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. Author manuscript; available in PMC: 2019 Jul 1.
Published in final edited form as: J Surg Res. 2018 Apr 3;227:246–256. doi: 10.1016/j.jss.2018.02.053

Can a Gastric Cancer Risk Survey Identify High-Risk Patients for Endoscopic Screening? A Pilot Study

Haejin In 1,2, Marisa Langdon-Embry 1, Lauren Gordon 1, Clyde B Schechter 2,3, Judith Wylie-Rosett 2, Philip E Castle 2, M Margaret Kemeny 4, Bruce D Rapkin 2
PMCID: PMC5972059  NIHMSID: NIHMS948912  PMID: 29622399

Abstract

Background

A questionnaire that distinguishes how variability in gastric cancer prevalence is associated with ethnicity/birth country/immigration/cultural diet along with known risk factors may improve targeting populations for gastric cancer screening in the United States.

Methods

Existing literature was used to identify the item pool. Cluster analysis, focus groups and cognitive interviewing were used to reduce collinear items and refine the questionnaire. Logistic regression analysis was used to determine which items distinguished gastric cancer cases from the primary care and community controls.

Results

Analysis of data from 40 cases and 100 controls (primary care=47; community =53) were used to reduce the 227 item pool to 12 items. After ranking these variables using model bootstrapping, a logistic regression model using the highest ranked 8 variables was chosen as the final model. Older age, foreign nativity, daily consumption of cultural food at ages 15 to 18, less than high-school education and greater acculturation were significantly associated with being a gastric cancer case compared to the controls.

Conclusions

An 8-item survey that addresses gastric cancer risk factors, ethnicity, cultural habits and immigration patterns has potential to identify high-risk persons from multicultural areas within the US, who might benefit from endoscopic screening for gastric cancer.

Keywords: Gastric Cancer Screening, Risk Prediction Model, Early detection of Gastric Cancer, Risk Assessment Questionnaire

Introduction

Gastric adenocarcinoma is the fifth most common cancer and third leading cause of cancer mortality in the world, with an estimated 723,000 deaths in 2012.1 In the United States (US), gastric cancer is one of the deadliest cancers ranking only behind lung, pancreas, and esophageal cancer.2 Screening for gastric cancer has been shown to be effective and attribute a 30-60% decrease in gastric cancer mortality in countries with national gastric cancer screening programs.3–5 Despite the success of gastric cancer screening programs in high-incidence countries, screening for gastric cancer is not performed in the US due to the low incidence rate of the disease (3.9 cases per 100,000 in the general population).1

In a low incidence region such as the US, screening persons at higher risk would make screening feasible.6 Methods to identify persons at risk should be easy to administer and applicable in both health care and community settings. There are many well known risk factors for gastric cancer, including diet, lifestyle, older age, gender, race, tobacco smoking, radiation, family history, Helicobacter pylori infection, low socioeconomic status, high intake of salty and smoked foods, low consumption of fruits and vegetables, obesity and gastroesophageal reflux disease (GERD).7,8 However, little is known about which of these variables will be most contributory in the discrimination of gastric cancer risk in the US with its extraordinary ethnic and racially diverse population.

Racial and ethnic minorities represent 38.3% of the total US population.9 Among these groups, there is large variation in gastric cancer incidence. African Americans, Hispanics, Asians, and Pacific Islanders have 1.7-2.0 fold higher incidence than Whites.10–12 Foreign-born immigrants from high-incidence countries continue to have a higher risk of gastric cancer even after immigration.13–16 Yet, few studies have examined gastric cancer risk factors across the various ethnicities and racial subgroups in the US. Additionally, there are few studies evaluating country of birth, immigration, and cultural dietary habits as risk factors among various ethnic subgroups in the US. These factors, in combination with known risk factors, may help identify a sub-population at elevated risk that might benefit from gastric cancer screening.

To this end, our ultimate long-term goal is to develop a short pre-screening questionnaire that can be used in both the community setting and health care settings to identify persons at high risk for gastric cancer so they can undergo screening endoscopy. As a preliminary step to a population–based, case-control study of gastric cancer risk factors in the US, we developed and pilot tested a risk assessment questionnaire. The aims of the present pilot case-control study were to 1) develop the item pool to assess gastric cancer risk in the US, 2) establish and test the procedures for optimal case and control ascertainment, and 3) analyze the pilot case-control data that were obtained in two health care sites serving racially and ethnically diverse patient populations.

Methods

Materials and process

Exposure was assessed through information collected from a comprehensive questionnaire created specifically for this purpose. The details of the questionnaire development process are provided in Appendix 1. A literature review was conducted to design a questionnaire to collect data on known risk factors for gastric cancer. A preliminary draft of the questionnaire was reviewed and modified through focus groups for the comprehensibility of survey questions. Risk factors assessed included demographics, race, socioeconomic status, food frequency, smoking and alcohol habits, family history, and Helicobacter pylori exposure, as well as less well studied factors that have potential to be highly discriminating in a multicultural country such as the US, including ethnicity, country of birth, acculturation index and lifetime ethnic dietary habits. A complete list of risk factors, references and questionnaires used to create the questionnaire is shown in table 1. The questionnaire then went through a process of translation and back-translation into Spanish, Mandarin Chinese and Korean. Cognitive interviews were used to test comprehension of the questionnaire in different ethnic populations and ensure items carried the same meaning across languages.

Table 1.

Gastric Cancer Risk Factors, Strength of Association and Questionnaires Used for development of gastric cancer risk questionnaire

Strength of Association (OR Range) Questionnaires Used References
Diet (129 questions)
Fruit intake 1.1–1.65 Nurses’ Health Study Questionnaire [38–43]
Vegetable Intake 1.25–1.65 Nurses’ Health Study Questionnaire [38–45]
Allium vegetable intake 1.4–2.0 ACS Cancer Prevention Study Questionnaire, based on questions asked in Gao 1999 and You 1989 (questionnaire not available) [26] [46], [47] [48–50]
Red meat consumption 1.4–1.7 Hutchinson Cancer Center FFQ, ACS Cancer Prevention Study Questionnaire [23][51–53]
Processed meats 1.15–1.45 Hutchinson Cancer Center FFQ, ACS Cancer Prevention Study Questionnaire [23] [51–56]
Soy (low vs. high) 1.4–3.3 Ko 14-item FFQ, ACS Cancer Prevention Study Questionnaire [26] [57]
Salt consumption 1.4–2.2 Ko 14-item FFQ [23, 26, 39]
Pickled foods 1.25–2.2 Hutchinson Cancer Center FFQ [42, 44, 53, 55, 58]
Chili consumption 1.9 Hutchinson Cancer Center FFQ, Ko 14-item FFQ, ACS Cancer Prevention Study Questionnaire, [39], [59]
Fiber (low vs. high) 1.65–2.0 Hutchinson Cancer Center FFQ, ACS Cancer Prevention Study Questionnaire [60, 61]
General dietary questions - Added by study team -
Lifetime intake of fruits, vegetables, meat, bbq smoked foods, processed meats - ACS Cancer Prevention Study Questionnaire -
Vitamins and supplements 1.4–1.65 Swedish Mammography Study Questionnaire, Hutchinson Cancer Center FFQ [62–64], [65–67]
Lifestyle (12 Questions)
Physical Activity 1.2–1.4 NIH-AARP Baseline Questionnaire 1995 [68],[69]
Smoking 1.2 – 1.7 NIH-AARP Baseline Questionnaire 1995 [70–74],[75]
Alcohol Consumption 0.9–1.4 Million Women’s Health Study Questionnaire [76–81],[82]
Lifetime exercise, smoking and alcohol habits - Added by study team -
Quality of Health - Added by study team -
Medical History (22 questions)
Body Mass Index 1.05–1.2 NIH-AARP Baseline Questionnaire 1995 [83–86], [87]
Blood Type A 1.1 Added by study team [88]
H. Pylori 1.1–3.0 Aklavik H. Pylori Project Clinical Questionnaire [89–92], [93]
Antacids 1.4 NIH-AARP Risk Factor Questionnaire 1998 [94]
NSAIDS (non-use) 1.25–1.65 NIH-AARP Risk Factor Questionnaire 1998 [95–99], [100]
Family history of gastric cancer 1.7–2.9 Based on questions asked in Dhillon 2001 study (questionnaire not available) [101–103]
Gastric-associated symptoms - Added by study team
Prior medical care/screening - Added by study team
Immigration/Acculturation
Country of origin - HCHS/SOL Personal Information Questionnaire
Immigration history - Cha-Cha Demographic Questionnaire
Vancouver acculturation scale (degree of agreement on scale of 1–9 with statements about American culture and own culture) - Vancouver Acculturation Index
Ethnic food intake 1.6 Added by study team [81]
Demographics (11 questions)
Gender - NIH-AARP Study Questionnaire 1995 -
Marital Status NIH-AARP Study Questionnaire 1995 -
Date of Birth - NIH-AARP Study Questionnaire 1995 -
Low SES - HCHS/SOL Economic Questionnaire [104]
Occupation 1.25, N.S. HCHS/SOL Occupation Classification and Exposures Questionnaire [104]
Education 4.3 NIH-AARP Baseline Questionnaire 1995 [104, 105]
Race/ethnicity 3.0 U. S. Census Bureau American Community Survey -
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Case-control Selection

