In this study, we aimed to assess the efficacy and acceptability of SSRIs, SNRIs, and placebo for internalizing symptoms of children and adults diagnosed with anxiety, obsessive-compulsive, or stress-related disorders, accounting for clinical and methodological differences. Our results revealed higher efficacy of medications than placebo on the aggregate measure of internalizing symptoms. Effect sizes were small to moderate in overall psychopathology for all considered diagnoses and in all symptom domains. We also found significant results when restricting the analysis to the most used assessment instrument in each diagnosis; however, this restriction led to the exclusion of 72.71% of all available outcome measures. Moreover, estimates of efficacy were moderated by patient diagnosis, treatment duration, study funding, and study year of publication. Finally, concerning pairwise comparisons, we found small between-medication differences for paroxetine and escitalopram when compared to sertraline, considering efficacy. When evaluating acceptability through discontinuation rate due to any cause, no differences among medications were found; nevertheless, fluvoxamine was associated with a higher rate of discontinuation due to adverse events than all other medications, except fluoxetine.
8]. All included SSRIs and SNRIs showed greater reduction in overall psychopathology than placebo, with effect sizes comparable to those of other interventions in medicine . Combined with data on major depression , this should address concerns on the benefit of SSRIs and SNRIs in global mental health, given that one of the main criticisms about previous studies is that they did not account for multiple domains of emotional distress . Moreover, our findings provide support for transdiagnostic systems of psychopathology, which emphasize that psychosocial impairment is better explained and predicted by transdiagnostic dimensions than traditional diagnoses [31,32]. Studies assessing comorbidity in patients with anxiety, obsessive-compulsive, and stress-related disorders report rates above 50% . Standard network meta-analyses are designed to evaluate symptom domains separately , which might not represent most patients in clinical settings; thus, current evidence may be potentially misleading. This suggests the need to evaluate efficacy of treatments in multiple symptom domains, given that patients seek help for overall improvement in symptoms and functioning rather than improvements in specific symptom domains. In addition, there is no gold standard for assessing symptom severity for anxiety disorders, and standard network meta-analyses often restrict outcome measures to specific scales [13,14]. We also found small to moderate effect sizes when restricting the analysis to the most used assessment instrument in each diagnosis in our sensitivity analysis; nevertheless, this restriction led to the exclusion of 72.71% of all available outcome measures. This may indicate that a great amount of the literature is not included in previous studies, which significantly constraints current evidence and limits power. Hence, multiple-endpoint design also addresses low item overlap between assessment instruments, ranging from 37% similarity for anxiety scales to 45% for post-traumatic stress disorder, and concerns about biases inherent to each scale, given the inconsistent and highly heterogeneous current assessment landscape [11,12].
8] as these analyses have been recognized as the highest level of evidence in treatment guidelines . Nonetheless, unlike major depression and other narrowly defined psychiatric disorders, which allow a more “unidimensional” construct assessment, anxiety disorders are a group of highly correlated emotional disorders that require a distinct approach. The 3-level design addresses this important issue, at the same time allowing us to combine direct and indirect information in a network [34–36]. Although 3-level network meta-analyses, like standard meta-analyses, are susceptible to the quality of the primary studies, 3-level network meta-analyses may represent a significant methodological advancement to be used in this research field.
