When I was inducted into the Honor Society in winter 2013, I thought that being on top of my batch will be enough to get me through my journey as a Public Health Ph.D. candidate. Recruiting a dissertation chair is the most challenging so far, especially getting a response from them. What if I do not get a dissertation chair who will be a good match with my dissertation topic? Can I submit my premise and finish my dissertation to another university? A night before my youngest brother passed away; I was on the phone with him. He told me that he is too tired, and I responded that it is okay to let go. He asked me to promise him to go back to school and take on a graduate degree to make a difference. “Promise me that at some point to be involved in a research project that could make a difference to individuals diagnosed with pancreatic cancer.” He passed away in 2007, a few weeks before his 40th birthday, and three months before his only daughter’s first birthday.
Focusing on the impact of cigarette smoking as a factor that promotes pancreatic cancer rather than initiates it will amplify the importance of behavioral change, and enhance the quality of life. The outcome of pancreatic cancer remains dismal, even with treatment combinations of surgery, radiotherapy and chemotherapy with an estimated annual economic burden of $4.9 billion annually (Pandol, Apte, Wilson, Gukovskaya, and Edderkaoui, 2012). Advances in patient management and understanding the biology of pancreatic cancer has taken substantial progress over the years. Herman, Schulick, Hruban and Goggins (2011) found that screening first-degree relatives of individuals with family members affected by pancreatic cancer can identify non-invasive precursors of the disease. In this 2011 study shows the gradual rise in the incidence and number of deaths caused by pancreatic tumors, even with the decline in incidence and mortality of other common cancers. Furthermore, Vincent et al. found that despite developments in detection and management of pancreatic cancer, only about 4% of patients will live five years after diagnosis. Moreover, Vincent et al. (2011) found that present surgical resectioning offers the only chance of cure and improve the survival rate for those with malignant disease localized to the pancreas. Statistical analysis in 2012 study shows 80–85% of patients with advanced unresectable disease responds poorly to most chemotherapeutic agents. Therefore, it is warranted to have continued understanding of the biological mechanisms contributory to the development and progression of pancreatic tumors. On the other hand, Klein et al. (2004) emphasized the significance of quantification of the risk of individuals with a family history of pancreatic cancer as a rational basis for cancer risk screening and counseling. In a prospective registry-based approach of this 2004 study, the risk of these individuals showed an increased risk of developing the disease. Klein et al. (2004) performed standardized incidence ratios and compared the number of incident pancreatic cancers observed with those expected using Surveillance, Epidemiology and End Results (SEER) rates. It was quantified in this registry-based study the pancreatic cancer risk in kindreds with a family member who was diagnosed with the disease, supporting the hypothesis of increased risk in association with family history. While Blackford et al. (2009) failed to identify the signature tobacco-related mutation in cigarette smokers that could have strong implication to the development of pancreatic cancer; this 2009 study found the nonspecific DNA damage caused by tobacco carcinogens. Furthermore, the combined causality of non-tobacco-related mutagenic risk factors such as inherited predisposition to cancer may share mutagenic properties with the tobacco mutagens active in pancreatic tissues (Ding et al., 2008; Prokopczyk et al., 2002). The types and patterns of these mutations provide insight into the mechanisms by which cigarette smoking causes pancreatic cancer (Blackford et al., 2009). Porta et al. (2009) and Blackford et al. (2009) suggested that smoking enhances the risk for pancreatic cancer through mechanisms other than genetic mutation. The development of pancreatic cancer may have a non-significant association to pipe smoking and smokeless tobacco use, but in a large collaborative pooled analysis of non-cigarette tobacco use in 11 studies within the International Pancreatic Cancer Case-Control Consortium (PanC4) found that cigar smoking is associated with an excess risk of the disease (Bertuccio et al., 2011). Cigarette smoking was found to be an established risk factors— both exposure to environmental tobacco smoke (ETS), and active cigarette smoking (Vrieling et al., 2010). Over 40,000 individuals are diagnosed with pancreatic cancer, and less than 5% of patients diagnosed has a survival rate of five years. The component of the smoke of cigarettes that produced in the body as a metabolite of nicotine and the most abundant carcinogens in tobacco smoke is 4-(methyl nitrosamine)-1-(3-pyridyl)-1-butanone (NNK). Vary widely in nicotine content and carcinogenic nicotine metabolites, cigarettes, cigars, and other tobacco products—nicotine reaches the lungs and is quickly absorbed into the bloodstream during smoking. A cigar containing as many as 20 grams of tobacco can have nicotine between 5.9 and 335.2 mg per gram of tobacco (Henningfield, Fant, Radzius, & Frost, 1999). Prokopczyk et al. (2002) noted that the nicotine levels in pancreatic juice in smokers is seven times higher than non-smokers. Blackford et al. (2009) concluded that smokers diagnosed with pancreatic carcinomas harbors more mutations than the non-smoker, therefore, doubles the risk, accounting for 20 to 25% of pancreatic cancers.
Pandol et al. (2012) stated that the pro-carcinogenic effects of smoking on the pancreas are inadequately studied, confirming that tobacco smoking is the strongest avoidable risk and the major environmental factor for pancreatic cancer. Pandol et al. provided valuable insights into the pathogenesis of pancreatic cancer, particularly in the initiation and progression of the disease. Determining the mechanisms underlying the effect of smoking compounds on fibrosis and inflammation will improve our limited knowledge of pancreatic biology. Pancreatic cancer can be classified as genetic, environmental, or both; as well as a disease caused by inherited DNA mutation or mutation by chance. While advances in Genomics gives the promise to early pancreatic cancer detection through better understanding of pancreatic biology, it is paramount to embrace the significance of lifestyle habits that can be modified to evidence-based healthier concepts that translates to reduced cancer risk. Applying lessons learned from the outcome of my proposed study, and existing body of knowledge will prevent the emergence of pancreatic cancer, reduce cancer risk and advance population health. Early behavioral change and interventions will improve the survival rate and quality of life during the time course of pancreatic cancer progression.
Bayraktar, S., Bayraktar, U. D., & Rocha-Lima, C. M. (2010). Recent developments in palliative chemotherapy for locally advanced and metastatic pancreas cancer. World journal of gastroenterology: WJG, 16(6), 673.
Bertuccio, P., La Vecchia, C., Silverman, D. T., Petersen, G. M., Bracci, P. M., Negri, E., … & Boffetta, P. (2011). Cigar and pipe smoking, smokeless tobacco use and pancreatic cancer: an analysis from the International Pancreatic Cancer Case-Control Consortium (PanC4). Annals of Oncology, mdq613.
Blackford, A., Parmigiani, G., Kensler, T. W., Wolfgang, C., Jones, S., Zhang, X., … & Hruban, R. H. (2009). Genetic mutations associated with cigarette smoking in pancreatic cancer. Cancer research, 69(8), 3681-3688.
Bosetti, C., Lucenteforte, E., Silverman, D. T., Petersen, G., Bracci, P. M., Ji, B. T., … & La Vecchia, C. (2012). Cigarette smoking and pancreatic cancer: an analysis from the International Pancreatic Cancer Case-Control Consortium (Panc4). Annals of oncology, 23(7), 1880-1888.
Bouvier, A. M., David, M., Jooste, V., Chauvenet, M., Lepage, C., & Faivre, J. (2010). Rising incidence of pancreatic cancer in France. Pancreas, 39(8), 1243-1246.
Breslow, N. E., Day, N. E., & Davis, W. (1980). The analysis of case-control studies. International Agency for Research on Cancer.
Chowdhury, P., Chang, L. W., & Rayford, P. L. (1993). Tissue distribution of [3H]-nicotine in rats. Biomedical and environmental sciences: BES, 6(1), 59-64.
Chowdhury, P., Doi, R., Tangoku, A., & Rayford, P. L. (1995). Structural and functional changes of rat exocrine pancreas exposed to nicotine. International journal of pancreatology, 18(3), 257-264.
Colby, S. M., Clark, M. A., Rogers, M. L., Ramsey, S., Graham, A. L., Boergers, J., … & Abrams, D. B. (2012). Development and reliability of the lifetime interview on smoking trajectories. Nicotine & Tobacco Research, 14(3), 290-298.
Colditz, G. A., Wolin, K. Y., & Gehlert, S. (2012). Applying what we know to accelerate cancer prevention. Science translational medicine, 4(127), 127rv4-127rv4.
DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled clinical trials, 7(3), 177-188.
Ding, L., Getz, G., Wheeler, D. A., Mardis, E. R., McLellan, M. D., Cibulskis, K., … & Sawyer, C. S. (2008). Somatic mutations affect key pathways in lung adenocarcinoma. Nature, 455(7216), 1069-1075. Chicago.
Edderkaoui, M., Park, C., Lee, I., Nitsche, C., Gerloff, A., Grippo, P. J., … & Gukovskaya, A. S. (2011, November). Novel model of pancreatic neoplastic lesions induced by smoking compound NNK. In Pancreas (Vol. 40, No. 8, pp. 1321-1321). 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA: LIPPINCOTT WILLIAMS & WILKINS.
Feuer, E. J., & Wun, L. M. DEVCAN: probability of developing or dying of cancer software, version 4.1.[internet]. Bethesda (MD): National Cancer Institute (NCI); 1999 [accessed 2002 May 28].[1 p].
Gould, G. S., Watt, K., Cadet-James, Y., & Clough, A. R. (2015). Using the risk behaviour diagnosis scale to understand Australian Aboriginal smoking—a cross-sectional validation survey in regional New South Wales. Preventive Medicine Reports, 2, 4-9.
Greenland, S. (1987). Quantitative methods in the review of epidemiologic literature. Epidemiologic reviews, 9(1), 1-30.
Henningfield, J. E., Fant, R. V., Radzius, A., & Frost, S. (1999). Nicotine concentration, smoke pH and whole tobacco aqueous pH of some cigar brands and types popular in the United States. Nicotine & Tobacco Research, 1(2), 163-168.
Hoffmann, D., Hoffmann, I., & El-Bayoumy, K. (2001). The less harmful cigarette: a controversial issue. A tribute to Ernst L. Wynder. Chemical research in toxicology, 14(7), 767-790.
Hruban, R. H., Iacobuzio-Donahue, C., Wilentz, R. E., Goggins, M., & Kern, S. E. (2000). Molecular pathology of pancreatic cancer. Cancer journal (Sudbury, Mass.), 7(4), 251-258.
Institute for Health Metrics and Evaluation. (2015). US County Profile: Dallas County, Texas. 2301 Fifth Ave., Suite 600 Seattle, WA 98121 USA.
Jiao, L., Mitrou, P. N., Reedy, J., Graubard, B. I., Hollenbeck, A. R., Schatzkin, A., & Stolzenberg-Solomon, R. (2009). A combined healthy lifestyle score and risk of pancreatic cancer in a large cohort study. Archives of internal medicine, 169(8), 764-770.
Kadam, P., & Bhalerao, S. (2010). Sample size calculation. International journal of Ayurveda research, 1(1), 55.
Kirby, A., Gebski, V., & Keech, A. C. (2002). Determining the sample size in a clinical trial. Medical journal of Australia, 177(5), 256-257.
Klein, A. P., Brune, K. A., Petersen, G. M., Goggins, M., Tersmette, A. C., Offerhaus, G. J. A., … & Hruban, R. H. (2004). Prospective risk of pancreatic cancer in familial pancreatic cancer kindreds. Cancer Research, 64(7), 2634-2638. Chicago
Janghorban, R., Roudsari, R. L., & Taghipour, A. (2014). Skype interviewing: the new generation of online synchronous interview in qualitative research. International journal of qualitative studies on health and well-being, 9.
Labilles, U. (2015).(Unpublished, Advanced Quantitative Reasoning and Analysis (RSCH – 8250H – 3), 2015 Summer Qtr. Wk11Assgn3LabillesU) Walden University, Minneapolis.
Larsson, S. C., Permert, J., Håkansson, N., Näslund, I., Bergkvist, L., & Wolk, A. (2005). Overall obesity, abdominal adiposity, diabetes and cigarette smoking in relation to the risk of pancreatic cancer in two Swedish population-based cohorts. British journal of cancer, 93(11), 1310-1315.
Lau, P. P., Dubick, M. A., Gloria, S. M., Morrill, P. R., & Geokas, M. C. (1990). Dynamic changes of pancreatic structure and function in rats treated chronically with nicotine. Toxicology and applied pharmacology, 104(3), 457-465.
Le Houezec, J. (2003). Role of nicotine pharmacokinetics in nicotine addiction and nicotine replacement therapy: a review. The International Journal of Tuberculosis and Lung Disease, 7(9), 811-819.
Lowenfels, A. B., & Maisonneuve, P. (2003). Environmental factors and risk of pancreatic cancer. Pancreatology, 3(1), 1-8.
Lynch, S. M., & Rebbeck, T. R. (2013). Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach. Cancer Epidemiology Biomarkers & Prevention, 22(4), 485-495.
