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Correlates of benzodiazepine use in major depressive disorder: The effect of anhedonia
Journal of Affective Disorders 187 (2015) 101–105
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Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research report
Correlates of benzodiazepine use in major depressive disorder: The effect of anhedonia Sakina J. Rizvi a,b,n, Beth A. Sproule c,d, Laura Gallaugher b, Roger S. McIntyre b,e, Sidney H. Kennedy b,e a
Department of Psychiatry, St. Michael’s Hospital, Toronto, Ontario, Canada Department of Psychiatry, University Health Network, Toronto, Ontario, Canada c Department of Pharmacy, Centre for Addiction and Mental Health, Toronto, Ontario, Canada d Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada e Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada b
art ic l e i nf o
a b s t r a c t
Article history: Received 25 May 2015 Received in revised form 22 July 2015 Accepted 29 July 2015 Available online 21 August 2015
Background: Current treatment guidelines emphasize the limited role of benzodiazepines in Major Depressive Disorder (MDD), mainly due to the absence of long-term data, risk of abuse and potential adverse effects. However, benzodiazepines continue to be prescribed for long-term use in a significant number of patients. This study sought to evaluate benzodiazepine use in a large sample of MDD patients seen at a tertiary care clinic, and determine whether use is related to illness severity or complexity, as well as to identify the clinical predictors of benzodiazepine use. Methods: This was a naturalistic cross-sectional study conducted in MDD patients seen at the Mood Disorders Pyschopharmacology Unit at the University Health Network (N¼ 326). Detailed information on current medication regimens was collected. A structured diagnostic interview, in addition to measures of symptom severity, quality of life, and personality were administered. Participants were grouped according to the presence or absence of prescribed benzodiazepines for daily use. Results: The prevalence of regular benzodiazepine use was 25%. Benzodiazepine users were more likely to be female, unemployed, have a history of child abuse, and have comorbid panic disorder. Depression and anxiety scores were not significantly different between groups, although anhedonia was greater in the benzodiazepine group. A logistic regression revealed anhedonia was the strongest predictor of regular benzodiazepine use. Conclusion: The groups were similar in clinical profile suggesting benzodiazepine use is not necessarily linked to greater illness complexity or severity. Benzodiazepine use appears to be associated with specific diagnostic and symptom characteristics, possibly providing insight into the potential pharmacodynamic and neurobiological effects of frequent use. & 2015 Elsevier B.V. All rights reserved.
Keywords: Benzodiazepine Major depressive disorder Anhedonia Anxiety
1. Introduction Benzodiazepines are primarily utilized as sedative hypnotics in patients with Major Depressive Disorder (MDD) to alleviate anxiety (either as a symptom of depression or as a disorder on its own) and insomnia. International guidelines recommend limited use of benzodiazepines in MDD beyond 4 weeks (Davidson, 2010; Higuchi, 2010), due to their addictive potential and negative cognitive effects in the domains of memory, attention, and psychomotor speed (Barker et al., 2004; Lader, 2011). Benzodiazepines are also
n Correspondence to: Department of Psychiatry, St. Michael’s Hospital, University Health Network, 193 Yonge St, 6-009, Toronto, ON, Canada M5B 1M8. E-mail address: [email protected] (S.J. Rizvi).
http://dx.doi.org/10.1016/j.jad.2015.07.040 0165-0327/& 2015 Elsevier B.V. All rights reserved.
associated with an increased risk of dementia as well as falls (Lavsa et al., 2010; Billioti de Gage et al., 2012). In addition to lack of efficacy data in prospective trials, there is evidence to suggest that adjunctive benzodiazepine therapy may impede antidepressant response with electroconvulsive therapy (ECT) and transcranial direct current stimulation (Delva et al., 2001; Nordenskjöld et al., 2011; Lader, 2011; Brunoni et al., 2013). Despite these findings and guideline recommendations, prescribing practices have not been significantly affected (Lai et al., 2011; Schneider et al., 2005; Zhang, 2010), and benzodiazepines remain commonly used (Olfson et al., 2015). Current estimates across Canada, the US and Europe indicate upwards of 40% of individuals with MDD are prescribed concomitant benzodiazepine therapy (Sanyal et al., 2011; Demyttenaere et al., 2008; Valenstein et al., 2004). However, chronic benzodiazepine use in depression remains
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sparsely investigated. Therefore, it is unclear whether individuals who receive benzodiazepines represent a more chronically ill and psychiatrically comorbid group or whether long-term use contributes to worse outcomes. The effect of acute benzodiazepine use on depressive symptoms can be understood by its allosteric binding to benzodiazepine receptors on GABA neurons throughout the brain, specifically the GABA-A subtype, resulting in increased GABA release (Luscher et al., 2011). However, reports of decreased GABAergic functioning following chronic benzodiazepine administration in preclinical models (Miller et al., 1990; Fahey et al., 2001; Gallager et al., 1984) suggest benzodiazepines could exacerbate depression severity. GABA signaling has been shown to directly modulate processes implicated in the etiopathology of MDD, including HPA axis signaling, neurogenesis, monoamine and glutamate transmission (Luscher et al., 2011; Biswas and Carlsson, 1977). There are also consistent reports of reduced GABA metabolites in plasma and cerebrospinal fluid in MDD compared to healthy controls (Gerner and Hare, 1981; Petty et al., 1992), in addition to neuroimaging evidence of lower concentrations of GABA in depression from adolescence into adulthood (Gabbay et al., 2012; Sanacora et al., 1999; Kugaya et al., 2003; Hasler et al., 2007; Price et al., 2009). Predictors of long-term benzodiazepine use include older age, female gender, presence of MDD or Anxiety Disorder, antidepressant initiation and pain (Hawkins et al., 2012; Manthey et al., 2011; Liu et al., 2010; Patten et al., 2010; Préville et al., 2011; Valenstein et al., 2004). However, in addition to demographic predictors, it is important to identify clinical symptoms that may predict benzodiazepine use in order to address the questions of whether exposure exacerbates illness or is a confound by association (i.e., patients with greater illness complexity are more likely to receive benzodiazepines). Therefore, the objective of this study is to evaluate benzodiazepine use in a large sample of MDD patients seen at a tertiary care clinic, and determine whether use is related to illness severity or complexity, as well as to identify the clinical predictors of benzodiazepine use.
2. Methods 2.1. Design Data for this study were extracted from the Mood Disorder Psychopharmacology Unit (MDPU) database at the Department of Psychiatry, University Health Network, Toronto. The methodology has been previously published (McIntyre et al., 2010). Briefly, patients referred for consultation to the MDPU were enrolled into a naturalistic cross-sectional study following written informed consent. Participants underwent a battery of clinician administered and self-report questionnaires during a single visit. The clinical characteristics of a subset of subjects diagnosed with MDD were assessed in relation to benzodiazepine use. 2.2. Subjects Subject selection criteria for data inclusion were: male and female patients who were between the ages of 18–60, outpatient status, met DSM-IV criteria for MDD in a current major depressive episode, confirmed through the Mini-International Neuropsychiatric Interview-Plus (MINI-Plus) (Sheehan et al., 1998). Psychiatric and medical comorbidities were allowed, as effects of comorbidity were directly related to the study aims. Only those with confirmed daily benzodiazepine use or no use were included in the analysis.
2.3. Procedure Eligible subjects provided informed consent before undergoing a battery of clinician administered and self-report questionnaires during a single visit. Assessment data used in the current study included demographic and medication information, the MINI-Plus (Sheehan et al., 1998), the HRSD-17 (Hamilton, 1960), Montgomery–Åsberg Depression Rating Scale (MADRS) (Montgomery and Åsberg, 1979), the Trimodal Anxiety Questionnaire (TAQ) (Lehrer and Woolfolk, 1982), the Quality of Life Enjoyment and Satisfaction Questionnaire (QLESQ) (Endicott et al., 1993), the Sheehan Disability Scale (SDS) (Sheehan et al., 1996), the Endicott Work Productivity Scale (EWPS) (Endicott and Nee, 1997), the NEO-Five Factor Inventory (NEO-FFI) (Costa and McCrae, 1992) and the Klein Trauma and Abuse-Neglect scale (Lizardi et al., 1995). 2.4. Statistical analysis Exploration of between group differences, using Student t-tests and Mann Whitney U tests corrected for multiple comparisons, were conducted. In order to determine group differences based on depression and anxiety scores with a power of 0.80 and an alpha of 0.05, a minimum of 60 participants per group was needed. A logistic regression was performed to determine the model that best predicted benzodiazepine use. Specifically, data were entered into a stepwise logistic regression with benzodiazepine use as the dependent variable. Differences identified in the between group analysis were included in the model as covariates.