A pilot case-control study was conducted using the final version of the questionnaire to examine the feasibility of recruiting participants in primary care (PC-controls) and community settings (community control) and to identify questionnaire items that distinguish gastric cancer cases from non-cancer controls. A patient list of persons with gastric cancer and persons served in primary care clinics was obtained from two sites, a large urban academic medical center and a inner city public hospital. Both serve a large population of ethnic minorities. After excluding subjects who did not meet age and health-related eligibility criteria, invitation mailings were sent to eligible recruits providing study details and the opportunity to opt out if they did not wish to participate. Patients who did not opt out were contacted by phone for participation. PC-control phone recruitment proved problematic, and recruitment strategy was expanded to direct clinic recruitment for the remaining two-thirds of the PC-controls. Verbal or written informed consent was obtained from all study participants. Participants were initially asked to complete survey questions by telephone interview. This was modified to include paper survey administration about mid-way in the study. The study protocol was approved by the institutional review boards of each site.

Inclusion criteria for the cases and controls were as follows: 1) ages 40 to 85 years old, 2) mental and physical ability to participate, 3) no prior cancer diagnosis (other than gastric cancer or non-melanoma skin cancers), 4) no prior diagnosis that requires endoscopic surveillance (Barrett’s esophagus, esophageal or gastric adenoma, gastric ulcer, etc.), and 4) no known personal or family history of genetic syndromes associated with higher risk of gastric cancer (i.e. hereditary diffuse gastric cancer, Peutz-Jeghers syndrome, familial adenomatous polyposis, hereditary non-polyposis colorectal cancer, and Li-Fraumeni syndrome). Cases also needed to meet the following criterion: diagnosed with biopsy-proven gastric adenocarcinoma in the last five years.

A database was created for data input using SurveyMonkey® (San Mateo, CA). Interview staff entered phone interview responses directly into the database at the time of interview. Paper surveys were collected and separately entered into the database.

Statistical Analysis

Our primary goal of this pilot analysis was to see if it is feasible to develop a logistic regression model to distinguish cases from controls. The cognitive interview data (n=60) were combined with the pilot case-control data (n=90) for the analysis. This was acceptable given that interviews were conducted using translated versions of the completed comprehensive questionnaire, and the case and control selection generally followed the same protocol as the pilot case-control study.

Age was examined in 1-year increments for the model but presented as <55, 55-69 and greater than 70 in the descriptive tables. Race was categorized as non-Hispanic (NH) white, NH-Black, Hispanic and Asian/Pacific Islander (PI)/other. US generation was classified as US-born with one or both parents being US-born (3rd generation), US-born with both parents being foreign-born (2nd generation) and being foreign-born (1st generation). The incidence rate of gastric cancer in a given country where the participant was born as reported by the WHO GLOBOCAN [1] (IR_GCa) was categorized into 3 categories; <5, 5-<15 and 15 or more cases per 100,000. The frequency of cultural food consumption at ages 15 to 18 years was categorized as daily or more, less than daily and never or rarely. The Vancouver Index is a series of questions aimed at assessing a person’s level of acculturation. The questions are examined as heritage subscore and mainstream subscore [17]. Heritage subscore was grouped into tertiles. Alcohol consumption was ascertained as any frequency of any alcohol and aggregated as more than 4 times per week, 2-3 times per week and less than once per week. The frequency of barbequed foods (BBQ) was categorized as greater or less than once per week. PC-controls and community-controls were combined for the analysis.

Given the large number of items and limited sample size, we first underwent a process of item reduction. Items first underwent a quality check and were dropped if response sets were out of range or had inconsistent values and outliers. Cluster analysis was then performed for domains with large numbers of items, namely the food frequency items and acculturation items. The resulting items when checked and removed if found to be collinear. Due to the small sample size, we found the use of a single regression model to be unstable, so we used a bootstrapping technique of entering the items into a multivariable model with selection algorithms (backwards and stepwise elimination procedures) to rank the variables that most commonly pass the selection algorithms [18]. The top-ranked variables were then used to generate an adjusted regression model. The model with the least number of items, and with all individual variable chi-square p-values having values of <0.2 was chosen.

Information on the numbers of participants eligible, contacted, recruited and enrolled was collected at the time of recruitment. Information on difficulties encountered during survey administration and reasons for non-completion or withdrawal were collected and analyzed. All analysis was performed using SAS 9.4 (Cary, NC).

Results

Recruitment and participant characteristics

The recruitment process for the pilot case-control study is shown in Figure 1. Of 218 cases approached, 103 (47%) were unreachable and 30 (14%) were deceased. Of the 72 eligible cases that remained, 39 (54%) were recruited and 30 completed the survey. Of the 191 PC-controls that were approached, we found 96 (50%) were unreachable. Of 84 eligible persons, 61 (73%) refused participation. Reasons cited were lack of interest (38%), survey being too lengthy (18%), being too busy (18%), not being comfortable doing a phone interview (15%) and language barrier (13%). With a completion rate of only 5% using phone recruitment, we expanded the PC-control recruitment to direct recruitment in clinics. This had greater success with only 37% refusal rate and ultimate completion rate of 34%. Community control recruitment was fairly successful, with a recruitment rate of 52%, and a completion rate of 28%.

Figure 1.

Figure 1

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Recruitment and Interview Flowchart of Pilot Study

Data from 40 cases, 47 PC-controls and 53 community controls were eligible for analysis using combined data from cognitive interviews and pilot study and after exclusion of persons obtained from outside of catchment areas (n=10).

A comparison of PC-controls and community-controls is shown in Appendix 2. There were more PC control participants that were older than 70 (17% vs. 6%), Black (40% vs. 26%), and education level > high school (HS) (47% vs. 64%) than community controls. PC controls had less participants that had IR_GCa >15 (4% vs. 19%). Most noticeably, PC-controls more often completed phone interviews (72% vs. 7%) while community controls generally completed paper surveys (93% vs. 28%).