Lynch, S. M., Vrieling, A., Lubin, J. H., Kraft, P., Mendelsohn, J. B., Hartge, P., … & Stolzenberg-Solomon, R. Z. (2009). Cigarette smoking and pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium. American journal of epidemiology, 170(4), 403-413.
Miller, T. Q. (1997). Statistical methods for describing temporal order in longitudinal research. Journal of clinical epidemiology, 50(10), 1155-1168.
NHIS – Adult Tobacco Use – Smoking Status Recodes. (n.d.). Retrieved from http://www.cdc.gov/nchs/nhis/tobacco/tobacco_recodes.htm
Pancreatic Expression Database. (n.d.). Retrieved from http://pancreasexpression.org/
Pandol, S. J., Apte, M. V., Wilson, J. S., Gukovskaya, A. S., & Edderkaoui, M. (2012). The burning question: why is smoking a risk factor for pancreatic cancer? Pancreatology, 12(4), 344-349.
Philip, P. A. (2008). Targeted therapies for pancreatic cancer. Gastrointestinal cancer research: GCR, 2(4 Suppl 2), S16.
Prokopczyk, B., Hoffmann, D., Bologna, M., Cunningham, A. J., Trushin, N., Akerkar, S., … & El-Bayoumy, K. (2002). Identification of tobacco-derived compounds in human pancreatic juice. Chemical research in toxicology, 15(5), 677-685. Chicago.
Porta, M., Crous-Bou, M., Wark, P. A., Vineis, P., Real, F. X., Malats, N., & Kampman, E. (2009). Cigarette smoking and K-ras mutations in pancreas, lung and colorectal adenocarcinomas: etiopathogenic similarities, differences and paradoxes. Mutation Research/Reviews in Mutation Research, 682(2), 83-93.
Prospective Ascertainment for Late Effects among Cancer … (n.d.). Retrieved from http://www.mskcc.org/cancer-care/trial/12-143
Raimondi, S., Maisonneuve, P., Löhr, J. M., & Lowenfels, A. B. (2007). Early onset pancreatic cancer: evidence of a major role for smoking and genetic factors. Cancer Epidemiology Biomarkers & Prevention, 16(9), 1894-1897.
Schottenfeld, D., & Fraumeni Jr, J. F. (1982). Cancer epidemiology and prevention. Eastbourne, UK; WB Saunders Co.
Silverman, D. T., Dunn, J. A., Hoover, R. N., Schiffiman, M., Lillemoe, K. D., Schoenberg, J. B., … & Pottern, L. M. (1994). Cigarette Smoking and Pancreas Cancer: a Case—Control Study Based on Direct Interviews. Journal of the National Cancer Institute, 86(20), 1510-1516.
Smith-Warner, S. A., Spiegelman, D., Ritz, J., Albanes, D., Beeson, W. L., Bernstein, L., … & Hunter, D. J. (2006). Methods for Pooling Results of Epidemiologic Studies the Pooling Project of Prospective Studies of Diet and Cancer. American journal of epidemiology, 163(11), 1053-1064.
Special Section: Pancreatic Cancer. (n.d.). Retrieved from http://www.cancer.org/acs/groups/content/@research/documents/document/acspc-0388
Thomas, J. K., Kim, M. S., Balakrishnan, L., Nanjappa, V., Raju, R., Marimuthu, A., … & Pandey, A. (2014). Pancreatic cancer database: an integrative resource for pancreatic cancer. Cancer biology & therapy, 15(8), 963-967.
Validation of risk assessment scales and predictors of … (n.d.). Retrieved from http://europepmc.org/articles/PMC4054635
Vincent, A., Herman, J., Schulick, R., Hruban, R. H., & Goggins, M. (2011). Pancreatic cancer. The Lancet, 378(9791), 607-620. Chicago
Vrieling, A., Bueno‐de‐Mesquita, H. B., Boshuizen, H. C., Michaud, D. S., Severinsen, M. T., Overvad, K., … & Riboli, E. (2010). Cigarette smoking, environmental tobacco smoke exposure and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition. International journal of cancer, 126(10), 2394-2403.
Wen, K. Y., & Gustafson, D. H. (2004). Needs assessment for cancer patients and their families. Health and quality of life outcomes, 2(1), 11.
Wilson, L. S., & Lightwood, J. M. (1999). Pancreatic cancer: total costs and utilization of health services. Journal of surgical oncology, 71(3), 171-181.
Witte, K. (1996). Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of health communication, 1(4), 317-342.
Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education & Behavior, 27(5), 591-615.
Wittel, U. A., Pandey, K. K., Andrianifahanana, M., Johansson, S. L., Cullen, D. M., Akhter, M. P., … & Batra, S. K. (2006). Chronic pancreatic inflammation induced by environmental tobacco smoke inhalation in rats. The American journal of gastroenterology, 101(1), 148-159.
Pathopoiesis Mechanism of Smoking and Shared Genes in Pancreatic Cancer
To raise new questions, new possibilities, to regard old problems from a new angle requires creative imagination and marks the real advance in science (Einstein & Infeld, 1938, p. 92).
Pancreatic cancer (PC) at the start of the 21st century continues to be a vital unresolved health problem, remaining as one of the deadliest human cancers. By the year 2030, it is projected that PC will be the second leading cause of cancer death after lung cancer among the major types of cancer (Rahib et al. 2014). The outcome of this study would provide valuable insights into the etiopathogenesis of PC and cancer types with a shared-gene association (CTSG-A), as well as the possible recognition of the probable unique pattern of PC malignancy among defined age groups, between men and women, in correlation to the modification effect of smoking to cancer predisposition genes (CPG), or its combined impact. Additional understanding of the pathopoiesis dynamics of smoking status, gender, and age in individuals with CPG in the induction and promotion of PC could help promote pre- and post behavioral diagnosis change. This study may assist in developing a novel patient management approach to accurately assess the disease burden under the lens of public health and modern epidemiology. Although genetic changes can be either somatic or hereditary, described as de novo (new), PC does not arise de novo (Maitra & Hruban, 2008), but rather initiated by a probable gene mutation such as p16/CDKN2A that results to debilitating metabolic effects of uncontrolled growth. Given the assumption that a disease is caused by a factor that can be controlled, exploring the relationship between modifiable health behaviors such as smoking and family cancer history (FCH), CPG or shared genes was a legitimate endeavor. In this study, genetic syndromes associated with PC were interchangeably referred to as FCH, CPG, or shared genes. Pancreatic cancer and other cancers found to have a shared-gene association (S-GA) were the dependent variables, and smoking status, age, and gender were the independent variables; this study addressed the following research questions (RQs) and hypotheses:
RQ1: Is cigarette smoking associated with the etiopathogenesis of pancreatic cancer and cancer types with shared gene association (CTSG-A)?
H01: Smoking level has no correlation with prevalence of PC and CTSG-A.
H1: Smoking can increase the risk of PC and CTSG-A.
RQ2: Is there a relationship between the combined role of age and gender in the etiopathogenesis of PC and CTSG-A?
H02: Age and gender have no correlation with prevalence of PC and CTSG-A.
H2: Age and gender are correlated with the prevalence of PC and CTSG-A.
The unique contribution of this dissertation to the current body of knowledge involved examining the links between tobacco use, gender, age, PC, and shared genes. This dissertation could promote population health, and lessons learned could reshape the current understanding of cancer epidemiology by providing the scientific justification for the implementation of screening, surveillance, and education programs. The outcome of this dissertation would fit into the practical intervention approach of adopting a healthy lifestyle such as smoking cessation as part of positive, meaningful social change to improve prognosis and quality of life during PC progression.
Pandol et al. (2012) noted the economic burden of PC with an expected yearly cost of $4.9 billion and underscored the significance of determining the mechanisms underlying the effect of smoking compounds that may provide additional insights into the pathogenesis of the disease. The investigation gave valuable insights into the etiopathogenesis of pancreatic growth from its induction and promotion. Moreover, findings of Hart, Kennedy, and Harvey (2008); and Schenk et al. (2001) support the unique probable contribution of this dissertation to the existing body of knowledge, generating a snapshot of a possible correlation of smoking, gender, and age to the development of PC and CTSG-A, enhancing the knowledge on the pathopoiesis mechanism of these predictors in disease induction and promotion. The plethora of findings of the past and present studies highlighted the causal significance of modifiable risk factors and genetics in the pathosis of PC. The goal of these studies falls largely within the confines of understanding the insights of genetic alterations and specific modifiable risk factors. Much of the recent research concentrates in this line of inquiry; therefore, recognizing the modifying effect of smoking to individuals with family aggregation justifies the merit of this dissertation and future endeavors.
Blackford et al. (2009) noted that previous researchers overlooked the distinction between the passenger and driver mutations that explains the often unconvincing associations between smoking and driver mutations. Recognizing this gap, and while there are continued studies on different aspects of the PC genomic landscape, this dissertation intends to provide a descriptive analysis of the prevalence pattern of PC and CTSG-A known to have increased risk of extrapancreatic malignancies versus nonsmokers. The mechanisms through which smoking, gender, age, and CPG affect PC remain unknown, making it critical to explore the role of these three predictors in the disease clustering to develop a more efficient management and clinical approach. With an exhaustive understanding of the patterns of somatic alteration in pancreatic carcinogenesis comes the opportunity to understand the influence of these factors on metastatic progression (Yachida & Iacobuzio-Donahue, 2013). The burden of chronic diseases such as PC is often neglected on the public agendas. The increasing annual economic burden of PC is beyond genetics and social inequalities, making it necessary to embrace the shift in the level of analysis from traditional to modern epidemiologic and New Public Health approach. The significance of the successful delivery of the New Public Health both at the level of society and individual behavior (Halpin et al., 2010) justifies the intent of this dissertation on the need for further exploration of the pathopoiesis mechanism of tobacco use and FCH, the etiopathogenic role of gender and age. The unveiling of the “Precision Medicine Initiative” during the State of the Union Address of President Barack Obama on January 20, 2015, springboard the new effort of revolutionizing a new model of patient-powered research that could accelerate biomedical discoveries and provide clinicians with new tools, knowledge, and therapies. New research directions are warranted to reverse the lethal outcome of this disease.
Study Design and Approach
The causality of tobacco-related mutagenic risk factors and the correlation between gender and age and CPG will not only raise awareness of the significance of cancer risk screening and counseling but will also increase the understanding of environmental, genetic, and biodemographic interaction (EGBI) contributing to the development and progression of PC. The results of this study may be used to promote lifestyle change in reducing cancer risk. Improving the perceived corollary of individuals with inherited genes and quality of life during the expression or final stage of the disease is dependent on the favorable adjustment of behavioral risk factors. This study intended to explore the association between smoking, gender, and age in individuals with CPG. I used a cross-sectional design to determine the prevalence of pancreatic cancer and CTSG-A among smokers and non-smokers. The potential association of smoking, gender, and age as predictors of the outcome variable (PC/CTSG-A) were explored using a cross-sectional design. Secondary data were recoded and randomized using IBM Statistical Package for the Social Sciences (SPSS, Version 23, 64-bit edition). Although logistic regression makes no assumptions about the distributions of the predictor variables (smoking, gender, age), ordinal modeling was the fundamental property of the design of this study to test whether smoking level and age are effect modifiers to inherited genes or combined causative predictors in the induction and promotion of PC and CTSG-A.
The population for the study was defined as participants of the Behavioral Risk Factor Surveillance System (BRFSS) survey. Subject selection criteria were set narrowly, by selecting specifically those who smoke and do not smoke with PC/CTSG-A (survivorship module), versus non-smokers with PC/CTSG-A. Association between smoking, age, gender, PC, and PC/CTSG-A are explored using hypothetical conceptual cohort. A hypothetical conceptual cohort is defined as participants from the 2014 BRFSS survey who qualified as high-risk based on the level of smoking. The dependent variable under Level 1 or Category 1 in this dissertation comprised cancer types with P16(CDKN2A) and PRSS1 mutations. The cancer types that were included as part of this category were pancreatic, melanoma, esophageal, leukemia, lung, bladder, renal, brain, osteosarcoma (bone), and cancer of the head and neck. Level two or category two includes cancer types with BRCA1, STK11, and LKB1 mutations. While p16 is related to breast cancer, BRCA1 is two times to have a relative risk of PC, with higher risk by age 70. The cancer types that are considered to be part of this category are breast, ovarian, and prostate cancer. Level three or category three are composed of cancer types with bMLH1, and bMSH2 mutations. The cancer types in this category are endometrial, colorectal, and stomach cancer. Regression methods were used to assess and adjust for confounding, and determine whether there is effect modification, as well as simultaneously evaluate the relationships of risk factors (smoking, age, gender). Given that this study involves PC/CTSG-A, and more than one independent variables, ordinal logistic regression analysis was performed to assess confounding and effect modification. The impact of multiple risk factors (smoking, gender, age) is examined as opposed to focusing on a single risk factor. Two separate logistic regression analyses were conducted to assess differences in induction and promotion of pancreatic cancer/CTSG-A by gender and three age groups (<51, 52-69, 70>).
