Predicting treatment effects in unipolar depression: A meta-review

Gillett, George; Tomlinson, Anneka; Efthimiou, Orestis; Cipriani, Andrea

doi:10.1016/j.pharmthera.2020.107557

Cited by 21 publications

(15 citation statements)

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“…In addition, web-based GCBT could be integrated into stepped care treatments if we understand how symptom severity predicts treatment response [40]. Identifying predictors of treatment response to GCBT could also aid the development of machine learning prediction models that use patient-level data to individualize student mental health care [41]. Predictors of treatment response for traditional interventions for mood disorders include sociodemographic variables (eg, age and sex) and clinical factors (eg, symptom profiles, comorbidities, and symptom severity) [41][42][43].…”

Section: Group Cognitive Behavioral Therapymentioning

confidence: 99%

A Web-Based Group Cognitive Behavioral Therapy Intervention for Symptoms of Anxiety and Depression Among University Students: Open-Label, Pragmatic Trial

et al. 2021

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Background Anxiety and depression are common among university students, and university counseling centers are under pressure to develop effective, novel, and sustainable interventions that engage and retain students. Group interventions delivered via the internet could be a novel and effective way to promote student mental health. Objective We conducted a pragmatic open trial to investigate the uptake, retention, treatment response, and level of satisfaction with a remote group cognitive behavioral therapy intervention designed to reduce symptoms of anxiety and depression delivered on the web to university students during the COVID-19 pandemic. Methods Preintervention and postintervention self-reported data on anxiety and depression were collected using the Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9. Satisfaction was assessed postintervention using the Client Satisfaction with Treatment Questionnaire. Results A total of 175 students were enrolled, 158 (90.3%) of whom initiated treatment. Among those initiating treatment, 86.1% (135/158) identified as female, and the mean age was 22.4 (SD 4.9) years. The mean number of sessions attended was 6.4 (SD 2.8) out of 10. Among participants with clinically significant symptoms at baseline, mean symptom scores decreased significantly for anxiety (t56=11.6; P<.001), depression (t61=7.8; P<.001), and composite anxiety and depression (t60=10.7; P<.001), with large effect sizes (d=1-1.5). Remission rates among participants with clinically significant baseline symptoms were 67.7%-78.9% and were not associated with baseline symptom severity. High overall levels of satisfaction with treatment were reported. Conclusions The results of this study serve as a proof of concept for the use of web-based group cognitive behavioral therapy to promote the mental health of university students.

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Section: Group Cognitive Behavioral Therapymentioning

confidence: 99%

A Web-Based Group Cognitive Behavioral Therapy Intervention for Symptoms of Anxiety and Depression Among University Students: Open-Label, Pragmatic Trial

et al. 2021

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“…Similarly, treatment response prediction, if informed by reliable clinical and biological data, could increase the success of pharmacological treatment of MDD, reducing the quandary of the trial and error approach and ultimately leading to the identification of the most effective drug on an individual basis in a timely manner [7]. However, although research on risk prediction has produced clinically relevant models [8], treatment response prediction remains lacking [9]. Indeed, there have been several attempts to develop predictive algorithms of treatment resistance to antidepressants.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Role of Gut Microbiota in Major Depressive Disorder and in Treatment Resistance to Antidepressants

et al. 2020

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Major depressive disorder (MDD) is a common severe psychiatric illness, exhibiting sub-optimal response to existing pharmacological treatments. Although its etiopathogenesis is still not completely understood, recent findings suggest that an altered composition of the gut microbiota might play a role. Here we aimed to explore potential differences in the composition of the gut microbiota between patients with MDD and healthy controls (HC) and to identify possible signatures of treatment response by analyzing two groups of MDD patients characterized as treatment-resistant (TR) or responders (R) to antidepressants. Stool samples were collected from 34 MDD patients (8 TR, 19 R and 7 untreated) and 20 HC. Microbiota was characterized using the 16S metagenomic approach. A penalized logistic regression analysis algorithm was applied to identify bacterial populations that best discriminate the diagnostic groups. Statistically significant differences were identified for the families of Paenibacillaceae and Flavobacteriaceaea, for the genus Fenollaria, and the species Flintibacter butyricus, Christensenella timonensis, and Eisenbergiella massiliensis among others. The phyla Proteobacteria, Tenericutes and the family Peptostreptococcaceae were more abundant in TR, whereas the phylum Actinobacteria was enriched in R patients. Moreover, a number of bacteria only characterized the microbiota of TR patients, and many others were only detected in R. Our results confirm that dysbiosis is a hallmark of MDD and suggest that microbiota of TR patients significantly differs from responders to antidepressants. This finding further supports the relevance of an altered composition of the gut microbiota in the etiopathogenesis of MDD, suggesting a role in response to antidepressants.

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“…It is an approach that aims to offer a new perspective of secondary research (meta-research), a field hallmarked by the need to provide the most integrated evidence possible, and in which several novel study designs have appeared during the last years, e.g., series of systematic reviews and meta-analyses in a single Abbreviations: BMI body mass index, OR odds ratio, RR relative risk, 95% CI 95% confidence interval Note: In this table, only statistically significant risk factors that appeared in more than two studies were included publication, where the analytical unit is the umbrella review study design [88]. Likewise, other attempts refer to field-wide meta-analyses, in which a meta-analysis of observational studies is conducted on the sum of risk factors under consideration [87], or to the synthesis of systematic reviews (e.g., in Neurology [89]), systematic reviews of systematic reviews [90], overviews of systematic reviews [91], meta-reviews [92], systematic meta-reviews, comprehensive reviews [93], research-on-research [94], and meta-meta-analyses [95,96]; these are all terms and study designs that future meta-umbrella reviews should include in their search strategy. Therefore, our metaumbrella review could represent another study design added to the armamentarium of meta-research [97].…”

Section: Discussionmentioning

confidence: 99%

Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews

Mentis

Dardiotis

Efthymiou

et al. 2021

BMC Med

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Background The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases. Methods We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified. Results We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia. Conclusions We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).

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Predicting treatment effects in unipolar depression: A meta-review

Cited by 21 publications

References 100 publications

A Web-Based Group Cognitive Behavioral Therapy Intervention for Symptoms of Anxiety and Depression Among University Students: Open-Label, Pragmatic Trial

A Web-Based Group Cognitive Behavioral Therapy Intervention for Symptoms of Anxiety and Depression Among University Students: Open-Label, Pragmatic Trial

Exploring the Role of Gut Microbiota in Major Depressive Disorder and in Treatment Resistance to Antidepressants

Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews

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