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Background: Depression is one of the leading causes of the global burden of disease, and it has particularly negative consequences for elderly patients. Antidepressants are the most frequently used treatment. We present the first single-group meta-analysis examining: 1) the response rates of elderly patients to antidepressants, and 2) the determinants of antidepressants response in this population., Methods: We searched multiple databases for randomized controlled trials on antidepressants in the elderly with major depressive disorder above 65 years (last search: December 2017). Response was defined as 50% improvement on validated rating scales. We extracted response rates from studies and imputed the missing ones with a validated method. Data were pooled in a single-group meta-analysis. Additionally, several potential moderators of response to antidepressants were examined by subgroup and meta-regression analyses., Results: We included 44 studies with a total of 6373 participants receiving antidepressants. On average, 50.7% of the patients reached a reduction of at least 50% on the Hamilton Depression Scale (HAMD). Subgroup and meta-regression analyses revealed a better response to treatment for patients in antidepressant-controlled trials compared to placebo-controlled trials. Mean age, study duration, percentage of woman, severity of illness at baseline, dose of antidepressants in fluoxetine equivalents, year of publication, setting (in- or out-patients), antidepressant groups (SSRI, TCA, SSNRI, α2-antagonist, SNRI, MAO-inhibitor), ITT (intention-to-treat) analysis vs completer analysis, sponsorship and overall risk of bias were not significant moderators of response., Conclusions: Our findings suggest an improvement in symptoms can be found in about 50% of the elderly with major depressive disorder treated with antidepressants.

Background: Cognitive behavioural therapy has been used for schizophrenia, but to which extent it is effective is still controversial. Results of existing meta-analyses are of difficult interpretation, because they mainly present effect sizes in the form of standardized mean differences between intervention and control groups based on rating scales, which are of unclear clinical meaning. No meta-analysis has considered the number of patients responding to treatment yet. Based on this ground, we present the first meta-analysis examining the response rates of patients with schizophrenia and positive symptoms to cognitive behavioural therapy., Methods: We searched multiple databases for randomized controlled trials on psychological interventions of schizophrenia including patients with positive symptoms, and included for this analysis the studies on cognitive behavioural therapy (last search: January 2018). We applied a validated imputation method to calculate the number of responders from rating scales for the outcomes overall symptoms and positive symptoms, based on two criteria, at least 20% and at least 50% reduction from baseline on PANSS or BPRS total scores. Data were pooled in a single-group summary meta-analysis using R software. Additionally, several potential moderators of response to cognitive behavioural therapy were examined by subgroup and meta-regression analyses. The protocol has been registered in PROSPERO (CRD42017067795)., Results: We included 33 studies with a total of 1142 participants receiving cognitive behavioural therapy. On average, 44.5 and 13.2% of the patients reached a 20% (minimally improved) and 50% (much improved) reduction of overall symptoms. Similarly, 52.9 and 24.8% of the patients reached a 20%/50% reduction of positive symptoms. Subgroup and meta-regression analyses revealed a better treatment response in overall symptoms for patients that were not treatment resistant and in studies with researchers' allegiance. Of borderline significance was the better response in studies employing expert therapists and in patients that were more severely ill at baseline. Blinding of outcome assessor, number of sessions, treatment duration, age and gender were not significant moderators of response., Conclusions: Our findings suggest that adding cognitive behavioural therapy to pharmacotherapy brings about a minimal improvement in overall symptoms among 44.5% of its recipients. Several study and patients characteristics can moderate response rates.

Background: Data on therapeutic interventions following deliberate self harm (DSH) in patients with treatment-resistant depression (TRD) are very scant and there is no unanimous consensus on the best pharmacological option for these patients. There is some evidence that lithium treatment might be effective in reducing the risk of completed suicide in adult patients with unipolar affective disorders, however no clear cut results have been found so far. The primary aim of the present study is to assess whether adding lithium to standard therapy is an effective treatment strategy to reduce the risk of suicidal behaviour in long term treatment of people with TRD and previous history of DSH., Methods/design: We will carry out a randomised, parallel group, assessor-blinded superiority clinical trial. Adults with a diagnosis of major depression, an episode of DSH in the previous 12 months and inadequate response to at least two antidepressants given sequentially at an adequate dose for an adequate time for the current depressive episode will be allocated to add lithium to current therapy (intervention arm) or not (control arm). Following randomisation, treatment is to be taken daily for 1 year unless some clear reason to stop develops. Suicide completion and acts of DSH during the 12 months of follow-up will constitute the composite primary outcome. To preserve outcome assessor blindness, an independent adjudicating committee, blind to treatment allocation, will anonymously review all outcome events., Discussion: The results of this study should indicate whether lithium treatment is associated with lower risk of completed suicide and DSH in adult patients with treatment resistant unipolar depression, who recently attempted suicide., Trial Registration: ClinicalTrials.gov identifier: NCT00927550.