Abstract
Background:
Family history may inform individuals that they are at risk of gastric cancer (GC). However, it is too extensive to conduct intensive screening strategies for all individuals with family history of GC instead of average-risk screening. To establish more precise prevention strategies, accurate risk estimates are necessary for individuals with family history of GC.
Methods:
We searched PubMed, EMBASE and Cochrane for all relevant studies from their inception to May 21, 2020, for cohort and case-control studies investigating the association between family history of GC and its risk. Relative risk (RR) and 95% confidence interval (CI) were pooled from studies using random-effects or fixed effects.
Results:
The RR of GC was 2.08 (95% CI=1.86–2.34) in individuals with family history of GC according to twenty-nine case-control studies and 1.83 (95%CI=1.67–2.01) from six cohort studies. The increased risk was higher in individuals with sibling history of GC than those with parental history of GC (RR=3.18, 95% CI=2.12–4.79 vs. RR=1.66, 95% CI=1.46–1.89, P=0.021). For individuals with 2 or more first-degree relatives (FDRs) with GC, the RR was 2.81(95% CI=1.89–3.99). Subjects with both family history and Helicobacter pylori (H. pylori) infection confer a higher risk of GC (RR = 4.03, 95%CI=2.46–6.59).
Conclusion:
The RR of GC among FDRs is lower than in previous studies. However, the risk of GC is markedly increased in individuals having a sibling with GC, more than 2 FDRs with GC. Intensified screening and eradication therapy for H. pylori could be considered for these individuals.
Keywords: Family history, Gastric cancer, Risk, Meta-analysis, Helicobacter pylori
Introduction
Globally, Gastric cancer (GC) is the fifth commonest cancer, and the third leading cause of cancer-related death (1). Especially in Eastern Asia, high incidence and mortality pose considerable public health challenges in terms of healthcare costs. Therefore, identification of high-risk population is crucial for preventing GC and reducing healthcare costs (2). Some screening guideline for GC recommends screening for all individuals with a family history of GC (3). However, these recommendations may be too wide to accurately guide the primary prevention of GC.
Epidemiologic studies have demonstrated that a family history of GC increases risk for GC (4, 5). This increased risk may be related to inherited genetic factors and shared environmental factors between family members (6, 7). Thus, for individuals with a positive family history of GC, the risk of developing GC is affected by various factors, such as the degree, number and type of family members developed GC, or the diagnostic age of GC. However, there is a lack of evidence-based estimates to quantify the risk of GC based on these factors. Otherwise, whether individuals with sibling history of GC have a higher risk than those with parent history of GC remains inconclusive. Individuals with family history of GC and colonized with H. pylori are rarely considered. Therefore, quantitative estimates and further stratified analyses are needed to determine in which individuals with family history of GC have a higher risk of GC.
Methods
This analysis was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement (8). The protocol was registered at PROSPERO [CRD 42020163421] (https://www.crd.york.ac.uk/prospero/).
Search strategy and study selection
We searched PubMed, EMBASE and Cochrane for all relevant studies from their inception to May 21, 2020. The search terms included four main categories: “gastric cancer”, “family”, “cohort study” and “case-control study”. No publication status and language restrictions were imposed. Moreover, the reference lists of selected articles were examined for additional eligible studies. The following studies were excluded: 1) case reports, reviews and conference abstracts; 2) studies did not define family history of GC clearly; 3) controls had other malignant diseases; 4) The Newcastle-Ottawa Scale (NOS) <6; 5) studies with duplicated data.
Data extraction and Quality assessment
Two reviewers independently extracted data from all included studies. The following data were extracted: name of the first author, year of publication, country, study design, number of cases, variables adjusted in the analysis, type of family history exposure, effect estimates (odds ratio, relative risk, standardized incidence ratio and 95% confidence interval) and other stratified data. The odd ratios (ORs) were collected as good estimates of relative risk (RR) because of extremely low incidence of GC in symptomatic populations (9). The adjusted estimates were extracted if a study reported both crude and adjusted risk estimates. Stratified data were also collected for subgroup analysis such as degree, number, age, site of GC and type of family history exposure. Quality assessment was independently assessed using NOS by two investigators. The NOS scores ranging 0 to 9 based on eight items. Studies with scores≥6 were included. (http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp)
Statistical analysis
The pooled estimates RR as the effect of outcomes. Assessment of heterogeneity between the included studies was tested using the I2 statistic of chi-square test. The RR estimate was pooled by random-effects model, when I2>50% (suggested high heterogeneity), otherwise, the fixed-effects model was used. Subgroup analyses and meta-regression were conducted to explore potential sources of heterogeneity (10). Sensitivity analysis was performed to evaluate the robustness of the results by sequentially omitting one study at a time. Possible publication bias was assessed using Begg’s regression test and funnel plot, and P<0.05 was considered to reflect statistically significant. All these statistical analyses were calculated using STATA/SE 15.1 (Stata Corp, College Station, TX).
