Comparative efficacy and tolerability of first-generation and newer-generation antidepressant medications for depressive disorders in children and adolescents: study protocol for a systematic review and network meta-analysis

Xinyu Zhou, Bin Qin, Craig Whittington, David Cohen, Yiyun Liu, Cinzia del Giovane, Kurt D. Michael, Yuqing Zhang, Peng Xie

► To cite this version:

Xinyu Zhou, Bin Qin, Craig Whittington, David Cohen, Yiyun Liu, et al.. Comparative efficacy and tolerability of first-generation and newer-generation antidepressant medications for depressive disorders in children and adolescents: study protocol for a systematic review and network meta-analysis. BMJ Open, 2015, 5 (9), pp.e007768. 10.1136/bmjopen-2015-007768. hal-01258892

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# BMJ Open Comparative efficacy and tolerability of first-generation and newer-generation antidepressant medications for depressive disorders in children and adolescents: study protocol for a systematic review and network meta-analysis

Xinyu Zhou,¹ Bin Qin,¹ Craig Whittington,² David Cohen,³ Yiyun Liu,¹ Cinzia Del Giovane,⁴ Kurt D Michael,⁵ Yuqing Zhang,¹ Peng Xie¹

**To cite:** Zhou X, Qin B, Whittington C, et al. Comparative efficacy and tolerability of first-generation and newer-generation antidepressant medications for depressive disorders in children and adolescents: study protocol for a systematic review and network meta-analysis. *BMJ Open* 2015;5:e007768. doi:10.1136/bmjopen-2015-007768

► Prepublication history for this paper is available online. To view these files please visit the journal online (http://dx.doi.org/10.1136/bmjopen-2015-007768).

XZ and BQ contributed equally.

Received 23 January 2015
Revised 6 August 2015
Accepted 12 August 2015

<figure><img src="image_2.png" /></figure>

CrossMark

For numbered affiliations see end of article.

Correspondence to
Professor Peng Xie;
xiepeng973@126.com

## ABSTRACT

**Introduction:** Depressive disorders are among the most common psychiatric disorders in children and adolescents, and have adverse effects on their psychosocial functioning. Questions concerning the efficacy and safety of antidepressant medications in the treatment of depression in children and adolescents, led us to integrate the direct and indirect evidence using network meta-analysis to create hierarchies of these drugs.

**Methods and analysis:** Seven databases with PubMed, EMBASE, the Cochrane Library, Web of Science, CINAHL, LiLACS and PsycINFO will be searched from 1966 to December 2013 (updated to May, 2015). There are no restrictions on language or type of publication. Randomised clinical trials assessing first-generation and newer-generation antidepressant medications against active comparator or placebo as acute treatment for depressive disorders in children and adolescents (under 18 years of age) will be included. The primary outcome for efficacy will be mean improvement in depressive symptoms, as measured by the mean change score of a depression rating scale from baseline to post-treatment. The tolerability of treatment will be defined as side effect discontinuation, as defined by the proportion of patients who discontinued treatment due to adverse events during the trial. We will also assess the secondary outcome for efficacy (response rate), acceptability (all-cause discontinuation) and suicide-related outcomes. We will perform the Bayesian network meta-analyses for all relative outcome measures. Subgroup analyses and sensitivity analyses will be conducted to assess the robustness of the findings.

**Dissemination:** The network meta-analysis will provide useful information on antidepressant treatment for child and adolescent depression. The results will be

## Strengths and limitations of this study

- This Bayesian network meta-analysis can integrate direct evidence with indirect evidence from multiple treatment comparisons to estimate the interrelations across all treatments.

- We will comprehensively assess the efficacy, tolerability, acceptability and suicide-related outcomes of first-generation and newer-generation antidepressant medications for depression in children and adolescents.

- Several subgroup and sensitivity analyses will address some clinically relevant questions.

- This method comprehensively synthesises data to provide a clinically useful summary that can guide treatment decisions and guideline development.

disseminated through peer-reviewed publication or conference presentations.

Trial registration number: PROSPERO
CRD42015016023.