3. Results 3.1. Subjects Of the 1861 subjects in the MDPU database, 851 subjects had a diagnosis of MDD. After excluding inpatients (n ¼ 502) and “unconfirmed” benzodiazepine users (n¼ 23), a final sample size of 326 was achieved. Participant characteristics are presented in Table 1. Benzodiazepine users were more likely to be slightly older, female, unemployed, have a history of hospitalization or child abuse and reported lower scores on the dimension of “Openness” as measured by the NEO. The overall prevalence of benzodiazepine use was 25%. Clonazepam and lorazepam were the most frequently utilized (50.6% and 45.6% of benzodiazepine users, respectively), although use with alprazolam, diazepam, temazepam, Table 1 Participant characteristics.
Age Gender (% female) Education achieved Employment status % Full-time % unemployed History of MDD hospitalization Age of MDD onset # Lifetime MDEs Family history of mental illness History of child abuse (Physical/sexual)
Non-BZD user (n¼247)
Daily BZD user (n¼ 79)
P-value
39.8 (12.6) 59.5% College/ University
44.1 (11.3) 72.2% College/ University
0.006 0.043 0.394
76.4% 23.6% 16.2%
56.3% 43.8% 31.7%
0.019
22.5 (12.2) 11.1 (23.2) 70.2%
20.8 (11.5) 11.0 (17.2) 83.7%
0.305 0.619 0.054
26.8%
40.0%
0.031
0.006
BZD: Benzodiazepine; MDD: Major Depressive Disorder; MDE: Major Depressive Episode.
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3.3. Functioning differences
Table 2 Average daily dosing among benzodiazepine usersa. Benzodiazepine
DDDb (mg)
Average dose (mg)
Alprazolam (n¼ 3) Clonazepam (n¼ 40) Diazepam (n¼ 2) Lorazepam (n¼ 36) Oxazepam (n¼ 3) Temazepam (n ¼2)
1 8 10 2.5 50 20
1 3.6 7.5 2.3 30 22.5
a
Frequencies for each drug include those taking more than one benzodiaze-
pine. b
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DDD: Daily defined dose (World Health Organization, 1997).
and oxazepam was also reported. The average daily dosing is presented in Table 2. A minority of patients (8.8%) were receiving more than one benzodiazepine. The majority of patients (79.7%) were receiving a benzodiazepine adjunctively to a selective serotonin reuptake inhibitor (SSRI), serotonin and norepinephrine reuptake inhibitor (SNRI) or bupropion. Of those receiving a benzodiazepine, 36% were also taking an atypical antipsychotic, with limited concomitant use of typical antipsychotics or stimulants. With respect to comorbidities, endocrine disorders were the only medical comorbidity that was more prevalent in benzodiazepine users (80.8% vs. 65.1%, p ¼0.04, respectively), while panic disorder and obsessive compulsive disorder were the only psychiatric comorbidities that were more prevalent in benzodiazepine users (23.7% vs. 6.8%, po 0.001; 16.7% vs. 7.1%, p¼ 0.023, respectively). None of the patients met criteria for benzodiazepine abuse or dependence. 3.2. Symptom severity differences There were no differences between non-benzodiazepine users and users in depression severity based on the MADRS (20.7 vs. 23.6, respectively) or HRSD-17 (15.0 vs. 17.7, respectively). There were also no differences on the HRSD-17 anxiety subscale (2.4 vs. 3.0, respectively), although there was a trend for non-benzodiazepine users to report lower anxiety levels on the TAQ (128.4 vs.150.6, p ¼.008, respectively, did not meet multiple correction). The only depressive symptom that distinguished between groups was the anhedonia item extracted from the on the HRSD-17, where benzodiazepine users reported greater severity than non-users (2.6 vs. 1.9, p o0.001) (Fig. 1).
Benzodiazepine users reported poorer quality of life compared to non-users, based on the Q-LES-Q (44.9 vs. 35.9, po 0.001). There were trends of significance based on both the SDS and EWPS, where worse overall and occupational functioning, respectively were worse in users compared to non-users (SDS: 20.0 vs. 16.9, p ¼0.021, respectively; EWPS: 74.8 vs. 55.1, p¼ 0.002, respectively; both tests did not meet multiple correction). 3.4. Prediction model Hence, the following variables were entered into the logistic regression based on the above tests: sex, employment status, hospitalization, comorbidity (i.e., endocrine, panic disorder, obsessive compulsive disorder), NEO-openness, TAQ total score, HRSD-item 7 (anhedonia). The only unique predictor in the model was the severity of anhedonia (β ¼0.93, p ¼ 0.016), which explained 11.6% of benzodiazepine use with 85.7% accuracy. Reducing the number of covariates to include the ones that remained significant in the model resulted in a 3-term model that predicted benzodiazepine use, which included anhedonia, openness and presence of panic disorder (β ¼0.66, p o.001; β ¼ 0.74, p¼ .012; β ¼ 1.66, p ¼0.015, respectively; model accuracy: R2: 0.2, 83.7%, χ ¼37.1, p o0.001) (Table 3).
4. Discussion The present analysis identified anhedonia as the only symptom that correlated with benzodiazepine use, along with panic disorder comorbidity and a lower score on Openness as measured by the NEO. While other clinical differences were found, they did not significantly contribute to the prediction model. Furthermore, benzodiazepine users appeared to have poorer life functioning, but this effect may be independent of depression severity, which did not differ between groups. The unique finding in this study was that higher severity of anhedonia, based on the HRSD-17 item 7, was associated with benzodiazepine use. In the context of the HRSD-17, anhedonia is defined as reduced interest, effort to pursue reward, and enjoyment of reward. Anhedonia has been reported in several large scale studies as a predictor of SSRI non-response (Uher et al., 2008, 2012). This was also observed in an adolescent MDD sample, which found anhedonia to be the only unique negative predictor of time to remission and depression free days with SSRI use (McMakin et al., 2012). Providing further generalizability across treatment modalities, anhedonia was a predictor of non-response to rTMS of the dorsomedial PFC in MDD (Downar et al., 2014). Anhedonia is also a prominent symptom in patients with treatment resistance (Malhi and Berk, 2007). However, a better understanding of anhedonia and its neurobiological underpinnings are necessary in order to determine whether the presence of this symptom represents a unique subtype. Among neurotransmitters, low dopamine levels in reward pathways historically been most frequently associated with Table 3 Multivariate logistic regression model.
Fig. 1. Differences between benzodiazepine users on HAMD-17 total score, anxiety subscale and anhedonia.