The effect of tobacco use, age, and sex in the etiopathogenesis of PC and CTSG-A was assessed using cumulative odds ordinal logistic regression with proportional odds. While the results of this study supported the null hypotheses that smoking does not correlate with the prevalence of PC and CTSG-A as confirmed by the GENLIN parameter estimates, both gender and age are statistically significant predictors with <.05 p-values. The odds of male respondents developing PC and CTSG-A versus the female respondents is .418 (95% Cl, .344 to .509) with a statistically significant effect, X2 (1) = 75.507. The odds ratio of 1.374 (95% CI, 1.184 to 1.595), Wald χ2(1) = 17.538 is suggestive to the increased probability of developing the disease as the persons reach the age between 62 and 69 years of age. Separate binomial logistic regression analysis shows age was associated with an increased likelihood of developing the disease. Analogous to the results of the ordinal logistic regression analysis, the odds of the male participants of the 2014 BRFSS survey is 2.472 times greater to develop the disease as opposed to female respondents. The findings of this study could support the importance of behavioral risk factor and their roles in reducing the prevalence of PC and CTSG-A, enhancing the late-stage quality of life.
Ab-initio studies have established that family history of PC can manifest due to genetic factors and shared environmental factors. The scientific perspective of this dissertation, current, and past studies are parallel to Albert Einstein’s concept of “natura naturans”—everything is connected. In this dissertation, the assumption that P16(CDKN2A), PRSS1, BRCA1, STK11, LKB1, bMLH1, and bMSH2 are correlated with the development of the disease is mathematically or statistically correct and deserves further investigation.
Presenting a New Metatheory
The Unified Paradigm of Cancer Causation (UPCC), a metatheory introduced in this dissertation could provide arguments on the positive association (synergism) between tobacco use and FCH, giving more clarity to Rothman’s notion of epidemiologic interaction or the paradigm of sufficient cause. UPCC is a composite construct of the germ theory and the somatic mutation theory of carcinogenesis (SMT) in combination with the traditional or Darwinian evolutionary system (Greaves & Maley, 2012), Knudson’s two-hit theory (Hermanowicz, 2015), genome theory, Darwinian theory of social change (Richerson & Boyd, 2000), and the multi-level biologic, social integrative construct (MBASIC). The theoretical cocktail of UPCC could interlock new insights on tumor initiation, metastases diagnostic, and treatment strategies. The dynamic interplay of gene-culture transmission recognized in UPCC could initiate the evolution of culture that embraces the value of evidence-based screening, surveillance, management, and personal genomics. Central to human adaptations is the use of socially learned information (Richerson, Boyd & Henrich, 2010), from literacy program of a health system, emphasizing the significance of 21st-century approach. The combined causal association of a variety of levels as recognized by Lynch and Rebbeck (2013) that are linked to cancer incidence and mortality justify the supposition of UPCC. It is critical to underscore the magnitude of intercalating the mandatory early screening, and management of the health system. 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).
New Public Health at the Level of Society and Individual Behavior
Darwinism is a collection of concepts, empirical methods and mathematical tools designed to understand the dynamics of genetics and cultural evolution (Richerson & Boyd, 2000). Therefore, this dissertation supports the rationale of cultural value transmission of smoking cessation that could lower the risk to individuals with CPG. Smoking cessation as a cultural item is a clear implication for positive social change. While smoking cessation is the probable social implication of this dissertation, 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 PC and 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 EGBIs. The results of this dissertation have several implications for social change, such as recognizing cultural values in developing effective communication structured from the statistically significant etiopathogenic role of gender and age in the development of PC and CTSG-A. This will give a clear understanding of what to ask, and what actions to take, allowing the family to openly explore treatment alternatives during the terminal phase of the illness (Ballard-Reisch & Letner, 2003). Primary prevention must be prioritized as an integral part of global cancer control. No regulatory standards nor advanced innovations could change the hearts and minds of the general population unless evidence-based studies support it. Social change will be dependent upon the continued dissemination of current cancer research built on integrative social molecular pathological epidemiology (MPE). Pearce (1996) argue that epidemiology must reintegrate itself into public health and must rediscover the population perspective. However, while the new paradigm of downstream (individual) approach could produce a lifestyle approach to social policy, the cumulative outcome of research in cancer epidemiology could equate positive implications to population health.
Improving the future of individuals diagnosed with PC through the concerted efforts of policymakers, public health professionals, clinicians and scientists, the Recalcitrant Cancer Research Act of 2012 lays the foundation for a heightened focused on further development and use of prevention, screening and therapeutic strategy (Rahib et al., 2014). The genuine progress against PC as recalcitrant cancer warrants strategic direction and guidance on the continued understanding, development of efficient early detection strategy and identifying therapeutic targets that could stem the tide of its growing economic burden.
Amundadottir, L. T., Thorvaldsson, S., Gudbjartsson, D. F., Sulem, P., Kristjansson, K., Arnason, S.,…Stefansson, K. (2004). Cancer as a complex phenotype: Pattern of cancer distribution within and beyond the nuclear family. PLoS Med, 1(3), e65. doi: 10.1371/journal.pmed.0010065
Ballard-Reisch, D. S., & Letner, J. A. (2003). Centering families in cancer communication research: Acknowledging the impact of support, culture and process on client/provider communication in cancer management. Patient Education and Counseling, 50(1), 61-66. http://dx.doi.org/10.1016/S0738-3991(03)00082-X
Blackford, A., Parmigiani, G., Kensler, T. W., Wolfgang, C., Jones, S., Zhang, X., … & Goggins, M. (2009). Genetic mutations associated with cigarette smoking in pancreatic cancer. Cancer research, 69(8), 3681-3688. doi: 10.1158/0008-5472.CAN-09-0015
Einstein, A & Infeld, L. (1938). The evolution of modern physics. New York: Simon and Schuster.
Garcia, M., Jemal, A., Ward, E. M., Center, M. M., Hao, Y., Siegel, R. L., & Thun, M. J. (2007). Global cancer facts & figures 2007. Atlanta, GA: American cancer society, 1(3), 52. https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/global-cancer-facts-and-figures/global-cancer-facts-and-figures-2007.pdf
Greaves, M., & Maley, C. C. (2012). Clonal evolution in cancer. Nature, 481(7381), 306-313. doi: 10.1038/nature10762
Halpin, H.A., Morales-Suarez-Varela, M. M., & Martin-Moreno, J. M. (2010). Chronic disease prevention and the new public health. Public Health Reviews, 32(1), 120. https://doi.org/10.1007/BF03391595
Hart, A. R., Kennedy, H., & Harvey, I. (2008). Pancreatic cancer: a review of the evidence on causation. Clinical Gastroenterology and Hepatology, 6(3), 275-282. https://doi.org/10.1016/j.cgh.2007.12.041
Hermanowicz, S. (2015). The Impact of BRCA2 on Homologous Recombination and PARP Inhibitor Sensitivity Examined in BRCA2 Heterozygous Cell Lines. Retrieved from http://skemman.is/stream/get/1946/21851/51118/1/Stefan_Hermanowicz_Thesis_Final_.pdf
Hidalgo, M. (2010). Pancreatic cancer. New England Journal of Medicine, 362(17), 1605-1617. http://dx.doi.org/10.1056/NEJMra0901557
Hidalgo, M., Cascinu, S., Kleeff, J., Labianca, R., Löhr, J. M., Neoptolemos, J., … & Heinemann, V. (2015). Addressing the challenges of pancreatic cancer: future directions for improving outcomes. Pancreatology, 15(1), 8-18. https://doi.org/10.1016/j.pan.2014.10.001
Hoeijmakers, J. H. (2009). DNA damage, aging, and cancer. New England Journal of Medicine, 361(15), 1475-1485. doi: 10.1056/NEJMra0804615
Krieger, N. (2011). Epidemiology and the people’s health: theory and context (Vol. 213). New York: Oxford University Press.
Krier, J. B., & Green, R. C. (2013). Management of incidental findings in clinical genomic sequencing. Current Protocols in Human Genetics, 9-23. doi: 10.1002/0471142905.hg0923s77
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.
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
Lynch, S. M., & Rebbeck, T. R. (2013). Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach. Cancer Epidemiology Biomarkers & Prevention, 22(4), 485-495. doi: 10.1158/1055-9965.EPI-13-0010
Maitra, A., & Hruban, R. H. (2008). Pancreatic cancer. Annu. Rev. pathmechdis. Mech. Dis., 3, 157-188. doi: 10.1146/annurev.pathmechdis.3.121806.154305
Makohon-Moore, A., Brosnan, J. A., & Iacobuzio-Donahue, C. A. (2013). Pancreatic cancer genomics: insights and opportunities for clinical translation. Genome medicine, 5(3), 26. https://doi.org/10.1186/gm430
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
Pandol, S. J., Apte, M. V., Wilson, J. S., Gukovskaya, A. S., & Edderkaoui, M. (2012). The burning question: why is smoking a risk factor for pancreatic cancer?. Pancreatology, 12(4), 344-349. doi: 10.1016/j.pan.2012.06.002
Pearce, N. (1996). Traditional epidemiology, modern epidemiology, and public health. American journal of public health, 86(5), 678-683.
Rahib, L., Smith, B. D., Aizenberg, R., Rosenzweig, A. B., Fleshman, J. M., & Matrisian, L. M. (2014). Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer research, 74(11), 2913-2921. doi: 10.1158/0008-5472.CAN-14-0155
Richerson, P. J., & Boyd, R. (2000). Evolution: The Darwinian theory of social change: an homage to Donald T. Campbell. Paradigms of Social Change: Modernization, Development, Transformation, Evolution, pp. 1-30. http://www.des.ucdavis.edu/faculty/richerson/evolutionberlin.pdf
Richerson, P. J., Boyd, R., & Henrich, J. (2010). Gene-culture coevolution in the age of genomics. Proceedings of the National Academy of Sciences, 107(Supplement 2), 8985-8992. doi: 10.1073/pnas.0914631107
Schenk, M., Schwartz, A. G., O’Neal, E., Kinnard, M., Greenson, J. K., Fryzek, J. P., … & Garabrant, D. H. (2001). Familial risk of pancreatic cancer. Journal of the National Cancer Institute, 93(8), 640-644. http://dx.doi.org/10.1093/jnci/93.8.640
Yachida, S., & Iacobuzio-Donahue, C. A. (2013). Evolution and dynamics of pancreatic cancer progression. Oncogene, 32(45), 5253-5260. doi: 10.1038/onc.2013.29
Indoor Tanning and Melanoma: A Public Health Issue
Ulysses Labilles and Jennifer Beito
In Minnesota and other parts of the U.S., increase melanoma continue to be common among women than men younger than 50 years. Lazovich et al. (2016) highlighted the gap between age- and the sex-specific association studies between indoor tanning and melanoma. It was found that the strongest correlation between indoor tanning and melanoma is the anatomic site, commonly developed on the trunk in women. Lazovich et al. (2016) stated that while not as strong as for women, 2-fold increase among men who tanned indoors was found to have a higher risk of developing melanomas of the trunk. Furthermore, the findings in this 2016 study are “consistent with the divergent pathway hypothesis for melanoma, which suggest that intermittent solar ultraviolet radiation exposure among those with many nevi, in contrast to chronic solar ultraviolet radiation exposure in persons with fewer nevi, induce the development of the lesion at a younger age, with tumors developing on anatomic sites typically protected from the sun” (Lazovich et al., 2016). Whereas Lazovich et al. (2016) found considerable variation in the correlation between indoor tanning and melanoma by anatomic site, confirming indoor tanning as a possible predictor, responsible for the increased among younger women. Given the timing of increased risk among women indoor tanning users, it is expected for the melanoma epidemic to continue unless indoor tanning is restricted and reduced (Lazovich et al., 2016).
