“Drivers” of Translational Cancer Epidemiology in the 21st Century: Needs and Opportunities
+ Author Affiliations
- Authors' Affiliations: 1Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, Maryland; 2Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas; and 3Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia
- Corresponding Author:
Tram Kim Lam, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Rockville, MD 20852. Phone: 301-435-2384; Fax: 301-402-4489; E-mail: email@example.com
Cancer epidemiology is at the cusp of a paradigm shift—propelled by an urgent need to accelerate the pace of translating scientific discoveries into health care and population health benefits. As part of a strategic planning process for cancer epidemiologic research, the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is leading a “longitudinal” meeting with members of the research community to engage in an on-going dialogue to help shape and invigorate the field. Here, we review a translational framework influenced by “drivers” that we believe have begun guiding cancer epidemiology toward translation in the past few years and are most likely to drive the field further in the next decade. The drivers include: (i) collaboration and team science, (ii) technology, (iii) multilevel analyses and interventions, and (iv) knowledge integration from basic, clinical, and population sciences. Using the global prevention of cervical cancer as an example of a public health endeavor to anchor the conversation, we discuss how these drivers can guide epidemiology from discovery to population health impact, along the translational research continuum. Cancer Epidemiol Biomarkers Prev; 22(2); 181–8. ©2013 AACR.
“Knowledge is not enough; we must apply. Willing is not enough; we must do.” This quote by Gothe encapsulates the overarching goal of cancer epidemiology, which is to apply knowledge gained through scientific discovery to improve population health. John Snow and his Broad Street Pump cholera's investigation in 1854 presents an historical illustration of the transcendent role of epidemiology across the translational research continuum—as a scientific field and a methodologic approach not only to identify disease-related risk factors, but also to influence effective policy for improved health outcomes at both the individual and population levels. Snow's testimonies to policymakers, buttressed by strong epidemiologic evidence that cholera is transmitted by water, led to the removal of the Broad Street Pump and the eventual reform of English public health legislation (1, 2). In cancer epidemiology, there are notable achievements in discovery and prevention (3). Yet as a discipline, cancer epidemiology has been too focused on etiologic research centered on the discovery and early characterization phase to have broader public health impact. In fact, a wide chasm exists in the field between discoveries and applications. Epidemiologists should broaden their perspective and extend a wider reach of epidemiologic methods and approaches across the entire translational research continuum to avoid this “translational valley of death” (4).
Needless to say, the movement from scientific discovery to public health impact across the research translational continuum in today's complex environment is slow, challenging, and arguably messy. The first decade of the 21st century brought about dramatic changes in epidemiology—accentuated by the sequencing of the human genome. Shpilberg and colleagues commented toward the end of the 20th century that “the sequencing of the human genome offers the greatest opportunity for epidemiology since John Snow discovered the Broad Street Pump” (5). In the era of postgenome-wide association studies (GWAS), cancer epidemiology is at the cusp of a significant paradigm shift—influenced by a cacophony of factors including: technologic and methodologic advancements, high dimensional and complex data and bioinformation, transdisciplinary and multidisciplinary innovations and discoveries, and demographic and ecologic shifts. And thus 21st century epidemiologists will need to evolve to meet this changing landscape.
In the face of these rapid changes, the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is engaging in a strategic planning effort to address the monumental public health burden of cancer. As an initial step, EGRP is hosting a “longitudinal” meeting, “Trends in 21st Century Epidemiology: From Scientific Discoveries to Population Health Impact” in December 2012 and calling for an active on-going engagement, both online and at a workshop, from both epidemiologists and related disciplines to help reshape the field of cancer epidemiology (6). To facilitate the ongoing dialogue, we have created an online forum blog-epi.grants.cancer.gov/2012. To further frame the conversation, we have identified at least 4 “drivers” of the cancer epidemiology to accelerate the translation of scientific discoveries into health care and population health benefits. This framework, by no means, is complete or sufficient, but is presented as a starting point. We envision that it will evolve to incorporate new ideas, insights, and commentaries from leaders of the field.
In this commentary, we briefly review the 4 “drivers” within a translational framework that are likely to influence the field in the next decade and discuss their relevance and caveats. We also use the global prevention of cervical cancer as an example of a tangible future public health endeavor to anchor the discussion of how cancer epidemiology can be the engine that drives the movement from discovery to population health impact.
Drivers of Translational Cancer Epidemiology: Needs, Opportunities, and Challenges
Khoury and colleagues described a framework of “translational epidemiology” as involving multiple phases (T0–T4), beginning with scientific discoveries and ending with population health impact (7). Using the framework (Fig. 1), epidemiologists have played a crucial role in discovery (T0 example: cigarette smoking and lung cancer; ref. 3), population characterization (T1 example: quantifying the magnitudes of genetic risk factors in cancer; ref. 8), evaluation (T2 example: randomized clinical trials of β-carotene in lung cancer prevention (9), implementation science (T3 example: evaluating provider practices on BRCA testing; ref. 10); and outcomes and surveillance research (T4 example: monitoring rates and determinants of lung cancer incidence at the population level; ref. 11). While most epidemiologists focus their research on discoveries and early translational work, there is an increasing trend of publications in the latter phases of translation (7), both in prevention as well as treatment and survivorship. Epidemiology also has a critical role in the translation of scientific evidence into policy and practice (12).Figure 1.
Translational research framework influenced by 4 “drivers” of epidemiology. Phases of translation: T0, discovery; T1, characterization; T2, evaluation; T3, implementation and health services); and T4, outcome research. Figure adapted from Khoury and colleagues (7).