of treatment, methylphenidate for the treatment of apathy in this population should probably be tried for about three months before concluding that it did not work.

Whether methylphenidate will be efficacious for apathy in patients with Alzheimer’s disease of more than mild severity or for apathy associated with dementia due to other etiologies remains to be seen.

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Are Internet use disorder and ADHD closely associated with each other?

Bielefeld et al. Comorbidity of Internet use disorder and attention deficit hyperactivity disorder: Two adult case-control studies. J Behav Addict. 2017 Dec 1;6(4):490-504.

PubMed PMID: 29280392.

Background

Attention-deficit hyperactivity disorder (ADHD) is associated with various addictive disorders.

These include both substance use disorders and so-called behavioral addictions like gambling disorder.

Internet Use Disorder or “internet addiction” is not a condition recognized in DSM-5. Internet Gaming Disorder is a condition identified as requiring further study before it can be included in DSM-5.

This study aimed to investigate the relationship between Internet Use Disorder and ADHD.

Methods

At a University outpatient service, two groups of adults were recruited—those with ADHD and those with Internet Use Disorder. For each of these two groups, a corresponding control group without that disorder was also recruited. In each of these four groups, there were 25 participants (total N = 100).

Detailed clinical and psychometric assessments were conducted on the participants.

Results

Of persons with ADHD, 20% had a comorbid Internet Use Disorder.

Similarly, 28% of persons with Internet Use Disorder had comorbid ADHD.

Not surprisingly, persons with Internet Use Disorder used the Internet for statistically significantly more hours per day than those with ADHD (mean 6.5 hours versus 2.5 hours).

Persons with ADHD group did not differ from their controls in terms of Internet use and playing video games. But, there were two differences in the details:

  • In addition to using video games for relaxation like the controls did, persons with ADHD reported that they used video games for stimulation, to overcome loneliness, and/or for socialization, while none of the controls reported these motivations.
     
  • Compared to their controls, persons with ADHD were significantly more likely to perceive themselves as being addicted to video games.

Persons with Internet Use Disorder were also more likely than their controls to perceive themselves as being addicted to video games.

Also, they were even more likely than persons with ADHD to play video games to avoid boredom and for social interaction rather than for relaxation.

In both groups, ADHD symptoms were positively associated with the amount of time spent using media and with symptoms of Internet addiction.

Conclusions

There is a close association between ADHD and Internet Use Disorder but these patients also differ in some details of the clinical characteristics.

Clinical Commentary

Persons with Internet Use Disorder should be evaluated for possible ADHD and vice versa.

Persons with ADHD should be encouraged to limit their use of the Internet and video games with the aim of reducing the risk of developing Internet Use Disorder. However, as the Authors noted, it is possible that these patients may “shift” from Internet addiction to another addiction.

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Can computers predict whose major depression will be "treatment-resistant"?

Kautzky et al. Refining Prediction in Treatment-Resistant Depression: Results of Machine Learning Analyses in the TRD III Sample. J Clin Psychiatry. 2017 Dec 5;79(1). pii:16m11385. [Epub ahead of print] PubMed PMID: 29228516.

Background

Many demographic and clinical variables have been associated with so-called “treatment-resistant” depression.

This study aimed to use machine learning (a set of computer algorithms) to process a large dataset including 47 clinical and socio-demographic variables believed to predict treatment outcome and generate a prediction model for treatment resistance.

Methods

The dataset contained data on 552 persons with major depressive disorder (MDD).

“Treatment-resistant depression” was defined as a Montgomery-Asberg Depression Rating Scale (MADRS) score of 22 or more despite at least two antidepressant trials of adequate dose and duration.  

Predictors entered into the algorithm included:

  • Sociodemographic variables (age, gender, etc.)
     
  • MDD history (Family history of MDD, number of MDD episodes, etc.)
     
  • Comorbidity (OCD, panic disorder, Young Mania Rating Scale score, etc.)
     
  • Medical comorbidity (Diabetes, Body Mass Index, etc.)
     