Predictor
β
SE β
Wald’s χ2
p-value
Odds Ratio
Constant Anhedonia Openness Panic disorder Overall model
0.575 0.661 0.74 1.656
1.196 0.179 0.029 0.680
0.233 13.643 6.361 5.931 37.107
0.629 o 0.001 0.012 0.015 o 0.001
NA 1.937 0.929 0.191
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anhedonia, however it is clear other systems including the opioid system are integral to reward function (Treadway and Zald, 2011; Der-Avakian and Markou, 2012). A link between GABA and anhedonia has also been reported. Gabbay et al. (2012) conducted a magnetic resonance spectroscopy (MRS) study assessing GABA concentrations in depressed adolescents compared to healthy controls. Adolescents had significantly reduced GABA in the anterior cingulate cortex, a key area in depression pathophysiology (Mayberg et al., 1999; Kennedy et al., 2007; Koolschijn et al., 2009). Furthermore, when participants were categorized according to the presence of anhedonia, only those with anhedonia had reduced GABA concentrations. Parallel preclinical evidence also supports a role for GABA in anhedonia. Activation of GABA neurons in rats within the ventral tegmentum, an area that primarily expresses dopamine neurons, resulted in altered rewarding properties of sucrose manifested as decreased sucrose consumption (van Zessen et al., 2012). The study also demonstrated ventral tegmentum GABA significantly reduced dopamine transmission in surrounding regions as well, including the nucleus accumbens. Overall, the higher level of anhedonia in benzodiazepine users suggests a dysfunction in both GABA and dopamine systems (and possibly others including glutamate and opioids) that could reflect a distinct depressive subtype that is likely to be prescribed benzodiazepines. Conversely, anhedonia may be exacerbated as a consequence of chronic benzodiazepine use. The latter hypothesis suggests the possibility that benzodiazepines may limit positive depression outcomes. This is particularly relevant to individuals with treatment resistant depression as this subgroup strongly presents with anhedonia and may also be more likely to be receiving a benzodiazepine (Malhi and Berk, 2007; Rizvi et al., 2014). Interestingly, low reported openness was also a predictor for benzodiazepine use. Based on the NEO, openness refers to a willingness to engage in a variety of experiences (Costa and McCrae, 1992), and it is related to other personality traits including sensation seeking and extraversion (García et al., 2005). The link between openness and reward function has also been demonstrated in a study of treatment resistant depression, where Takahashi et al. (2013) reported low openness correlated with lower levels of reward dependence (responsivity and seeking of reward; Cloninger et al., 1993). These findings parallel those of the present study. As mentioned anhedonia in the present study was defined as decreased interest in reward as well as the ability to pursue and enjoy reward. Therefore, considering anhedonia was a strong correlate of benzodiazepine use, it follows that low openness as a personality trait would also be a related predictor. The results of this study support a distinction between functioning and depression severity among benzodiazepine users, where differences in functional outcomes exist despite a lack of group difference in overall symptom severity. Considering benzodiazepines are used to target specific symptoms of depression (insomnia and anxiety), it follows that there would be differences among specific symptoms. However, group differences in anxiety symptoms did not meet statistical significance. This could also speak to the efficacy of the benzodiazepine in treating anxiety. Importantly, the finding of poorer functional outcomes in benzodiazepine users suggests either this group represents a more impaired population, or there are extra-depression effects of benzodiazepine use in depression. The presence of panic disorder as a key discriminator between groups is consistent with the indication of benzodiazepines for anxiety. The prevalence of benzodiazepine use was lower than reported in previous studies (Valenstein et al., 2004), although there are few studies evaluating prevalence of benzodiazepine use within an MDD sample. This difference may be related to the duration and frequency of benzodiazepine use, since previous studies included all frequencies of use, while the present study specified daily use.
A separate Canadian study revealed that, of the 3% of the general population receiving a benzodiazepine, 80% had been users for more than one year (Esposito et al., 2009). Limitations of the present study include the lack of a priori design to measure the effects of chronic benzodiazepine use. These results may not be generalizable to other clinical populations owing to a lack of random sampling and, therefore, may not reflect a representative sample. In addition, benzodiazepine use included all drugs within that class, therefore, we were unable to differentiate the effect of specific benzodiazepines on anhedonia. Finally, the cross-sectional nature of this study precludes any conclusions regarding whether patients worsened across any of the indices post-benzodiazepine use or about the effect of benzodiazepine discontinuation in those currently receiving a benzodiazepine. In conclusion, the findings of the present study suggest benzodiazepine use is not necessarily linked to greater illness complexity or severity. However, it may be associated with specific diagnostic and symptom characteristics that provide insight into the effects of frequent use. Future studies should evaluate whether chronic benzodiazepine use in MDD patients reduces GABA concentrations and the extent to which this could be associated with exacerbation of anhedonic and anxiety symptoms.
Acknowledgments The authors would like to thank Zilomi Panjwani, Kari Fulton, and Beata Eisfeld for support in data collection. The maintenance of the database was supported in part by Biovail.
References Barker, M.J., Greenwood, K.M., Jackson, M., Crowe, S.F., 2004. Cognitive effects of long-term benzodiazepine use: a meta-analysis. CNS Drugs 18, 37–48. Billioti de Gage, S., Bégaud, B., Bazin, F., Verdoux, H., et al., 2012. Benzodiazepine use and risk of dementia: prospective population based study. Br. Med. J. 345, e6231. Biswas, B., Carlsson, A., 1977. The effect of intraperitoneally administered GABA on brain monoamine metabolism. Naunyn Schmiedebergs Arch. Pharmacol. 299, 47–51. Brunoni, A.R., Ferrucci, R., Bortolomasi, M., et al., 2013. Interactions between transcranial direct current stimulation (tDCS) and pharmacological interventions in the Major Depressive Episode: findings from a naturalistic study. Eur. Psychiatry 28, 356–361. Cloninger, C.R., Svrakic, D.M., Przybeck, T.R., 1993. A psychological model of temperament and character. Arch. Gen. Psychiatry 50, 975–990. Costa, P.T., McCrae, R.R., 1992. NEO Personality Inventory Professional Manual. Psychological Assessment Resources, Odessa, FL. Davidson, J.R., 2010. Major depressive disorder treatment guidelines in America and Europe. J. Clin. Psychiatry 71 (Suppl E1), e04. Delva, N.J., Brunet, D.G., Hawken, E.R., et al., 2001. Characteristics of responders and nonresponders to brief-pulse right unilateral ECT in a controlled clinical trial. J. ECT 17, 118–123. Demyttenaere, K., Bonnewyn, A., Bruffaerts, R., et al., 2008. Clinical factors influencing the prescription of antidepressants and benzodiazepines: results from the European study of the epidemiology of mental disorders (ESEMeD). J. Affect. Disord. 110, 84–93. Der-Avakian, A., Markou, A., 2012. The neurobiology of anhedonia and other reward-related deficits. Trends Neurosci. 35, 68–77. Downar, J., Geraci, J., Salomons, T.V., Dunlop, K., Wheeler, S., McAndrews, M.P., Bakker, N., Blumberger, D.M., Daskalakis, Z.J., Kennedy, S.H., Flint, A.J., Giacobbe, P., 2014. Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal repetitive transcranial magnetic stimulation in major depression. Biol. Psychiatry 76, 176–185. Endicott, J., Nee, J., 1997. Endicott Work Productivity Scale (EWPS): a new measure to assess treatment effects. Psychopharmacol. Bull. 33 (1), 13–16. Endicott, J., Nee, J., Harrison, W., et al., 1993. Quality of life enjoyment and satisfaction questionnaire: a new measure. Psychopharmacol. Bull. 29, 321–326. Esposito, E., Barbui, C., Patten, S.B., 2009. Patterns of benzodiazepine use in a Canadian population sample. Epidemiol. Psichiatr. Soc. 18, 248–254. Fahey, J.M., Pritchard, G.A., Grassi, J.M., et al., 2001. Pharmacodynamic and receptor binding changes during chronic lorazepam administration. Pharmacol. Biochem. Behav. 69, 1–8. Gabbay, V., Mao, X., Klein, R.G., et al., 2012. Anterior cingulate cortex γ-aminobutyric acid in depressed adolescents: relationship to anhedonia. Arch. Gen.
