| Title |
CYberinfrastructure for COmparative effectiveness REsearch (CYCORE): improving data from cancer clinical trials
|
|---|---|
| Published in |
Translational Behavioral Medicine, December 2010
|
| DOI | 10.1007/s13142-010-0005-z |
| Pubmed ID | |
| Authors |
Kevin Patrick, Laura Wolszon, Karen M Basen-Engquist, Wendy Demark-Wahnefried, Alex V Prokhorov, Stephanie Barrera, Chaitan Baru, Emilia Farcas, Ingolf Krueger, Doug Palmer, Fred Raab, Phil Rios, Celal Ziftci, Susan Peterson |
| Abstract |
Improved approaches and methodologies are needed to conduct comparative effectiveness research (CER) in oncology. While cancer therapies continue to emerge at a rapid pace, the review, synthesis, and dissemination of evidence-based interventions across clinical trials lag in comparison. Rigorous and systematic testing of competing therapies has been clouded by age-old problems: poor patient adherence, inability to objectively measure the environmental influences on health, lack of knowledge about patients' lifestyle behaviors that may affect cancer's progression and recurrence, and limited ability to compile and interpret the wide range of variables that must be considered in the cancer treatment. This lack of data integration limits the potential for patients and clinicians to engage in fully informed decision-making regarding cancer prevention, treatment, and survivorship care, and the translation of research results into mainstream medical care. Particularly important, as noted in a 2009 report on CER to the President and Congress, the limited focus on health behavior-change interventions was a major hindrance in this research landscape (DHHS 2009). This paper describes an initiative to improve CER for cancer by addressing several of these limitations. The Cyberinfrastructure for Comparative Effectiveness Research (CYCORE) project, informed by the National Science Foundation's 2007 report "Cyberinfrastructure Vision for 21(st) Century Discovery" has, as its central aim, the creation of a prototype for a user-friendly, open-source cyberinfrastructure (CI) that supports acquisition, storage, visualization, analysis, and sharing of data important for cancer-related CER. Although still under development, the process of gathering requirements for CYCORE has revealed new ways in which CI design can significantly improve the collection and analysis of a wide variety of data types, and has resulted in new and important partnerships among cancer researchers engaged in advancing health-related CI. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 11% |
| Brazil | 1 | 2% |
| Unknown | 48 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 16% |
| Student > Ph. D. Student | 8 | 15% |
| Professor | 7 | 13% |
| Student > Postgraduate | 5 | 9% |
| Professor > Associate Professor | 4 | 7% |
| Other | 10 | 18% |
| Unknown | 12 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 18% |
| Medicine and Dentistry | 10 | 18% |
| Nursing and Health Professions | 5 | 9% |
| Social Sciences | 5 | 9% |
| Business, Management and Accounting | 3 | 5% |
| Other | 10 | 18% |
| Unknown | 12 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 04 January 2017.
All research outputs
#18,812,604
of 23,314,015 outputs
Outputs from Translational Behavioral Medicine
#872
of 1,008 outputs
Outputs of similar age
#162,947
of 183,353 outputs
Outputs of similar age from Translational Behavioral Medicine
#7
of 8 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,008 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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 183,353 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.