Subgroup analysis
Since 35 studies showed high heterogeneity, stratified meta-analysis on risk of GC was further performed by the following subgroups: 1) degree of affected relatives (at least 1 FDR versus at least 1 SDR); 2) number of FDR affected (1 FDR versus at least 2 FDR); 3) the types of FDR (parent, father versus sibling); 4) age of person at risk(younger than 60 versus 60 yr or older); 5) gender of person at risk; 6) anatomic site of GC (cardia versus noncardia); 7) Lauren classification (intestinal versus diffuse); 8) study design (cohort studies versus case-control studies); 9) geographic region of study (Asia versus Americas, Europe); 10) the covariates adjusted. These subgroup analyses are necessary because we perceive them as potential sources of heterogeneity of this meta-analysis.
Results
Literature search
Overall, 2331 articles were identified from the search strategy in PubMed, EMBASE and The Cochrane Library (Fig. 1).
Fig.1:
Flow diagram of selection of studies for meta-analysis
After the removal of meta-analyses, review and duplicate articles, 1841 articles remained. After the exclusion of 1634 irrelative articles based on title and abstract, 207 articles were reviewed for full texts screening. The 177 articles were excluded because of following reasons: No family history of GC (n=81), No GC risk reported (n=26), Insufficient data (n=9), Cross-sectional studies (n=51), No full text available (n=7), NOS scores <6 (n=3). Therefore, 30 articles from PubMed, EM-BASE and The Cochrane Library, and 5 additional articles from references of eligible studies. Finally, 35 articles were included in this meta-analysis (4–6, 11–42). Characteristics and NOS score of selected studies were summarized (Table 1).
Table 1:
Characteristics and NOS score of selected studies in the meta-analysis
| Author(year) | Country | Type of design | No. of case | Adjusted variables | NOS |
|---|---|---|---|---|---|
| Shen, J.(2001) | China | Cohort | 448 | Age and Sex | 6 |
| Wang, G. P.(2012) | China | PBC | 772 | Age, sex and occupation | 8 |
| Shin, C. M.(2010) | Korea | HBC | 497 | H. pylori infection, residency during childhood, smoking, current income, and spicy food diet | 7 |
| Lin, Y.(2019) | China | PBC | 622 | Age, sex, BMI, education, occupation, income, smoking, alcohol drinking, drinking tea, chronic atrophic gastritis, reflux, and H. pylori infection | 8 |
| Luo, H. Z.(2005) | China | PBC | 251 | None | 7 |
| Behnampour, N.(2014) | North Iran | PBC | 156 | Age, sex, smoking, Charred flesh, H. pylori infection, | 8 |
| Zhao, J. K.(2017) | China | PBC | 2216 | Age, sex, county of residence, education, income, pack-years of smoking, alcohol drinking | 8 |
| Wang, N.(2010) | China | PBC | 285 | Age and sex | 7 |
| Gao, S.(2011) | China | PBC | 398 | Age, sex, or histological classification. | 8 |
| Yatsuya H.(2004) | Japan | PBC | 220 | The number of siblings smoking status, drinking habit, consumption of vegetables, H. pylori infection, citrus fruits green tea and educational level | 9 |
| Song, H.(2018) | Swedish | Cohort | 1302 | Age, sex, family size and stratified by pathology department | 8 |
| Song, M.(2018) | Finland | Cohort | 307 | Age, type of assigned intervention, BMI, pack-years of smoking, vegetable intake, alcohol drinking, highest level of education, fruit | 9 |
| Dhillon, P. K.(2001) | America | PBC | 1143 | Age, sex, race, pack-years of smoking, gender-specific quartile of BMI, income and proxy status. | 8 |
| Hassan, M. M.(2008) | America | HBC | 740 | Age, sex, and race | 7 |
| Safaee, A.(2011) | Iran | PBC | 1010 | Age and sex | 7 |
| Lissowska, J.(1999) | Poland | PBC | 464 | Age, sex, education, smoking, fresh, fruits/vegetables | 8 |
