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Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?

Overview of attention for article published in Frontiers in Psychiatry, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

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Title
Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?
Published in
Frontiers in Psychiatry, August 2018
DOI 10.3389/fpsyt.2018.00360
Pubmed ID
Authors

Jan Scott, Bruno Etain, Frank Bellivier

Abstract

Clinical practice guidelines identify lithium as a first line treatment for mood stabilization and reduction of suicidality in bipolar disorders (BD); however, most individuals show sub-optimal response. Identifying biomarkers for lithium response could enable personalization of treatment and refine criteria for stratification of BD cases into treatment-relevant subgroups. Existing systematic reviews identify potential biomarkers of lithium response, but none directly address the conceptual issues that need to be addressed to enhance translation of research into precision prescribing of lithium. For example, although clinical syndrome subtyping of BD has not led to customized individual treatments, we emphasize the importance of assessing clinical response phenotypes in biomarker research. Also, we highlight the need to give greater consideration to the quality of prospective longitudinal monitoring of illness activity and the differentiation of non-response from partial or non-adherence with medication. It is unlikely that there is a single biomarker for lithium response or tolerability, so this review argues that more research should be directed toward the exploration of biosignatures. Importantly, we emphasize that an integrative science approach may improve the likelihood of discovering the optimal combination of clinical factors and multimodal biomarkers (e.g., blood omics, neuroimaging, and actigraphy derived-markers). This strategy could uncover a valid lithium response phenotype and facilitate development of a composite prediction algorithm. Lastly, this narrative review discusses how these strategies could improve eligibility criteria for lithium treatment in BD, and highlights barriers to translation to clinical practice including the often-overlooked issue of the cost-effectiveness of introducing biomarker tests in psychiatry.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 22%
Student > Ph. D. Student 7 12%
Student > Doctoral Student 5 8%
Other 4 7%
Student > Master 4 7%
Other 5 8%
Unknown 22 37%
Readers by discipline Count As %
Medicine and Dentistry 12 20%
Neuroscience 5 8%
Psychology 4 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Biochemistry, Genetics and Molecular Biology 3 5%
Other 9 15%
Unknown 24 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 25 August 2018.
All research outputs
#4,418,748
of 25,931,626 outputs
Outputs from Frontiers in Psychiatry
#2,543
of 12,937 outputs
Outputs of similar age
#78,025
of 344,080 outputs
Outputs of similar age from Frontiers in Psychiatry
#58
of 176 outputs
Altmetric has tracked 25,931,626 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,937 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has done well, scoring higher than 80% 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 344,080 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 77% of its contemporaries.
We're also able to compare this research output to 176 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.