Preliminary analysis of risk factors

The final survey questionnaire contained a pool of 227 items after the process of systematic review, focus groups and cognitive interviews. Appendix 3 describes the item reduction steps performed to identify the most predictive variable items with minimal collinearity. This resulted in the selection of 12 items. After ranking these variables using model bootstrapping, a logistic regression model using the highest ranked 8 variables was chosen as the final model.

In comparing gastric cancer cases to the controls (Table 2), gastric cancer cases were predominantly older (>55: 92% vs. 55%, p<0.01), male (50% vs. 24%, p<0.01) and Hispanic (60% vs. 28%, p<0.01) and were less well educated (education>HS 28% vs. 56%). Cases were more often foreign-born (85% vs. 54%, p<0.01), and born in countries with higher rates of gastric cancer (IR_GCa ≥ 5 per 100,000: 63% vs. 36%, p<0.01) and reported daily consumption of their cultural food at ages 15 to 18 (68% vs. 36%, p<0.01). Cases and controls appeared similar in frequency of family history, acculturation, alcohol, smoking, and BBQ_freq.

Table 2.

Descriptive Analysis of Cases and Controls (n=140)

Variables Categories Cases
N=40		 Controls
N=100		 p-value
Fisher’s exact
Age age <55 3 (7.5%) 45 (45.0%) <0.01
age 55–69 21 (52.5%) 44 (44.0%)
age 70+ 16 (40.0%) 11 (11.0%)
US generation US born, one or both parents US born (3rd) 2 (5.0%) 10 (10.0%) <0.01
US born, both parents foreign born (2nd) 4 (10.0%) 36 (36.0%)
Foreign born (1st) 33 (85.0%) 54(54.0%)
Cultural food consumption frequency at ages 15 to 18 Never or Rarely 2 (5.0%) 13 (13.0%) <0.01
Less than daily 7 (17.5%) 35 (35.0%)
Daily or more 27 (67.5%) 36 (36.0%)
Missing 4 (10.0%) 16 (16.0%)
Education Less than HS 19 (47.5%) 19 (19.0%) <0.01
High School 10 (25.0%) 25 (25.0%)
Greater than HS 11 (27.5%) 56 (56.0%)
Family History of Gastric No 32 (80.0%) 92 (92.0%) 0.07
Cancer Yes 8 (20.0%) 8 (8.0%)
Race NH-White 4 (10.0%) 17 (17.0%) <0.01
NH-Black 10 (25.0%) 33 (33.0%)
Hispanic 24 (60.0%) 28 (28.0%)
Asian/PI/Other 2 (5.0%) 22 (22.0%)
Acculturation (Heritage Subscore) Upper Tertile (less acculturated) 12 (30.0%) 29 (29.0%) 0.30
Middle Tertile (moderately acculturated) 17 (42.5%) 28 (28.0%)
Lower Tertile (more acculturated) 7 (17.5%) 30 (30.0%)
missing 4 (10.0%) 13 (13.0%)
Gender Male 20 (50.0%) 24 (24.0%) <0.01
Female 20 (50.0%) 76 (76.0%)
Alcohol Less than once per week 21 (52.5%) 66 (66.0%) 0.18
2–3 times per week 6 (15.0%) 16 (16.0%)
More than 4 time per week 12 (30.0%) 14 (14.0%)
Missing 1 (2.5%) 4 (4.0%)
Gastric Cancer Incidence <5 15 (37.5%) 64 (64.0%) 0.02
Rate of Country of Birth 5-<15 16 (40.0%) 24 (24.0%)
15+ 9 (22.5%) 12 (12.0%)
Smoking Yes 18 (45.0%) 32 (32.0%) 0.17
No 22 (55.0%) 68 (68.0%)
BBQ frequency 1 per week or more 5 (12.5%) 16 (16.0%) 0.12
Less than once per week 5 (12.5%) 25 (25.0%)
Never or rarely (ref) 29 (72.5%) 59 (59.0%)
missing 1 (2.5%) 0 (0%)
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Table 3 shows the results of 8-variable logistic regression. The model showed excellent discrimination (concordance index 0.941 95% CI 0.901-0.982) and calibration (Hosmer and Lemeshow Goodness-of-fit test p=0.8562). Increasing age (per year) (OR=1.14, 95% CI=1.07-1.22), being foreign-born (1st generation) (vs. one or both parents US-born [3rd generation])(OR=15.78 95% CI=2.02-123.13), daily or more frequent consumption of cultural food at ages 15 to 18 (vs. never or rarely) (OR=25.07 95% CI 2.04-308.20), having less than a high school education (vs. more than a high school education) (OR=4.85 95%CI=1.20-19.61), and being more acculturated (heritage subscore: lower vs. upper tertile) (OR=5.81 95%CI= 1.14-29.62) were associated with being a gastric cancer case compared to controls. A family history of gastric cancer (vs. none) (OR=3.37, 95%CI=0.78-14.50) and being male (vs. female) (OR=2.95, 95%CI=0.94-9.25) trended toward association with being a gastric cancer case.

Table 3.

Logistic Regression Models Predicting being a Gastric Cancer Case

Cases vs All Controls
(c-statistic 0.942)		 Case vs PC Controls
(c-statistic 0.938)		 Cases vs Community Controls
(c-statistic 0.969)
OR 95% CI p-value OR 95% CI p-value OR 95% CI p-value
Age (per year) 1.14 1.07–1.22 <0.001 1.12 1.05–1.20 <0.001 1.20 1.08–1.32 <0.001
US generation US born, one or both parents US born (3rd) (ref) ref - 0.025 ref - 0.045 ref 0.510
US born, both parents foreign born (2nd) 7.66 0.51–114.09 9.49 0.41–220.54 3.11 0.17–57.85
Foreign born (1st generation) 15.78 2.02–123.13 15.78 1.69–147.15 3.81 0.39–36.99
Consumption of Cultural Foods at ages 15 to 18 Daily or more 25.07 2.04–308.20 0.014 7.06 0.34–146.46 0.079 84.08 3.67–1925.05 0.023
Weekly or more (less than daily) 3.11 0.29–32.96 0.90 0.04–19.78 7.85 0.48–127.71
Less than once per week (Ref) ref - ref - ref -
missing 2.97 0.14–61.92 0.85 0.02–32.85 0.71 0.02–31.45
Education Less than High school 4.85 1.20–19.61 0.082 5.28 0.85–32.69 0.188 4.99 0.81–30.74 0.224
High School 1.92 0.47–7.85 2.01 0.33–12.24 2.05 0.38–11.16
Greater than high school (ref) ref - ref - ref -
Family history of GCa No (ref) ref - 0.103 ref - 0.249 ref - 0.202
Yes 3.37 0.78–14.50 2.65 0.51–13.87 3.79 0.49–29.34
Race NH-White (ref) ref - 0.106 ref - 0.281 ref - 0.051
NH-Black 0.63 0.12–3.40 0.27 0.03–2.46 2.66 0.32–22.34
Hispanic 1.77 0.34–9.13 0.84 0.09–8.18 4.56 0.56–37.23
Asian/PI/Other 0.16 0.02–1.49 0.19 0.01–2.71 0.11 0.01–1.79
Acculturation (Heritage Subscore) Upper Tertile (less acculturated) ref - 0.051 ref - 0.135 ref - 0.138
Middle Tertile (moderately acculturated) 2.83 0.69–11.61 1.32 0.24–7.34 4.43 0.64–30.43
Lower Tertile (more acculturation) 5.81 1.14–29.62 5.14 0.72–36.94 7.21 0.93–55.90
missing 42.74 2.33–784.12 48.06 1.61–1438.90 76.92 1.20–4919.15
Gender Male 2.95 0.94–9.25 0.064 2.78 0.74–10.49 0.132 1.92 0.47–7.78 0.362
Female (ref) ref - ref - ref -
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Bolded denotes statistical significance

When cases were compared to PC-controls alone, we found increasing age (per year) (OR=1.12, 95% CI=1.05-1.20) and being foreign-born (1st generation) (vs. 3rd generation) (OR=15.78 95% CI=1.69-147.15) to be significantly different for cases. When cases were compared to community controls alone, we found increasing age (per year) (OR=1.20, 95% CI=1.08-1.32) and daily or more frequent consumption of cultural food at ages 15 to 18 (vs. never or rarely) (OR=84.08 95% CI 3.67-1925.05) to be significantly different for cases.