The field of melanoma genetics with new platforms to investigate, makes this area epidemiology move at a high pace. According to Ribero, Glass and Bataille (2016), genes involved in the cell cycle and senescence, identified in the genome-wide association studies over the last ten years, explains the development of the lesion, in addition to telomere biology that further links to reduced senescence. In this study, the role of clinicians was highlighted in recognizing the phenotypic, environmental, and familial risk factors for melanoma to identify those patients at risk who require screening and long-term follow-up (Ribero et al., 2016, p. 338). In this country, skin cancer is the most commonly diagnosed cancer and increasingly becoming a major public health problem with more than 60,000 melanomas diagnosed in 2010 (Rogers et al. 2015; Guy et al. 2015). The potential causality for increased melanoma incidence was discussed by Rivera, Han, and Qureshi (2013), traced to the 1980 obbligato explosion in indoor tanning. It is, therefore, essential for continued investigation from scientists, professional societies and legislators (Rivera et al., 2013). Using REP resources aggregated from residents of Olmsted County, Minnesota between 1970 and 2009, 256 young adults their first lifetime diagnosis of melanoma, between the ages of 18 and 39 years of age (Reed et al. (2012). The study confirms the arguments of Bleyer et al. (2006) that “the incidence of cutaneous melanoma is increasing among young adults, with this rate increasing more than 6-fold among adult men than women, but incidence are reversed among young adults and adolescents, with the female-male incidence ratio of 1.8 in young adults aged 20 to 24 years.” (Reed et al., 2012, p. 331) Reed et al. (2012) noted that the results of studies from the Rochester Epidemiology Project (REP) might be explained by some sex-specific behaviors such the increase likelihood of young women to participate to different UV light exposure than young men. While De Giorgi et al. (2012) stated that only minimal changes in mortality had been observed, there is a continuous increase in melanoma incidence worldwide. De Giorgi et al. (2012) supported the argument that indoor tanning may have been responsible for increased melanoma incidence in women and younger tanning bed users with higher estimated risk ratio in the general population. Debates over reducing indoor tanning tend to dominate discussions for its potential to reduce melanoma incidence, mortality, and treatment costs, the findings of the 2016 study of Guy et al. underscored the increased economic benefits and quantified the significance of continued efforts to reduce indoor tanning in preventing melanoma. Using a Markov model to estimate the expected number of melanoma cases, lives and treatment costs saved, Guy et al. (2016) estimated 61,839 melanoma cases, prevent 6735 melanoma deaths, saving $342.9 million in treatment costs over the lifetime of the 61.2 million youth age 14 years or younger in the U.S. by restricting the use of indoor tanning among minors younger than 18 years (Acscan.org, n.d.).
Discussion. Melanoma remains a public health issue, despite efforts to reduce indoor tanning, making melanoma incidence to rise continuously in the U.S. and globally, over and above-attempted prevention efforts (Le Clair, & Cockburn, 2016). The increased risk of malignant melanoma and other forms of skin cancer are found to be correlated with the ultraviolet radiation from indoor tanning device, considered to be an urgent public health issue need to adopt the Action Model to Achieve Healthy People 2020. Ultraviolet light emitted from tanning beds is classified carcinogenic by the World Health Organization International Agency for Research on Cancer (IARC) in 2009, as an interceptive response to the associated risk of exposure with the initiation of melanoma (El Ghissassi et al., 2009). Tanning beds and its carcinogen, the length of time the skin is exposed, and whether or not the skin is protected with prescribed protection such sunscreen are all the key influences contributing the increased risk. Many individuals are exposed to sunlight during their quotidian lives, and popular alfresco activities elevate a person’s chance of developing skin cancer. For example, athletes who spend countless hours training and competing in the sun, workers who need to be under the direct sun exposure all day and children who play outside for countless hours are more prone to developing skin cancer. Exposure to UV radiation during childhood plays is a major role in the future development of melanoma and non-melanoma skin conditions. Many studies have determined that even short, intermittent but excruciating exposure to sunlight during childhood and adolescence significantly increase one’s risk of developing melanoma. More than one moiety of a person’s lifetime UV exposure occurs during childhood and adolescence. If a person has a history of one or more blistering sunburns during childhood or adolescence, such exposure could put these individuals two times greater risk to developing melanoma than those who did not have such exposures (Glanz, & Wechsler, 2002). Ultraviolet radiation is divided into three wavelengths ranges, however; only two of the ranges authentically perforate our atmosphere, UVA, and UVB. Scientists initially believed that only UVB rays played a role in the formation of skin cancer. UVB light does cause deleterious transmutations in skin cell DNA. UVB rays are responsible for sunburn and many basal and squamous cell cancers (English, Canchola & Finley, 1998). However, there are no safe UV rays. UVA rays withal contribute to skin cancer. These rays could cause a deeper skin damage than UVB, emasculates the skin’s immune system and increases the peril of cancer development, especially melanoma. Tanning lamps and tanning beds distribute high doses of UVA, which makes them especially hazardous (Goldstein & Goldstein, 2001). A 2002 Dartmouth study as noted by Goldstein and Goldstein (2001) showed tanning bed users had 2.5 times the peril of SCC and 1.5 times the jeopardy for BCC. Individuals more predisposed than others to the damaging effects of UV radiation could develop skin cancers. The increased risk of melanoma is shown to be higher among individual with family history. Melanoma and other types of skin cancer, risk factors include light or fair skin color, natural blond or red hair, sun sensitivity, immune suppression disease, vocation and geographic location (Goldstein & Goldstein, 2001).
Cases ascertained by a population-based, statewide cancer registry known as the Minnesota Cancer Surveillance System Skin Health Study and approved by the Institutional Review Board at the University of Minnesota, Lazovich et al. (2010) addressed the limitations on past studies in adjusting sun exposure and dose response of individuals using indoor tanning. Individuals diagnosed with any histologic type of melanoma between July 2004 and December 2007, between the ages of 25 and 59 was collected based on state driver’s license or state identification card. Previous studies show that indoor tanning use decreases with age. Therefore, the researchers truncated the age limit to 59 years old. Multiple regression was performed, and adjusted odd ratios show the likelihood of melanoma among users of indoor tanning, and never users were similarly elevated regardless of the age when indoor tanning began (Lazovich et al., 2010). The study of Lazovich et al. (2010) has several significant findings: “First, melanoma was found to be more frequent among indoor tanners compared with persons that never engaged in this activity. Second, measured by total hours, sessions, or years, a strong dose-response relationship was found between melanoma risk. Lastly, an increased risk of melanoma was found with the use of each type of tanning device examined as well as with each period of tanning use, suggesting that no device could be considered safe. Burns from indoor tanning seemed to be fairly common and conferred a similar risk of melanoma to sunburns, strengthening the associations explored significant even after adjusting for the potential confounding effects of known risk factors for melanoma.” (pp. OF9-OF10) Le Clair and Cockburn (2016) asserted the importance of prevention through doctor’s consultation, focusing on the significant impact of behavioral change than written intervention. The findings of this study suggest that knowledge of sun sensitivity in individuals with high UVR sensitivity may reinforce a positive outcome in sun exposure habits, and could represent a useful tool for reducing indoor tanning (Le Clair, & Cockburn, 2016, p.142). Spending an abundance of time alfresco for work or recreation without protective apparel and sunscreen increases the risk to develop skin cancers. However, no matter what treatment you may cull; the primary cause is something which is kenned and avoidable – natural and artificial UV rays. As a result, the 2 primary aversion methods are simple to recollect, edify and implement – they are endeavored and proven (Goldstein & Goldstein, 2001): “Significantly limit exposure to the sun between the hours of 10 am and 4 pm, utilizing a sunscreen with an SPF of 15 or higher at all times each day, cover your skin with apparel, wear a hat and use sunglasses. Second, verbally express “no” to all other sources of UV radiation such as tanning beds and tanning lamps. Ergo, the next time you visually perceive someone exiting the tanning salon, relaxing midday in the direct sun at the beach or ambulating around with a flamboyantly discernible tan, do not be envious. Instead, view this person as you would a person smoking a cigarette. They are acting temerariously and jeopardizing their lives in an endeavor to imitate what is occasionally introduced by the media. Recollect, despite what the media may lead you to believe; you do not require a tan to look good. During the 2012 meeting by the Centers for Disease Control and Prevention (CDC), it was concluded that future cases of skin cancer could be prevented, along with the associated morbidity, mortality, and healthcare costs through discussion of research gaps and current body of evidence on strategies to reduce indoor. The overarching goals of Healthy People 2020 should be the framework of existing and future studies embracing the state of the evidence on strategies to reduce indoor tanning; the tools necessary to adequately assess, monitor, and evaluate the short- and long-term impact of interventions designed to reduce indoor tanning; and strategies to align efforts at the national, state, and local levels through transdisciplinary collaboration and coordination across multiple sectors (Holman et al., 2013).
Conclusion. The participation of health care providers is required for information dissemination as well as physical and psychological screenings to improve education to address the misconception about tanning safety. According to Friedman et al. (2105) “Public perception of the purported health benefits of indoor tanning can be blamed for the popularity of tanning salons as a desire to prepare the skin before sun exposure, the most commonly cited motivations for indoor tanning.” improve education to address the misconception about tanning safety. Artificial UVR is often misconceived to produce a “safer” tan than outdoor sunlight (CDC, 2014). Le Clair, & Cockburn (2016) argued that this belief is “contradicted by scientific evidence, and must be addressed to effectively reduce the burden of indoor tanning on health outcomes worldwide.” (p. 140) According to Whitmore et al. (2001), Karagas et al. (2002), and Green et al. (2007), DNA damage in skin cells caused by exposure to indoor tanning UVR is associated with an increased risk of melanoma induction and other types of non-melanoma skin cancers. In-depth understanding of clinicians providing public health education outreach programs is critical from the epidemiology of melanoma to the increased risk of the developing tumors with the frequent use or use of tanning beds. Lobbying efforts such as the Indoor Tanning Association are the most significant barrier to state indoor tanning legislation (Obayan et al., 2010). The risk and benefits of indoor tanning was discussed during the 2012 report of the minority staff of the House Committee on Energy and Commerce, asserted that 80 % of tanning salons told investigators that indoor tanning was beneficial to fair-skinned teenage girls, while 90 % of tanning salons denied that sunlamp use posed any health risks to this vulnerable group (Gottlieb et al., 2015). Such argument not supported by peer-reviewed study should always be challenged, and leaders both political, healthcare and public health should continue to cooperate in drafting evidence-based legislations to ease the economic and individual burden of melanoma induced by indoor tanning. It is paramount to increase the height of prevention efforts, not only limiting the use of tanning beds to children aged 18 or younger, but also to young adults over 18 years old who have increased the risk to melanoma. The transdisciplinary, multilevel, and coordinated approach has the potential to combat future cases melanoma and other forms of skin cancers by reducing indoor tanning, withal many barriers and challenges. While the role of new common sense legislation in tandem with public education campaigns is paramount, mass media campaigns are critical in introducing strategies and highlighting shared environmental risk, as well as the avoidable risk of indoor tanning use. Holman et al. (2013) posit that by reducing indoor tanning use, future cases of skin cancer could be prevented through tailored interventions following the context of comprehensive skin cancer prevention that promotes sun protection and sunburn avoidance when outdoors (Coups, Manne & Heckman,2008). Addressing contextual factors that promote tanning, including environmental and systems changes, social norms, the indoor tanning industry and the media will be dependent upon close coordination and collaboration of key partner across multiple levels. Continued literature must be encouraged among legislators, clinicians, and public health leaders, spreading its highlights through effective mass media outreach.
Bleyer, A., O’Leary, M., Barr, R., & Ries, L. A. G. (2006). NIH Publication No 06-5767. Bethesda, MD: National Cancer Institute. Cancer epidemiology in older adolescents and young adults, 15, 1975-2000.
Coups, E. J., Manne, S. L., & Heckman, C. J. (2008). Multiple skin cancer risk behaviors in the US population. American journal of preventive medicine, 34(2), 87-93.
CDC (2014). The Burning Truth. Retrieved from http://www.cdc.gov/cancer/skin/burningtruth/index.htm (2014)
El Ghissassi, F., Baan, R., Straif, K., Grosse, Y., Secretan, B., Bouvard, V., … & Cogliano, V. (2009). A review of human carcinogens—part D: radiation. The lancet oncology, 10(8), 751-752.
English 3rd, J. C., Canchola, D. R., & Finley, E. M. (1998). Axillary basal cell carcinoma: a need for full cutaneous examination. American family physician, 57(8), 1860-1864.
De Giorgi, V., Gori, A., Grazzini, M., Rossari, S., Oranges, T., Longo, A. S., … & Gandini, S. (2012). Epidemiology of melanoma: is it still epidemic? What is the role of the sun, sunbeds, Vit D, betablocks, and others?. Dermatologic Therapy, 25(5), 392-396.
Faculty Expertise in Cancer – School of Public Health. (n.d.). Retrieved from http://sph.umn.edu/faculty1/expertise/cancer/name/deann-lazovich/
Friedman, B., English, J. C., & Ferris, L. K. (2015). Indoor tanning, skin cancer, and the young female patient: a review of the literature. Journal of pediatric and adolescent gynecology, 28(4), 275-283.
Glanz, K., Saraiya, M., & Wechsler, H. (2002). Guidelines for school programs to prevent skin cancer. MMWR. Recommendations and reports: Morbidity and mortality weekly report. Recommendations and reports/Centers for Disease Control, 51(RR-4), 1-18.
Goldstein, B. G., & Goldstein, A. O. (2001). Diagnosis and management of malignant melanoma. American family physician, 63(7), 1359-68.