## BACKGROUND

Depressive disorders in children and adolescents are a major public health problem, demonstrated by the disorders ranking as the third most important in the estimation of disease burden.¹ The prevalence of experiencing at least one episode of major depression before adulthood is estimated to be approximately 1–2% for children (6–12 years old), and 2–5% for adolescents (13–18 years old).²
The course of major depression in young people is often characterised by frequent recurrence, protracted episodes and comorbid psychiatric disorders.³ The con- sequences of an untreated episode of major depression in young people are likely to be serious impairment in social functioning, for example, poor school achieve- ment, or relational problems with family members and peers.⁴ A report from the American Academy of Child and Adolescent Psychiatry (AACAP) suggested that depression is responsible for over 500 000 suicide attempts by children and adolescents a year, with most of this group diagnosed with treatable forms of mental illness.⁵ ⁶ Thus, early recognition, diagnosis and treat- ment of depression in children and adolescents is an important strategy for curbing the rising rate of youth suicide, seen in many developed and advanced develop- ing nations.⁷

Since the late 1960s, first-generation antidepressants, for example, tricyclic antidepressant (TCA) drugs, have been used to treat depressive symptoms in young patients.⁸ In the US, the use of antidepressant medica- tion in children and adolescents grew 3–10-fold between 1987 and 1996.⁹ The efficacy of TCAs has been investi- gated in 13 randomised placebo-controlled trials,¹⁰ which showed marginal evidence to support the use of TCAs in the treatment of depression in only adolescents. However, methodological deficiencies in these trials, including small sample sizes and diagnostic heterogen- eity, restrict statistical inference and generalisability of the findings. At the same time, cardiovascular effects and overdose-related mortality associated with TCA use have greatly limited their utility in clinical practice.¹¹ ¹² Nevertheless, the TCA nortriptyline is still approved by the Food and Drug Administration (FDA) for the treat- ment of depression in adolescents and adults.¹³

In recent decades, newer-generation antidepressants, including second-generation antidepressants (eg, select- ive serotonin reuptake inhibitors (SSRIs)) and third- generation antidepressants (eg, serotonin-norepineph- rine reuptake inhibitors (SNRIs)), have been widely used for the treatment of depression in children and adolescents.¹⁴ The frequency of prescription of SSRIs and SNRIs in children and adolescents has progressively increased.¹⁵ In European countries, there has been a doubling of SSRI use over a 4-year period.¹⁶ However, only fluoxetine was approved by the US FDA for treating depression in children and adolescents in January 2003.¹⁷ In the same year, concerns about the increased risk of suicide and suicide attempts with SSRIs were first raised.¹⁸ In September 2004, the FDA cautioned practi- tioners in the use of antidepressant medications in chil- dren and adolescents.¹⁹ Similar warnings were issued by other health regulatory agencies.²⁰⁻²² Thus, concerns about this issue have refocused attention on the ques- tion of how effective antidepressant medications are in treating youth depression.

Nonetheless, currently, no published meta-analysis has
combined direct and indirect evidence for the use of

antidepressant medications on children and adolescents, though it is an important study to perform, given the conflicting results regarding the efficacy and tolerability of various antidepressant medications in this age group, and lack of head-to-head trials of such drugs.²³⁻²⁵ For these reasons, we will employ a network meta-analysis—a methodological approach that allows the simultaneous comparison of multiple psychotherapeutic interventions within a single analysis, while preserving randomisation.²⁶ This approach will be used to integrate direct evidence (from studies directly comparing interventions) with indirect evidence (information about two treatments derived via a common comparator) from multiple treatment comparisons to estimate the interrelations across all treatments.²⁷ We have previously compared the efficacy and acceptability of psychotherapies for depression in children and adolescents,²⁸ and the augmentation agents for treatment-resistant depression in adults²⁹ in this way. The aim of the network meta-analysis of randomised controlled trials (RCTs) is to systematically reanalyse the efficacy, tolerability, acceptability and suicide risk of both first-generation and newer-generation antidepressant medications against active comparator or control conditions, in the treatment of child and adolescent depression.

METHODS

Criteria for included studies

Types of studies

Any prospective RCTs, including cross-over design and cluster randomised trials, will be included. However, quasi-randomised trials (eg, those allocating using alternate days of the week) will be excluded. Trials with sample sizes smaller than 10 will be excluded in this review.

Types of participants

Children and adolescents (aged from 6 to 18 years when they initially enrolled in the trials) with a primary diagnosis of current major depressive disorder according to standardised diagnostic interviews, for example, the Diagnostic and Statistical Manual of Mental Disorders (DSM)³⁰⁻³² or the International Classification of Diseases (ICD),³³ ³⁴ will be included. Where a trial contains a portion of participants who are over 18 years of age, we will contact the trial authors in order to obtain data for only those participants within our age range. We will exclude trials focusing on child or adolescent bipolar disorder, but will include trials involving patients with comorbid general psychiatric disorders, such as attention deficit hyperactivity disorder, anxiety disorder and substance-related disorder. Also, we will not exclude trials in which participants have a diagnosis of psychotic depression; these participants will be considered within a separate subgroup analysis. However we will exclude trials in which participants have a diagnosis of treatment-resistant depression, because these patients tend to have a different treatment response compared with patients with non-resistant depression.
## Types of interventions

RCTs comparing any first-generation and newer-generation antidepressant drug against active comparator or placebo for treatment of depression in children and adolescents will be included. Trials comparing the same type of antidepressant but at different therapeutic dose (fixed or flexible dose) and different treatment duration will be considered as the same node in the network analysis. We will exclude trials involving combination therapy (ie, combination of antidepressant medications, combination of antidepressant medication with psychotherapy, or other non-psychotherapeutic interventions); however, trials will be considered as eligible if the concomitant psychotherapy is not predefined in the study.