| La Vecchia, C.(1992) | Italy | HBC | 628 | Age, sex, area of residence, education, and number of siblings. | 7 |
| Foschi, R.(2008) | Italy | HBC | 230 | Age, sex, education, BMI, smoking | 8 |
| Hagy, G. W(1954) | America | HBC | 106 | None | 6 |
| Zanghieri, G.(1990) | Japan | HBC | 970 | Age, sex, education, BMI, smoking | 7 |
| Toyoshima, H.(1997) | Japan | Cohort | 907 | None | 7 |
| Huang, X.(1999) | Japan | HBC | 850 | Age and sex | 6 |
| Huang, X. E.(2004) | Japan | HBC | 1988 | Age and Sex | 7 |
| Ikeguchi, M.(2001) | Japan | HBC | 926 | None | 6 |
| Ihamaki, T.(1991) | Finland | Cohort | 301 | Age and Sex | 7 |
| Muñoz, N.(2001) | Venezuela. | PBC | 292 | Age, Sex, BMI and socio-economic status | 8 |
| Palli, D.(1992) | Italy | PBC | 819 | Age, Sex, smoking, alcohol drinking, and BMI drinking, BMI, Social class and histological classification. | 8 |
| Palli, D.(2000) | Italy | Cohort | 84 | Age, Sex, area of residence, smoking, alcohol | 9 |
| Brenner, H.(2000) | Germany | PBC | 68 | Age, sex, education and H. pylori infection | 8 |
| García, M. A.(2007) | Spain | PBC | 404 | Age, Sex, smoking and alcohol drinking | 9 |
| T Bakir(2000) | Turkey | PBC | 1240 | Age and Sex | 7 |
| Nagase, H(1996) | Japan | HBC | 136 | Age and Sex | 6 |
| Minami, Y.(2003) | Japan | HBC | 614 | Age, sex, year of survey, alcohol consumption, occupation | 8 |
| Chen, M. J.(2004) | China | HBC | 176 | Age, sex, education, income, smoking | 8 |
| Gong, E. J.(2014) | Korea | PBC | 237 | Age and Sex H. pylori infection | 9 |
PBC: Population-based case-control; HBC: Hospital-based case-control; BMI: Body mass index; H. pylori: Helicobacter pylori; NOS: Newcastle-Ottawa Quality Assessment Scale
Risk of gastric cancer and family history
From included studies, subjects with family history of GC were significantly more likely to develop GC (RR=2.00, 95%CI=1.83–2.20; P<0.001) compared to subjects without family history (Fig. 2). Thirty-five studies showed high heterogeneity (I2=57.1%; Q=79.33; P heterogeneity <0.001). The sensitivity analysis meant that the result of meta-analysis was robustness. The Begg’s test provided that no publication bias was observed (Begg’s regression test P=0.256; funnel plot in Fig. 3).
Fig.2:
Forest plot of individuals with family history of gastric cancer and gastric cancer risk
Fig.3:
Begg’s plot for publication bias of all studies (P=0.256>0.5)
Risk of gastric cancer based on degree of family members
Family history of GC in first-degree relatives (FDRs) conferred an increased risk of GC (RR=2.07, 95%CI=1.88–2.29, P<0.001). The heterogeneity was high (I2=52.6%, Q=54.85, P heterogeneity <0.001). No publication bias was observed (Begge’s regression test P=0.279). Subjects having second-degree relatives (SDRs) with GC were 1.84-fold (95%CI=1.06–3.02, P=0.031) increased risk of GC compared to without such a family history. High heterogeneity was observed (I2=54.8%, Q=6.64, P heterogeneity =0.084). When individuals with at least one third-degree relatives (TDRs), the two studies corrected RR was not statistically significant (P=0.214). (Fig. 4)
Fig.4:
Pooled relative risk of gastric cancer in individuals based on degree of family members
Risk of gastric cancer according to type of first-degree relative
Since the impact of at least one FDR with GC was statistically significant and very robustness, we further analyzed the pooled effect of type of FDR. The risk was higher in individuals having sibling with GC than those having parent with GC (RR=3.18, 95%CI=2.12–4.79, I2=81.9% versus RR=1.66, 95%CI=1.46–1.89, I2=21.5%, P=0.021) (Fig. 5). Considered separately, paternal history of GC was statistically significant (RR=1.58, 95%CI=1.23–2.03, P=0.004, I2=38.0%), whereas maternal history was non-significant (RR=1.50, 95%CI=0.77–2.93, P=0.238, I2=78.6%).
