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.
Methods: Pancreatic Cancer and Environmental Tobacco Smoke (ETS)
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.
Results of the Systematic Literature Review
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.
Conclusion
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.
References
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.
O.N.E.—One Nation’s Echo 