ArticleContemporary clinical trials communications2017
Statistical Analysis Plan for Stage 1 EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care) Study.
Article in Contemporary clinical trials communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01407094 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) for Depression
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.Statistics in medicine · 2021Pooled it
- Early Change in Depressive Symptom Severity With Naltrexone-Bupropion Combination and Its Association With Reduction in Methamphetamine Use in ADAPT-2 Trial.The Journal of clinical psychiatry · 2025Trial
- A sparse additive model for treatment effect-modifier selection.Biostatistics (Oxford, England) · 2022Trial
- Sex differences in the association of baseline c-reactive protein (CRP) and acute-phase treatment outcomes in major depressive disorder: Findings from the EMBARC study.Journal of psychiatric research · 2019Trial
- Recent innovations in adaptive trial designs: A review of design opportunities in translational research.Journal of clinical and translational science · 2023Review
- A Single Index Model for Longitudinal Outcomes to Optimize Individual Treatment Decision Rules.Stat · 2022Article
- Multiple domain and multiple kernel outcome-weighted learning for estimating individualized treatment regimes.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2022Article
- A Bayesian approach to joint modeling of matrix-valued imaging data and treatment outcome with applications to depression studies.Biometrics · 2020Article
- Machine learning methods for developing precision treatment rules with observational data.Behaviour research and therapy · 2019Article
- Towards Algorithmic Analytics for Large-scale Datasets.Nature machine intelligence · 2019Article
- Cerebral Blood Perfusion Predicts Response to Sertraline versus Placebo for Major Depressive Disorder in the EMBARC Trial.EClinicalMedicine · 2019Article
- Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?Frontiers in psychiatry · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Antidepressant medications are commonly used to treat depression, but only about 30% of patients reach remission with any single first-step antidepressant. If the first-step treatment fails, response and remission rates at subsequent steps are even more limited. The literature on biomarkers for treatment response is largely based on secondary analyses of studies designed to answer primary questions of efficacy, rather than on a planned systematic evaluation of biomarkers for treatment decision. The lack of evidence-based knowledge to guide treatment decisions for patients with depression has lead to the recognition that specially designed studies with the primary objective being to discover biosignatures for optimizing treatment decisions are necessary. Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) is one such discovery study. Stage 1 of EMBARC is a randomized placebo controlled clinical trial of 8 week duration. A wide array of patient characteristics is collected at baseline, including assessments of brain structure, function and connectivity along with electrophysiological, biological, behavioral and clinical features. This paper reports on the data analytic strategy for discovering biosignatures for treatment response based on Stage 1 of EMBARC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.