Gottlieb, M., Balk, S. J., Geller, A. C., & Gershenwald, J. E. (2015). Teens and Indoor Tanning: Time to Act on the US Food and Drug Administration’s Black-Box Warning. Annals of surgical oncology, 22(3), 701-703.
Green, A., Autier, P., Boniol, M., Boyle, P., Doré, J. F., Gandini, S., … & Westerdahl, J. (2007). The association of use of sunbeds with cutaneous malignant melanoma and other skin cancers. International Journal of Cancer, 120(5), 1116-1122.
Guy, G. P., Machlin, S. R., Ekwueme, D. U., & Yabroff, K. R. (2015). Prevalence and Costs of Skin Cancer Treatment in the US, 2002− 2006 and 2007− 2011. American journal of preventive medicine, 48(2), 183-187.
Guy, G. P., Zhang, Y., Ekwueme, D. U., Rim, S. H., & Watson, M. (2016). The potential impact of reducing indoor tanning on melanoma prevention and treatment costs in the United States: An economic analysis. Journal of the American Academy of Dermatology.
Holman, D. M., Fox, K. A., Glenn, J. D., Guy, G. P., Watson, M., Baker, K., … & Sampson, B. P. (2013). Strategies to reduce indoor tanning: current research gaps and future opportunities for prevention. American journal of preventive medicine, 44(6), 672-681.
Increasing Incidence of Melanoma Among Young Adults: An … (n.d.). Retrieved from http://www.sciencedirect.com/science/article/pii/S0025619612002091
Indoor tanning for kids? Might as well expose them to … (n.d.). Retrieved from https://acscan.org/news/indoor-tanning-kids-might-well-expose-them-plutonium
Karagas, M. R., Stannard, V. A., Mott, L. A., Slattery, M. J., Spencer, S. K., & Weinstock, M. A. (2002). Use of tanning devices and risk of basal cell and squamous cell skin cancers. Journal of the National Cancer Institute, 94(3), 224-226.
Lazovich, D., Vogel, R. I., Berwick, M., Weinstock, M. A., Anderson, K. E., & Warshaw, E. M. (2010). Indoor tanning and risk of melanoma: a case-control study in a highly exposed population. Cancer Epidemiology and Prevention Biomarkers, 1055-9965.
Lazovich, D., Vogel, R. I., Weinstock, M. A., Nelson, H. H., Ahmed, R. L., & Berwick, M. (2016). Association between indoor tanning and melanoma in younger men and women. JAMA Dermatology, 152(3), 268-275.
Le Clair, M. Z., & Cockburn, M. G. (2016). Tanning bed use and melanoma: Establishing risk and improving prevention interventions. Preventive Medicine Reports, 3, 139-144.
Obayan, B., Geller, A. C., Resnick, E. A., & Demierre, M. F. (2010). Enacting legislation to restrict youth access to tanning beds: A survey of advocates and sponsoring legislators. Journal of the American Academy of Dermatology, 63(1), 63-70.
Position Statement on Indoor Tanning (Approved by the … (n.d.). Retrieved from https://www.aad.org/Forms/Policies/Uploads/PS/PS-Indoor%20Tanning.pdf
Reed, K. B., Brewer, J. D., Lohse, C. M., Bringe, K. E., Pruitt, C. N., & Gibson, L. E. (2012). Increasing incidence of melanoma among young adults: an epidemiological study in Olmsted County, Minnesota. In Mayo Clinic Proceedings (Vol. 87, No. 4, pp. 328-334). Elsevier.
Ribero, S., Glass, D., & Bataille, V. (2016). Genetic epidemiology of melanoma. European Journal of Dermatology, 26(4), 335-339.
Rivera, A. R., Han, J., & Qureshi, A. A. (2013). Has too much blame been placed on tanning beds for the rise in melanoma diagnosis?. Expert Review of Dermatology, 8(2), 135-143.
Rogers, H. W., Weinstock, M. A., Feldman, S. R., & Coldiron, B. M. (2015). Incidence estimate of nonmelanoma skin cancer (keratinocyte carcinomas) in the US population, 2012. JAMA Dermatology, 151(10), 1081-1086.
US House of Representatives Committee on Energy and Commerce (2012). A new report reveals indoor tanning industry’s false and
misleading practices. Retrieved from HTTP://
Whitmore, S. E., Morison, W. L., & Potten, C. S. (2001). Tanning salon exposure and molecular alterations. Journal of the American Academy of Dermatology, 44(5), 775-780.
Cancer is a growing global problem and is increasing in the proportion of the burden among low income and middle-income countries. While the pattern can be blamed on demographic change and to transition in risk factors, it can be prevented by present knowledge of modifiable risk factors and continued research on cancer genetic landscape. Pancreatic cancer (PC) has the lowest 5-year relative survival rate, and treatment for metastatic pancreatic cancer are minimally effective. In early 2000, incidence rates of PC have been approximately stable in many European countries. Ma, Siegel, & Jemal (2013) noted that the complex patterns of PC death rate trends remain unexplained by known risk factors. Given that there are only 20% of patients diagnosed with the disease are eligible for surgical resection (Spanknebel & Conlon, 2000); it is paramount to rationalize the importance of the development of public health policies designed in lowering the economic burden of the disease. Money saved from reducing the overall economic burden of the disease could open up resources and funding allocation to pursue other public health projects for the better good of the many. A synergy begets by outcomes research and epidemiology can provide unique and compelling insights on the significance of interventions designed to improve the quality and effectiveness of care in populations. Recent developments in non-communicable diseases (NCDs) epidemiology highlight the increasing worldwide burden of NCDs as the result of complicated interactions between several demographic, economic and social structural changes (Suhrcke et al., 2006), considered to be strongly associated with the globalization of unhealthy lifestyles (Ferretti, 2015). Between 1997 and 2002, unhealthy behavior index (UBI) tends to increase along with the level of human development. In the USA and Japan, mortality has been declining since the previous decades, including Argentina, Colombia, Puerto Rico and Hong Kong, with a reversal of trends over the most recent years (Bosetti et al., 2012). Trends were also declining in countries of central/eastern Europe with highest rates, such as the Czech Republic, Croatia, and Hungary, but mortality rates reached 8.5/100,000 men in 2006 in Russia. Ferretti (2015) found that Belarus and Russian Federation are the two countries with the unhealthiest NCD-related lifestyle. Tobacco use, and in particular cigarette smoking, is the single largest preventable cause of cancer in the European Union (EU), including second-hand smoke (SHS), that is still common in indoor, indoor public places, and more so in the homes of smokers (Leon et al., 2015). Secondhand smoke, referred to as ETS, contains many of the same carcinogenic compounds as the mainstream smoke inhaled by active smokers (World Health Organization, International Agency for Research on Cancer, 2004; Bao et al., 2009).
In early 2000, incidence rates of PC have been approximately stable in many European countries, Japan, Australia and the US. Overall trends are likely to improve in the next future with more favorable recent trends in young adults from 30 to 49 years old (Bosetti et al., 2012). PC has the global ranking of 13 as the most common cause of cancer and represents the 7th most frequent cause of cancer death, and accounts for about 3% of all cancers in the US with cancer mortality of 7% (American Cancer Society, Inc., 2016). PC ranked fourth among all cancers in the U.S. (Jamal et al., 2003), the mortality rate of the disease in China ranks sixth (Ding et al., 2015). There are more than 278,000 new diagnoses of pancreatic ductal adenocarcinoma (PDAC) annually worldwide, accounting for 10% of all digestive system cancers (Ferlay, et al., 2010). The 5-year survival rate makes the prognosis of this disease dismal and the twelfth most common cancer in the world with 338,000 new cases diagnosed in 2012. Czech Republic had the highest rate of pancreatic cancer with a 9.7 age-standardized rate per 100,000 (World), followed by Slovakia and Armenia. (World Cancer Research Fund International, 2015). The highest incidence of PC is found in the Czech Republic, ranking second in men (11.9 per 100,000) and first in women (7.9 per 100,000). The key PC statistics according to the American Cancer Society are lifetime risk of 1.5% (1 in 65) for both men and women; 27,670 men and 25,400 women will be diagnosed; 21,450 men and 20,330 women will die of the disease. Using data from nine registries of the Surveillance, Epidemiology and End Results (SEER) program, Shaib, Davila and El‐Serag (2006) examined temporal changes in the incidence and survival of patients with pancreatic adenocarcinoma. The study identified 58,655 cases of pancreatic cancer. Age-adjusted and age-specific was calculated grouped in 5 yearly intervals: 1977–1981, 1982–1986, 1987–1991, 1992–1996 and 1997–2001. The average age-adjusted yearly incidence of PC was 11.3 per 100 000 in 1977–1981 and 10.9 per 100 000 in 1997–2001. Overall incidence rates were also calculated for different subgroups based on gender (men, women) and race (White, Black, others) and geographic location as defined by SEER registries. Men had approximately 30% higher incidence rates than women with an overall average age-adjusted yearly incidence rate of 13.0 per 100 000 (95% CI: 12.9–13.2) among men and 9.8 per 100 000 (95% CI: 9.7–9.9) among women. Among different racial groups, Blacks were approximately 50% more affected when compared with Whites and people of other races. The overall average age-adjusted yearly incidence rates were 16.4 per 100 000 (95% CI: 16.0–16.9) for Blacks, 10.8 per 100 000 (95% CI: 10.7–10.9) for Whites and 9.8 per 100 000 (95% CI: 9.4–10.1) for people of other races. The overall average age-adjusted yearly incidence rates were 16.4 per 100 000 (95% CI: 16.0–16.9) for Blacks, 10.8 per 100 000 (95% CI: 10.7–10.9) for Whites and 9.8 per 100 000 (95% CI: 9.4–10.1) for people of other races.
Primary prevention must be prioritized as an integral part of global cancer control. According to Vineis et al., (2014), primary prevention has several advantages: the effectiveness could have benefits for people other than those directly targeted, avoidance of exposure to carcinogenic agents is likely to prevent other non-communicable diseases, and the cause could be removed or reduced in the long term through regulatory measures against occupational or environmental exposures such as environmental tobacco smoke (ETS). Improving the future of individuals diagnosed with PC through the concerted efforts of policymakers, public health professionals, clinicians and scientists, the Recalcitrant Cancer Research Act of 2012 lays the foundation for a heightened focused on further development and use of prevention, screening and therapeutic strategy (Rahib et al., 2014). Introduced initially as the Pancreatic Cancer Research and Education Act, the Recalcitrant Cancer Research Act was signed into law as part of the National Defense Authorization Act on January 2, 2013, through broad bi-partisan and bi-cameral support (The Pancreatic Cancer Action Network, 2013). The genuine progress against PC as a recalcitrant cancer warrants strategic direction and guidance on the continued understanding, development of efficient early detection strategy and identifying therapeutic targets that could stem the tide of its growing economic burden.
PubMed, Google Scholar, and JSTOR were searched from 1990 to present. Scholarly materials considered in this systematic literature review are epidemiologic research of environmental tobacco smoke (ETS) and assess its relationship to pancreatic cancer, as well as other demographics related to the disease. Peer-reviewed literature is identified using Thoreau Multi-Database. I identified a total of 25 studies, 15 articles met the final inclusion criteria.
After the completion of the Human Genome Project (HGP) in 2003, the theory used in the studies in this systematic scholarly literature review is the Genome Theory of Cancer Evolution. Moreover, building on the premise of one of the variants of sociopolitical epidemiologic theory, the fundamental cause approach in the 2014 study of Rubin et al. stated that while the variant’s hypothesis predicts the increased prevention of lung cancer with the development and dissemination of knowledge of the causal link of tobacco use to the disease. There has been no change in the mortality of pancreatic cancer because of lack of major prevention or treatment innovations. The data analyzed in this study supported the fundamental cause hypothesis and asserted the impact of access to resources amplified by the availability of preventive knowledge. The study highlighted the role of public health interventions and policies in facilitating more equitable distribution of new health-enhancing knowledge and the faster uptake and utilization among lower socioeconomic status (SES) group. On the contrary, the argument of integrating the individual-biologic and population levels of analysis that embody the premise of ecosocial framework put public health in the conundrum of the proximal-distal divide. The interlinking of the traditional epidemiologic level of intervention (upstream or distal) and the modern epidemiologic level of intervention (downstream or proximal) embraced by both biomedical and social determinist frameworks are proposed to be replaced with explicit language about levels, pathways, and power (Krieger, 2008). Parallel to the argument of integrating the individual-biologic and population levels of analysis (Chen et al., 2015), utilizing a 2 × 2 factorial design, patients were randomized to either observation, 5-FU based chemotherapy, 5-FU based chemoradiation, or both after undergoing curative resection, Neoptolemos et al. (2004) investigated the efficacy of both chemotherapy and chemoradiation in patients undergoing surgical resection (p. 15565). In this 2004 study of Neoptolemos et al., a significant survival benefit was found in patients who received systemic 5-FU based chemotherapy, leading to a European standard of care that does not include radiation therapy in the multimodal treatment of the disease. On the other hand, because of the randomization scheme, the relatively low-dose of radiation administered and the lack of quality control of the radiotherapy administered, the negative prognostic effect of chemoradiotherapy was not accepted within the United States. Overall, after a review of clinically relevant biomarkers in PC, while the neoadjuvant approach is presently the best available strategy, both epigenetic profiling and the identification of various oncologic microRNA molecules, contributes to the field of PC treatment (Neoptolemos et al., 2004). While the predictive and prognostic abilities, of molecular biomarkers, have gained popularity, surgical resection in combination with chemotherapy and/or chemoradiation have the best opportunity for long-term survival.
