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Issue 47, Mar 2016
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Do antidepressants lead to suicide and aggression?

Sharma et al. Suicidality and aggression during antidepressant treatment: systematic review and meta-analyses based on clinical study reports. BMJ. 2016 Jan 27;352:i65. PubMed PMID: 26819231.

Why is this study important?

In recent years, there has been a lot of concern about an increased risk of suicidal ideation and behavior in persons prescribed antidepressant medications. This led to a boxed warning by the FDA.

Not surprisingly, therefore, this article, published in BMJ recently, received a huge amount of attention in the press.

Both the FDA warning and the concern of patients and their families make it essential that those who prescribe antidepressants stay up-to-date on data about these risks. We must be prepared to discuss this and similar studies with patients and their families.

Background

 The study aimed to evaluate several serious harms that may be associated with selective serotonin and serotonin-norepinephrine reuptake inhibitors (SSRIs and SNRIs).

Methods

This was a systematic review and meta-analysis of selected relevant studies.

The main outcome measures they focused on were mortality and suicidality, but they also looked at aggressive behavior and akathisia.

In any meta-analysis, we must first and foremost look at what went in. What were the studies that were meta-analyzed? This meta-analysis included:

a) Double-blind, placebo-controlled clinical trials only, and

b) Only trials that contained any patient narratives or individual patient listings of harms.

Published papers usually contain little or no details about harms. Results of clinical trials are provided to regulators in long, detailed documents called “Clinical Study Reports.”  The Clinical Study Reports for duloxetine, fluoxetine, paroxetine, sertraline, and venlafaxine were obtained from European and UK drug regulators, and summary trial reports for duloxetine and fluoxetine were obtained from Eli Lilly's website. The authors expressed frustration at how difficult it was for them to get data and to have to wade through tens of thousands of pages to find information about serious harms.

As is conventional and appropriate, two researchers extracted the data independently.

Results

Seventy clinical trials that studied 18,526 patients were included in this meta-analysis.

The authors comment that problems with both study design and reporting of results make it likely that harms are under-reported.

Overall, there were no statistically significant differences in mortality, suicidality, or akathisia between antidepressant and placebo.

Patients taking antidepressants displayed statistically significantly more aggressive behavior than those taking placebo (odds ratio 1.9).

The authors then looked at the data separately for adults and for children.

For adults, there were no statistically significant differences between antidepressants and placebo for suicidality, aggression, or akathisia.

However, for children and adolescents, persons who manifested suicidality (odds ratio 2.4) or aggression (odds ratio 2.8) were statistically significantly more likely to have been on antidepressant than on placebo. For akathisia, the difference was not statistically significantly different.

Conclusions

In adults there was no statistically significant increase in any of the four harms evaluated.

In children and adolescents, there was an association between being on an antidepressant and suicidality and aggression. The odds ratios comparing antidepressants to placebo were more than two.

The authors called for better reporting of serious harms and for access to anonymized individual patient data from clinical trials in order to be able to better estimate risks of potential harms.

Clinical Commentary

The findings of this meta-analysis about suicidality are consistent with those of previous studies. However, this is the first large study to show an increased risk of aggression in children and adolescents receiving antidepressants. Lastly, no increased risk of akathisia was found in this study even though it is known that antidepressants can be associated with akathisia. Unfortunately, unlike in clinical trials of antipsychotics, in antidepressant clinical trials, akathisia rating scales are not used. Therefore, in my opinion, the failure to find increased risk of akathisia should not be considered as evidence that antidepressants do not cause akathisia. In fact, as the accompanying Editorial (Moncrieff J. BMJ. 2016 Jan 28;352:i217. PubMed PMID: 26823531) notes, antidepressants may be associated with an akathisia-like agitation along with suicidal preoccupation.

The risks of antidepressants should be viewed quite differently in children, adolescents, and young adults (early 20s). Patients and caregivers should be educated about these risks and patients must be carefully monitored for potential worsening.

A huge problem is created though when pediatricians and others become more reluctant to prescribe antidepressants to clinically depressed children and adolescents, but are not given the resources to help their patients access high quality psychotherapy.

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Does CBT for insomnia work in the presence of other mental disorders?