Fig.5:
Pooled relative risk of gastric cancer in individuals based on type of first-degree relative
Subgroup and meta-regression analysis
Stratified analyses were performed according to number of FDRs, age and gender of person at risk, anatomic site, study design, geographic area of study, and H. pylori infection (Table 2).
Table 2:
Stratified analysis of family history and risk of gastric cancer
| Category | Studies(n) | RR(95%CI) | Heterogeneity | P-value | |
|---|---|---|---|---|---|
|
| |||||
| I 2 (%) | P | ||||
| Gender of person at risk | |||||
| Male | 3 | 2.29(1.80–2.91) ** | 0.0 | 0.373 | Ref |
| Female | 3 | 2.40(1.83–3.14) ** | 0.0 | 0.454 | 0.818 |
| Age of person at risk | |||||
| Higher than 60 | 3 | 2.20(1.58–3.08) ** | 0.0 | 0.714 | Ref |
| Lower than 60 | 3 | 2.93(1.81–4.47) ** | 0.0 | 0.374 | 0.398 |
| No. of FDR | |||||
| 1 FDR | 3 | 1.82(1.53–2.15) ** | 22.8 | 0.274 | Ref |
| At least 2 FDR | 6 | 2.81(1.98–3.99) ** | 36.1 | 0.166 | 0.132 |
| Anatomic subsite | |||||
| Cardia | 5 | 1.65 (1.24–2.20) ** | 21.7 | 0.276 | Ref |
| Non-cardia | 4 | 2.23 (1.87–2.67) ** | 39.6 | 0.174 | 0.171 |
| Lauren classification | |||||
| Intestinal | 4 | 4.08 (3.49–4.76) ** | 81.3 | 0.001 | Ref |
| Diffuse | 4 | 3.89 (3.26–4.64) ** | 66.4 | 0.030 | 0.803 |
| Design | |||||
| Cohort | 6 | 1.83(1.67–2.01) ** | 0.0 | 0.549 | Ref |
| Case-control | 29 | 2.08(1.86–2.34) ** | 62.8 | <0.001 | 0.410 |
| Region | |||||
| Asia | 18 | 1.99 (1.73–2.27) ** | 64.9 | <0.001 | Ref |
| Americas | 3 | 2.35 (1.60–3.45) ** | 0.0 | 0.897 | 0.449 |
| Europe | 9 | 1.94 (1.78–2.10) ** | 49.6 | 0.037 | 0.753 |
| Adjust smoking | |||||
| Yes | 14 | 2.09(1.79–2.45) ** | 59.0 | 0.003 | Ref |
| No | 21 | 1.97(1.75–2.22) ** | 56.4 | 0.001 | 0.559 |
| Adjust alcohol consumption | |||||
| Yes | 7 | 1.65(1.54–1.76) ** | 42.6 | 0.107 | Ref |
| No | 28 | 2.04(1.91–2.17) ** | 44.8 | 0.001 | 0.016 |
| Adjust H. pylori infection | |||||
| Yes | 6 | 2.61(1.96–3.47) ** | 0.0 | 0.985 | Ref |
| No | 29 | 1.96(1.78–2.16) ** | 61.6 | <0.001 | 0.126 |
| Factor | |||||
| Family history positive | 35 | 2.00(1.83–2.20) ** | 57.1 | <0.001 | Ref |
| Family history and H. pylori positive | 4 | 4.03(2.46–6.59) ** | 0.0 | 0.517 | 0.015 |
The“*”indicate statistically significant levels: **P≤0.001.