S.J. Rizvi et al. / Journal of Affective Disorders 187 (2015) 101–105
Psychiatry 69, 139–149. Gallager, D.W., Lakoski, J.M., Gonsalves, S.F., Rauch, S.L., 1984. Chronic benzodiazepine treatment decreases postsynaptic GABA sensitivity. Nature 308, 74–77. García, L.F., Aluja, A., García, Ó., Cuevas, L., 2005. Is openness to experience an independent personality dimension? J. Indiv. Differ. 26, 132–138. Gerner, R.H., Hare, T.A., 1981. CSF GABA in normal subjects and patients with depression, schizophrenia, mania, and anorexia nervosa. Am. J. Psychiatry 138, 1098–1101. Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56–62. Hasler, G., van der Veen, J.W., Tumonis, T., Meyers, N., Shen, J., Drevets, W.C., 2007. Reduced prefrontal glutamate/glutamine and gamma-aminobutyric acid levels in major depression determined using proton magnetic resonance spectroscopy. Arch. Gen. Psychiatry 64, 193–200. Hawkins, E.J., Malte, C.A., Imel, Z.E., et al., 2012. Prevalence and trends of benzodiazepine use among Veterans Affairs patients with posttraumatic stress disorder, 2003–2010. Drug Alcohol Depend. 124, 154–161. Higuchi, T., 2010. Major depressive disorder treatment guidelines in Japan. J. Clin. Psychiatry 71 (Suppl E1), e05. Kennedy, S.H., Konarski, J.Z., Segal, Z.V., Lau, M.A., Bieling, P.J., McIntyre, R.S., Mayberg, H.S., 2007. Differences in brain glucose metabolism between responders to CBT and venlafaxine in a 16-week randomized controlled trial. Am. J. Psychiatry 164, 778–788. Koolschijn, P.C., van Haren, N.E., Lensvelt-Mulders, G.J., Hulshoff Pol, H.E., Kahn, R.S., 2009. Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Hum. Brain Mapp. 30, 3719–3735. Kugaya, A., Sanacora, G., Verhoeff, N.P., et al., 2003. Cerebral benzodiazepine receptors in depressed patients measured with [123I]iomazenil SPECT. Biol. Psychiatry 54, 792–799. Lader, M., 2011. Benzodiazepines revisited—will we ever learn? Addiction 106, 2086–2109. Lai, I.C., Wang, M.T., Wu, B.J., et al., 2011. The use of benzodiazepine monotherapy for major depression before and after implementation of guidelines for benzodiazepine use. J. Clin. Pharm. Ther. 36, 577–584. Lavsa, S.M., Fabian, T.J., Saul, M.I., et al., 2010. Influence of medications and diagnoses on fall risk in psychiatric inpatients. Am J Health Syst Pharm. 67, 1274–1280. Lizardi, H., Klein, D.N., Ouimette, P.C., Riso, L.P., Anderson, R.L., Donaldson, S.K., 1995. Reports of the childhood home environment in early-onset dysthymia and episodic major depression. J. Abnorm. Psychol. 104, 132–139. Lehrer, P.M., Woolfolk, R.L., 1982. Self-report assessment of anxiety: somatic, cognitive, and behavioral modalities. J. Behav. Assess. 4, 167–177. Liu, X., Ye, W., Watson, P., Tepper, P., 2010. Use of benzodiazepines, hypnotics, and anxiolytics in major depressive disorder: association with chronic pain diseases. J. Nerv. Ment. Dis. 198, 544–550. Luscher, B., Shen, Q., Sahir, N., 2011. The GABAergic deficit hypothesis of major depressive disorder. Mol. Psychiatry 16 (4), 383–406. Malhi, G.S., Berk, M., 2007. Does dopamine dysfunction drive depression? Acta Psychiatr. Scand. 115 (Suppl 433), 116–124. Manthey, L., Giltay, E.J., van Veen, T., et al., 2011. Determinants of initiated and continued benzodiazepine use in the Netherlands study of depression and anxiety. J. Clin. Psychopharmacol. 31, 774–779. Mayberg, H.S., Liotti, M., Brannan, S.K., McGinnis, S., Mahurin, R.K., Jerabek, P.A., Silva, J.A., Tekell, J.L., Martin, C.C., Lancaster, J.L., Fox, P.T., 1999. Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am. J. Psychiatry 156, 675–682. McIntyre, R.S., Kennedy, S.H., Soczynska, J.K., Nguyen, H.T., Bilkey, T.S., Woldeyohannes, H.O., Nathanson, J.A., Joshi, S., Cheng, J.S., Benson, K.M., Muzina, D.J., 2010. Attention-deficit/hyperactivity disorder in adults with bipolar disorder or major depressive disorder: results from the international mood disorders collaborative project. Prim. Care Companion J. Clin. Psychiatry, 12, pii: PCC.09m00861. McMakin, D.L., Olino, T.M., Porta, G., Dietz, L.J., Emslie, G., Clarke, G., Wagner, K.D., Asarnow, J.R., Ryan, N.D., Birmaher, B., Shamseddeen, W., Mayes, T., Kennard, B., Spirito, A., Keller, M., Lynch, F.L., Dickerson, J.F., Brent, D.A., 2012. Anhedonia predicts poorer recovery among youth with selective serotonin reuptake
105
inhibitor treatment-resistant depression. J. Am. Acad. Child Adolesc. Psychiatry 51, 404–411. Miller, L.G., Greenblatt, D.J., Lopez, F., et al., 1990. Chronic benzodiazepine administration: effects in vivo and in vitro. Adv. Biochem. Psychopharmacol. 46, 167–175. Montgomery, S.A., Åsberg, M., 1979. A new depression scale designed to be sensitive to change. Br. J. Psychiatry 134, 382–389. Nordenskjöld, A., von Knorring, L., Engström, I., 2011. Predictors of time to relapse/ recurrence after electroconvulsive therapy in patients with major depressive disorder: a population-based cohort study. Depression Res. Treat. 2011, 470985. Olfson, M., King, M., Schoenbaum, M., 2015. Benzodiazepine use in the United States. JAMA Psychiatry 72, 136–142. Patten, S.B., Williams, J.V., Lavorato, D.H., et al., 2010. Pharmacoepidemiology of benzodiazepine and sedative-hypnotic use in a Canadian general population cohort during 12 years of follow-up. Can. J. Psychiatry 55, 792–799. Petty, F., Kramer, G.L., Gullion, C.M., Rush, A.J., 1992. Low plasma gamma-aminobutyric acid levels in male patients with depression. Biol. Psychiatry 32, 354–363. Préville, M., Vasiliadis, H.M., Bossé, C., et al., 2011. Pattern of psychotropic drug use among older adults having a depression or an anxiety disorder: results from the longitudinal ESA study. Can. J. Psychiatry 56, 348–357. Price, R.B., Shungu, D.C., Mao, X., et al., 2009. Amino acid neurotransmitters assessed by proton magnetic resonance spectroscopy: relationship to treatment resistance in major depressive disorder. Biol. Psychiatry 65, 792–800. Rizvi, S.J., Grima, E., Tan, M., Rotzinger, S., Lin, P., McIntyre, R.S., Kennedy, S.H., 2014. Treatment resistant depression in primary care across Canada: results from the insight study. Can. J. Psychiatry 59, 349–357. Sanacora, G., Mason, G.F., Rothman, D.L., et al., 1999. Reduced cortical gammaaminobutyric acid levels in depressed patients determined by proton magnetic resonance spectroscopy. Arch. Gen. Psychiatry 56, 1043–1047. Sanyal, C., Asbridge, M., Kisely, S., et al., 2011. The utilization of antidepressants and benzodiazepines among people with major depression in Canada. Can. J. Psychiatry 56, 667–676. Schneider, F., Härter, M., Brand, S., et al., 2005. Adherence to guidelines for treatment of depression in in-patients. Br. J. Psychiatry 187, 462–469. Sheehan, D.V., Harnett-Sheehan, K., Raj, B.A., 1996. The measurement of disability. Int. Clin. Psychopharmacol. 11 (Suppl 3), 89–95. Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., et al., 1998. The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 59 (Suppl 20), 22–33. Takahashi, M.1, Shirayama, Y., Muneoka, K., Suzuki, M., Sato, K., Hashimoto, K., 2013. Low openness on the revised NEO personality inventory as a risk factor for treatment-resistant depression. PLoS One 8, e71964. Treadway, M.T., Zald, D.H., 2011. Reconsidering anhedonia in depression: lessons from translational neuroscience. Neurosci. Biobehav. Rev. 35, 537–555. Uher, R., Farmer, A., Maier, W., Rietschel, M., Hauser, J., Marusic, A., Mors, O., Elkin, A., Williamson, R.J., Schmael, C., Henigsberg, N., Perez, J., Mendlewicz, J., Janzing, J.G., Zobel, A., Skibinska, M., Kozel, D., Stamp, A.S., Bajs, M., Placentino, A., Barreto, M., McGuffin, P., Aitchison, K.J., 2008. Measuring depression: comparison and integration of three scales in the GENDEP study. Psychol. Med. 38, 289–300. Uher, R., Perlis, R.H., Henigsberg, N., Zobel, A., Rietschel, M., Mors, O., Hauser, J., Dernovsek, M.Z., Souery, D., Bajs, M., Maier, W., Aitchison, K.J., Farmer, A., McGuffin, P., 2012. Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms. Psychol. Med. 42, 967–980. Valenstein, M., Taylor, K.K., Austin, K., et al., 2004. Benzodiazepine use among depressed patients treated in mental health settings. Am. J. Psychiatry 161, 654–661. van Zessen, R., Phillips, J.L., Budygin, E.A., Stuber, G.D., 2012. Activation of VTA GABA neurons disrupts reward consumption. Neuron 73, 1184–1194. World Health Organization, 1997. WHO Collaborating Centre for Drug Statistics Methodology. ATC Index with DDD’s. Oslo:WHO. Zhang, M., 2010. Major depressive disorder treatment guidelines in China. J. Clin. Psychiatry 71 (Suppl E1), e06.