In the discussions on the impact of environmental exposures on human health, Peters, Hoek and Katsouyanni (2012) emphasized on the significance of environmental epidemiology in providing robust evidence to assist timely and sufficient protection of vulnerable subgroups of populations from environmental hazards. While the researchers discussed some limitations of the exposome in biological samples, the study noted individual’s exposure that begins before birth and over his or her lifetime. The notion of considering the vulnerable periods and assessment of environmental exposures in a life-course fashion is a precious concept embedded in the exposome paradigm argued in this study as a missing feature in environmental epidemiology. Another missing feature is the combined analyses of studies from different life phases that need conceptual and statistical methodological developments along with integrative exposures assessment combined with traditional and novel approaches. Peters et al. acknowledged the significance of emerging wealth of methods and data, as well as asserted the necessity to integrate environmental questions into research on disease mechanisms that is overturning paradigms based on technical innovations (p. 104). ETS is an example of environmental exposure that has been associated with an array of adverse effects on health. Secondhand smoke, referred to as ETS, contains many of the same carcinogenic compounds as the mainstream smoke inhaled by active smokers (World Health Organization, International Agency for Research on Cancer, 2004; Bao et al., 2009). Given that the role of passive smoking in pancreatic carcinogenesis remains unclear, Bao et al. (2009) examined the association of ETS with PC risk. In this prospective study, 86,673 women in the Nurses’ Health Study was considered, and ETS exposure was assessed through questionnaires. Using Cox proportional hazards models, relative risks (RR) and 95% confidence intervals (CI) were estimated. Bao et al. (2009) found that maternal smoking significantly increased the risk of PC (RR, 1.42; 95% CI, 1.07–1.89). Conceding the fact that the risk associated with maternal smoking remained elevated, no association was found for adult passive exposure at work or home. Paternal smoking was not related to the risk (RR, 0.97; 95% CI, 0.77–1.21). In addition to self-reported indicators of exposure through questionnaires or interviews that was used by the Bao et al. in their 2009 study, there are other ways to measure ETS: measuring tobacco smoke components in the air to which subjects are exposed (environmental measurements), and the use of biomarkers to measure concentrations of components of smoke in the body of exposed individuals. While environmental measures are considered suboptimal and may not reflect the dose of ETS that reaches the body; self-reports and biomarkers have been more commonly used in epidemiologic studies. Questionnaires are not only inexpensive to administer to large numbers of subjects; this measurement tool has been successfully used in many smoking cessation studies (Fergusson et al., 1998; World Health Organization, 2001; Brooks et al., 2004). A meta-analysis of studies that validated self-reported smoking behavior with biochemical measurements, Patrick et al. (1994) concluded that self-reports of smoking status are accurate in most studies. However, using questionnaire data alone makes analysis and quantification of ETS exposure challenging and need more objective and reliable methods. Hatsukami et al. (2003) proposed several potential biomarkers that measure ETS exposure and include carboxyhemoglobin, thiocyanate, carbon monoxide (CO), DNA adducts, protein adducts, nicotine, and cotinine (p. 11). Both self-reports and biomarkers help in producing evidence-based studies needed in the development of smoke-free air policies. Without reliable ETS exposure measurements, there will be no scientific evidence that will support the significance of smoke-free policy adoption. On the other hand, environment measurements could play a major role in evaluating policies that have been implemented. In the Netherlands Cohort Study, Heinen et al. (2010) examined the role of active cigarette smoking, smoking cessation, and passive smoking as determinants consisted of 120,852 men and women who completed a baseline in a 1986 questionnaire. Using a case-cohort approach, person-years of follow-up of a random subcohort (n = 5,000) was chosen. Multivariable-adjusted hazard rate ratio (HR) of 1.34; 95% confidence interval (CI), 1.02-1.75 and HR, 1.82; 95% CI, 1.40-2.38 after comparison with never cigarette smokers. While there are no association was observed between passive smoking exposure and PC risk in women; Heinen et al. observed an increased risk per increment of 10 years of smoking (HR, 1.15; 95% CI, 1.08-1.22) and an HR of 1.08 per increment of 10 cigarettes/d (95% CI, 0.98-1.19). There are 520 PC incident cases was observed after 16.3 years of follow-up. The study confirmed that cigarette smoking is an important risk factor for the disease, and quitting smoking benefits the burden on incidence level.
While smoking has been established as a PC risk factor, passive smoking remains to confirm as an environmental factor. According to Simard, Rosner and Michels (2008), recent studies argue that passive smoking put fetuses to have a higher risk of illnesses later in life. Ding et al. (2015) explored the relationship between PC and passive smoking. In this study, a Hospital-based case-control study on PC was conducted from the inpatient of five hospitals from Oct. 1991 to Sep. 2014. History of exposure to ETS was quantified using Cox proportional hazards models to estimate relative risks (RR) and 95% confidence intervals (CI). From 1991 to 2014, 686 men and 390 women were diagnosed with PC, and compared to paternal smoking (RR, 0.97; 95% CI, 0.77-1.21; P = 0.084), maternal smoking significantly increased the risk of pancreatic cancer (R, 1.56; 95% CI, 1.13-1.98; P = 0.018). In this study, the risk associated with maternal smoking remained elevated compared to the never smokers (RR, 1.49; 95% CI, 1.072.27). The results of this study are suggestive of the positive association between maternal smoking and the potential role of early exposure to environmental tobacco smoke in pancreatic carcinogenesis. Ding et al. confirmed the significant overall risk of PC maternal smokers, but not among paternal smokers. The researchers suggested that the only way to reduce the burden of the disease is maternal smoking inhibition. Canada like the U.S., PC is the fourth leading cause of cancer mortality. While obesity and diet have been identified as modifiable risk factors associated with the etiology of this disease (Hanley, Johnson, Villeneuve & Mao, 2001; Michaud et al., 2001), it has been estimated that both active and passive smoking is 27-33% attributable to all PC cases (Silverman et al., 1994; Siemiatycki, Krewski, Franco & Kaiserman, 1995), containing numerous carcinogenic constituents. ETS contains 43 known carcinogens with smaller particle sizes (vapor phase constituents rather than particulate phase) making it unclear which cancer sites may be affected by ETS exposure. In 2004 of Villeneuve, Johnson, Mao, and Hanley, the relationship between PC incidence and ETS was explored using data collected from a Canadian population-based case-control study that was conducted in 8 provinces between 1994 and 1997. The researchers examined the same subjects of their 2000 study who formed the basis of risk assessment to evaluate the associations between PC, coffee consumption, alcohol, and measures of tobacco use among smokers, and using methods developed previously to assess the relationship between ETS and other type of cancers within is a large-scale Canadian research initiative called as the National Enhanced Cancer Surveillance System (NECSS). Mailed questionnaires, with telephone follow-up if necessary to clarify the lifetime history of potential exposure at home and work to passive smoking. Multivariate models were adjusted for the effects of other known or suspected risk factors of PC, and risk assessment was performed for males, females and both. An odds ratio of 1.21 (95% CI=0.60-2.44) among never smokers, those who were exposed to ETS both as a child and as an adult relative to those with no exposure. Villeneuve et al. (2004) found that risk increases were more pronounced among active smoker with an increased number of years of smoking, cigarette pack-years, years since quit smoking, and an average number of cigarettes smoked daily, compared to those who are never smokers and had not been regularly exposed to ETS (p. 34). While the results of this study are suggestive of a weak association between PC and ETS, the results show the probable confounding role of ETS smoking in the association of active smoking with PC.
In the study on pathological changes in the pancreas of smokers, Tomioka et al. (1990) examined histopathologically 73 pancreases obtained by autopsy from 42 heavy cigarette smokers and 31 non-smoker patients. One invasive adenocarcinoma measuring 2 cm in diameter and three small carcinomas (2-5 mm in diameter) were found in smokers and one small carcinoma in a non-smoker patient. The pathological difference between smokers and non-smokers in this study was statistically not significant, albeit the incidence of PC in smokers was higher than in non-smokers. The type and the incidence of ductal alterations, two had lung cancer, one skin cancer, one colon cancer and one was free of any malignancies. Ductal changes, including mucinous or squamous cell metaplasia and papillary hyperplasia) were found with equal frequencies in both smokers and non-smokers. Exclusion of other relevant variables (diet, diabetes, alcohol) weakens the strength of this study. Considering that the results of this study are subjective to age-related incidence rather than smoking history, the researchers should have included risk factors such as family history of PC, high-risk inherited syndromes such as among Ashkenazi Jews, and other environmental tobacco exposures such as cigar, and pipe smoking. Using these approach, the researchers could have the chance to compare tumor size differences between smokers and non-smokers that could be associated with these demographics including race, and high fat/high cholesterol diet., obesity, chronic pancreatitis, and diabetes mellitus. Results of such research design could have a more meaningful outcome and amplify the significance of the result especially in correlating the study shared exposure of subjects to ETS. It is important to acknowledge the need for continued research to establish a meaningful risk prediction models that could be practically applied in clinical settings to raise the accuracy of predicting the potential for PC. Given that surgical resection procedure is the only treatment approach that could improve survival rate, establishing a high-risk prediction model using novel early identification protocol of pre-malignant lesions and molecular profiling is paramount, as part of a personalized therapeutic approach and standardized methods of early detection, and prevention.
PC involves both genetic and environmental factors, and like any other human diseases, PC is complex and multifactorial that has the greatest burden on society. According to Bookman et al. (2011), the development of high-density genotyping platforms has allowed investigators to screen hundreds of thousands of genetic variants to test for associations with disease (p.2). Hindorff et al. (2011) asserted that to date, Genome Wide Association Studies (GWAS) have identified over 900 statistically significant findings in various diseases and conditions. Parallel to this argument, Yeo et al. (2009) characterized one of the largest national registries of familial PC and sporadic PC, focusing on demographics, survival status, clinical factors, self-reported environmental and occupational lifetime exposures. In this retrospective cross-sectional study, the data was aggregated from the Johns Hopkins National Familial Pancreas Tumor Registry (NFPTR) enrolled between 1994 and 2005. While the study did not perform a comparative histopathological assessment, Yeo et al. conducted a case-only analysis that includes cases of 569 FPC (n=569) and 689 SPC. In addition to the reported risk factors such high-risk inherited syndromes, family history of PC, exposure to occupational and environmental carcinogens, cigarette, pipe smoking, and cigar, other demographics included in this study are age, race, chronic pancreatitis, diabetes mellitus, high fat/high cholesterol diet and obesity. The results show that exposure to tobacco carcinogens and environmental tobacco smoke (ETS) could lead to the earlier occurrence of PC. Yeo et al. (2009) concluded that the findings provided a risk prediction model that support the benefit of early identification of pre-malignant lesions and molecular profiling, as methods of early detection, prevention, and personalized therapy for high-risk individuals. While Yeo et al. was the first to generate the findings that occupational and environmental exposures may act synergistically with inherited or acquired genetic polymorphisms; Gallicchio et al. (2006) examined the association of household passive smoke exposure and active cigarette smoking in the development of PC using a prospective cohort design from the Washington County Cancer Registry. Current active smokers were found to have a two-fold increased risk of PC using Poisson regression analysis in both cohorts, the 1963 cohort to 1978 (n = 45,749) and 1975 cohort from 1975–1994 (n = 48,172). While household passive smoke exposure was not associated with an increased risk of PC among never-smokers in each cohort that could be explained by wide confidence limits due to a small number of cases, Gallicchio et al. further documents the approximate doubling of PC risk in current active smokers. Vrieling et al. (2010) examined the association between ETS exposure and tobacco use with PC risk within the European Prospective Investigation into Cancer and Nutrition (EPIC). Data analysis was based on 465,910 participants, including 524 first incident PC cases diagnosed after a median follow-up of 8.9 years. In this study, using Cox proportional hazard models, an increased risk of PC was found among current cigarette smokers with greater intensity and pack-years compared with never smokers (HR = 1.71, 95% CI = 1.36–2.15). Among never smokers with daily ETS exposure during childhood, increased PC risk was found with HR = 2.61, 95% CI = 0.96–7.10 and HR = 1.54, 95% CI = 1.00–2.39 among those who are exposed to ETS at home and/or work. The results of this study show that while PC risk is reduced to levels of never smokers within five years of quitting, increased risk of the disease is associated with both active cigarette smoking and ETS exposure. Studies of passive smoking or the use of noncigarette tobacco products often are limited by the small number of exposed individuals among never smokers, albeit the high prevalence of cigarette smoking among PC patients. Hassan et al. (2007) assessed the associations between the risk of pancreatic cancer and passive smoking and the use of other tobacco products using a large-scale case-control study from 2000 to 2006. In this hospital-based study of 808 patients with pancreatic adenocarcinoma with a control group of 808 healthy individuals, analysis of data includes the relation between PC and smoking cigarettes, cigars, and pipes; the use of smokeless tobacco products; and passive smoking after controlling for the effects of other confounders and major risk factors for this disease (p. 2). All participants were enrolled prospectively at The University of Texas M. D. Anderson Cancer Center and controls were selected from M. D. Anderson healthy visitors who accompanied cancer patients. All controls have no cancer history and are not genetically related family members (spouses) of patients with cancers. The patients and controls were frequency-matched by age (±5 years), race/ethnicity, and sex (Hassan et al., 2007). Stata software (Stata Corporation, College Station, TX) was used for data management and statistical analysis. Univariate and multivariate analyses, unconditional logistic regression was performed to compare the demographic characteristics and proportions of potential risk factors among patients and controls. Previously reported association between active smoking and increased risk for PC was confirmed in this study with adjusted odds ratio (AOR) of 1.7 (95% CI, 1.4-2.2) for regular smokers, 1.8 (95% CI, 1.4-2.4) for long-term smokers, and 3.1 (95% CI, 2.2-4.3) for former smokers. While passive smoking has an AOR of 1.3; 95% CI, 0.9-1.7 and never smokers (AOR, 1.1; 95% CI, 0.8-1.6), suggesting to nonsignificantly elevated risk for PC in the entire study population (AOR, 1.3; 95% CI, 0.9-1.7), Hassan et al. found the association of ever smokers with the disease (AOR, 1.7; 95% CI, 1.03-2.6) but was absent among never smokers (AOR, 1.1; 95% CI, 0.8-1.6). Chewing tobacco, snuff, and pipes also showed a non-significant risk elevation for PC after controlling for the confounding effects of demographics and other known risk factors. Hassan et al. noted that neither intensity nor duration of passive smoking modified the risk of PC among never smokers, but the use of cigars in never smokers showed a borderline significant increase in risk for the disease with an AOR, 2.2; 95% CI, 1.0-4.7; P =.05. It was concluded in this study that results are not enough to support the role of passive smoking or the use of noncigarette tobacco products in the PC etiology. Hassan et al. asserted the need to confirm the association between cigar use and the disease in other study populations.