RR: relative risk; 95%CI: 95% confidence interval; FDR: first-degree relative, H. pylori: Helicobacter pylori
The RR of GC was 2.08(95%CI=1.86–2.34) in individuals with family history of GC according to twenty-nine case-control studies and 1.83 (95%CI=1.67–2.01) according to six cohort studies. The RR of GC was 4.03 (95%CI=2.46–6.59, I2=0.0%) in subjects with both a family history and H. pylori positive compared with the uninfected subjects without a family history. Individuals with at least 2 FDRs with GC were more likely to develop GC (RR=2.81, 95% CI=1.89–3.99, I2=36.1%). The higher risk of GC is associated with a family history of GC for individuals who is younger than 60 yr old, compared with those who is older than 60 yr (RR=2.93, 95%CI=1.81–4.47, I2=0.0% compared with RR=2.20, 95%CI=1.58–3.08, I2=0.00%), but there was no statistically significant (P=0.398). The RR of GC among those with family history of GC remained statistically significant when studies were further stratified by the adjusted variables for smoking, alcohol consumption, and H. pylori infection. Meta-regression analysis found alcohol consumption (coefficient=−0.251, 95%CI=−0.443–0.059, P=0.012) was a source of heterogeneity (Table 3).
Table 3:
Meta-regression of potential moderator variables
| Factors | Single factor | Multiple factors | ||
|---|---|---|---|---|
|
| ||||
| Coefficient (95%CI) | P-value | Coefficient (95%CI) | P- value | |
| Publication Year | −0.003(−0.013,0.007) | 0.549 | – | – |
| No. of case | −0.00008(−0.00029,0.00006) | 0.205 | – | – |
| Adjusted for age | 0.843(0.639,1.112) | 0.218 | – | – |
| Adjusted for gender | 0.069(−0.241,0.426) | 0.592 | – | – |
| Adjusted for BMI | 0.013(−0.225,0.251) | 0.912 | – | – |
| Adjusted for smoking | 0.063(−0.155,0.281) | 0.559 | – | – |
| Adjusted for alcohol consumption | −0.250(−0.451, −0.050) | 0.016 | −0.251(−0.443, −0.059) | 0.012 |
| Adjusted for race | 0.259(−0.157,0.674) | 0.214 | – | – |
| Adjusted for income | 0.022(−0.283,0.327) | 0.885 | – | – |
| Adjusted for education | 0.153(−0.115,0.421) | 0.254 | – | – |
| Adjusted for H. pylori infection | 0.281(−0.083,0.644) | 0.126 | 0.301(−0.047,0.648) | 0.087 |
BMI: Body mass index; H. pylori: Helicobacter pylori; 95%CI: 95% confidence interval
Discussion
According to this systematic review, a positive family history of GC was associated with a 2-fold increased risk of GC compared to those without such family history. The RR of GC was 2.07-fold for individuals having at least 1 FDR with GC, and almost 3-fold for having sibling with GC and having at least 2 FDRs with GC. Moreover, there was 4.03-fold increased risk of GC in subjects with both family history and H. pylori infection, and it was higher than the sum of risks for each risk factor alone (13, 43). Individuals with a positive family history of GC might be at high risk groups for developing GC. We suggest H. pylori eradication should be considered for these individuals, especially those having sibling with GC.
There are many problems in detecting and eradicating H. pylori infection in the general population, such as lack of a robust study with cost-effective proof, abuse of antibiotics and antibiotic resistance of H. pylori (44), however, a recent study demonstrated that H. pylori treatment can reduce the risk of GC in individuals with a positive family history (45). Therefore, it is necessary to separate individuals with family history of GC from the general population as high-risk groups for H. pylori screening and eradication therapy. For individuals having sibling with GC and more than 2 FDRs with GC, this need is more urgent. However, the data on age of person at risk were limited in this meta-analysis, the best age of the H. pylori eradication might be determined cautiously.
