Testimony by Jeff Allen, PhD, Executive Director, Friends of Cancer Research, April 14, 2009

Good afternoon.  My name is Jeff Allen, Executive Director of Friends of Cancer Research.  My brief remarks are based on a project we recently convened to bring 23 leading cancer researchers and advocates together in order to provide recommendations on the future of comparative effectiveness research (CER).  The final report from this group will be released on May 13^th.

The recent commitment in the American Reinvestment & Recovery Act of 2009 to comparative effectiveness research and other health programs present the one of the greatest opportunities to improve this country’s research infrastructure since the doubling of the NIH. 

CER has historically been conducted to generate evidence that is lacking surrounding the use of different medical interventions, and is often based on literature reviews of individual trials.

These reviews generally cannot create new knowledge, provide little insight into the effectiveness of health care interventions outside of clinical trials, and will not lead to a health care system that develops research insights as a natural byproduct of the care process. 

In order to truly improve understanding of the outcomes of different treatment options and health services, and to incorporate emerging information as it is developed, a new model and system for performing CER is needed.

Given limited resources, the impossibility of designing randomized clinical trials to answer every question, and the rapid evolution of scientific data, the analysis of data on large numbers of patients, by linking public and private databases, could be a useful hypothesis generating tool.

The databases routinely established, maintained, and audited for clinical research (and in some cases, preclinical research) contain detailed information about individual patients and their health outcomes. Administrative databases such as insurance claims databases, though not as detailed as clinical databases, are another potentially valuable source of information on health outcomes and associated factors.

Insufficient funding for any public or private entity responsible for aligning and maintaining a robust data network has resulted in piecemeal and potentially misleading clinical outcomes research. 

A coordinated effort to link currently isolated public and private databases has the potential to generate an unprecedented amount of information for a variety of research activities.

To support the growth of personalized medicine, which is essential for the future of cancer research, the analysis of data from integrated networks can begin to identify factors that contribute to disease susceptibilities and characteristics that result in different outcomes to treatment.

It is important not to over generalize from these analyses, ensure privacy, and to acknowledge that understanding the biological basis for any difference identified through data analysis will require additional research.  

However, the initial data analysis will help identify gaps in evidence and generate new hypotheses for future clinical studies based upon subpopulation characteristics, which in turn, will help to further advance personalized medicine.

Moreover, the use of harmonized data networks will help increase transparency of research priorities, and create an expansive collection of outcomes data for which CER can be performed, thereby providing better assessment of effectiveness in real-world populations.

This Council clearly has the diverse expertise and the immediate opportunity to bring together the multiple government agencies necessary to help coordinate such a revolutionary undertaking. 

Placing high priority on the development of a health care system infrastructure to routinely conduct comparative effectiveness research in the U.S. will greatly improve the care delivered for decades to come.