Title |
Can Synovial Pathobiology Integrate with Current Clinical and Imaging Prediction Models to Achieve Personalized Health Care in Rheumatoid Arthritis?
|
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Published in |
Frontiers in Medicine, May 2017
|
DOI | 10.3389/fmed.2017.00041 |
Pubmed ID | |
Authors |
Frances Claire Humby, Farida Al Balushi, Gloria Lliso, Alberto Cauli, Costantino Pitzalis |
Abstract |
Although great progress has been made in the past decade toward understanding the pathogenesis of rheumatoid arthritis (RA), clinicians remain some distance from a goal of personalized health care. The capacity to diagnose RA early, predict prognosis, and moreover predict response to biologic therapies has been a research focus for many years. How currently available clinical prediction models can facilitate such goals is reviewed in this article. In addition, the role of current imaging techniques in this regard is also discussed. Finally, the authors review the current literature regarding synovial biomarkers and consider whether integration of synovial pathobiology into clinical prediction algorithms may enhance their predictive value. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Belgium | 1 | 25% |
United Kingdom | 1 | 25% |
Denmark | 1 | 25% |
Switzerland | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 50% |
Members of the public | 2 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 25 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 16% |
Student > Doctoral Student | 4 | 16% |
Researcher | 4 | 16% |
Student > Postgraduate | 2 | 8% |
Professor > Associate Professor | 2 | 8% |
Other | 4 | 16% |
Unknown | 5 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 11 | 44% |
Immunology and Microbiology | 4 | 16% |
Biochemistry, Genetics and Molecular Biology | 1 | 4% |
Computer Science | 1 | 4% |
Unknown | 8 | 32% |