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Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research report
Correlates of benzodiazepine use in major depressive disorder: The effect of anhedonia Sakina J. Rizvi a,b,n, Beth A. Sproule c,d, Laura Gallaugher b, Roger S. McIntyre b,e, Sidney H. Kennedy b,e a
Department of Psychiatry, St. Michael’s Hospital, Toronto, Ontario, Canada Department of Psychiatry, University Health Network, Toronto, Ontario, Canada c Department of Pharmacy, Centre for Addiction and Mental Health, Toronto, Ontario, Canada d Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada e Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada b
art ic l e i nf o
a b s t r a c t
Article history: Received 25 May 2015 Received in revised form 22 July 2015 Accepted 29 July 2015 Available online 21 August 2015
Background: Current treatment guidelines emphasize the limited role of benzodiazepines in Major Depressive Disorder (MDD), mainly due to the absence of long-term data, risk of abuse and potential adverse effects. However, benzodiazepines continue to be prescribed for long-term use in a significant number of patients. This study sought to evaluate benzodiazepine use in a large sample of MDD patients seen at a tertiary care clinic, and determine whether use is related to illness severity or complexity, as well as to identify the clinical predictors of benzodiazepine use. Methods: This was a naturalistic cross-sectional study conducted in MDD patients seen at the Mood Disorders Pyschopharmacology Unit at the University Health Network (N¼ 326). Detailed information on current medication regimens was collected. A structured diagnostic interview, in addition to measures of symptom severity, quality of life, and personality were administered. Participants were grouped according to the presence or absence of prescribed benzodiazepines for daily use. Results: The prevalence of regular benzodiazepine use was 25%. Benzodiazepine users were more likely to be female, unemployed, have a history of child abuse, and have comorbid panic disorder. Depression and anxiety scores were not significantly different between groups, although anhedonia was greater in the benzodiazepine group. A logistic regression revealed anhedonia was the strongest predictor of regular benzodiazepine use. Conclusion: The groups were similar in clinical profile suggesting benzodiazepine use is not necessarily linked to greater illness complexity or severity. Benzodiazepine use appears to be associated with specific diagnostic and symptom characteristics, possibly providing insight into the potential pharmacodynamic and neurobiological effects of frequent use. & 2015 Elsevier B.V. All rights reserved.
Keywords: Benzodiazepine Major depressive disorder Anhedonia Anxiety
1. Introduction Benzodiazepines are primarily utilized as sedative hypnotics in patients with Major Depressive Disorder (MDD) to alleviate anxiety (either as a symptom of depression or as a disorder on its own) and insomnia. International guidelines recommend limited use of benzodiazepines in MDD beyond 4 weeks (Davidson, 2010; Higuchi, 2010), due to their addictive potential and negative cognitive effects in the domains of memory, attention, and psychomotor speed (Barker et al., 2004; Lader, 2011). Benzodiazepines are also
n Correspondence to: Department of Psychiatry, St. Michael’s Hospital, University Health Network, 193 Yonge St, 6-009, Toronto, ON, Canada M5B 1M8. E-mail address: [email protected] (S.J. Rizvi).
http://dx.doi.org/10.1016/j.jad.2015.07.040 0165-0327/& 2015 Elsevier B.V. All rights reserved.
associated with an increased risk of dementia as well as falls (Lavsa et al., 2010; Billioti de Gage et al., 2012). In addition to lack of efficacy data in prospective trials, there is evidence to suggest that adjunctive benzodiazepine therapy may impede antidepressant response with electroconvulsive therapy (ECT) and transcranial direct current stimulation (Delva et al., 2001; Nordenskjöld et al., 2011; Lader, 2011; Brunoni et al., 2013). Despite these findings and guideline recommendations, prescribing practices have not been significantly affected (Lai et al., 2011; Schneider et al., 2005; Zhang, 2010), and benzodiazepines remain commonly used (Olfson et al., 2015). Current estimates across Canada, the US and Europe indicate upwards of 40% of individuals with MDD are prescribed concomitant benzodiazepine therapy (Sanyal et al., 2011; Demyttenaere et al., 2008; Valenstein et al., 2004). However, chronic benzodiazepine use in depression remains
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sparsely investigated. Therefore, it is unclear whether individuals who receive benzodiazepines represent a more chronically ill and psychiatrically comorbid group or whether long-term use contributes to worse outcomes. The effect of acute benzodiazepine use on depressive symptoms can be understood by its allosteric binding to benzodiazepine receptors on GABA neurons throughout the brain, specifically the GABA-A subtype, resulting in increased GABA release (Luscher et al., 2011). However, reports of decreased GABAergic functioning following chronic benzodiazepine administration in preclinical models (Miller et al., 1990; Fahey et al., 2001; Gallager et al., 1984) suggest benzodiazepines could exacerbate depression severity. GABA signaling has been shown to directly modulate processes implicated in the etiopathology of MDD, including HPA axis signaling, neurogenesis, monoamine and glutamate transmission (Luscher et al., 2011; Biswas and Carlsson, 1977). There are also consistent reports of reduced GABA metabolites in plasma and cerebrospinal fluid in MDD compared to healthy controls (Gerner and Hare, 1981; Petty et al., 1992), in addition to neuroimaging evidence of lower concentrations of GABA in depression from adolescence into adulthood (Gabbay et al., 2012; Sanacora et al., 1999; Kugaya et al., 2003; Hasler et al., 2007; Price et al., 2009). Predictors of long-term benzodiazepine use include older age, female gender, presence of MDD or Anxiety Disorder, antidepressant initiation and pain (Hawkins et al., 2012; Manthey et al., 2011; Liu et al., 2010; Patten et al., 2010; Préville et al., 2011; Valenstein et al., 2004). However, in addition to demographic predictors, it is important to identify clinical symptoms that may predict benzodiazepine use in order to address the questions of whether exposure exacerbates illness or is a confound by association (i.e., patients with greater illness complexity are more likely to receive benzodiazepines). Therefore, the objective of this study is to evaluate benzodiazepine use in a large sample of MDD patients seen at a tertiary care clinic, and determine whether use is related to illness severity or complexity, as well as to identify the clinical predictors of benzodiazepine use.
2. Methods 2.1. Design Data for this study were extracted from the Mood Disorder Psychopharmacology Unit (MDPU) database at the Department of Psychiatry, University Health Network, Toronto. The methodology has been previously published (McIntyre et al., 2010). Briefly, patients referred for consultation to the MDPU were enrolled into a naturalistic cross-sectional study following written informed consent. Participants underwent a battery of clinician administered and self-report questionnaires during a single visit. The clinical characteristics of a subset of subjects diagnosed with MDD were assessed in relation to benzodiazepine use. 2.2. Subjects Subject selection criteria for data inclusion were: male and female patients who were between the ages of 18–60, outpatient status, met DSM-IV criteria for MDD in a current major depressive episode, confirmed through the Mini-International Neuropsychiatric Interview-Plus (MINI-Plus) (Sheehan et al., 1998). Psychiatric and medical comorbidities were allowed, as effects of comorbidity were directly related to the study aims. Only those with confirmed daily benzodiazepine use or no use were included in the analysis.
2.3. Procedure Eligible subjects provided informed consent before undergoing a battery of clinician administered and self-report questionnaires during a single visit. Assessment data used in the current study included demographic and medication information, the MINI-Plus (Sheehan et al., 1998), the HRSD-17 (Hamilton, 1960), Montgomery–Åsberg Depression Rating Scale (MADRS) (Montgomery and Åsberg, 1979), the Trimodal Anxiety Questionnaire (TAQ) (Lehrer and Woolfolk, 1982), the Quality of Life Enjoyment and Satisfaction Questionnaire (QLESQ) (Endicott et al., 1993), the Sheehan Disability Scale (SDS) (Sheehan et al., 1996), the Endicott Work Productivity Scale (EWPS) (Endicott and Nee, 1997), the NEO-Five Factor Inventory (NEO-FFI) (Costa and McCrae, 1992) and the Klein Trauma and Abuse-Neglect scale (Lizardi et al., 1995). 2.4. Statistical analysis Exploration of between group differences, using Student t-tests and Mann Whitney U tests corrected for multiple comparisons, were conducted. In order to determine group differences based on depression and anxiety scores with a power of 0.80 and an alpha of 0.05, a minimum of 60 participants per group was needed. A logistic regression was performed to determine the model that best predicted benzodiazepine use. Specifically, data were entered into a stepwise logistic regression with benzodiazepine use as the dependent variable. Differences identified in the between group analysis were included in the model as covariates.