## Types of outcome measures

The acute phase will be defined as from 4 to 16 weeks, and if a trial presents data beyond 16 weeks or for more than one time period within our predefined acute phase periods, we will take the 8-week or close to 8-week time point.³⁵ We will exclude trials with treatment duration of <4 weeks. Where depression symptoms are measured using more than one depression scale in a trial, we will extract data from the depressive scales on the basis of a hierarchy of rating scales. This hierarchy will be based on psychometric properties and appropriateness for use with children and adolescents, and for consistency of use across trials (referred from the Hetrick¹⁴ *et al* study) (table 1). The Children's Depression Rating Scale Revised (CDRS-R)³⁶ is adapted for children and adolescents from the Hamilton Depression Rating Scale (HAMD),³⁷ a tool validated and commonly used in adult populations.³⁸ Both the CDRS-R and HAMD have good reliability and validity.³⁸ The Beck Depression Inventory (BDI)³⁹ and the Children's Depression Inventory (CDI)⁴⁰ are the most commonly used among depression symptom severity self-rated scales and are ranked second highest in the hierarchy.

### 1. Overall efficacy

The primary outcome for efficacy will be mean improvement in depressive symptoms, as measured by the mean change score of depression rating scales (self-rated or assessor-rated) from baseline to end point.

The secondary outcome for efficacy will be response in depressive symptoms, as estimated by the proportion of patients who achieved a decrease of a certain percentage (eg, a reduction of 50% or more) in depression rating score.⁴¹ When 'response' is not reported, we will use 'remission', if available. Remission will be defined as the proportion of patients who achieved a depression rating score below the published threshold (eg, CDRS-R≤28).⁴¹

### 2. Overall tolerability

The tolerability of treatment will be defined as side effect discontinuation in this review, as defined by the

<table><caption>**Table 1** Hierarchy of depression symptom severity measurement scales</caption><thead><tr><th>Hierarchy</th><th>Depression symptom severity measurement scales</th><th>Abbreviation</th></tr></thead><tbody><tr><td>1</td><td>Children's Depression Rating Scale</td><td>CDRS</td></tr><tr><td>2</td><td>Hamilton Depression Rating Scale</td><td>HAMD</td></tr><tr><td>3</td><td>Montgomery Asberg Depression Rating Scale</td><td>MADRS</td></tr><tr><td>4</td><td>Beck Depression Inventory</td><td>BDI</td></tr><tr><td>5</td><td>Children's Depression Inventory</td><td>CDI</td></tr><tr><td>6</td><td>Schedule for Affective Disorders and Schizophrenia for School Aged Children</td><td>K-SADS</td></tr><tr><td>7</td><td>Mood and Feeling Questionnaire</td><td>MFQ</td></tr><tr><td>8</td><td>Reynolds Adolescent Depression Scale</td><td>RADS</td></tr><tr><td>9</td><td>Bellevue Index of Depression</td><td>BID</td></tr><tr><td>10</td><td>Child Depression Scale</td><td>CDS</td></tr><tr><td>11</td><td>Centre for Epidemiologic Studies Depression Scale</td><td>CESD</td></tr><tr><td>12</td><td>Child Assessment Schedule</td><td>CAS</td></tr><tr><td>13</td><td>Child Behaviour Checklist—Depression</td><td>CBCL-D</td></tr></tbody></table>

proportion of patients who discontinued treatment due to adverse events during the study.

### 3. Overall acceptability

The acceptability of treatment will be defined as all-cause discontinuation, as measured by the proportion of patients who discontinued treatment (during the delivery of the intervention) up to the post-intervention time point.

### 4. Suicide-related outcomes

Suicide-related dichotomous and continuous outcomes will be measured. If data are available, we will extract the number of participants with suicide-related events (combined suicidal ideation and suicidal behaviour) during the acute treatment, as measured on a standardised, validated and reliable rating scale, or reported cases of suicidality.⁴² In addition, we will also collect data on suicidal ideation as a continuous outcome where a standardised, validated and reliable rating scale, such as the Suicidal Ideation Questionnaire-Junior High School version (SIQ-JR),⁴³ has been used.