Discussion

In this study, we successfully developed an item pool that could be used to assess gastric cancer risk that was comprehensible, culturally sensitive and able to be translated into multiple different languages. Control ascertainment proved to be challenging through phone recruitment and procedure modification to direct recruitment in primary care clinics was necessary. We also found that expanding our survey administration options to include phone interview and paper format resulted in increased completion rates.

The questionnaire item pool was developed to assess gastric cancer risk factors that could subsequently be used to identify the key variables able to discriminate between persons at higher risk for gastric cancer. Questionnaire items combined conventional factors known to be associated with gastric cancer risk with less studied items including ethnicity, birth country, acculturation and ethnic diet. Though our pilot data, we were able to show that racial/ethnic variables were significant even with this small sample size and our findings showed promise that the addition of these variables will result in identifying a parsimonious list of risk factors that could be easily applied to multiple settings and used for public health initiatives to screen gastric cancer patients.

Given the diversity of the US population, these ethnic/cultural variables provide a straightforward and practical way of indirectly incorporating the genetic makeup and environmental exposures that underlie differences seen between countries, races and ethnicities in their gastric cancer incidence. While the US reports a low incidence rate of gastric cancer at 5-10 cases per 100,000.19 this aggregate incidence rate masks very large racial and ethnic disparities.20,21 Although overall rates for whites are low, among Blacks, Asians, and Hispanics, gastric cancer is one of the 10 most common cancers in the US.22 In studies examining SEER population-based registry data by race and ethnicity, Asians/Pacific Islanders, Blacks, and Hispanics were observed to have a two times higher incidence rate of non-cardia gastric cancer as compared with Non-Hispanic whites.11,20,21 In a retrospective cohort study in Southern California, Dong et al. found up to 50% increased gastric cancer incidence risk in racial minorities compared to Non-Hispanic whites.23 However, race alone is inadequate at characterizing gastric cancer risk.

Our study found US generation, cultural food consumption during ages 15 to 18 and acculturation to be risk factors for gastric cancer. Our finding is constant with other literature that shows variation in risk by birth country, ethnic origin and immigration generation. In a study of first-generation Hispanic males in Florida, gastric cancer rates were higher for men from Puerto Rico (21.3 per 100,000) than those from Mexico (14.0) or Cuba (9.7).15 In a study of Asians living in the US, gastric cancer was a top 5 cancer for Koreans, Chinese, Japanese, Laotian and Vietnamese, but not for Asian Indians, Pakistani and Kampucheans.24 The higher incidence observed among immigrants from specific countries, not just in Asia but in the Latin America and Eastern Europe, demonstrates the importance of country of birth in characterizing gastric cancer risk.25,26 Interestingly, we found that after adjusting for other variables in the model, greater acculturation appeared to have a higher risk of gastric cancer. When the acculturation variables were examined by US generation, we found that many 3rd generation participants declined to answer these questions, which may attribute to this finding (appendix 4). An alternative explanation may be that once generation status is accounted for, that following “American” habits, such as consuming a western diet, which is known to be a risk factor,27 becomes more pronounced. Given our small sample size, this would need to be tested in a larger sample.

Although rates are highest among foreign-born Koreans and Japanese, studies indicate the incidence of gastric cancer remains high in US-born Japanese-American and Korean-Americans as compared with non-Hispanic whites.13, 14 Similarly, in a study examining incidence patters among Hispanics in California, gastric cancer was higher in both foreign-born Hispanic men and US-born Hispanic women residing in high ethnic enclave neighborhoods with low socioeconomic status.28 While gastric cancer risk generally decreases with each generation’s length of time in the US, it’s not clear why this occurs.29 The shift from traditional to more acculturated/Western diets without high intake of pickled and salted foods, differences in lifestyle and exposures in the built environment may elucidate gastric cancer risk in immigrant subgroups.28,30,31 These findings suggest that immigrants have specific cancer risks of their native countries32,33 and continue to have a higher risk of gastric cancer in subsequent generations after immigration.13–16. As such, immigration generation, as well as their level of acculturation, should be considered when determining the risk of gastric cancer.6,29,34

The variation in incidence and mortality for gastric cancer among different racial and ethnic populations pose a challenge for management. While the American Society for Gastrointestinal Endoscopy (ASGE) recommends screening new US immigrants above the age of 40 from high-risk endemic regions, namely Japan, Korea, China, Russia and South America,35 there are no recommendations for other high-risk groups in the US, including future- generation immigrants from endemic regions or for high-risk racial groups, such as Hispanic/Latinos and Black Americans. In a survey of primary care providers and gastroenterologists, less than 30% of providers were able to correctly identify and categorize individuals from Black, Hispanic and Eastern European ethnicities as “high risk” for gastric cancer. Although 53% of providers believed screening for select populations, 85% of providers answered that they did not routinely test and treat for H. pylori in patients from endemic areas that were otherwise asymptomatic. The results of this survey indicate the providers have an insufficient understanding of gastric cancer risk36 and educating providers as to which individuals comprise high-risk in the US as well as developing methods that can be used to easily and objectively identify persons at risk should be made a priority.

Our study has the following limitations; first, this pilot study collected data from a small number of subjects and the derived model should not be taken as a definitive model for risk prediction. Second, the questions included in our item pool were specifically selected to be applicable for a future development of a gastric cancer risk questionnaire, and not designed to be used to identify new or novel risk factors. As such, we omitted risk factors that were burdensome to administer (e.g. food frequency questionnaires), inconstant (e.g. vitamin supplement consumption, presence of symptoms) or could not be assessable in questionnaire form and only assessable through invasive methods or specialized testing (e.g. H. pylori, serum-pepsinogen-levels). Third, while there is a potential for H. pylori or serum-pepsinogen testing to further specify the degree of an individual’s risk, a given the significant knowledge gap of health care providers36 and lack of awareness in the general population,37 make it imperative that a method to identify high-risk patients in the general population be developed and established into practice. Lastly, stage information had not been collected as part of this study. This information would have been beneficial to explore whether the cancer stage of persons included in this study were largely different than the overall stage distribution for gastric cancer. This provided us guidance that we will need to collect this information for the large case-control study being informed by this pilot study.

In summary, this pilot study found that a risk prediction model using a parsimonious set of items has the potential to identify persons at higher risk for gastric cancer for use in a targeted screening program for gastric cancer in the US. The findings of this pilot case-control study will be used to refine the methods for a future large case-control study of gastric cancer risk factors in the US. A proposal for a large scale case-control study aimed to fully develop and validate a risk prediction model that can identify high-risk persons is currently underway. Once developed, the model would need to be prospectively examined as a targeted screening program using the model to first identify persons at higher risk followed by endoscopy to detect gastric cancer. Our ultimate goal is to establish a targeted screening program for gastric cancer to decrease gastric cancer mortality in the US.