3. Results 3.1. Subjects Of the 1861 subjects in the MDPU database, 851 subjects had a diagnosis of MDD. After excluding inpatients (n ¼ 502) and “unconfirmed” benzodiazepine users (n¼ 23), a final sample size of 326 was achieved. Participant characteristics are presented in Table 1. Benzodiazepine users were more likely to be slightly older, female, unemployed, have a history of hospitalization or child abuse and reported lower scores on the dimension of “Openness” as measured by the NEO. The overall prevalence of benzodiazepine use was 25%. Clonazepam and lorazepam were the most frequently utilized (50.6% and 45.6% of benzodiazepine users, respectively), although use with alprazolam, diazepam, temazepam, Table 1 Participant characteristics.
Age Gender (% female) Education achieved Employment status % Full-time % unemployed History of MDD hospitalization Age of MDD onset # Lifetime MDEs Family history of mental illness History of child abuse (Physical/sexual)
Non-BZD user (n¼247)
Daily BZD user (n¼ 79)
P-value
39.8 (12.6) 59.5% College/ University
44.1 (11.3) 72.2% College/ University
0.006 0.043 0.394
76.4% 23.6% 16.2%
56.3% 43.8% 31.7%
0.019
22.5 (12.2) 11.1 (23.2) 70.2%
20.8 (11.5) 11.0 (17.2) 83.7%
0.305 0.619 0.054
26.8%
40.0%
0.031
0.006
BZD: Benzodiazepine; MDD: Major Depressive Disorder; MDE: Major Depressive Episode.
S.J. Rizvi et al. / Journal of Affective Disorders 187 (2015) 101–105
3.3. Functioning differences
Table 2 Average daily dosing among benzodiazepine usersa. Benzodiazepine
DDDb (mg)
Average dose (mg)
Alprazolam (n¼ 3) Clonazepam (n¼ 40) Diazepam (n¼ 2) Lorazepam (n¼ 36) Oxazepam (n¼ 3) Temazepam (n ¼2)
1 8 10 2.5 50 20
1 3.6 7.5 2.3 30 22.5
a
Frequencies for each drug include those taking more than one benzodiaze-
pine. b
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DDD: Daily defined dose (World Health Organization, 1997).
and oxazepam was also reported. The average daily dosing is presented in Table 2. A minority of patients (8.8%) were receiving more than one benzodiazepine. The majority of patients (79.7%) were receiving a benzodiazepine adjunctively to a selective serotonin reuptake inhibitor (SSRI), serotonin and norepinephrine reuptake inhibitor (SNRI) or bupropion. Of those receiving a benzodiazepine, 36% were also taking an atypical antipsychotic, with limited concomitant use of typical antipsychotics or stimulants. With respect to comorbidities, endocrine disorders were the only medical comorbidity that was more prevalent in benzodiazepine users (80.8% vs. 65.1%, p ¼0.04, respectively), while panic disorder and obsessive compulsive disorder were the only psychiatric comorbidities that were more prevalent in benzodiazepine users (23.7% vs. 6.8%, po 0.001; 16.7% vs. 7.1%, p¼ 0.023, respectively). None of the patients met criteria for benzodiazepine abuse or dependence. 3.2. Symptom severity differences There were no differences between non-benzodiazepine users and users in depression severity based on the MADRS (20.7 vs. 23.6, respectively) or HRSD-17 (15.0 vs. 17.7, respectively). There were also no differences on the HRSD-17 anxiety subscale (2.4 vs. 3.0, respectively), although there was a trend for non-benzodiazepine users to report lower anxiety levels on the TAQ (128.4 vs.150.6, p ¼.008, respectively, did not meet multiple correction). The only depressive symptom that distinguished between groups was the anhedonia item extracted from the on the HRSD-17, where benzodiazepine users reported greater severity than non-users (2.6 vs. 1.9, p o0.001) (Fig. 1).
Benzodiazepine users reported poorer quality of life compared to non-users, based on the Q-LES-Q (44.9 vs. 35.9, po 0.001). There were trends of significance based on both the SDS and EWPS, where worse overall and occupational functioning, respectively were worse in users compared to non-users (SDS: 20.0 vs. 16.9, p ¼0.021, respectively; EWPS: 74.8 vs. 55.1, p¼ 0.002, respectively; both tests did not meet multiple correction). 3.4. Prediction model Hence, the following variables were entered into the logistic regression based on the above tests: sex, employment status, hospitalization, comorbidity (i.e., endocrine, panic disorder, obsessive compulsive disorder), NEO-openness, TAQ total score, HRSD-item 7 (anhedonia). The only unique predictor in the model was the severity of anhedonia (β ¼0.93, p ¼ 0.016), which explained 11.6% of benzodiazepine use with 85.7% accuracy. Reducing the number of covariates to include the ones that remained significant in the model resulted in a 3-term model that predicted benzodiazepine use, which included anhedonia, openness and presence of panic disorder (β ¼0.66, p o.001; β ¼ 0.74, p¼ .012; β ¼ 1.66, p ¼0.015, respectively; model accuracy: R2: 0.2, 83.7%, χ ¼37.1, p o0.001) (Table 3).
4. Discussion The present analysis identified anhedonia as the only symptom that correlated with benzodiazepine use, along with panic disorder comorbidity and a lower score on Openness as measured by the NEO. While other clinical differences were found, they did not significantly contribute to the prediction model. Furthermore, benzodiazepine users appeared to have poorer life functioning, but this effect may be independent of depression severity, which did not differ between groups. The unique finding in this study was that higher severity of anhedonia, based on the HRSD-17 item 7, was associated with benzodiazepine use. In the context of the HRSD-17, anhedonia is defined as reduced interest, effort to pursue reward, and enjoyment of reward. Anhedonia has been reported in several large scale studies as a predictor of SSRI non-response (Uher et al., 2008, 2012). This was also observed in an adolescent MDD sample, which found anhedonia to be the only unique negative predictor of time to remission and depression free days with SSRI use (McMakin et al., 2012). Providing further generalizability across treatment modalities, anhedonia was a predictor of non-response to rTMS of the dorsomedial PFC in MDD (Downar et al., 2014). Anhedonia is also a prominent symptom in patients with treatment resistance (Malhi and Berk, 2007). However, a better understanding of anhedonia and its neurobiological underpinnings are necessary in order to determine whether the presence of this symptom represents a unique subtype. Among neurotransmitters, low dopamine levels in reward pathways historically been most frequently associated with Table 3 Multivariate logistic regression model.
Fig. 1. Differences between benzodiazepine users on HAMD-17 total score, anxiety subscale and anhedonia.
