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Background Lithium augmentation of antidepressants for treatment of unipolar major depression was one of the first adjunctive strategies based on a neuropharmacologic rationale. Randomized controlled trials supported its efficacy but most trials added lithium to tricyclic antidepressants (TCAs). Despite its efficacy, use of lithium augmentation remains infrequent. The current systematic review and meta-analysis examines the efficacy of lithium augmentation as an adjunct to second generation antidepressants as well as to TCAs and considers reasons for its infrequent use. Method A systematic search of Medline and the Cochrane Clinical Trials database was performed. Randomized, placebo-controlled trials of lithium augmentation were selected. A fixed-effects meta-analysis was performed. Odds ratios for response were calculated for each treatment-control contrast, for the trials grouped by type of initial antidepressant (TCA or second generation antidepressant), and as a meta-analytic summary for all treatments combined. Results Nine trials that included 237 patients were selected. The odds ratio for response to lithium vs. placebo in all contrasts combined was 2.89 (95% CI 1.65, 5.05, z=3.72, p=0.0002). Heterogeneity was very low, I²=0%. Adjunctive lithium was effective with TCAs (7 contrasts) and with second generation agents (3 contrasts). Discontinuation due to adverse events was infrequent and did not differ between lithium and placebo. Limitations The meta-analysis is limited by the small size and number of trials and limited data for treatment resistant patients. Conclusions Adjunctive lithium appears to be as effective for second generation antidepressants as it was for the tricyclics. [ABSTRACT FROM AUTHOR]

Background: Uncontrolled antidepressant trials suggest that anxious patients with major depressive disorder (MDD) are less responsive to antidepressant treatment than less anxious patients. The objective of this study is to determine whether specific antidepressant effects, estimated by drug-placebo differences, are reduced in anxious depression during treatment of MDD with duloxetine. Methods: This is a retrospective secondary pooled analysis of all placebo-controlled trials of duloxetine at therapeutic doses conducted by the sponsor in outpatients with nonpsychotic unipolar MDD, using the Hamilton Depression Rating Scale (HAMD). Anxious depression was defined by ≥7 on the anxiety/somatization factor of the HAMD. Response was defined as ≥50% improvement from baseline to endpoint on the HAMD. Remission was defined as an endpoint HAMD≤7. Analyses were performed in the intent-to-treat sample with at least one post-treatment rating. Results: Eleven trials included 2,841 patients of whom 1,326 were classified as anxious and 1,515 as nonanxious. Change on the HAMD was greater with duloxetine than placebo in both anxious (9.91 versus 7.55, P<.001) and nonanxious (6.65 versus 5.23, P<.001) patients. Level of anxiety had no effect on the drug–placebo differences. Response and remission rates were significantly greater in duloxetine than placebo-treated patients and drug–placebo differences were unaffected by anxious status. Use of HAMD items psychic and somatic anxiety to define anxious subgroups had similar outcomes. Conclusions: Duloxetine was more effective than placebo in achieving response and remission in both anxious and nonanxious patients. Anxious status did not affect the magnitude of the drug effect. Depression and Anxiety, 2010. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

The author reflects on a study which demonstrates the successful use of adjunctive L-methylfolate as treatment for patients with major depressive disorder. He says that study involved two trials, the comparison of L-methylfolate and placebo in 148 patients with nonpsychotic unipolar depression and the use of 15 milligrams per day (mg/day) L-methylfolate or placebo in 75 patients. He is interested on the impact of L-methylfolate's long-term administration in depressed individuals.

The article comments the study on the sequential series of treatments for depression. The author stresses the aspects which made this study differs from typical clinical trials. An overview of the reasons behind the decline of remission rates in patients is offered. He asserts that the study provides an interesting information about relapse but it limits in offering comparisons between treatment strategies.

The article reports on a clinical trial which showed that mirtazapine orally disintegrating tablets were well tolerated and effective in reducing depression in nursing home residents 85 years of age or older. The study reported a mean increase in weight among treated subjects of 1.1 lbs by day 28 and 1.32 lbs by day 84.

Background Randomised, placebo-controlled trials of treatments for depression typically collect outcomes data but traditionally only analyse data to demonstrate efficacy and safety. Additional post-hoc statistical techniques may reveal important insights about treatment variables useful when considering inter-individual differences amongst depressed patients. This paper aims to examine the Gradient Boosted Model (GBM), a statistical technique that uses regression tree analyses and can be applied to clinical trial data to identify and measure variables that may influence treatment outcomes. Methods GBM was applied to pooled data from 12 randomised clinical trials of 4987 participants experiencing an acute depressive episode who were treated with duloxetine, an SSRI or placebo to predict treatment remission. Additional analyses were conducted on the same dataset using the logistic regression model for comparison between these two methods. Results With GBM, there were noticeable differences between treatments when identifying which and to what extent variables were associated with remission. A single logistic regression only revealed a decreasing or increasing relationship between predictors and remission while GBM was able to reveal a complex relationship between predictors and remission. Limitations These analyses were conducted post-hoc utilising clinical trials databases. The criteria for constructing the analyses data were based on the characteristics of the clinical trials. Conclusions GBM can be used to identify and quantify patient variables that predict remission with specific treatments and has greater flexibility than the logistic regression model. GBM may provide new insights into inter-individual differences in treatment response that may be useful for selecting individualised treatments. Trial registration IMPACT clinical trial number 3327; IMPACT clinical trial number 4091; IMPACT clinical trial number 4689; IMPACT clinical trial number 4298; NCT00071695; NCT00062673; NCT00036335; NCT00067912; NCT00073411; NCT00489775; NCT00536471; NCT00666757 (note that trials with IMPACT numbers predate mandatory clinical trial registration requirements) [ABSTRACT FROM AUTHOR]