To our knowledge, there was a published meta-analysis that assessed the association between risk of GC and family history of GC in FDRs. Data on relative risk for number and type of family members affected in FDRs, SDRs, TDRs and H. pylori infection were not analyzed. The individuals having FDRs with GC were about 2.5-fold more likely to develop GC (46). The relative risk was lower than the reported in this meta-analysis, especially based on cohort studies. This may be because the previous meta-analysis only included case-control study, with greater recall bias compared to the cohort study. Furthermore, we also demonstrated a 1.84-fold risk when individuals have SDRs with GC, whereas having TDRs with GC was non-significant. This may be the result of interactions between genes and environment. FDRs and SDRs may have more opportunities to share exposure to many environmental factors, such as smoking, drinking, salt intake and H. Pylori infection (47). We further estimated the pooled RR among studies that adjusted for smoking, alcohol consumption and H. pylori infection factor, and the significantly increased risk of GC and family history persisted. In addition, positive family history was strong risk factor of GC regardless of H. pylori infection (20, 21, 48). Seventeen studies adjusted for lifestyle and other potential confounding factors such as income, smoking, alcohol drinking, drinking tea, vegetable intake, and H. pyloric infection in this meta-analysis. Therefore, the observed increased risks are creditable and less likely to be affected by known confounding factors.
The reasons why the increased risk of GC conferred by individuals having sibling with GC was higher than those having parent with GC remain speculative. The higher risk with sibling history may be due to critical causal exposures are more shared between siblings from childhood to adulthood, for example, H. pylori infection general occurs in childhood (43, 49). The stronger association with paternal history of GC compared to maternal history may be due to the small sample size and need to be further studied.
Several strengths should be acknowledged. Firstly, our meta-analysis is the first study to examine the association between risk of GC and family history of GC according to the degree of affected relatives, number and type of family history exposure. Secondly, this study includes a large number of individuals from 35 studies in Western and Asian population. Thirdly, adequate subgroup analyses were performed according to various effect modifiers. Furthermore, all studies included in this meta-analysis met the inclusion criteria and were assessed by NOS scale.
There are several limitations in the meta-analysis. Firstly, as with other meta-analyses, high heterogeneity was observed. However, alcohol consumption was partially accounted for the heterogeneity. Secondly, both case-control and cohort designs included the current analysis, but case-control study was more likely to have a recall bias. Thirdly, the data on the TDR and age for the diagnosis of affected relative were limited in this meta-analysis. Because of the lacking of studies, we were unable to conduct a more detailed meta-analysis to estimate the risk of GC for subjects with both sibling history and H. pylori infection. The association between sibling history and risk of GC was stronger if subjects with H. pylori infection. Two studies have shown that GC risks were higher in individuals with relative diagnosed at a younger age (5, 50). The age of diagnosis of relatives is important to evaluate the GC risk in family history of GC. Therefore, more studies should be conducted to examine these issues.
Conclusion
This meta-analysis is likely to be of clinical relevance to inform individuals with a family history of GC that they have increased risk to develop GC, especially those having sibling with GC and more than 2 FDRs with GC. More intensified screening and eradication for H. pylori are urgently needed for these individuals. Further studies should focus on analyzing more detailed family history such as how risk estimates change when relatives are diagnosed with different ages.
Ethical considerations
Ethical issues (Including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc.) have been completely observed by the authors.
Acknowledgements
We would like to thank Yuehua Zhang, MD and Jingjing Yin, MD for the statistical advice, optimizing search strategy and critical revision of language on this manuscript. Henan Medical Science and Technique Foundation (Co-sponsored by Province and Ministry, SB201901115, LHGJ20190838), Henan Science and Technology Development Plan (202400410199). This work was funded by the National Natural Science Foundation of China (81373097) and Research Project of Henan Science and Technology Think Tanks (HNKJZK-2021-05A).
Footnotes
Conflicts of interest
The authors declare that they have no conflict of interest.