Supplementary Material

supplement

Acknowledgments

Support: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under the Award Number UG1CA189823 (Alliance for Clinical Trials in Oncology NCORP Grant). Partial support also provided by the Montefiore Medical Center (MMC) minority-based NCORP community site (UG1CA189859). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

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Author Contributions:

Analysis and interpretation of data – HI, ML, CS

Editing and drafting of the manuscripts – ALL

Conception and design of study, and/or acquisition of data – HI, MS, CS, JW, BR

All authors gave final approval for the manuscript to be published

Conflict of Interest: none

References

  • 1.World Health Organization, editor. International Agency for Research on Cancer. GLOBOCAN 2012: Estimated Cancer Incidence, Mortality and Prevalence Worldwide in 2012. Lyon, France: 2012. [Google Scholar]
  • 2.American Cancer Society. Cancer Facts and Figures 2017. 2017 Oct; Available from: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2017/cancer-facts-and-figures-2017.pdf.
  • 3.Oshima A, et al. Evaluation of a mass screening program for stomach cancer with a case-control study design. Int J Cancer. 1986;38(6):829–33. doi: 10.1002/ijc.2910380608. [DOI] [PubMed] [Google Scholar]
  • 4.Hamashima C, et al. A community-based, case-control study evaluating mortality reduction from gastric cancer by endoscopic screening in Japan. PLoS One. 2013;8(11):e79088. doi: 10.1371/journal.pone.0079088. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Lin S, et al. Prognostic value of SOX2 in digestive tumors: a meta-analysis. Hepatogastroenterology. 2014;61(133):1274–8. [PubMed] [Google Scholar]
  • 6.Kim Gwang Ha, et al. Screening and surveillance for gastric cancer in the United States: Is it needed? Gastrointest Endosc. 2016;84:18–28. doi: 10.1016/j.gie.2016.02.028. [DOI] [PubMed] [Google Scholar]
  • 7.Fock K. Review article: the epidemiology and prevention of gastric cancer. Alimentary pharmacology & therapeutics. 2014;40(3):250–260. doi: 10.1111/apt.12814. [DOI] [PubMed] [Google Scholar]
  • 8.Karimi P, et al. Gastric cancer: descriptive epidemiology, risk factors, screening, and prevention. Cancer Epidemiol Biomarkers Prev. 2014;23(5):700–13. doi: 10.1158/1055-9965.EPI-13-1057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.United States Census Bureau. Population Estimates: Race and Hispanic Origin. Quick Facts; 2016. [cited 2017 8/31]; Available from: https://www.census.gov/quickfacts/fact/table/US/PST045216. [Google Scholar]
  • 10.Lui FH, et al. Ethnic disparities in gastric cancer incidence and survival in the USA: an updated analysis of 1992–2009 SEER data. Digestive diseases and sciences. 2014;59(12):3027–3034. doi: 10.1007/s10620-014-3275-3. [DOI] [PubMed] [Google Scholar]
  • 11.Wu X, et al. Incidence of esophageal and gastric cancers among Hispanics, non-Hispanic whites and non-Hispanic blacks in the United States: subsite and histology differences. Cancer causes & control. 2007;18(6):585–593. doi: 10.1007/s10552-007-9000-1. [DOI] [PubMed] [Google Scholar]
  • 12.Schlansky B, Sonnenberg A. Epidemiology of noncardia gastric adenocarcinoma in the United States. The American journal of gastroenterology. 2011;106(11):1978–1985. doi: 10.1038/ajg.2011.213. [DOI] [PubMed] [Google Scholar]
  • 13.Kamineni A, et al. The incidence of gastric carcinoma in Asian migrants to the United States and their descendants. Cancer Causes & Control. 1999;10(1):77–83. doi: 10.1023/a:1008849014992. [DOI] [PubMed] [Google Scholar]
  • 14.Lee J, et al. Cancer incidence among Korean-American immigrants in the United States and native Koreans in South Korea. Cancer Control. 2007;14(1):78. doi: 10.1177/107327480701400111. [DOI] [PubMed] [Google Scholar]
  • 15.Pinheiro PS, et al. Cancer incidence in first generation US Hispanics: cubans, Mexicans, Puerto Ricans, and new Latinos. Cancer Epidemiology Biomarkers & Prevention. 2009;18(8):21622169. doi: 10.1158/1055-9965.EPI-09-0329. [DOI] [PubMed] [Google Scholar]
  • 16.Byfield SAD, et al. Treatment and outcomes of gastric cancer among United States-born and foreign-born Asians and Pacific Islanders. Cancer. 2009;115(19):4595–4605. doi: 10.1002/cncr.24487. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Ryder AG, Alden L, Paulhus DL. Is acculturation unidimensional or bidimensional?: A head-to-head comparison in the prediction of demographics, personality, self-identity, and adjustment. Journal of Personality and Social Psychology. 2000;79:49–65. doi: 10.1037//0022-3514.79.1.49. [DOI] [PubMed] [Google Scholar]
  • 18.Steyerberg E. Clinical Prediction Models: A Practical Approach to Development, Validation and Updating. New York, NY: Springer; 2009. [Google Scholar]
  • 19.Prevention, C.f.D.C.a. National Program of Cancer Registries (NPCR) 2015 Jan 15; Available from: http://www.cdc.gov/cancer/npcr/
  • 20.Lui FH, et al. Ethnic disparities in gastric cancer incidence and survival in the USA: an updated analysis of 1992-2009 SEER data. Dig Dis Sci. 2014;59(12):3027–34. doi: 10.1007/s10620-014-3275-3. [DOI] [PubMed] [Google Scholar]
  • 21.Schlansky B. Epidemiology of noncardia gastric adenocarcinoma in the United States. The American journal of gastroenterology. 2011;106(11):1978–1985. doi: 10.1038/ajg.2011.213. [DOI] [PubMed] [Google Scholar]
  • 22.Group, U.S.C.S.W. United States Cancer Statistics: 1999–2011 Incidence and Mortality Web-based Report. 2014 [January 01 2015] Available from: www.cdc.gov/uscs.
  • 23.Dong E, Duan L, Wu BU. Racial and ethnic minorities at increased risk for gastric cancer in a regional US population study. Clinical Gastroenterology and Hepatology. 2017;15:511–517. doi: 10.1016/j.cgh.2016.11.033. [DOI] [PubMed] [Google Scholar]
  • 24.Gomez SL. Cancer incidence trends among Asian American populations in the United States, 1990-2008. JNCI : Journal of the National Cancer Institute. 2013;10515:1096–1110. doi: 10.1093/jnci/djt157. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Corral JE, et al. The descriptive epidemiology of gastric cancer in Central America and comparison with United States Hispanic populations. Journal of gastrointestinal cancer. 2015;46(1):21–28. doi: 10.1007/s12029-014-9672-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Bertuccio P, et al. Recent patterns in gastric cancer: a global overview. Int J Cancer. 2009;125(3):666–73. doi: 10.1002/ijc.24290. [DOI] [PubMed] [Google Scholar]