## Data sources and search strategy

Seven electronic databases (PubMed, EMBASE, the Cochrane Library, Web of Science, CINAHL, LiLACS and PsycINFO) will be searched from 1966 to December 2013 (updated to May, 2015), with Medical Subject Headings (MeSH) and text words: 'depress*' or 'dysthymi*' or 'mood disorder*' or 'affective disorder*' and 'selective serotonin reuptake inhibitor*' or 'SSRIs' or
'serotonin norepinephrine reuptake inhibitor*' or
'SNRIs' or 'noradrenergic and specific serotonergic anti-
depressants' or 'NaSSA' or 'citalopram' or 'fluoxetine'
or 'paroxetine' or 'sertraline' or 'escitalopram[' or 'flu-
voxamine' or 'venlafaxine' or 'duloxetine' or 'milnaci-
pran' or 'reboxetine' or 'bupropion' or 'mirtazapine' or
'tricyclic' or 'amersergide' or 'amineptine' or 'amitriptyl-
ine' or 'amoxapine' or 'butriptyline' or 'chlorpoxiten'
or 'clomipramine' or 'clorimipramine' or 'demexipti-
line' or 'desipramine' or 'dibenzipin' or 'dothiepin' or
'doxepin' or 'imipramine' or 'lofepramine' or 'melitra-
cen' or 'metapramine' or 'nortriptyline' or 'noxiptiline'
or 'opipramol' or 'protriptyline' or 'quinupramine' or
'tianeptine' or 'trimipramine' and 'adolesc*' or 'child*'
or 'boy*' or 'girl*' or 'juvenil*' or 'minors' or 'paedia-
tri*' or 'pediatri*' or 'pubescen*' or 'school*' or
'student*' or 'teen*' or 'young' or 'youth*'. Also,
ClinicalTrials.gov, WHO's trial portal, and US FDA
reports will be reviewed. There are no restrictions on
language or type of publication. Additional studies will
be searched in the reference lists of all identified publi-
cations including relevant meta-analyses and systematic
reviews. All relevant authors and principal manufac-
turers will be contacted to supplement incomplete
reports of the original papers or to provide new data for
unpublished trials.

Study selection

Two reviewers (BQ and YL) will independently scan cita-
tions at the title/abstract level identified from the search
strategies and then obtain potentially relevant studies in
full text, and determine whether to include them by the
same eligibility criteria. Besides, the references of rele-
vant reviews and included trials will also be checked by
the two reviewers. The reasons for exclusion of trials will
be reported in the characteristics of excluded studies
tables. Any disagreements will be resolved by a third
review author (XZ).

Data extraction and risk of bias assessment

Two independent reviewers (YL, BQ) will independently
extract the key trial parameters using a standardised
data abstraction form and assess the risk of bias. The
standardised data extraction forms will include the trial
characteristics (eg, first listed author, publication year,
journal, country, institution and sponsor), patient
characteristics (eg, diagnostic criteria for depression, the
type of patients, the number of patients, level of depres-
sive symptoms, comorbidities, the age of patients and
the gender of patients), intervention details (eg, anti-
depressant type, dose of antidepressant and the duration
of treatment) and outcome measures (efficacy, tolerabil-
ity, acceptability and suicide-related outcome). The risk
of bias in trials will be assessed by the Cochrane risk of
bias tool.⁴² Trials attracting a rating of high risk of bias
in one or more domains will be considered as 'high
risk', low risk of bias in all domains as 'low risk' and one
or more unclear risk of bias in each domain as 'unclear

risk’.⁴² Any disagreements will be resolved by a third
review author (XZ). In addition, we will calculate the
inter-rater reliability of the two raters.

Data synthesis and analysis

We will perform Bayesian network meta-analysis to
compare the relative outcomes of different antidepres-
sant medications and placebo with each other from the
median of the posterior distribution.²⁶ ²⁷ The pooled
estimates of standardised mean difference (SMD) with
95% credible intervals (CrIs) will be calculated for the
continuous outcomes; and ORs with 95% CrIs will be
calculated for the categorical outcomes. The SMD is
that the difference in means (MD) of change scores
between the two groups divided by the pooled SD of the
measurements, with a negative SMD value, indicates
greater symptomatic relief. In the presence of minimally
informative priors, CrIs can be interpreted similarly to
CIs, and at conventional levels of statistical significance a
two sided p<0.05 can be assumed if 95% CrIs do not
include 0. If means and SDs are not provided, we will
calculate them from the p value or other statistical
indices as described elsewhere.⁴⁴ ⁴⁵ Results from
intention-to-treat analysis (ITT) or modified ITT will be
preferred over results from completer analyses, while we
will also consider the data set for the means and SDs
that are presented in the literature.

