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Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Overview of attention for article published in BMC Psychiatry, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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11 X users
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1 patent
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1 Facebook page

Citations

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116 Dimensions

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Title
Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort
Published in
BMC Psychiatry, April 2016
DOI 10.1186/s12888-016-0785-x
Pubmed ID
Authors

Raymond W. Lam, Roumen Milev, Susan Rotzinger, Ana C. Andreazza, Pierre Blier, Colleen Brenner, Zafiris J. Daskalakis, Moyez Dharsee, Jonathan Downar, Kenneth R. Evans, Faranak Farzan, Jane A. Foster, Benicio N. Frey, Joseph Geraci, Peter Giacobbe, Harriet E. Feilotter, Geoffrey B. Hall, Kate L. Harkness, Stefanie Hassel, Zahinoor Ismail, Francesco Leri, Mario Liotti, Glenda M. MacQueen, Mary Pat McAndrews, Luciano Minuzzi, Daniel J. Müller, Sagar V. Parikh, Franca M. Placenza, Lena C. Quilty, Arun V. Ravindran, Tim V. Salomons, Claudio N. Soares, Stephen C. Strother, Gustavo Turecki, Anthony L. Vaccarino, Fidel Vila-Rodriguez, Sidney H. Kennedy, on behalf of the CAN-BIND Investigator Team

Abstract

Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 269 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Portugal 1 <1%
Unknown 265 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 42 16%
Student > Ph. D. Student 36 13%
Researcher 36 13%
Student > Master 30 11%
Professor 15 6%
Other 51 19%
Unknown 59 22%
Readers by discipline Count As %
Psychology 54 20%
Neuroscience 38 14%
Medicine and Dentistry 37 14%
Computer Science 9 3%
Biochemistry, Genetics and Molecular Biology 8 3%
Other 46 17%
Unknown 77 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 January 2021.
All research outputs
#3,690,725
of 25,756,911 outputs
Outputs from BMC Psychiatry
#1,486
of 5,511 outputs
Outputs of similar age
#53,600
of 297,942 outputs
Outputs of similar age from BMC Psychiatry
#25
of 104 outputs
Altmetric has tracked 25,756,911 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,511 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 297,942 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.