  • 27.Bertuccio P, et al. Dietary patterns and gastric cancer risk: a systematic review and meta-analysis. Ann Oncol. 2013;24(6):1450–8. doi: 10.1093/annonc/mdt108. [DOI] [PubMed] [Google Scholar]
  • 28.Chang E, Gomez S, et al. Gastric cancer incidence among Hispanics in California: Patterns by Time, Nativity, and Neighborhood Characteristics. Cancer Epidemiol Biomarkers Prev. 2012;21(5):709–719. doi: 10.1158/1055-9965.EPI-11-1208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Higa JT, Hwang JH. Gastric intestinal metaplasia: An irreversible risk factor for gastric cancer? Gastrointestinal Endoscopy. 84(4):625–627. doi: 10.1016/j.gie.2016.04.028. [DOI] [PubMed] [Google Scholar]
  • 30.Gomez SL, et al. The impact of neighborhood social and built environment factors across the cancer continuum: Current research, methodological considerations, and future directions. Cancer. 2015;121(14):2314–2330. doi: 10.1002/cncr.29345. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Kim Y, et al. Stomach cancer incidence rates among Americans, Asian Americans and Native Asians from 1988 to 2011. Epidemiol Health. 2015;37:e2015006. doi: 10.4178/epih/e2015006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Chang ET, et al. Gastric cancer incidence among Hispanics in California: patterns by time, nativity, and neighborhood characteristics. Cancer Epidemiol Biomarkers Prev. 2012;21(5):709–19. doi: 10.1158/1055-9965.EPI-11-1208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Kolonel LN, et al. Association of diet and place of birth with stomach cancer incidence in Hawaii Japanese and Caucasians. Am J Clin Nutr. 1981;34(11):2478–85. doi: 10.1093/ajcn/34.11.2478. [DOI] [PubMed] [Google Scholar]
  • 34.Mousavi S, Sundquist J, Hemminki K. Does immigration play a role in the risk of gastric cancer by site and by histological type? A study of first-generation immigrants in Sweden. Gastric Cancer. 2011;14:285–289. doi: 10.1007/s10120-011-0033-5. [DOI] [PubMed] [Google Scholar]
  • 35.Cash BD, et al. Ethnic issues in endoscopy. Gastrointest Endosc. 2010;71(7):1108–12. doi: 10.1016/j.gie.2010.03.001. [DOI] [PubMed] [Google Scholar]
  • 36.Shah SC, Itzkowitz SH, Jandorf L. Knowledge Gaps among Physicians Caring for Multiethnic Populations at Increased Gastric Cancer Risk. Gut Liver. 2017 doi: 10.5009/gnl17091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Esposito L. Stomach Cancer: Awareness and Advances Needed. 2016 [Google Scholar]
  • 38.Lunet N, et al. Fruit and vegetable consumption and gastric cancer by location and histological type: case-control and meta-analysis. Eur J Cancer Prev. 2007;16(4):312–27. doi: 10.1097/01.cej.0000236255.95769.22. [DOI] [PubMed] [Google Scholar]
  • 39.Bonequi P, et al. Risk factors for gastric cancer in Latin America: a meta-analysis. Cancer Causes Control. 2013;24(2):217–31. doi: 10.1007/s10552-012-0110-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Bae JM, Lee EJ, Guyatt G. Citrus fruit intake and stomach cancer risk: a quantitative systematic review. Gastric Cancer. 2008;11(1):23–32. doi: 10.1007/s10120-007-0447-2. [DOI] [PubMed] [Google Scholar]
  • 41.Wang QCY, Wang X, Gong G, Li G, Li C. Consumption of fruit, but not vegetables, may reduce risk of gastric cancer: Results from a meta-analysis of cohort studies. Eur J Cancer. 2014;50(8):1498–509. doi: 10.1016/j.ejca.2014.02.009. [DOI] [PubMed] [Google Scholar]
  • 42.Woo HD, P S, Oh K, Kim HJ, Shin HR, Moon HK, et al. Diet and Cancer Risk in the Korean Population: A Meta-analysis. Asian Pac J Cancer Prev. 2014;15(19):8509–19. doi: 10.7314/apjcp.2014.15.19.8509. [DOI] [PubMed] [Google Scholar]
  • 43.Steevens J, et al. Vegetables and fruits consumption and risk of esophageal and gastric cancer subtypes in the Netherlands Cohort Study. International Journal of Cancer. 2011;129(11):2681–2693. doi: 10.1002/ijc.25928. [DOI] [PubMed] [Google Scholar]
  • 44.Kim HJ, L S, Lee JS, Park S, Shin A, Choi BY, et al. Fresh and pickled vegetable consumption and gastric cancer in Japanese and Korean populations: A meta-analysis of observational studies. Cancer Sci. 2010;102(2):508–16. doi: 10.1111/j.1349-7006.2009.01374.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Yang TS, Y X, Wang XD, Wang YL, Song Z. The role of tomato products and lycopene in the prevention of gastric cancer: A meta-analysis of epidemiologic studies. Med Hypotheses. 2013;80(4):383–8. doi: 10.1016/j.mehy.2013.01.005. [DOI] [PubMed] [Google Scholar]
  • 46.Zhou Y, Z W, Hu W, Liu GJ, Wu TX, XT W. Consumption of large amounts of Allium vegetables reduces risk for gastric cancer in a meta-analysis. Gastroenterology. 2011;141(1):80–9. doi: 10.1053/j.gastro.2011.03.057. [DOI] [PubMed] [Google Scholar]
  • 47.Gao CM, T T, Ding JH, Li MS, T K. Protective Effect of Allium Vegetables against Both Esophageal and Stomach Cancer: A Simultaneous Case-referent Study of a High-epidemic Area in Jiangsu Province, China. Japanese Journal of Cancer Research. 1999;90(6):614–21. doi: 10.1111/j.1349-7006.1999.tb00791.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Turati F, et al. Allium vegetable intake and gastric cancer: A case-control study and meta-analysis. Mol Nutr Food Research. 2015;59(1):171–129. doi: 10.1002/mnfr.201400496. [DOI] [PubMed] [Google Scholar]
  • 49.Fleischauer AT, P C, Arab L. Garlic consumption and cancer prevention: meta-analyses of colorectal and stomach cancers. J Clin Nutr. 2000;72(4):1047–52. doi: 10.1093/ajcn/72.4.1047. [DOI] [PubMed] [Google Scholar]
  • 50.You WC, B W, Chang YS, Ershow A, Yang ZT, An Q, Henderson BE, Fraumeni JF, Wang TG. Allium vegetables and reduced risk of stomach cancer. Journal of the National Cancer Institute. 1989;81(2):162–164. doi: 10.1093/jnci/81.2.162. [DOI] [PubMed] [Google Scholar]
  • 51.Song P, L M, Yin Q, Wu L, Zhang D, Fu B, et al. Red meat consumption and stomach cancer risk: a meta-analysis. J Cancer Res Clin Oncol. 2014;140(6):979–92. doi: 10.1007/s00432-014-1637-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Zhu HC, X Y, Zhang C, Zhu C, Tao GZ, Zhao LJ, et al. Red and Processed Meat Intake Is Associated with Higher Gastric Cancer Risk: A Meta-Analysis of Epidemiological Observational Studies. PLoS One. 2013;8 doi: 10.1371/journal.pone.0070955. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Navarro Silvera SA, M S, Risch H, Gammon MD, Vaughan TL, Chow WH, Dubrow R, Schoenberg JB, Stanford JL, West AB, Rotterdam H. Food group intake and risk of subtypes of esophageal and gastric cancer. International journal of cancer. 2008;123(4):852–60. doi: 10.1002/ijc.23544. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Perez V, A D, LW D. Processed meat consumption and stomach cancer: A meta-analysis of prospective epidemiologic studies. Am J Epidemiol. 2011;173:S35. [Google Scholar]
