Bridging Cancer Epidemiology and Social Evolution

Modern epidemiology is a direct result of the paradigm shift from a population-based (upstream) to a downstream (individual) approach. The impact of modern epidemiology such as ‘molecular’ and ‘genetic’ epidemiology (Loomis & Wing, 1990; Diez-Roux, 1998) requires an explanatory power that mostly dependent upon the advances in technology and information systems. Moreover, before estimating the economic effect of a specific intervention before it is implemented, nor assess the economic and/or quality-of-life value of an ongoing or anticipated intervention (Rothermel, 2013); it is critical to recognize not only the significance of sophisticated technologies that go beyond the established genome, proteome, and gene expression platforms, but also new techniques of study design and data analysis (Pearce, 1996; Verma, Khoury & Ioannidis, 2013). Given the remarkable progress in the last decade in advanced technology and new methods for biologic measurements, the reductionist approach of modern epidemiology often ignored the significant causes of disease. Pearce (1996) argue that epidemiology must reintegrate itself into public health and must rediscover the population perspective. However, while the new paradigm could produce a lifestyle approach to social policy, the cumulative outcome of research in cancer epidemiology could equate positive implications to population health.

The key figures in the new epidemiologic model not only acknowledges the development of new techniques of study design and data analysis but also recognize the need for a multidisciplinary approach (social, biologic, statistical), and specifying the population group as the unit of study (Susser, 1985). While occupational carcinogens can be controlled with some difficulty through regulatory measures (Pearce, 1996), it is essential to acknowledge the fundamental problem of tobacco use, not by its consumption but in its production. Pearch (1996) focused on some of these fundamental changes in epidemiology over the past few decades and considered the concepts of causality involved, as well as their ideological and practical consequences. While smoking cessation could be the probable social implication, it is important to stress the epidemiologic value of a study on the apparent correlation between gender and age, modification effect of tobacco use among individuals with pancreatic cancer (PC) and cancer types with a shared-gene association (CTSG-A). The outcome of a risk factor epidemiologic study in individual terms could uplift precision medicine to meet the challenges in tailoring medical interventions based on patient’s biological profile, genetic and epigenetic traits, giving a better understanding of the environment, genetic, biodemographic interactions (EGBIs).

Embraced by both biomedical and social determinist frameworks, the interlinking of the traditional epidemiologic level of intervention (upstream or distal) and the modern epidemiologic level of intervention (downstream or proximal) put public health in the conundrum of the proximal-distal divide. Signal the importance of the argument of the 2008 study of Krieger in replacing the terms proximal and distal from the public health lexicon, supports the recommendation of Wemrell et al. (2016) on the critical need for open interdisciplinary debates on the contribution of social theory to the epidemiological inquiry. While coping with the demand of the 21st-century, global health could still be viewed and approached within the mindset of traditional epidemiology, and the purview of molecular and cancer epidemiology.

The discovery of tobacco smoking as a cause of lung cancer in the early 1950s gave the field of epidemiology its recognition (Pearce, 1996), shifting the epidemiologic paradigm in the object of study in the mid-20th century on the role of multiple causes. Establishing the correlation of age, gender a modifiable risk factor (smoking) with PC and CTSG-A requires the use of early and current epidemiologic theories, and contemporary mainstream epidemiologic concept coalescing to a United Paradigm of Cancer Causation (UPCC). The complex, integrative approach of UPCC supports the views of Loomis, and Wing (1990), Pearce (1996), and McEwen and Getz (2013) in embracing the new epidemiologic paradigm congruent to the advances in cancer genome sequencing. Theorizing the pathopoiesis mechanism of smoking, inherited genes, and association of gender and age in the etiopathogenesis of PC/CTSG-A warrants exploration of its causal footprints, conjoining both biomedical and lifestyle (Krieger, 2011).

Follow-up and future research on the role of molecular epidemiology in emphasizing individual susceptibility to PC will assess the relative contribution of modifiable risk factors to non-modifiable genetic factors. In this premise, the etiopathogenesis of the disease could be explored from the bottom up. Bridging cancer epidemiology and social evolution will be dependent upon the incorporation of the strength of the social network and social contagion theory. The testable assumption of the social network theory as its strength states that the social structure of the network itself be primarily responsible for determining individual behavior and attitudes by shaping the flow of resources which determines access to opportunities and constraints on behavior (Berkman et al., 2000). Why choose if a single theory cannot make a change? Incorporating these ideas in addition to the composite and underpinnings of UPCC could springboard a priori argument on the role of social networks in the spread of an intervention such as smoking cessation, or amplifying the promotion of the significance of early screening to improve mortality and morbidity.

