You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis
|
|---|---|
| Published in |
Nature Communications, August 2016
|
| DOI | 10.1038/ncomms12460 |
| Pubmed ID | |
| Authors |
Solveig K. Sieberts, Fan Zhu, Javier García-García, Eli Stahl, Abhishek Pratap, Gaurav Pandey, Dimitrios Pappas, Daniel Aguilar, Bernat Anton, Jaume Bonet, Ridvan Eksi, Oriol Fornés, Emre Guney, Hongdong Li, Manuel Alejandro Marín, Bharat Panwar, Joan Planas-Iglesias, Daniel Poglayen, Jing Cui, Andre O. Falcao, Christine Suver, Bruce Hoff, Venkat S. K. Balagurusamy, Donna Dillenberger, Elias Chaibub Neto, Thea Norman, Tero Aittokallio, Muhammad Ammad-ud-din, Chloe-Agathe Azencott, Víctor Bellón, Valentina Boeva, Kerstin Bunte, Himanshu Chheda, Lu Cheng, Jukka Corander, Michel Dumontier, Anna Goldenberg, Peddinti Gopalacharyulu, Mohsen Hajiloo, Daniel Hidru, Alok Jaiswal, Samuel Kaski, Beyrem Khalfaoui, Suleiman Ali Khan, Eric R. Kramer, Pekka Marttinen, Aziz M. Mezlini, Bhuvan Molparia, Matti Pirinen, Janna Saarela, Matthias Samwald, Véronique Stoven, Hao Tang, Jing Tang, Ali Torkamani, Jean-Phillipe Vert, Bo Wang, Tao Wang, Krister Wennerberg, Nathan E. Wineinger, Guanghua Xiao, Yang Xie, Rae Yeung, Xiaowei Zhan, Cheng Zhao, Jeff Greenberg, Joel Kremer, Kaleb Michaud, Anne Barton, Marieke Coenen, Xavier Mariette, Corinne Miceli, Nancy Shadick, Michael Weinblatt, Niek de Vries, Paul P. Tak, Danielle Gerlag, Tom W. J. Huizinga, Fina Kurreeman, Cornelia F. Allaart, S. Louis Bridges Jr., Lindsey Criswell, Larry Moreland, Lars Klareskog, Saedis Saevarsdottir, Leonid Padyukov, Peter K. Gregersen, Stephen Friend, Robert Plenge, Gustavo Stolovitzky, Baldo Oliva, Yuanfang Guan, Lara M. Mangravite |
| Abstract |
Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 43% |
| Canada | 1 | 14% |
| United Kingdom | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 2 | 29% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 2 | 1% |
| Indonesia | 1 | <1% |
| Germany | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Unknown | 141 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 21% |
| Student > Ph. D. Student | 22 | 15% |
| Student > Master | 12 | 8% |
| Professor | 11 | 7% |
| Student > Bachelor | 8 | 5% |
| Other | 27 | 18% |
| Unknown | 36 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 26 | 18% |
| Biochemistry, Genetics and Molecular Biology | 25 | 17% |
| Agricultural and Biological Sciences | 16 | 11% |
| Computer Science | 13 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 3% |
| Other | 22 | 15% |
| Unknown | 40 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 16 November 2016.
All research outputs
#1,493,229
of 25,837,817 outputs
Outputs from Nature Communications
#21,781
of 58,118 outputs
Outputs of similar age
#26,546
of 357,770 outputs
Outputs of similar age from Nature Communications
#340
of 861 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 58,118 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.5. This one has gotten more attention than average, scoring higher than 62% 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 357,770 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 861 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 60% of its contemporaries.