  • 55.D’Elia L, et al. Habitual salt intake and risk of gastric cancer: a meta-analysis of prospective studies. Clin Nutrition. 20124:489–98. doi: 10.1016/j.clnu.2012.01.003. [DOI] [PubMed] [Google Scholar]
  • 56.Larsson SC, O N, Wolk A. Processed meat consumption and stomach cancer risk: a meta-analysis. J Natl Cancer Institute. 2006;98(15):1078–87. doi: 10.1093/jnci/djj301. [DOI] [PubMed] [Google Scholar]
  • 57.Ko KP, et al. Intake of soy products and other foods and gastric cancer risk: a prospective study. J Epidemiol. 2013;23(5):337–43. doi: 10.2188/jea.JE20120232. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Ren JS, K F, Forman D, Islami F. Pickled food and risk of gastric cancer–a systematic review and meta-analysis of English and Chinese literature. Cancer Epidemiol Biomarkers Prev. 2012;6:905–915. doi: 10.1158/1055-9965.EPI-12-0202. [DOI] [PubMed] [Google Scholar]
  • 59.Galván-Portillo MV, C A, Onate-Ocana LF, Chen J, Herrera-Goepfert R, Torres-Sanchez L, Hernandez-Ramirez RU, Palma-Coca O, López-Carrillo L. Gastric cancer in relation to the intake of nutrients involved in one-carbon metabolism among MTHFR 677 TT carriers. European journal of nutrition. 2009;48(5):269–76. doi: 10.1007/s00394-009-0010-5. [DOI] [PubMed] [Google Scholar]
  • 60.Jacobs DR, Jr, et al. Whole-grain intake and cancer: an expanded review and meta-analysis. Nutr Cancer. 1998;30(2):85–96. doi: 10.1080/01635589809514647. [DOI] [PubMed] [Google Scholar]
  • 61.Zhang ZZ, X G, Ma MM, L XF, Yang J. Dietary Fiber Intake Reduces Risk for Gastric Cancer: A Meta-analysis. Gastroenterology. 2013;145(1):113. doi: 10.1053/j.gastro.2013.04.001. [DOI] [PubMed] [Google Scholar]
  • 62.Li P, H Z, Chen J, Shi Y, Cai J, Yang J, et al. Association between dietary antioxidant vitamins intake/blood level and risk of gastric cancer. Int J Cancer. 2014;135(6):1444–53. doi: 10.1002/ijc.28777. [DOI] [PubMed] [Google Scholar]
  • 63.Druesne-Pecollo N, L-M P, Norat T, Barrandon E, Bertrais S, Galan P, et al. Beta-carotene supplementation and cancer risk: a systematic review and metaanalysis of randomized controlled trials. Int J Cancer. 2010;127(1):172–84. doi: 10.1002/ijc.25008. [DOI] [PubMed] [Google Scholar]
  • 64.Lam TK, F N, Fan JH, Qiao YL, Dawsey SM, Taylor PR, et al. Prediagnostic plasma vitamin C and risk of gastric adenocarcinoma and esophageal squamous cell carcinoma in a Chinese population. Am J Clin Nutrition. 2013;98(5):1289–97. doi: 10.3945/ajcn.113.061267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Larsson SC, B L, Näslund I, Rutegård J, W A. Vitamin A, retinol, and carotenoids and the risk of gastric cancer: a prospective cohort study. The American journal of clinical nutrition. 2007;85(2):497–503. doi: 10.1093/ajcn/85.2.497. [DOI] [PubMed] [Google Scholar]
  • 66.Dawsey SP, et al. A Prospective Study of Vitamin and Mineral Supplement Use and the Risk of Upper Gastrointestinal Cancers. Plos One. 2014;9(2) doi: 10.1371/journal.pone.0088774. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Zheng W, S T, Doyle TJ, Kushi LH, Potter JD, Folsom AR. Retionol, antioxidant vitamins and cancers of the upper digestive tract in a prospective cohort study of postmenopausal women. American Journal of Epidemiology. 1995;142(9):955–960. doi: 10.1093/oxfordjournals.aje.a117743. [DOI] [PubMed] [Google Scholar]
  • 68.Chen Y, Y C, Li Y. Physical activity and risks of esophageal and gastric cancers: a meta-analysis. PLoS One. 2014;9(2):e88082. doi: 10.1371/journal.pone.0088082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Cook MB, et al. Physical Activity and Sedentary Behavior in Relation to Esophageal and Gastric Cancers in the NIH-AARP Cohort. Plos One. 2013;8(12) doi: 10.1371/journal.pone.0084805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Tredaniel J, B P, Buiatti E, Saracci R, Hirsch A. Tobacco smoking and gastric cancer: review and meta-analysis. Int J Cancer. 1997;72(4):565–73. doi: 10.1002/(sici)1097-0215(19970807)72:4<565::aid-ijc3>3.0.co;2-o. [DOI] [PubMed] [Google Scholar]
  • 71.Nishino Y, I M, Tsuji I, Wakai K, Nagata C, Mizoue T, et al. Tobacco smoking and gastric cancer risk: an evaluation based on a systematic review of epidemiologic evidence among the Japanese population. Jpn J Clin Oncol. 2006;36(12):800–7. doi: 10.1093/jjco/hyl112. [DOI] [PubMed] [Google Scholar]
  • 72.Ladeiras-Lopes R, P A, Nogueira A, Pinheiro-Torres T, Pinto I, Santos-Pereira R, et al. Smoking and gastric cancer: systematic review and meta-analysis of cohort studies. Cancer Causes Control. 2008;7:689–701. doi: 10.1007/s10552-008-9132-y. [DOI] [PubMed] [Google Scholar]
  • 73.La Torre G, C G, Gianfagna F, De Lauretis A, Boccia S, Mannocci A. Smoking status and gastric cancer risk: an updated meta-analysis of case-control studies published in the past ten years. Tumori. 2009;95(1):13–22. doi: 10.1177/030089160909500103. [DOI] [PubMed] [Google Scholar]
  • 74.Koizumi Y, T Y, Nakaya N, Kuriyama S, Shibuya D, Matsuoka H. Cigarette smoking and the risk of gastric cancer: a pooled analysis of two prospective studies in Japan. Int J Cancer. 2004;112(6):1049–55. doi: 10.1002/ijc.20518. [DOI] [PubMed] [Google Scholar]
  • 75.Inoue M, et al. Influence of habitual smoking on gastric cancer by histologic subtype. International Journal of Cancer. 1999;81(1):39–43. doi: 10.1002/(sici)1097-0215(19990331)81:1<39::aid-ijc8>3.0.co;2-#. [DOI] [PubMed] [Google Scholar]
  • 76.Tramacere I, et al. A meta-analysis on alcohol drinking and gastric cancer risk. Ann Oncol. 2012;23(1):28–36. doi: 10.1093/annonc/mdr135. [DOI] [PubMed] [Google Scholar]
  • 77.de Menezes RF, Bergmann A, Thuler LC. Alcohol consumption and risk of cancer: a systematic literature review. Asian Pac J Cancer Prev. 2013;14(9):4965–72. doi: 10.7314/apjcp.2013.14.9.4965. [DOI] [PubMed] [Google Scholar]
  • 78.Bagnardi V, et al. Alcohol consumption and site-specific cancer risk: a comprehensive dose-response meta-analysis. Br J Cancer. 2015;112(3):580–93. doi: 10.1038/bjc.2014.579. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79.Shimazu T, et al. Alcohol drinking and gastric cancer risk: An evaluation based on a systematic review of epidemiologic evidence among the Japanese population. Japanese Journal of Clinical Oncology. 2008;38(1):8–25. doi: 10.1093/jjco/hym152. [DOI] [PubMed] [Google Scholar]