Wu et al. Cognitive Behavioral Therapy for Insomnia Comorbid With Psychiatric and Medical Conditions: A Meta-analysis. JAMA Intern Med. 2015 Sep;175(9):1461-72. PubMed PMID: 26147487.

Why is this study important?

Insomnia is one of the commonest symptoms that accompany mental disorders. Use of hypnotic medications is widespread but is associated with adverse effects and potential dependence.

We have all heard that cognitive behavior therapy for insomnia (CBT-I) is efficacious. It has been adopted as first-line treatment for persons with insomnia by the American Academy of Sleep Medicine.

Background

Cognitive behavioral therapy for insomnia (CBT-I) is the best established non-pharmacologic treatment for insomnia disorders.

It consists of a multicomponent treatment including sleep restriction, stimulus control, cognitive therapy, etc.

This study aimed to examine the efficacy of CBT-I for insomnia comorbid with psychiatric and/or other medical conditions. Outcome measures were:

1. Remission from insomnia

2. Self-reported measures: sleep efficiency, sleep onset latency, wake after sleep onset, total sleep time, subjective sleep quality

3. Symptoms of the comorbid illness.

Methods

This was a meta-analysis of 37 studies that included 2189 subjects.

A systematic search of various literature databases was conducted.

Studies were included if they:

1. Studied adults who had insomnia as well as another mental or physical disorder

2. Were randomized clinical trials

3. Included CBT-I as one of the treatments

Thirty-seven studies were included.

What was CBT-I compared to? Different things in different trials: waiting list (i.e., no treatment), symptom monitoring only, relaxation therapy, medication, mindfulness based stress reduction, behavioral placebo, etc.

As is conventional and appropriate, data were independently extracted by 2 authors.

A sleep diary and other self-report measures were used.

Results

After treatment, 36% of patients who received CBT-I were in remission from insomnia compared with 17% of those in control or comparison conditions.

Remember that remission from insomnia is a high bar, so 36% is a good percentage.

Also, remember that a 10% or greater difference between a treatment and the control condition is considered clinically meaningful and a 20% difference is considered excellent. Here, the difference between the CBT-I and control groups was about 19% indicating that the treatment was highly efficacious.

Effect size is a statistical measure that can be used to indicate the magnitude of the effect of a treatment. An effect size of about 0.5 is considered a medium effect and 0.8 is considered a large effect. For each of the self report measures, the effect size was medium to large: 

Sleep efficiency: 0.9

Sleep onset latency: 0.8

Wake after sleep onset: 0.7

Sleep quality: 0.8

Now, here’s the really interesting part. Not only did CBT-I lead to improvement in the insomnia, it also led to improvement in the comorbid psychiatric or other medical condition as well. This improvement was more when the comorbid condition was a psychiatric disorder (effect size 0.8) than when it was another medical illness (effect size 0.2).

Conclusions

Cognitive behavioral therapy for insomnia (CBT-I) is efficacious for insomnia in persons with comorbid psychiatric or other medical disorders.

In addition, the comorbid condition tends to improve as well, especially if the comorbidity is a psychiatric disorder.

Clinical Commentary

An accompanying Editorial (Grandner MA, Perlis ML. JAMA Intern Med. 2015 Sep;175(9):1472-3. PubMed PMID: 26147221) notes, “Clinicians who provide treatment for patients with insomnia should consider CBT-I; even if the insomnia exists in the context of depression, pain, or some other condition, the therapy is likely to be helpful.”

The data are very convincing. So what’s the problem? The problem is that clinicians are not trained in delivering high quality CBT-I and in an efficient manner. Both psychiatrists and other mental health clinicians should be provided this training.

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What can be done to reduce risk of developing Alzheimer’s disease?

Xu et al. Meta-analysis of modifiable risk factors for Alzheimer's disease. J Neurol Neurosurg Psychiatry. 2015 Dec;86(12):1299-306. PubMed PMID: 26294005.

Why is this study important?

Alzheimer’s disease is the most common cause of dementia and a very important cause of morbidity and mortality.

It has been estimated that nearly half of the cases of Alzheimer’s disease around the world might be attributable to common and potentially modifiable risk factors.  That is an amazing statement and may come as a surprise to many readers.

