Abstract
BackgroundScientists and experts in science policy have become increasingly interested in strengthening translational research. Efforts to understand the nature of translational research and monitor policy interventions face an obstacle: how can translational research be defined in order to facilitate analysis of it? We describe methods of scientometric analysis that can do this.MethodsWe downloaded bibliographic and citation data from all articles published in 2009 in the 75 leading journals in cancer and in cardiovascular medicine (roughly 15,000 articles for each field). We calculated citation relationships between journals and between articles and we extracted the most prevalent natural language concepts.ResultsNetwork analysis and mapping revealed polarization between basic and clinical research, but with translational links between these poles. The structure of the translational research in cancer and cardiac medicine is, however, quite different. In the cancer literature the translational interface is composed of different techniques (e.g., gene expression analysis) that are used across the various subspecialties (e.g., specific tumor types) within cancer research and medicine. In the cardiac literature, the clinical problems are more disparate (i.e., from congenital anomalies to coronary artery disease); although no distinctive translational interface links these fields, translational research does occur in certain subdomains, especially in research on atherosclerosis and hypertension.ConclusionsThese techniques can be used to monitor the continuing evolution of translational research in medicine and the impact of interventions designed to enhance it.
Highlights
Scientists and experts in science policy have become increasingly interested in strengthening translational research
In this paper we extend our previous work by comparing the structure of the translational interface in oncology and cardiovascular medicine in 2009
As we have described in detail elsewhere, one approach to natural language processing (NLP) uses hard-coded dictionaries and a sequence of morphological, syntactic, semantic, pragmatic, and statistical treatments in order to recognize parts of speech, to examine relationships between terms, to resolve ambiguities, and to select candidate single- and multiword concepts[31]
Summary
Scientists and experts in science policy have become increasingly interested in strengthening translational research. One team used citation analysis to track stages in the development of angioplasty research [16,17,18] Another researcher analyzed citation networks to study the prevalence of the belief in a relationship between b-amyloid and Alzheimer’s Disease, showing for instance that researchers often failed to cite papers that did not support the model[19]. A third group looked at breast cancer research from 1945 to 2008, focusing on research output by country; countries with higher rates of international research cooperation produced papers that were more likely to be highly cited[20] Another group has looked more broadly at cancer publications and studied the impact of funding and public policy on cancer research [21,22,23]. This work shows that scientometric techniques can be a powerful way to reveal patterns in medical research and publishing that would not be evident with traditional methods of reviewing the medical literature
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