The most comprehensive network meta-analysis on medications for anxiety disorders before this analysis , which assessed only generalized anxiety disorder, found results consistent with our findings, indicating that SSRIs and SNRIs are effective for generalized anxiety disorder and that there are no significant differences among medications. Nevertheless, this previous work assessed only 89 outcome measures, which represents 18.98% of the 469 evaluated in our study. This significant difference is partially related to the exclusion of comorbidities. Given that anxiety disorders often co-occur, we understand that the inclusion of distinct disorders is a crucial aspect of this field. Bandelow and colleagues  also assessed the efficacy of antidepressants for anxiety disorders, including not only generalized anxiety disorder but also social anxiety disorder and panic disorder. Bandelow and colleagues’ work represents the largest meta-analysis in this field, evaluating 206 treatment arms related to the efficacy of medications. Without using a network meta-analysis approach, this work reported effect sizes of 2.09 for SSRIs and 2.25 for SNRIs and indicated substantial differences between medications, with effect sizes ranging from 1.06 for citalopram to 2.75 for escitalopram. These conflicting findings may be due to the use of pre–post effect sizes, which estimate the improvement within one group and not the difference between the intervention and the placebo group. This suggests a large variation in placebo response rates in trials assessing different medications for these disorders. Despite being commonly used, pre–post effect estimates have been criticized in the literature , given that it is impossible to disentangle which proportion of the effect size is caused by the intervention and which by other processes, such as natural recovery or the expectations of the patients.
9]. Sugarman and colleagues reported similar results, indicating an effect size of 0.34 based on 56 outcome measures . These discrepancies compared to our findings and to our number of outcome measures reflect a major difference related to our 3-level approach. All previous meta-analyses included only 1 outcome measure for study. We took these dependencies into account with the 3-level meta-analytical model , including assessment instrument as a random variable, and also using a network meta-analysis approach, including medication as a random variable. Moreover, these 2 previous studies restricted assessment instruments to the scales most commonly used in each diagnosis, which can lead to biased estimates and not account for co-occurring symptoms of distinct domains. Furthermore, our larger quantity of data allowed us to explore different potential moderators, given the higher statistical power.
We found no age group moderation effect, indicating that SSRIs and SNRIs are also effective for anxiety symptoms in younger individuals. These findings contrast with previous evidence on the efficacy of antidepressants for depressive symptoms indicating that children and adolescents do not present good response to treatments with SSRIs or SNRIs compared with adults . Given that the temporal relationship of comorbidity suggests that the onset of anxiety disorders often occurs earlier, aiming to reduce psychopathology and morbidity before the onset of depression may be an important prevention strategy in clinical practice to be further investigated. Also, children and adolescents do not respond as well to psychotherapy as adults do , so pharmacological interventions may be of great importance.
Strengths and limitations of the study
This study has some major strengths. To the best of our knowledge, this is the first 3-level network meta-analysis in the field of psychiatry and the largest meta-analysis to date to evaluate the efficacy of antidepressants on mental health symptoms of patients diagnosed with anxiety, obsessive-compulsive, or stress-related disorders, due to full inclusion of all available outcome measures in this field, and an extensive search for both published and unpublished trials, with no restriction regarding participant age, date of publication, or study language. This approach allows a well-powered comparison of efficacy and acceptability among these medications, exploring the multilevel structure of efficacy, avoiding exclusion of a great amount of available outcome measures, and avoiding biases related to specific symptoms or inherent to assessment instruments. Moreover, we extracted detailed clinical and methodological information for each included study, exploring potential moderators of efficacy estimates.
18], and the assumed correlation was based on previous reports concerning mental health . Lastly, we identified moderate heterogeneity in our data analysis, as expected in meta-analyses with a 3-level design and with a large number of studies . Accordingly, we explored and identified potential sources of heterogeneity through meta-regression and sensitivity analysis.
To our knowledge, our 3-level network meta-analysis represents the most comprehensive review of available evidence to date regarding the efficacy of SSRIs and SNRIs for the treatment of anxiety, obsessive-compulsive, and stress-related disorders, considering not only specific domains but all assessments of internalizing symptoms related to these disorders. Our findings, estimated using a 3-level approach, improve the evidence for the benefit of SSRIs and SNRIs for anxiety disorders, given that previous meta-analyses were restricted to specific scales or specific symptom domains, which reduces statistical power and does not reflect clinical practice. This method allowed us to properly estimate the efficacy of these medications on overall psychopathology, avoiding potential biases related to assessment instruments, and also to explore the multilevel structure of transdiagnostic efficacy. Our study might contribute to guiding psychiatrists, patients, clinicians, and policy makers on better evidence-based decisions for the initial treatment of these disorders.