Even small reductions in these modifiable risk factors could be very valuable to those who may have otherwise developed the disease and to society at large.

Background

The etiology of Alzheimer's disease is believed to involve both genetic vulnerability and environmental factors.

This systematic review and meta-analysis aimed to evaluate modifiable risk factors for Alzheimer’s disease.

While a large number of studies about modifiable risk factors have been published, the results are inconsistent. This is the most extensive and comprehensive systematic review and meta-analysis done so far on this topic.

Methods

A systematic search of the literature was done.

Both prospective cohort studies and retrospective case-control studies on this topic were included.

Only studies of modifiable risk factors were included. That is, the numerous studies of genetic risk factors were not included in this meta-analysis.

Results

The meta-analysis included 323 articles that looked at 93 risk factors.

Some factors were considered to have good quality evidence for them.

There was good evidence that the following 8 factors protect against Alzheimer’s disease:

- Four medications: estrogen, statins, antihypertensives, non-steroidal anti-inflammatory drugs.

- Four dietary/nutritional factors: folate, vitamin E, vitamin C, coffee.

There was good evidence that the following two factors increase the risk of developing Alzheimer’s disease:

- Increased homocysteine levels, depression.

There also appeared to be less certain association between other factors and either increased or decreased risk. These factors should not be taken as being well established.  

- Increased risk: frailty, carotid atherosclerosis, hypertension, low diastolic blood pressure, type 2 diabetes mellitus, low education, high body mass index (BMI) in mid-life and low BMI in late-life

- Decreased risk: history of arthritis, heart disease, metabolic syndrome, cancer, cognitive activity, current smoking, light-to-moderate drinking, stress, high BMI in late-life.

Conclusions

Interventions in diet, medications, biochemical exposures, treatment of depression, treatment of other medical illnesses, and lifestyle modifications may decrease risk of developing Alzheimer’s disease.

Clinical Commentary

The prevalence of Alzheimer’s disease is increasing but there is no cure for it. Therefore, we must make vigorous attempts to identify modifiable risk factors and to reduce them as much as possible.

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Should all obese persons be screened for ADHD?

Cortese et al. Association Between ADHD and Obesity: A Systematic Review and Meta-Analysis. Am J Psychiatry. 2016 Jan 1;173(1):34-43. PubMed PMID: 26315982.

Why is this study important?

The majority of persons with Attention Deficit Hyperactivity Disorder (ADHD) go undiagnosed. Rather, attention is focused on its consequences: depression, anxiety, divorce, substance abuse, etc.

Is obesity also in some cases a consequence of having ADHD? If this turns out to be true, the implication would be that persons with obesity should be screened for ADHD and maybe treatment of ADHD could lead to improvement in obesity.

Background

Impulsivity and inattention related to attention deficit hyperactivity disorder (ADHD) may be responsible in part for overeating, especially of high calorie food.

This study is the first meta-analysis ever that assessed the relationship between ADHD and obesity.

Methods

A meta-analysis of studies on the association of being obese/overweight and having ADHD was performed.

Multiple databases were searched for studies on this topic. Unpublished studies were also obtained, which was a good thing to do since failure to include unpublished studies often biases the results of a meta-analysis.

Results

Forty-two studies were included in the meta-analysis. These studies included about 48,000 persons with ADHD and about 680,000 control subjects. 

There was a statistically significant association between obesity and ADHD in both children  (odds ratio=1.2) and adults (odds ratio=1.6).

The prevalence of obesity was 28% in adults with ADHD versus 16% in those without ADHD.

In children with ADHD, the prevalence of obesity was 10% versus 7% in those without ADHD.

The authors also addressed 3 potential problems in drawing these conclusions.  In addition to the main analyses, they looked only at the studies that:

1. Adjusted the odds ratios for other possible factors that may explain why it seemed that persons with ADHD were more likely to be obese (confounding factors).

2. Diagnosed ADHD by direct interview rather than only self-report questionnaires.

3. Used directly measured height and weight.

The association between ADHD and obesity remained in each case.

In contrast to some previous data suggesting that the association between having ADHD and being obese was particularly true for adolescent females rather than males, in this meta-analysis, the association was present for both males and females. The association also applied to being overweight but not obese.