  • Clinical features (suicidality, fatigue, psychomotor agitation, etc.)
     
  • Other predictors (social/work/family functioning, etc.)
Results

The accuracy of prediction of “treatment-resistant depression” was 75% for the full model with 47 predictors, and 68% to 71% for an abbreviated model with 15 predictors.

With all 47 predictors, the sensitivity was up to 82%, specificity up to 63%, positive predictive value up to 80%, and negative predictive value up to 68%.

What variables best predicted “treatment-resistant depression”?

  • MADRS score at baseline
  • Functional impairment (family, social, and work life)
  • Time between first and last depressive episode
  • Severity of the illness
  • Suicide risk
  • Age
  • Education and Profession
  • Body Mass Index (BMI)
  • Number of lifetime depressive episodes
  • Lifetime duration of hospitalization.

The variables that were statistically significantly associated with outcome even when correcting for multiple comparisons were: severity of illness, number of depressive episodes, impairment of social functioning, impairment of family functioning, and suicidality.

Conclusions

Using a machine learning algorithm, a prediction model with an accuracy of 75% was developed.

The simplified algorithm of 15 clinical and sociodemographic predictors that can be identified within a few minutes had an accuracy of 68% to 71%.

Clinical Commentary

Machine learning algorithms have started to be used in mental health to take advantage of large datasets. This is one of first few studies applying machine learning to “treatment-resistant depression.”

Before this algorithm can be used more broadly, it will be important to see how well it does when applied to a completely new dataset.

Also, it is not really surprising that a history of more severe illness and illness that has persisted for a longer period of time predict worse outcome in the future. An even more useful algorithm would be one that could help predict poor outcome while the person is still in the early stages of the illness and/or treatment.

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Does the therapeutic relationship matter when prescribing medications?

Totura et al. The Role of the Therapeutic Relationship in Psychopharmacological Treatment Outcomes: A Meta-analytic Review. Psychiatr Serv. 2018 Jan 1;69(1):41-47. PubMed

PMID: 28945182.

Background

Non-adherence is a very important problem in psychopharmacological treatment.

This study aimed to combine the results of all available studies on the association between the therapeutic relationship and the effectiveness of psychopharmacological treatment.

Methods

A detailed search of the literature was conducted to identify relevant studies.

Meta-analysis was used to combine the results of these studies.

Results

Eight studies with a total of 1065 participants were included in the analysis.

The therapeutic alliance was assessed in these studies by using a variety of rating scales.

There was a statistically significant association between the therapeutic relationship and outcome of psychopharmacological treatment. The weighted effect size for this association was Fisher’s z=0.30. This indicates a moderate effect size for the correlation and is similar to the effect size found in psychotherapy studies.

Conclusions

The results of this analysis suggest that a positive therapeutic relationship between the clinician and the patient is associated with greater improvement during psychopharmacological treatment.

Clinical Commentary

It is important for clinicians to remember that a positive therapeutic relationship is important not only in psychotherapy but also in psychopharmacology.

Future studies should clarify whether the therapeutic relationship is associated with the outcome of psychopharmacological treatment by enhancing the placebo effect, improving adherence to medications, or through other mechanisms as well.

They should also clarify whether the effects of the therapeutic relationship are different in different types of patients and for different types of medications.

Last, but not least, I hope that future studies will also explore what exactly clinicians can do to enhance this relationship specifically with reference to psychopharmacology. 

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Rajnish Mago, MD
Medical Editor, GME Research Review

GME Research Review is a monthly newsletter edited by Rajnish Mago, MD, who is author of "The Latest Antidepressants" and "Side Effects of Psychiatric Medications: Prevention, Assessment, and Management." Dr. Mago selects, summarizes, and provides a clinical commentary on the latest published research in psychiatry. 

We are always carefully evaluating which research papers to discuss in GME Research Review. Have come across a research paper published in the last 6 months that you thought is clinically relevant? Do you want me to analyze it for you and for the benefit of others? Please email Dr. Mago the citation at [email protected].

To contact GME, email us at [email protected]


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