While the causal nature of peer effects could be associated with tobacco use; the social contagion theory of Christakis and Fowler (2013) set an argument on human social networks exhibiting a “three degrees of separation.” Such association could support the assumption of spreading the interpersonal influence that acknowledges the significance of early screening, and the promise of a novel therapeutic approach. Like the widely discussed classic paper of Travers and Milgram (1969) on ‘six degrees of separation,’ the three degrees of separation or the three degrees of separation rule (Christakis & Fowler, 2009) agreed on the premise that telegraph phrases are meant to be evocative, and not definitive. For example, the role of interpersonal influence in spreading novel ideas such as advances in early screening to achieve a more significant therapeutic outcome. The preponderance of the evidence that points to the added significance of a passive-broadcast viral messaging to create social contagion warrants the recognition of the approach. Taking into account factors such as the promise of the outcome of a research study in the quality of life, social and economic incentives could expand the social network and amplify social support needed by individuals with PC or any deadly diseases. According to Kroenke et al. (2013), effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

References

Berkman, L. F., Glass, T., Brissette, I., & Seeman, T. E. (2000). From social integration to health: Durkheim in the new millennium. Social Science & Medicine, 51(6), 843-857. https://doi.org/10.1016/S0277-9536(00)00065-4

Christakis, N.A & Fowler, J.H. (2009). Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. (First ed.). New York: Little, Brown, and Company.

Christakis, N. A., & Fowler, J. H. (2013). Social contagion theory: examining dynamic social networks and human behavior. Statistics in medicine, 32(4), 556-577. doi: 10.1002/sim.5408

Diez-Roux, A. V. (1998). On genes, individuals, society, and epidemiology. American Journal of Epidemiology, 148(11), 1027-1032. http://dx.doi.org/10.1093/oxfordjournals.aje.a009578

Krieger, N. (2008). Proximal, Distal, and the Politics of Causation: What’s Level Got to Do With It?  American Journal of Public Health (AJPH), 98(2). http://dx.doi.org/10.2105/AJPH.2007.111278

Krieger, N. (2011). Epidemiology and the people’s health: theory and context (Vol. 213). New York: Oxford University Press.

Kroenke, C. H., Kwan, M. L., Neugut, A. I., Ergas, I. J., Wright, J. D., Caan, B. J., … & Kushi, L. H. (2013). Social networks, social support mechanisms, and quality of life after breast cancer diagnosis. Breast cancer research and treatment, 139(2), 515-527. doi:  10.1007/s10549-013-2477-2

Labilles, U. (2015a). Reevaluating the Impact of Cigarette Smoking on Pancreatic Cancer. Unpublished manuscript, College of Health Sciences, Public Health, Epidemiology, Walden University, Minneapolis.

Labilles, U. (2015b, September 27). A Promise to a Dying Brother [Web log post]. Retrieved from https://onenationsecho.com/2015/09/27/a-promised-to-a-dying-brother/.

Labilles, U. (2015c). Prospectus: Tobacco Use and Family Cancer History in the Pathopoiesis of Pancreatic Cancer. Unpublished manuscript, College of Health Sciences, Public Health, Epidemiology, Walden University, Minneapolis.

Labilles, U. (2016). The New Public Health: Beyond Genetics and Social Inequalities. Unpublished manuscript, College of Health Sciences, Public Health, Epidemiology, Walden University, Minneapolis.

Labilles, U. (2017). Pathopoiesis Mechanism of Smoking and Shared Genes in Pancreatic Cancer. ProQuest-CSA, LLC. Library of Congress, Copyright R# TX 8-490-984, Washington DC. doi: 10.13140/RG.2.2.30721.35681

Loomis, D., & Wing, S. (1990). Is molecular epidemiology a germ theory for the end of the twentieth century?. International journal of epidemiology, 19(1), 1-3. http://dx.doi.org/10.1093/ije/19.1.1

McEwen, B. S., & Getz, L. (2013). Lifetime experiences, the brain, and personalized medicine: An integrative perspective. Metabolism, 62, S20-S26. https://doi.org/10.1016/j.metabol.2012.08.020

Pearce, N. (1996). Traditional epidemiology, modern epidemiology, and public health. American journal of public health, 86(5), 678-683.

Rothermel, C. (2013). What is health economics and outcomes research? A primer for medical writers. AMWA Journal, 28(3)

Susser, M. (1985). Epidemiology in the United States after World War II: the evolution of technique. Epidemiologic reviews, 7(1), 147-177. http://dx.doi.org/10.1093/oxfordjournals.epirev.a036280

Travers, J., & Milgram, S. (1969). An experimental study of the small world problem. Sociometry, 425-443. doi: 10.2307/2786545

Verma, M., Khoury, M. J., & Ioannidis, J. P. (2013). Opportunities and challenges for selected emerging technologies in cancer epidemiology: mitochondrial, epigenomic, metabolomic, and telomerase profiling. Cancer Epidemiology Biomarkers & Prevention, 22(2), 189-200. http://dx.doi.org/10.1158/1055-9965.EPI-12-1263

Wemrell, M., Merlo, J., Mulinari, S., & Hornborg, A. C. (2016). Contemporary epidemiology: a review of critical discussions within the discipline and a call for further dialogue with social theory. Sociology Compass, 10(2), 153-171. doi: 10.1111/soc4.12345