Going back to the concept of gene-environment (G x E) interaction by Fisher (1958) and Hogben (1968) emphasized the need to consider the fundamental, philosophical differences between a variation partitioning approach and a mechanism-elucidation approach that provides the initial understanding of some aspects of genetics in association to smoking in cancer causation. The reason why the results of risk factor research for PC appears to be generic could be explained by the failure of the researchers to focus on a multi-level approach, failing to connect the gap between individual, macroenvironmental and biologic level. While the failure to appreciate the importance of the biological pathways is a more serious problem, Rutter (2015) noted that failure to pay proper attention to the methodological checks needed to highlight G X E in cancer causation results in some poor research that lead to disputable outcomes.
Bao et al. (2009) and Heinen et al. (2010) shared the same argument of the positive association between maternal smoking and the development of PC. In this study, it was found that early exposure to ETS and maternal smoking could lead the potential in utero to a lifetime risk of this lethal disease. An earlier study of Villeneuve et al. (2004) also recognized the role of ETS as a risk factor for PC and noted the probable confounding role of active cigarette smoke. Gallicchio et al. (2006) confirmed the approximate doubling of pancreatic cancer risk in current active smokers. While Hassan et al. (2007) observed significant associations between passive smoking, the use of noncigarette tobacco products and risk of pancreatic cancer, Hassan et al. highlighted the need for future assessment of the role of passive tobacco use in population-based studies. The synergistic interaction of occupational and environmental exposures and its role in the early occurrence of PC was explored in the 2009 study by Yeo, Hruban, Brody, Brune, Fitzgerald, and Yeo, C. J., aligning to the intent of the 2010 study of Vrieling et al. to examine the association between cigarette smoking and exposure to ETS with PC risk in the European Prospective Investigation into Cancer and Nutrition (EPIC). The overall findings of these studies support the obligation of environmental epidemiology and the importance of inter-disciplinary collaboration to provide robust evidence on the positive role of active and passive smoking, ETS-related carcinogens to protect vulnerable population subgroups. Identification of pre-malignant lesions and molecular profiling is paramount, as methods of early detection, prevention, and personalized therapy for high-risk individuals. While the study of Yeo et al. considered the causality of predictors at an individual and biologic level; including etiologic agents at macroenvironment-level could have given a more citable outcome. Given that the study has access to one of the largest national registries of familial PC, the researchers did not utilize the extensive data available and assessed the data within hierarchical levels. Integrating individual and biologic level to macroenvironment-level into a multilevel framework will allow the interdisciplinary exchange of knowledge, optimizing the value of multilevel studies for both clinical and public health activities. Lynch et al. (2013) proposed a multilevel approach to bridge the gap between individual, macroenvironmental and biologic level called “Multi-level Biological And Social Integrative Construct” (MBASIC). The primary goal of the MBASIC is to guide researchers to consistently, and systematically incorporate biological mechanisms generate significant statistical or epidemiological model better to understand the complex nature a lethal disease like PC. Lynch et al. highlighted the significance of MBASIC in expanding the utility of the multilevel approach by including levels of etiology and carcinogenesis with levels of intervention and implementation/evaluation. The interaction of these levels could provide a resource-efficient approach to early PC screening and detection.
The exposure to rare chemicals may pose a large individual risk if a child is exposed, justifying the need to consider the impact of maternal smoking during pregnancy and postnatal environmental tobacco smoke (ETS) exposure. ETS exposure and other exposures to common substances in the perspective of public health equates a relative risk that could have a progressive/cumulative effect to the public. Röösli (2011) argued that children differ from adults in many aspects which are relevant when assessing health risks from chemicals; therefore future research warrants a working framework that addresses the potential for non-cancer effects resulting from continuous short-duration and intermittent exposures to chemicals. A good example is the framework of Haber et al. (2016) presents an integrated, tiered approach that could be adopted in assessing the acceptability of toxicity reference values (TRVs) in relation to short-duration or intermittent exposure scenarios. Environmental tobacco smoke (ETS) is an example of environmental exposure that has been associated with an array of adverse effects on health. Secondhand smoke, referred to as ETS, contains many of the same carcinogenic compounds as the mainstream smoke inhaled by active smokers (World Health Organization, International Agency for Research on Cancer, 2004; Bao et al., 2009). Under the lens of public health, quitting smoking could decrease the incidence of PC, by protecting vulnerable members of the population. The rapid uptake and use of new health information among groups with lower SES and access to health-enhancing treatment and technologies will be dependent upon the development and implementation of public health policies that include equal allocation of resources to every enclave of the community. While the past and current research could help continue the improvement of the accuracy of passive smoking measurement, it is critical for the continuance of applying the exposome concept to environmental health problems. Research outcomes that help the drafting of amendments to policies and approaches, built on existing policies such as cigarette labeling acts, smoking bans, and distribution of cessation tools will not only improve mortality level of the disease, but population health as a whole. Overall, the results of articles reviewed between 1990 to present suggest the potential role of early exposure to environmental tobacco smoke in pancreatic carcinogenesis. While maternal smoking cessation is the only way to reduce the burden of PC to both the baby, the mother and others who shared the exposure, future research needs to confirm the positive association of PC with maternal smoking and ETS. Continued research on the association between passive smoking exposure and the disease, as well as early shared exposure of these predictors, are critical to better understand its association to lifetime risk. The focus on obtaining a larger number of endpoints, it is paramount for future research to combine more cohorts to have a stronger and standardized sampling that yields a statistically significant assessment of predictors associated with pancreatic cancer.
The argument on the gene-environment interaction paradigm to genome-wide studies in relation to the development of a public issue was discussed in the 2014 study of Boardman et al., highlighting the importance of integrating social and genetic perspectives in enhancing findings for both biologically and socially focused research such as the causality of active and passive smoke exposure to lifetime risk of a fetus to develop a lethal disease like PC. For decades, behavior geneticists have been working to disentangle the genomic component of family risk from the social and behavioral component. According to Boardman et al. (2104), understanding the genomic component in combination with specific environmental contexts could provide the pertinent information about an individual’s likelihood of exhibiting a particular behavior at a given time, critical not only to social and genetic epidemiologists, but to the understanding of the association of modifiable behavioral risk and adjustable predictors in the development of the disease. New evidence for genetic influences on most health behaviors, new statistical methods, and new genetic data sources could help confirm the impact of environmental influences on individual’s genetic composition that could be contingent on the social environment in which one resides, works, and plays. The findings of the literature reviewed in this paper will not only add to the wealth of information needed in the development of a standard PC risk model but also highlight the significance of the early screening and molecular profiling, as a prudent approach to the prevention of PC. Parallel to the intent of my dissertation on “Pathopoiesis Mechanism of Smoking and Family Cancer History in Pancreatic Cancer,” findings discussed in this paper emphasize the need for novel therapeutic strategies that will improve survival level and quality of life for late-stage PC patients.
American Cancer Society, Inc. (2016). Key statistics for pancreatic cancer. Retrieved 15 June, 2016, from http://m.cancer.org/cancer/pancreaticcancer/detailedguide/pancreatic-cancer-key-statistics
Bao, Y., Giovannucci, E., Fuchs, C. S., & Michaud, D. S. (2009). Passive smoking and pancreatic cancer in women: a prospective cohort study. Cancer Epidemiology Biomarkers & Prevention, 18(8), 2292-2296.
Bookman, E. B., McAllister, K., Gillanders, E., Wanke, K., Balshaw, D., Rutter, J., … & Atienza, A. (2011). Gene‐environment interplay in common complex diseases: forging an integrative model—recommendations from an NIH workshop. Genetic epidemiology, 35(4), 217-225.
Boardman, J. D., Domingue, B. W., Blalock, C. L., Haberstick, B. C., Harris, K. M., & McQueen, M. B. (2014). Is the gene-environment interaction paradigm relevant to genome-wide studies? The case of education and body mass index. Demography, 51(1), 119-139.
Brooks, D. R., Mucci, L. A., Hatch, E. E., & Cnattingius, S. (2004). Maternal smoking during pregnancy and risk of brain tumors in the offspring. A prospective study of 1.4 million Swedish births. Cancer Causes & Control,15(10), 997-1005.
Bosetti, C., Bertuccio, P., Negri, E., La Vecchia, C., Zeegers, M. P., & Boffetta, P. (2012). Pancreatic cancer: overview of descriptive epidemiology. Molecular carcinogenesis, 51(1), 3-13.
Cameron, A. C., & Trivedi, P. K. (1986). Econometric models based on count data. Comparisons and applications of some estimators and tests. Journal of Applied Econometrics, 1, 29e53
Chen, H., Qin, S., Wang, M., Zhang, T., & Zhang, S. (2015). Association between cholesterol intake and pancreatic cancer risk: evidence from a meta-analysis. Scientific reports, 5, 8243.
Ding, Y., Yu, C., Han, Z., Xu, S., Li, D., Meng, X., & Chen, D. (2015). Environmental tobacco smoke and pancreatic cancer: a case-control study. International journal of clinical and experimental medicine, 8(9), 16729.
Fergusson, D. M., Woodward, L. J., & Horwood, L. J. (1998). Maternal smoking during pregnancy and psychiatric adjustment in late adolescence. Archives of general psychiatry, 55(8), 721-727.
Fisher, R. A. (1958). Cancer and smoking. Nature 1958; 182:108.
Florescu, A., Ferrence, R., Einarson, T., Selby, P., Soldin, O., & Koren, G. (2009). Methods for quantification of exposure to cigarette smoking and environmental tobacco smoke: focus on developmental toxicology. Therapeutic drug monitoring, 31(1), 14.9(9), 1619-1625.
Gallicchio, L., Kouzis, A., Genkinger, J. M., Burke, A. E., Hoffman, S. C., Diener-West, M., … & Alberg, A. J. (2006). Active cigarette smoking, household passive smoke exposure, and the risk of developing pancreatic cancer. Preventive medicine, 42(3), 200-205.
Gourieroux, C., Monfort, A., & Trognon, A. (1984). Pseudo maximum likelihood methods: applications to Poisson models. Econometrica: Journal of the Econometric Society, 701e720.
