20 November 2008
Contact: Maggie De Pano, DCRI Communications

Duke researchers called for the integration of traditional clinical epidemiology with six other disciplines to take advantage of unprecedented developments in biological sciences and information technology.

In an editorial published November 19 in The Journal of the American Medical Association, Robert M. Califf, M.D., Director of the Duke Translational Medicine Institute, and Geoffrey Ginsburg, M.D., Ph.D., Director of the Center for Genomic Medicine at the Duke Institute for Genome Sciences & Policy, advocated that traditional clinical epidemiology be placed within a systems framework that integrates its contributions with those of biobanking, genomics and molecular profiling, imaging, bioinformatics, biostatistics, and decision making.

Connecting these once-isolated areas would benefit clinicians and the public if necessary preconditions are met, the authors wrote.

Traditional clinical epidemiology assesses and describes the causes and distribution of disease in patients based on observable characteristics such as morphology, development, and behavior.

These characteristics, known as phenotypes, result from the expression of a patient’s genes, the influence of environmental factors, and interactions between the two.

However, scientific and technological innovations now allow clinicians to study not just outward characteristics but also molecular pathways, the signaling systems by which cells read and react to their environment. Understanding how a series of molecular actions can lead to certain cell functions has enabled more accurate estimations of prognosis. It has also made personalized medicine possible, where treatments with higher probabilities of benefit and lower risks of toxicity can be matched to patients based on their molecular "signatures."

Appropriate strategies

Califf and Ginsburg emphasized, however, that appropriate strategies must be developed within the biomedical enterprise to maximize the potential of these innovations. They described specific actions associated with each of the disciplines that are essential to successful integration and the hastening of a medical revolution.

In summary, participants within the clinical and biomedical enterprise need to:

• Agree on standard classifications of clinical phenomena and measurements of research outcomes (traditional clinical epidemiology);

• Clarify ethical rules governing biobanking and assign higher priority to the coordination of biospecimen collection (biobanking);

• Make genomic technologies broadly available through shared consortia within and among institutions (genomics and molecular profiling);

• Focus on standards that allow imaging data to be combined and correlated with other data about individual patients and whole populations (imaging);

• Develop effective cross-platform systems that facilitate cooperation among industry, academia, the National Institutes of Health (NIH), and other groups so that a unified concept of data sharing can be achieved (bioinformatics);

• Address the critical shortage of biostatisticians and existing deficits in clinicians’ and researchers’ quantitative skills (biostatistics); and

• Stress, as part of healthcare professionals’ training, the importance of understanding the biology, psychology, and sociology of human decision-making (decision-making).

Califf and Ginsburg encouraged interdisciplinary investigative teams to meet these conditions by developing, aggregating, and sharing “disease state models” that integrate their fundamental knowledge with clinical and molecular databases and population records. They noted that this enhanced field of modern clinical epidemiology can provide intensive cross-sectional information about patient populations and long-term data on outcomes to improve healthcare.

In the meantime, funding agencies, academic health systems, regulatory agencies, and payers should anticipate and plan for the changes that this interdisciplinary work will entail.