Predictor
β
SE β
Wald’s χ2
p-value
Odds Ratio
Constant Anhedonia Openness Panic disorder Overall model
0.575 0.661 0.74 1.656
1.196 0.179 0.029 0.680
0.233 13.643 6.361 5.931 37.107
0.629 o 0.001 0.012 0.015 o 0.001
NA 1.937 0.929 0.191
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anhedonia, however it is clear other systems including the opioid system are integral to reward function (Treadway and Zald, 2011; Der-Avakian and Markou, 2012). A link between GABA and anhedonia has also been reported. Gabbay et al. (2012) conducted a magnetic resonance spectroscopy (MRS) study assessing GABA concentrations in depressed adolescents compared to healthy controls. Adolescents had significantly reduced GABA in the anterior cingulate cortex, a key area in depression pathophysiology (Mayberg et al., 1999; Kennedy et al., 2007; Koolschijn et al., 2009). Furthermore, when participants were categorized according to the presence of anhedonia, only those with anhedonia had reduced GABA concentrations. Parallel preclinical evidence also supports a role for GABA in anhedonia. Activation of GABA neurons in rats within the ventral tegmentum, an area that primarily expresses dopamine neurons, resulted in altered rewarding properties of sucrose manifested as decreased sucrose consumption (van Zessen et al., 2012). The study also demonstrated ventral tegmentum GABA significantly reduced dopamine transmission in surrounding regions as well, including the nucleus accumbens. Overall, the higher level of anhedonia in benzodiazepine users suggests a dysfunction in both GABA and dopamine systems (and possibly others including glutamate and opioids) that could reflect a distinct depressive subtype that is likely to be prescribed benzodiazepines. Conversely, anhedonia may be exacerbated as a consequence of chronic benzodiazepine use. The latter hypothesis suggests the possibility that benzodiazepines may limit positive depression outcomes. This is particularly relevant to individuals with treatment resistant depression as this subgroup strongly presents with anhedonia and may also be more likely to be receiving a benzodiazepine (Malhi and Berk, 2007; Rizvi et al., 2014). Interestingly, low reported openness was also a predictor for benzodiazepine use. Based on the NEO, openness refers to a willingness to engage in a variety of experiences (Costa and McCrae, 1992), and it is related to other personality traits including sensation seeking and extraversion (García et al., 2005). The link between openness and reward function has also been demonstrated in a study of treatment resistant depression, where Takahashi et al. (2013) reported low openness correlated with lower levels of reward dependence (responsivity and seeking of reward; Cloninger et al., 1993). These findings parallel those of the present study. As mentioned anhedonia in the present study was defined as decreased interest in reward as well as the ability to pursue and enjoy reward. Therefore, considering anhedonia was a strong correlate of benzodiazepine use, it follows that low openness as a personality trait would also be a related predictor. The results of this study support a distinction between functioning and depression severity among benzodiazepine users, where differences in functional outcomes exist despite a lack of group difference in overall symptom severity. Considering benzodiazepines are used to target specific symptoms of depression (insomnia and anxiety), it follows that there would be differences among specific symptoms. However, group differences in anxiety symptoms did not meet statistical significance. This could also speak to the efficacy of the benzodiazepine in treating anxiety. Importantly, the finding of poorer functional outcomes in benzodiazepine users suggests either this group represents a more impaired population, or there are extra-depression effects of benzodiazepine use in depression. The presence of panic disorder as a key discriminator between groups is consistent with the indication of benzodiazepines for anxiety. The prevalence of benzodiazepine use was lower than reported in previous studies (Valenstein et al., 2004), although there are few studies evaluating prevalence of benzodiazepine use within an MDD sample. This difference may be related to the duration and frequency of benzodiazepine use, since previous studies included all frequencies of use, while the present study specified daily use.
A separate Canadian study revealed that, of the 3% of the general population receiving a benzodiazepine, 80% had been users for more than one year (Esposito et al., 2009). Limitations of the present study include the lack of a priori design to measure the effects of chronic benzodiazepine use. These results may not be generalizable to other clinical populations owing to a lack of random sampling and, therefore, may not reflect a representative sample. In addition, benzodiazepine use included all drugs within that class, therefore, we were unable to differentiate the effect of specific benzodiazepines on anhedonia. Finally, the cross-sectional nature of this study precludes any conclusions regarding whether patients worsened across any of the indices post-benzodiazepine use or about the effect of benzodiazepine discontinuation in those currently receiving a benzodiazepine. In conclusion, the findings of the present study suggest benzodiazepine use is not necessarily linked to greater illness complexity or severity. However, it may be associated with specific diagnostic and symptom characteristics that provide insight into the effects of frequent use. Future studies should evaluate whether chronic benzodiazepine use in MDD patients reduces GABA concentrations and the extent to which this could be associated with exacerbation of anhedonic and anxiety symptoms.
Acknowledgments The authors would like to thank Zilomi Panjwani, Kari Fulton, and Beata Eisfeld for support in data collection. The maintenance of the database was supported in part by Biovail.
References Barker, M.J., Greenwood, K.M., Jackson, M., Crowe, S.F., 2004. Cognitive effects of long-term benzodiazepine use: a meta-analysis. CNS Drugs 18, 37–48. Billioti de Gage, S., Bégaud, B., Bazin, F., Verdoux, H., et al., 2012. Benzodiazepine use and risk of dementia: prospective population based study. Br. Med. J. 345, e6231. Biswas, B., Carlsson, A., 1977. The effect of intraperitoneally administered GABA on brain monoamine metabolism. Naunyn Schmiedebergs Arch. Pharmacol. 299, 47–51. Brunoni, A.R., Ferrucci, R., Bortolomasi, M., et al., 2013. Interactions between transcranial direct current stimulation (tDCS) and pharmacological interventions in the Major Depressive Episode: findings from a naturalistic study. Eur. Psychiatry 28, 356–361. Cloninger, C.R., Svrakic, D.M., Przybeck, T.R., 1993. A psychological model of temperament and character. Arch. Gen. Psychiatry 50, 975–990. Costa, P.T., McCrae, R.R., 1992. NEO Personality Inventory Professional Manual. Psychological Assessment Resources, Odessa, FL. Davidson, J.R., 2010. Major depressive disorder treatment guidelines in America and Europe. J. Clin. Psychiatry 71 (Suppl E1), e04. Delva, N.J., Brunet, D.G., Hawken, E.R., et al., 2001. Characteristics of responders and nonresponders to brief-pulse right unilateral ECT in a controlled clinical trial. J. ECT 17, 118–123. Demyttenaere, K., Bonnewyn, A., Bruffaerts, R., et al., 2008. Clinical factors influencing the prescription of antidepressants and benzodiazepines: results from the European study of the epidemiology of mental disorders (ESEMeD). J. Affect. Disord. 110, 84–93. Der-Avakian, A., Markou, A., 2012. The neurobiology of anhedonia and other reward-related deficits. Trends Neurosci. 35, 68–77. Downar, J., Geraci, J., Salomons, T.V., Dunlop, K., Wheeler, S., McAndrews, M.P., Bakker, N., Blumberger, D.M., Daskalakis, Z.J., Kennedy, S.H., Flint, A.J., Giacobbe, P., 2014. Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal repetitive transcranial magnetic stimulation in major depression. Biol. Psychiatry 76, 176–185. Endicott, J., Nee, J., 1997. Endicott Work Productivity Scale (EWPS): a new measure to assess treatment effects. Psychopharmacol. Bull. 33 (1), 13–16. Endicott, J., Nee, J., Harrison, W., et al., 1993. Quality of life enjoyment and satisfaction questionnaire: a new measure. Psychopharmacol. Bull. 29, 321–326. Esposito, E., Barbui, C., Patten, S.B., 2009. Patterns of benzodiazepine use in a Canadian population sample. Epidemiol. Psichiatr. Soc. 18, 248–254. Fahey, J.M., Pritchard, G.A., Grassi, J.M., et al., 2001. Pharmacodynamic and receptor binding changes during chronic lorazepam administration. Pharmacol. Biochem. Behav. 69, 1–8. Gabbay, V., Mao, X., Klein, R.G., et al., 2012. Anterior cingulate cortex γ-aminobutyric acid in depressed adolescents: relationship to anhedonia. Arch. Gen.