Haber, L. T., Sandhu, R., Li‐Muller, A., Mohapatra, A., Petrovic, S., & Meek, M. E. (2016). Framework for human health risk assessment of non‐cancer effects resulting from short‐duration and intermittent exposures to chemicals. Journal of Applied Toxicology, 36(9), 1077-1089.
Halpin, H.A., Morales-Suarez-Varela, M. M., & Martin-Moreno, J. M. (2010). Chronic disease prevention and the new public health. Public Health Reviews, 32(1), 120.
Hanley, A. J., Johnson, K. C., Villeneuve, P. J., & Mao, Y. (2001). Physical activity, anthropometric factors, and risk of pancreatic cancer: results from the Canadian enhanced cancer surveillance system. International journal of cancer, 94(1), 140-147.
Hassan, M. M., Abbruzzese, J. L., Bondy, M. L., Wolff, R. A., Vauthey, J. N., Pisters, P. W., … & Li, D. (2007). Passive smoking and the use of noncigarette tobacco products in association with risk for pancreatic cancer: A case‐control study. Cancer, 109(12), 2547-2556.
Hatsukami, D. K., Hecht, S. S., Hennrikus, D. J., Joseph, A. M., & Pentel, P. R. (2003). Biomarkers of tobacco exposure or harm: application to clinical and epidemiological studies. Nicotine & Tobacco Research, 5(3), 387-396.
Heinen, M. M., Verhage, B. A., Goldbohm, R. A., & van den Brandt, P. A. (2010). Active and passive smoking and the risk of pancreatic cancer in the Netherlands Cohort Study. Cancer Epidemiology Biomarkers & Prevention,19(6), 1612-1622.
Hindorff, L. A., Junkins, H. A., Hall, P. N., Mehta, J. P., & Manolio, T. A. (2011). A catalog of published genome-wide association studies.
Hogben, L. T. (1968). Mathematics for the Million. WW Norton & Company.
Hyland, A., Barnoya, J., & Corral, J. E. (2012). Smoke-free air policies: past, present, and future. Tobacco Control, 21(2), 154-161.
Jamal, A., Murray, T., Samuels, A., Ghafoor, A., Ward, E., & Thun, M. (2003). Cancer statistics, 2003. CA Cancer J Clin, 53(1), 5-26.
Krieger, N. (2008). Proximal, distal, and the politics of causation: what’s level got to do with it?. American journal of public health, 98(2), 221-230.
Krieger, N. (2011). Epidemiology and the people’s health: theory and context (Vol. 213). New York: Oxford University Press.
Long, J. S. (1997). Regression models for categorical and limited dependent variables advanced quantitative techniques in the social sciences. Thousand Oaks, CA: Sage Publications.
Michaud, D. S., Giovannucci, E., Willett, W. C., Colditz, G. A., Stampfer, M. J., & Fuchs, C. S. (2001). Physical activity, obesity, height, and the risk of pancreatic cancer. Jama, 286(8), 921-929.
Neoptolemos, J. P., Stocken, D. D., Friess, H., Bassi, C., Dunn, J. A., Hickey, H., … & Falconi, M. (2004). A randomized trial of chemoradiotherapy and chemotherapy after resection of pancreatic cancer. New England Journal of Medicine, 350(12), 1200-1210.
Ma, J., Siegel, R., & Jemal, A. (2013). Pancreatic cancer death rates by race among US men and women, 1970–2009. Journal of the National Cancer Institute, 105(22), 1694-1700.
National Cancer Institute. (2010). Cancer trends progress report e 2009/2010 Update. Bethesda, MD: N.C. Institute.
Patrick, D. L., Cheadle, A., Thompson, D. C., Diehr, P., Koepsell, T., & Kinne, S. (1994). The validity of self-reported smoking: a review and meta-analysis. American journal of public health, 84(7), 1086-1093.
Pearce, N. (1996). Traditional epidemiology, modern epidemiology, and public health. American journal of public health, 86(5), 678-683.
Peters, A., Hoek, G., & Katsouyanni, K. (2012). Understanding the link between environmental exposures and health: does the exposome promise too much?. Journal of epidemiology and community health, 66(2), 103-105.
Rahib, L., Smith, B. D., Aizenberg, R., Rosenzweig, A. B., Fleshman, J. M., & Matrisian, L. M. (2014). Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer research, 74(11), 2913-2921.
Roger, V. L. (2011). Outcomes Research and Epidemiology the Synergy Between Public Health and Clinical Practice. Circulation: Cardiovascular Quality and Outcomes, 4(3), 257-259.
Röösli, M. (2011). Non-cancer effects of chemical agents on children’s health. Progress in biophysics and molecular biology, 107(3), 315-322.
Rubin, M. S., Clouston, S., & Link, B. G. (2014). A fundamental cause approach to the study of disparities in lung cancer and pancreatic cancer mortality in the United States. Social Science & Medicine, 100, 54-61.
Rutter, M. (2015). Some of the complexities involved in gene-environment interplay. International journal of epidemiology, 44(4), 1128-1129.
Shaib, Y. H., Davila, J. A., & El‐Serag, H. B. (2006). The epidemiology of pancreatic cancer in the United States: changes below the surface. Alimentary pharmacology & therapeutics, 24(1), 87-94.
Siemiatycki, J., Krewski, D., Franco, E., & Kaiserman, M. (1995). Associations between cigarette smoking and each of 21 types of cancer: a multisite case-control study. International Journal of Epidemiology, 24(3), 504-514.
Silverman, D. T., Dunn, J. A., Hoover, R. N., Schiffiman, M., Lillemoe, K. D., Schoenberg, J. B., … & Wacholder, S. (1994). Cigarette Smoking and Pancreas Cancer: A Case—Control Study Based on Direct Interviews. Journal of the National Cancer Institute, 86(20), 1510-1516.
Simard, J. F., Rosner, B. A., & Michels, K. B. (2008). Exposure to cigarette smoke in utero: comparison of reports from mother and daughter. Epidemiology (Cambridge, Mass.), 19(4), 628.
Spanknebel, K., & Conlon, K. C. (2000). Advances in the surgical management of pancreatic cancer. Cancer journal (Sudbury, Mass.), 7(4), 312-323.
The pancreatic cancer action network. (2013). The Recalcitrant Cancer Research Act. Retrieved 2 July, 2016, from https://www.pancan.org/facing-pancreatic-cancer/
Tomioka, T., Andrén-Sandberg, A., Fujii, H., Egami, H., Takiyama, Y., & Pour, P. M. (1990). Comparative histopathological findings in the pancreas of cigarette smokers and non-smokers. Cancer letters, 55(2), 121.
Villeneuve, P. J., Johnson, K. C., Hanley, A. J. G., & Mao, Y. (2000). Alcohol, tobacco and coffee consumption and the risk of pancreatic cancer: results from the Canadian Enhanced Surveillance System case-control project. European journal of cancer prevention, 9(1), 49-58.
Villeneuve, P. J., Johnson, K. C., Mao, Y., & Hanley, A. J. (2004). Environmental tobacco smoke and the risk of pancreatic cancer: findings from a Canadian population-based case-control study. Canadian Journal of Public Health/Revue Canadienne de Sante’e Publique, 32-37.
Von Hoff, D. D., Ervin, T., Arena, F. P., Chiorean, E. G., Infante, J., Moore, M., … & Harris, M. (2013). Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. New England Journal of Medicine, 369(18), 1691-1703.
Vrieling, A., Bueno‐de‐Mesquita, H. B., Boshuizen, H. C., Michaud, D. S., Severinsen, M. T., Overvad, K., … & Kaaks, R. (2010). Cigarette smoking, environmental tobacco smoke exposure and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition. International journal of cancer, 126(10), 2394-2403.
World Health Organization. (2001). Biomarkers in risk assessment: Validity and validation. In Environmental Health Criteria (Vol. 222). WHO.
World Health Organization, International Agency for Research on Cancer. (2004). Tobacco Smoke and Involuntary Smoking. Retrieved from http://monographs.iarc.fr/ENG/Monographs/vol83/mono83-1.pdf
World Health Organization. (2012). In W.H. Organization (Ed.), International classification of diseases. Geneva, SW
World Health Organization, International Agency for Research on Cancer. (2004). Tobacco Smoke and Involuntary Smoking. Retrieved from http://monographs.iarc.fr/ENG/Monographs/vol83/mono83-1.pdf
Yeo, T. P., Hruban, R. H., Brody, J., Brune, K., Fitzgerald, S., & Yeo, C. J. (2009). Assessment of “gene–environment” interaction in cases of familial and sporadic pancreatic cancer. Journal of Gastrointestinal Surgery, 13(8), 1487-1494.
The ethical challenges in the 2009 study of Osrin et al. are consent from cluster guardians, consent by individuals, benefits to control areas and requests by participants. The ethical issues that revolved around cluster guardianship noted in this study are the participants’ perceived adequate information about the trial according to the guidelines of the Declaration of Helsinki. In a complex society or in a society where participation is decided by the concept of a utilitarian judgment there will always be a burning concern for the guaranteed unalloyed voluntary nature of involvement. While cluster randomized controlled trials have been around for a long time, there is a growing concern to evaluate the delivery of health services, public education, and policy on social care (Edwards et al., 1999). Utilitarianism and Kantian ethics are the two most important moral traditions that the ethical aspects of medical practice and medical research are most often discussed. Concerned with increasing social utility (value), utilitarianism, in the long run, the social utility will not be served by demanding that individuals be self-sacrificing for the common good. The collective decision of a local guardian or representative may be contested given that communities are usually amalgams of smaller communities. There is the question whether the decision is in the best interest of the participants or the expected interest is based on the hidden personal agenda of the cluster guardian. It is a matter of distributive justice whereby utility and disutility, benefits and costs, are distributed as fairly and evenly as possible across society (Edwards et al. 1999). On the other hand, Kantian tradition refers to our moral duty to respect a person’s autonomy, significant in individual-cluster trials that differ with the paramount importance of the utilitarian welfare of the cluster in cluster-cluster trials.
Positioning ourselves as researchers within the ethical folds, and not cross the thin red line of a moral dilemma; we should remember that ethics establish the fundamental principles of “right and wrong.” While laws may set the legal parameters that govern data use, ethics are critical to the appropriate management and use of research data. The burning questions are: Do we have the prior knowledge on the unethical collection of the data? Did we learn about the breach after we are done analyzing the data? I believe, it is our responsibility to assess the quality and the manner data was collected. Even if the intent of the research is for the better good, we should not be blinded by the urgency of the endeavor and justify the beneficial outcomes at the expense of the suffering of the participants. Using a secondary data obtained unethically for the better good that could impact a community, presents a blur between right and wrong. Would the use of unethically collected secondary data a personal choice? Assuming that the institutional review board (IRB) approved the use of such data, would it give us the option to use the data for the common goods? A point to ponder, given that the Nuremberg Code was not established until after World War II, the collection of NAZI experiments could not be considered “illegal’ (Vollmann, 1996). Given this scenario, would current researchers be free to use the data from these experiments for ethical and beneficial results? Would it justify the use of Dr. Sigmund Racher’s data on hypothermia and altitude experiments at Dachau to inform on ethically sound studies on hypothermia prevention and treatment? The study of Dr. Robert Pozos of the University of Minnesota was denied publication in the New England Journal of Medicine (NEJM) after using Dr. Racher’s data on rewarming techniques to fill in critical gaps in his research (Cohen, 1990). Having this said, personally, regardless how comprehensive the secondary data, if unethically aggregated, I would refrain from using such data even if the data could have a positive outcome. Within the argument of guilty by association, I believe that using unethically collected research data; we are as guilty as the person/individuals who collected the data. The best recourse is to look for a more superior data that follows the prescribed ethical guidelines. On the other hand, if the data could lead to discovery to save lives of the many, for example, a vaccine to prevent the spread of an infectious disease, or prevent a bioterrorism event, then it is justifiable to use such data considering the benefits outweigh the harms of the methods.
Cohen, B. (1989). The ethics of using medical data from Nazi experiments. Journal of Halacha and Contemporary Society, 103-126.
Edwards, S. J., Braunholtz, D. A., Lilford, R. J., & Stevens, A. J. (1999). Ethical issues in the design and conduct of cluster randomised controlled trials. British Medical Journal, 318(7195), 1407.
Ford, N., Mills, E. J., Zachariah, R., & Upshur, R. (2009). Ethics of conducting research in conflict settings. Confl Health, 3(7).
Osrin, D., Azad, K., Fernandez, A., Manandhar, D. S., Mwansambo, C. W., Tripathy, P., & Costello, A. M. (2009). Ethical challenges in cluster randomized controlled trials: experiences from public health interventions in Africa and Asia. Bulletin of the World Health Organization, 87(10), 772-779.84-887.
Steinberg, J. (2015). The Ethical Use of Unethical Human Research. New York University, nd Web, 30.
Vollmann, J., & Winau, R. (1996). Informed consent in human experimentation before the Nuremberg code. BMJ: British Medical Journal,313(7070), 1445.