Investigating data-driven biological subtypes of psychiatric disorders using specification-curve analysis.

Background: Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results.

Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics.

The identification of biomarkers associated with major depressive disorder (MDD) holds great promise to develop an objective laboratory test. However, current biomarkers lack discriminative power due to the complex biological background, and not much is known about the influence of potential modifiers such as gender. We first performed a cross-sectional study on the discriminative power of biomarkers for MDD by investigating gender differences in biomarker levels.

Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping.

Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies.

Effectiveness of psychotherapy for treatment-resistant depression: a meta-analysis and meta-regression.

Despite substantial advances in treatment and management strategies for major depression, less than 50% of patients respond to first-line antidepressant treatment or psychotherapy. Given the growing number of controlled studies of psychotherapy for treatment-resistant depression (TRD) and the preference for psychotherapy of depressed subjects as a treatment option, we conducted a meta-analysis and meta-regression analysis to investigate the effectiveness of psychotherapy for TRD. Seven different psychotherapies were studied in 21 trials that included a total of 25 comparisons.

Biomarker-based subtyping of depression and anxiety disorders using Latent Class Analysis. A NESDA study.

Background: Etiological research of depression and anxiety disorders has been hampered by diagnostic heterogeneity. In order to address this, researchers have tried to identify more homogeneous patient subgroups. This work has predominantly focused on explaining interpersonal heterogeneity based on clinical features (i.

Spin in RCTs of anxiety medication with a positive primary outcome: a comparison of concerns expressed by the US FDA and in the published literature.

Objectives: This study aimed to determine the presence of spin in papers on positive randomised clinical trials (RCTs) of antidepressant medication for anxiety disorders by comparing concerns expressed in the Food and Drug Administration (FDA) reviews with those expressed in the published paper.

Methods: For every positive anxiety medication trial with a matching publication (n=41), two independent reviewers identified the concerns raised in the US FDA reviews and those in the published literature. Spin was identified when concerns or limitations were expressed by the FDA (about the efficacy of the study drug) but not in the corresponding published paper.

Bias in the reporting of harms in clinical trials of second-generation antidepressants for depression and anxiety: A meta-analysis.

Previous research has shown that reporting bias has inflated the apparent efficacy of antidepressants. We investigated whether apparent safety was also affected. We included 133 trials, involving 31,296 patients, of second-generation antidepressants for the treatment of major depressive disorder (MDD) or anxiety disorders, obtained from Food and Drug Administration (FDA) reviews.