S.J. Rizvi et al. / Journal of Affective Disorders 187 (2015) 101–105
Psychiatry 69, 139–149. Gallager, D.W., Lakoski, J.M., Gonsalves, S.F., Rauch, S.L., 1984. Chronic benzodiazepine treatment decreases postsynaptic GABA sensitivity. Nature 308, 74–77. García, L.F., Aluja, A., García, Ó., Cuevas, L., 2005. Is openness to experience an independent personality dimension? J. Indiv. Differ. 26, 132–138. Gerner, R.H., Hare, T.A., 1981. CSF GABA in normal subjects and patients with depression, schizophrenia, mania, and anorexia nervosa. Am. J. Psychiatry 138, 1098–1101. Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56–62. Hasler, G., van der Veen, J.W., Tumonis, T., Meyers, N., Shen, J., Drevets, W.C., 2007. Reduced prefrontal glutamate/glutamine and gamma-aminobutyric acid levels in major depression determined using proton magnetic resonance spectroscopy. Arch. Gen. Psychiatry 64, 193–200. Hawkins, E.J., Malte, C.A., Imel, Z.E., et al., 2012. Prevalence and trends of benzodiazepine use among Veterans Affairs patients with posttraumatic stress disorder, 2003–2010. Drug Alcohol Depend. 124, 154–161. Higuchi, T., 2010. Major depressive disorder treatment guidelines in Japan. J. Clin. Psychiatry 71 (Suppl E1), e05. Kennedy, S.H., Konarski, J.Z., Segal, Z.V., Lau, M.A., Bieling, P.J., McIntyre, R.S., Mayberg, H.S., 2007. Differences in brain glucose metabolism between responders to CBT and venlafaxine in a 16-week randomized controlled trial. Am. J. Psychiatry 164, 778–788. Koolschijn, P.C., van Haren, N.E., Lensvelt-Mulders, G.J., Hulshoff Pol, H.E., Kahn, R.S., 2009. Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Hum. Brain Mapp. 30, 3719–3735. Kugaya, A., Sanacora, G., Verhoeff, N.P., et al., 2003. Cerebral benzodiazepine receptors in depressed patients measured with [123I]iomazenil SPECT. Biol. Psychiatry 54, 792–799. Lader, M., 2011. Benzodiazepines revisited—will we ever learn? Addiction 106, 2086–2109. Lai, I.C., Wang, M.T., Wu, B.J., et al., 2011. The use of benzodiazepine monotherapy for major depression before and after implementation of guidelines for benzodiazepine use. J. Clin. Pharm. Ther. 36, 577–584. Lavsa, S.M., Fabian, T.J., Saul, M.I., et al., 2010. Influence of medications and diagnoses on fall risk in psychiatric inpatients. Am J Health Syst Pharm. 67, 1274–1280. Lizardi, H., Klein, D.N., Ouimette, P.C., Riso, L.P., Anderson, R.L., Donaldson, S.K., 1995. Reports of the childhood home environment in early-onset dysthymia and episodic major depression. J. Abnorm. Psychol. 104, 132–139. Lehrer, P.M., Woolfolk, R.L., 1982. Self-report assessment of anxiety: somatic, cognitive, and behavioral modalities. J. Behav. Assess. 4, 167–177. Liu, X., Ye, W., Watson, P., Tepper, P., 2010. Use of benzodiazepines, hypnotics, and anxiolytics in major depressive disorder: association with chronic pain diseases. J. Nerv. Ment. Dis. 198, 544–550. Luscher, B., Shen, Q., Sahir, N., 2011. The GABAergic deficit hypothesis of major depressive disorder. Mol. Psychiatry 16 (4), 383–406. Malhi, G.S., Berk, M., 2007. Does dopamine dysfunction drive depression? Acta Psychiatr. Scand. 115 (Suppl 433), 116–124. Manthey, L., Giltay, E.J., van Veen, T., et al., 2011. Determinants of initiated and continued benzodiazepine use in the Netherlands study of depression and anxiety. J. Clin. Psychopharmacol. 31, 774–779. Mayberg, H.S., Liotti, M., Brannan, S.K., McGinnis, S., Mahurin, R.K., Jerabek, P.A., Silva, J.A., Tekell, J.L., Martin, C.C., Lancaster, J.L., Fox, P.T., 1999. Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am. J. Psychiatry 156, 675–682. McIntyre, R.S., Kennedy, S.H., Soczynska, J.K., Nguyen, H.T., Bilkey, T.S., Woldeyohannes, H.O., Nathanson, J.A., Joshi, S., Cheng, J.S., Benson, K.M., Muzina, D.J., 2010. Attention-deficit/hyperactivity disorder in adults with bipolar disorder or major depressive disorder: results from the international mood disorders collaborative project. Prim. Care Companion J. Clin. Psychiatry, 12, pii: PCC.09m00861. McMakin, D.L., Olino, T.M., Porta, G., Dietz, L.J., Emslie, G., Clarke, G., Wagner, K.D., Asarnow, J.R., Ryan, N.D., Birmaher, B., Shamseddeen, W., Mayes, T., Kennard, B., Spirito, A., Keller, M., Lynch, F.L., Dickerson, J.F., Brent, D.A., 2012. Anhedonia predicts poorer recovery among youth with selective serotonin reuptake
105
inhibitor treatment-resistant depression. J. Am. Acad. Child Adolesc. Psychiatry 51, 404–411. Miller, L.G., Greenblatt, D.J., Lopez, F., et al., 1990. Chronic benzodiazepine administration: effects in vivo and in vitro. Adv. Biochem. Psychopharmacol. 46, 167–175. Montgomery, S.A., Åsberg, M., 1979. A new depression scale designed to be sensitive to change. Br. J. Psychiatry 134, 382–389. Nordenskjöld, A., von Knorring, L., Engström, I., 2011. Predictors of time to relapse/ recurrence after electroconvulsive therapy in patients with major depressive disorder: a population-based cohort study. Depression Res. Treat. 2011, 470985. Olfson, M., King, M., Schoenbaum, M., 2015. Benzodiazepine use in the United States. JAMA Psychiatry 72, 136–142. Patten, S.B., Williams, J.V., Lavorato, D.H., et al., 2010. Pharmacoepidemiology of benzodiazepine and sedative-hypnotic use in a Canadian general population cohort during 12 years of follow-up. Can. J. Psychiatry 55, 792–799. Petty, F., Kramer, G.L., Gullion, C.M., Rush, A.J., 1992. Low plasma gamma-aminobutyric acid levels in male patients with depression. Biol. Psychiatry 32, 354–363. Préville, M., Vasiliadis, H.M., Bossé, C., et al., 2011. Pattern of psychotropic drug use among older adults having a depression or an anxiety disorder: results from the longitudinal ESA study. Can. J. Psychiatry 56, 348–357. Price, R.B., Shungu, D.C., Mao, X., et al., 2009. Amino acid neurotransmitters assessed by proton magnetic resonance spectroscopy: relationship to treatment resistance in major depressive disorder. Biol. Psychiatry 65, 792–800. Rizvi, S.J., Grima, E., Tan, M., Rotzinger, S., Lin, P., McIntyre, R.S., Kennedy, S.H., 2014. Treatment resistant depression in primary care across Canada: results from the insight study. Can. J. Psychiatry 59, 349–357. Sanacora, G., Mason, G.F., Rothman, D.L., et al., 1999. Reduced cortical gammaaminobutyric acid levels in depressed patients determined by proton magnetic resonance spectroscopy. Arch. Gen. Psychiatry 56, 1043–1047. Sanyal, C., Asbridge, M., Kisely, S., et al., 2011. The utilization of antidepressants and benzodiazepines among people with major depression in Canada. Can. J. Psychiatry 56, 667–676. Schneider, F., Härter, M., Brand, S., et al., 2005. Adherence to guidelines for treatment of depression in in-patients. Br. J. Psychiatry 187, 462–469. Sheehan, D.V., Harnett-Sheehan, K., Raj, B.A., 1996. The measurement of disability. Int. Clin. Psychopharmacol. 11 (Suppl 3), 89–95. Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., et al., 1998. The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 59 (Suppl 20), 22–33. Takahashi, M.1, Shirayama, Y., Muneoka, K., Suzuki, M., Sato, K., Hashimoto, K., 2013. Low openness on the revised NEO personality inventory as a risk factor for treatment-resistant depression. PLoS One 8, e71964. Treadway, M.T., Zald, D.H., 2011. Reconsidering anhedonia in depression: lessons from translational neuroscience. Neurosci. Biobehav. Rev. 35, 537–555. Uher, R., Farmer, A., Maier, W., Rietschel, M., Hauser, J., Marusic, A., Mors, O., Elkin, A., Williamson, R.J., Schmael, C., Henigsberg, N., Perez, J., Mendlewicz, J., Janzing, J.G., Zobel, A., Skibinska, M., Kozel, D., Stamp, A.S., Bajs, M., Placentino, A., Barreto, M., McGuffin, P., Aitchison, K.J., 2008. Measuring depression: comparison and integration of three scales in the GENDEP study. Psychol. Med. 38, 289–300. Uher, R., Perlis, R.H., Henigsberg, N., Zobel, A., Rietschel, M., Mors, O., Hauser, J., Dernovsek, M.Z., Souery, D., Bajs, M., Maier, W., Aitchison, K.J., Farmer, A., McGuffin, P., 2012. Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms. Psychol. Med. 42, 967–980. Valenstein, M., Taylor, K.K., Austin, K., et al., 2004. Benzodiazepine use among depressed patients treated in mental health settings. Am. J. Psychiatry 161, 654–661. van Zessen, R., Phillips, J.L., Budygin, E.A., Stuber, G.D., 2012. Activation of VTA GABA neurons disrupts reward consumption. Neuron 73, 1184–1194. World Health Organization, 1997. WHO Collaborating Centre for Drug Statistics Methodology. ATC Index with DDD’s. Oslo:WHO. Zhang, M., 2010. Major depressive disorder treatment guidelines in China. J. Clin. Psychiatry 71 (Suppl E1), e06.