Conclusions

There is a statistically significant association between having ADHD and being obese or overweight, though the difference is not huge (no pun intended).

The possible underlying mechanisms and the effects of long-term treatment of ADHD on weight need to be researched. The authors discussed many hypotheses. One of these relates to a “reward deficiency syndrome” that has been described in both ADHD and in obesity. This syndrome is characterized by lowered levels of natural dopamine-related reinforcement that leads to “unnatural” immediate rewards (such as inappropriate eating). 

Clinical Commentary

To the list of the many negative and serious consequences of having ADHD, we should now add being overweight and obese with the implied serious medical consequences of that. This should further motivate patients, their families, and their treating clinicians to energetically pursue treatment of ADHD (medication or ADHD-specific psychotherapy). While this has not been specifically shown, presumably treatment of ADHD will lead to reduced impulsive overeating and help these persons to reduce their weight.

I also think that persons who are significantly overweight or obese should be screened for a variety of conditions that may predispose them to being obese including depressive disorders, ADHD, and taking medications that cause weight gain.

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Why exactly do persons with ADHD stop their medications?

Frank et al. Examining why patients with attention-deficit/hyperactivity disorder lack adherence to medication over the long term: a review and analysis. J Clin Psychiatry. 2015 Nov;76(11):e1459-68. PubMed PMID: 26646041.

Why is this study important?

As is true for many other mental disorders, perhaps the main reason for poor outcomes in attention-deficit hyperactivity disorder (ADHD) in the long-term is non-adherence to medication.

I think that if we know exactly why persons taking a particular medication are likely to stop it (and this is different for each medication), we can try to intervene with those factors. For example, we might specifically warn the person about certain misconceptions or we may try to energetically manage the specific adverse effects that tend to lead to non-adherence.

Background

This review aimed to determine the reasons why patients with ADHD adhere poorly to medications over the long term (≥ 1 year).

Methods

A literature search was done and articles with follow up of medication treatment of ADHD for at least one year were identified.

The review included 41 published articles that met this criterion and cited reasons for subjects withdrawing from treatment.

Most of the studies were of children and adolescents. This will be relevant when we will later look at the adverse effect most likely to lead to discontinuation of medication.

Similar reasons for medication discontinuation were grouped together for analysis, but some unique reasons were analyzed individually.

Results

Reasons for discontinuing medication after 1 year included the following:

1. Own wish/remission/don't need (20%)

2. Withdrew consent (16%)

3. Adverse effects (15%)

4.  Suboptimal effect (15%)

Better adherence was also reported when age was < 12 years, long-acting medications were used, and psychosocial stressors were less, but adherence was impaired in patients who complained that they had "stopped feeling like myself" on the medication.

Within the category of adverse events that were attributed to the medication by patients, the specific complaints that led most commonly (5% or more) to discontinuation were as follows. Note: percentages given below are out of those who discontinued due to adverse effects.

1. Reduction in weight/appetite (19%)

2. Aggressive behavior/ irritability (17%)

3. Sleeping difficulties (11%)

4. Abdominal pain (8%)

5. Motor tics (7%)

6. Worsening of ADHD (6%)

7. Depression (6%)

Conclusions

The reasons why patients do not adhere to medication for ADHD, especially over the long term, need to be better studied.

Clinical Commentary

In many cases, the reason for discontinuation was not documented. Whenever possible, we should take the time to determine the reason for discontinuation of medication. Of course, this should be done in a nonjudgmental manner.

Based on the findings of this paper, clinicians should remain vigilant for potential nonadherence in the future. In trying to reduce nonadherence, we should:

1. Counsel patients proactively about issues related to non-adherence

2. Energetically manage adverse effects

3. In cases of partial response, discuss potential changes to the treatment plan. There is data to indicate that being allowed to switch medication increases adherence.

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Rajnish Mago, MD
Professor of Psychiatry, Thomas Jefferson University

GME Research Review is a monthly newsletter edited by Rajnish Mago, MD, who is Professor of Psychiatry at Thomas Jefferson University and 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 you come across a research paper published in the last 6 months that you think is clinically relevant? If you would like to ask Dr. Mago to consider analyzing it, please email him the citation at: [email protected]

To contact GME, email us at [email protected]


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