The pooled estimates will be obtained using the
Markov Chains Monte Carlo method. Two Markov chains
will be run simultaneously with different arbitrarily
chosen initial values. To ensure convergence, trace plots
and the Brooks-Gelman-Rubin statistic will be assessed.⁴⁶
Convergence will be found to be adequate after running
50 000 samples for both chains. These samples will be
then discarded as 'burn-in', and posterior summaries will
be based on 100 000 subsequent simulations. The node
splitting method will be used to calculate the inconsist-
ency of the model, which separates evidence on a particu-
lar comparison into direct and indirect evidence.⁴⁷
Probability values will be summarised and reported as
surface under the cumulative ranking curve (SUCRA)
and rankograms, a simple transformation of the mean
rank used to provide a hierarchy of the treatments and
accounts for both the location and the variance of all
relative treatment effects.⁴⁸ Network meta-analysis will be
performed using the WinBUGS software package
(V.1.4.3, MRC Biostatistics Unit, Cambridge, UK) with
random-effects models for multiarm trials. The other
analyses will be performed and presented by the Stata
V.11.0 and R 2.11.1 software packages.

Subgroup analyses

The antidepressant medications will be coded according
to clinical characteristics, risk of bias and sample size.
We will conduct the subgroup analyses of data in
primary outcome for efficacy. We will perform the fol-
lowing subgroup analyses by using the meta-regression
model, and calculate Somer's D (a correlation
coefficient for a dichotomous and an ordinal variable):⁴⁹
(1) sex ratio (male-to-female ratio >1 vs male-to-female ratio <1); (2) age group; (3) treatment duration; (4) severity of depressive symptom (mild-to-moderate vs moderate-to-severe); (5) comorbid general psychiatric disorders (with vs without comorbidity); (6) risk of bias ('high risk' literature vs 'unclear and low risk' literature); (7) sample size; (8) company sponsor (with vs without sponsor); and (9) the type of trials (published literature vs unpublished literature). When there is the limitation of a small number of comparisons for some potential modifiers in carrying out subgroup analyses on these variables, we will perform the sensitivity analyses by omitting specific trials from the overall analysis.

## Other analyses

Funnel plot analyses will be performed to check for publication bias. Moreover, we will carry out meta-regression analyses to investigate the effect of sponsorship or year published on outcome estimate.

## Ethics and dissemination

This network meta-analysis does not need ethical approval, as data used here are not individual or private. The analysis will be published in a peer-reviewed journal. The results will provide a general overview, and evidence of efficacy and safety of antidepressant medications for depression in children and adolescents. The results will also have implications for clinical practice and further research.

## Author affiliations

**Collaborators** Andrea Cipriani and Sarah E Hetrick.

**Contributors** XZ and BQ conceived the study and drafted the protocol. XZ and PX wrote the first draft of the manuscript. KDM, CW and DC assisted in protocol design and revision. YL and YZ participated in the search strategy development. CDG and BQ participated in the design of data synthesis and analysis. All the authors have approved the publication of the protocol.

**Funding** This work is supported by the National Basic Research Program of China (973 Program) (grant number 2009CB918300).

**Competing interests** None declared.

**Provenance and peer review** Not commissioned; externally peer reviewed.

**Open Access** This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

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<footnote n="1">¹Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China</footnote>

<footnote n="2">²Research Department of Clinical, Educational and Health Psychology, University College London, London, UK</footnote>

<footnote n="3">³Department of Child and Adolescent Psychiatry, AP-HP, Hôpital Pitié-Salpétrière, Institut des Systèmes Intelligents et de Robotiques (ISIR), Centre National pour la Recherche Scientifique, Université Pierre et Marie Curie, Paris, France</footnote>

<footnote n="4">⁴Department of Diagnostic, Clinical, and Public Health Medicine, University of Modena and Reggio, Emilia, Modena, Italy</footnote>

<footnote n="5">⁵Department of Psychology, Appalachian State University, Boone, North Carolina, USA</footnote>
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# Comparative efficacy and tolerability of first-generation and newer-generation antidepressant medications for depressive disorders in children and adolescents: study protocol for a systematic review and network meta-analysis

Xinyu Zhou, Bin Qin, Craig Whittington, David Cohen, Yiyun Liu, Cinzia Del Giovane, Kurt D Michael, Yuqing Zhang and Peng Xie

BMJ Open 2015 5:

doi: 10.1136/bmjopen-2015-007768

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