| Title |
Evolution of the “Drivers” of Translational Cancer Epidemiology: Analysis of Funded Grants and the Literature
|
|---|---|
| Published in |
American Journal of Epidemiology, March 2015
|
| DOI | 10.1093/aje/kwu479 |
| Pubmed ID | |
| Authors |
Tram Kim Lam, Christine Q. Chang, Scott D. Rogers, Muin J. Khoury, Sheri D. Schully |
| Abstract |
Concurrently with a workshop sponsored by the National Cancer Institute, we identified key "drivers" for accelerating cancer epidemiology across the translational research continuum in the 21st century: emerging technologies, a multilevel approach, knowledge integration, and team science. To map the evolution of these "drivers" and translational phases (T0-T4) in the past decade, we analyzed cancer epidemiology grants funded by the National Cancer Institute and published literature for 2000, 2005, and 2010. For each year, we evaluated the aims of all new/competing grants and abstracts of randomly selected PubMed articles. Compared with grants based on a single institution, consortium-based grants were more likely to incorporate contemporary technologies (P = 0.012), engage in multilevel analyses (P = 0.010), and incorporate elements of knowledge integration (P = 0.036). Approximately 74% of analyzed grants and publications involved discovery (T0) or characterization (T1) research, suggesting a need for more translational (T2-T4) research. Our evaluation indicated limited research in 1) a multilevel approach that incorporates molecular, individual, social, and environmental determinants and 2) knowledge integration that evaluates the robustness of scientific evidence. Cancer epidemiology is at the cusp of a paradigm shift, and the field will need to accelerate the pace of translating scientific discoveries in order to impart population health benefits. While multi-institutional and technology-driven collaboration is happening, concerted efforts to incorporate other key elements are warranted for the discipline to meet future challenges. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 4 | 80% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
| Members of the public | 1 | 20% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 11% |
| Researcher | 4 | 11% |
| Student > Ph. D. Student | 4 | 11% |
| Student > Bachelor | 3 | 8% |
| Other | 2 | 5% |
| Other | 7 | 19% |
| Unknown | 13 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 19% |
| Nursing and Health Professions | 5 | 14% |
| Social Sciences | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 7 | 19% |
| Unknown | 12 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 March 2015.
All research outputs
#13,580,253
of 24,081,774 outputs
Outputs from American Journal of Epidemiology
#7,666
of 9,248 outputs
Outputs of similar age
#119,138
of 262,952 outputs
Outputs of similar age from American Journal of Epidemiology
#54
of 87 outputs
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