  • 80.Li Y, Yang HA, Cao J. Association between Alcohol Consumption and Cancers in the Chinese Population-A Systematic Review and Meta-Analysis. Plos One. 2011;6(4) doi: 10.1371/journal.pone.0018776. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.Shu L, et al. Dietary Patterns and Stomach Cancer: A Meta-Analysis. Nutrition and Cancer-an International Journal. 2013;65(8):1105–1115. doi: 10.1080/01635581.2013.828086. [DOI] [PubMed] [Google Scholar]
  • 82.Allen NE, et al. Moderate Alcohol Intake and Cancer Incidence in Women. Journal of the National Cancer Institute. 2009;101(5):296–305. doi: 10.1093/jnci/djn514. [DOI] [PubMed] [Google Scholar]
  • 83.Chen Y, L L, Wang X, Wang J, Yan Z, Cheng J. Body mass index and risk of gastric cancer: a meta-analysis of a population with more than ten million from 24 prospective studies. Cancer Epidemiol Biomarkers Prev. 2013;22(8):1395–408. doi: 10.1158/1055-9965.EPI-13-0042. [DOI] [PubMed] [Google Scholar]
  • 84.Kubo A, C D. Body mass index and adenocarcinomas of the esophagus or gastric cardia: A systematic review and meta-analysis. Cancer Epidemiology Biomarkers and Prevention. 2006;15(5):872–8. doi: 10.1158/1055-9965.EPI-05-0860. [DOI] [PubMed] [Google Scholar]
  • 85.Lin XJ, W C, Liu XD, Yan KK, Li S, Bao HH. Body mass index and risk of gastric cancer: A meta-analysis. Jpn J Clin Oncol. 2014;444(9):783–791. doi: 10.1093/jjco/hyu082. [DOI] [PubMed] [Google Scholar]
  • 86.Yang P, Z Y, Chen B, Wan HW, Jia GQ, Bai HL, et al. Overweight, obesity and gastric cancer risk: results from a meta-analysis of cohort studies. Eur J Cancer. 2009;45(16):2867–73. doi: 10.1016/j.ejca.2009.04.019. [DOI] [PubMed] [Google Scholar]
  • 87.O’Doherty MG, et al. A prospective cohort study of obesity and risk of oesophageal and gastric adenocarcinoma in the NIH-AARP Diet and Health Study. Gut. 2012;61(9):1261–1268. doi: 10.1136/gutjnl-2011-300551. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 88.Wang ZB, Y M, Cai H, Li B, Zhao X, Ma LY. ABO blood group and the risk of gastric cancer: A case-control study and meta-analysis. Academic Journal of Second Military Medical University. 2014;35(5):560–565. [Google Scholar]
  • 89.Huan JQ, S S, Chen Y, Hunt RH. Meta-analysis of the relationship between Helicobacter pylori seropositivity and gastric cancer. Gastroenterology. 1998;114(6):1169–79. doi: 10.1016/s0016-5085(98)70422-6. [DOI] [PubMed] [Google Scholar]
  • 90.Pinto M, P B, Lunet N. H pylori infection and gastric cardia cancer: Systematic review and meta-analysis. Helicobacter. 2009;14(4):380. doi: 10.1007/s10552-010-9707-2. [DOI] [PubMed] [Google Scholar]
  • 91.Xue FB, X Y, Wan Y, Pan BR, Ren J, Fan DM. Association of H-pylori infection with gastric carcinoma: a Meta analysis. World J Gastroenterol. 2001;7(6):801–4. doi: 10.3748/wjg.v7.i6.801. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92.Cavaleiro-Pinto M, P B, Lunet N, Barros H. Helicobacter pylori infection and gastric cardia cancer: systematic review and meta-analysis. Cancer Causes Control. 2011;22(3):375–87. doi: 10.1007/s10552-010-9707-2. [DOI] [PubMed] [Google Scholar]
  • 93.Carraher S, C H, Munday R, Goodman KJ, CAN Help Working Group Helicobacter pylori incidence and re-infection in the Aklavik H. pylori project. International journal of circumpolar health. 2013;5(72) doi: 10.3402/ijch.v72i0.21594. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94.Ahn JS, E C, Jeon CY, Park SM. Acid suppressive drugs and gastric cancer: a meta-analysis of observational studies. World J Gastroenterol. 2013;19(16):2560–2568. doi: 10.3748/wjg.v19.i16.2560. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 95.Gonzalez-Perez A, R L, Lopez-Ridaura R. Effects of non-steroidal anti-inflammatory drugs on cancer sites other than the colon and rectum: a meta-analysis. BMC Cancer. 2003;3(12) doi: 10.1186/1471-2407-3-28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96.Tian W, Z Y, Liu S, Li X. Meta-analysis on the relationship between nonsteroidal anti-inflammatory drug use and gastric cancer. Eur J Cancer Prev. 2010;19(4):288–98. doi: 10.1097/CEJ.0b013e328339648c. [DOI] [PubMed] [Google Scholar]
  • 97.Bosetti C, et al. Aspirin and cancer risk: a quantitative review to 2011. Ann Oncol. 2012;23(6):1403–15. doi: 10.1093/annonc/mds113. [DOI] [PubMed] [Google Scholar]
  • 98.Yang P, Z Y, Chen B, Wan HW, Jia GQ, Bai HL, et al. Aspirin use and the risk of gastric cancer: a meta-analysis (Structured abstract) Dig Dis Sci [Internet] 2010;55(6):1533–9. doi: 10.1007/s10620-009-0915-0. [DOI] [PubMed] [Google Scholar]
  • 99.Abnet CC, F N, Kamangar F, Leitzmann MF, Hollenbeck AR, Schatzkin A. Non-steroidal anti-inflammatory drugs and risk of gastric and oesophageal adenocarcinomas: results from a cohort study and a meta-analysis. Br J Cancer. 2009;100(3):551–557. doi: 10.1038/sj.bjc.6604880. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100.Shebl FM, et al. Non-Steroidal Anti-Inflammatory Drugs Use Is Associated with Reduced Risk of Inflammation-Associated Cancers: NIH-AARP Study. Plos One. 2014;9(12) doi: 10.1371/journal.pone.0114633. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101.Yaghoobi M, Bijarchi R, Hunt RH. Risk of Development of Gastric Cancer in Relatives of Patients with Non-Hereditary Gastric Cancer: A Meta-Analysis. Gastroenterology. 2009;136(5):A450–A450. [Google Scholar]
  • 102.Dong CH, Hemminki K. Modification of cancer risks in offspring by sibling and parental cancers from 2,112,616 nuclear families. International Journal of Cancer. 2001;92(1):144–150. [PubMed] [Google Scholar]
  • 103.Dhillon PK, et al. Family history of cancer and risk of esophageal and gastric cancers in the United States. International Journal of Cancer. 2001;93(1):148–152. doi: 10.1002/ijc.1294. [DOI] [PubMed] [Google Scholar]
  • 104.Uthman O, Jadidi E, Moradi T. Socioeconomic position and incidence of gastric cancer: a systematic review and meta-analysis. J Epidemiol Community Health. 2013;67(10):854–860. doi: 10.1136/jech-2012-201108. [DOI] [PubMed] [Google Scholar]
  • 105.Mouw T, et al. Education and Risk of Cancer in a Large Cohort of Men and Women in the United States. Plos One. 2008;3(11) doi: 10.1371/journal.pone.0003639. [DOI] [PMC free article] [PubMed] [Google Scholar]

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