References
- 1.Ferlay J, Colombet M, Soerjomataram I, et al. (2019). Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer, 144(8):1941–53. [DOI] [PubMed] [Google Scholar]
- 2.Bray F, Ferlay J, Soerjomataram I, et al. (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 68(6):394–424. [DOI] [PubMed] [Google Scholar]
- 3.Cai Q, Zhu C, Yuan Y, et al. (2019). Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study. Gut, 68(9):1576–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Lin Y, Wu C, Yan W, et al. (2020). Sociodemographic and Lifestyle Factors in Relation to Gastric Cancer in a High-Risk Region of China: A Matched Case-Control Study. Nutr Cancer, 72(3):421–30. [DOI] [PubMed] [Google Scholar]
- 5.Song M, Camargo MC, Weinstein SJ, et al. (2018). Family history of cancer in first-degree relatives and risk of gastric cancer and its precursors in a Western population. Gastric Cancer, 21(5):729–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Gao S, Zhang X, Wang P, et al. (2011). Genetic epidemiological analysis reveals a multi-gene additive model for gastric cancer. Fam Cancer, 10(1):119–25. [DOI] [PubMed] [Google Scholar]
- 7.Duan F, Song C, Zhang J, et al. (2019). Evaluation of the Epidemiologic Efficacy of Eradicating Helicobacter pylori on Development of Gastric Cancer. Epidemiol Rev, 41(1):97–108. [DOI] [PubMed] [Google Scholar]
- 8.Liberati A, Altman DG, Tetzlaff J, et al. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ, 339:b2700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Greenland S. (1987). Quantitative methods in the review of epidemiologic literature. Epidemiol Rev, 9:1–30. [DOI] [PubMed] [Google Scholar]
- 10.McKenzie JE, Beller EM, Forbes AB. (2016). Introduction to systematic reviews and meta-analysis. Respirology, 21(4):626–37. [DOI] [PubMed] [Google Scholar]
- 11.Shen J, Xing H, Wang L. (2001). [Studies on the spatial and familial aggregation of double Y nuclear family in gastric cancer pedigree]. Chinese Journal of Preventive Medicine, 35(1):33–6. [PubMed] [Google Scholar]
- 12.Wang GP, Han XY, Ding T, et al. (2012). [Studies on the risks of cardia neoplasm among immediate relatives of the patients in Shanxi province]. Chinese Journal of Epidemiology, 33(11):1123–6. [PubMed] [Google Scholar]
- 13.Shin CM, Kim N, Yang HJ, et al. (2010). Stomach cancer risk in gastric cancer relatives: interaction between Helicobacter pylori infection and family history of gastric cancer for the risk of stomach cancer. J Clin Gastroenterol, 44(2):e34–9. [DOI] [PubMed] [Google Scholar]
- 14.Bakir T, Can G, Erkul S, et al. (2000). Stomach cancer history in the siblings of patients with gastric carcinoma. Eur J Cancer Prev, 9(6):401–8. [DOI] [PubMed] [Google Scholar]
- 15.Luo H, Mi D, Jing T, et al. (2005). [Risk factors of gastric cancer in Wuwei City---an endemic region of gastric cancer]. Chinese journal of cancer, 24(5):563–6. [PubMed] [Google Scholar]
- 16.Gong EJ, Ahn JY, Jung HY, et al. (2014). Risk factors and clinical outcomes of gastric cancer identified by screening endoscopy: a case-control study. J Gastroenterol Hepatol, 29(2):301–9. [DOI] [PubMed] [Google Scholar]
- 17.Chen MJ, Wu DC, Ko YC, et al. (2004). Personal history and family history as a predictor of gastric cardiac adenocarcinoma risk: a case-control study in Taiwan. Am J Gastroenterol, 99(7):1250–7. [DOI] [PubMed] [Google Scholar]
- 18.Behnampour N, Hajizadeh E, Zayeri F, et al. (2014). Modeling of influential predictors of gastric cancer incidence rates in Golestan province, North Iran. Asian Pac J Cancer Prev, 15(3):1111–7. [DOI] [PubMed] [Google Scholar]
- 19.Zhao J, Wu M, Kim C, et al. (2017). Jiangsu Four Cancers Study: a large case-control study of lung, liver, stomach, and esophageal cancers in Jiangsu Province, China. Eur J Cancer Prev, 26(4):357–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Yatsuya H, Toyoshima H, Tamakoshi A, et al. (2004). Individual and joint impact of family history and Helicobacter pylori infection on the risk of stomach cancer: a nested case-control study. Br J Cancer, 91(5):929–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Brenner H, Arndt V, Stürmer T, et al. (2000). Individual and joint contribution of family history and Helicobacter pylori infection to the risk of gastric carcinoma. Cancer, 88(2):274–9. [DOI] [PubMed] [Google Scholar]
- 22.Wang N, Song G, Jin G, et al. (2010). A genetic epidemiological study on esophageal and cardia cancers in Ci County of Hebei Province. Chinese Journal of Clinical Oncology, 37:970–73. [Google Scholar]
- 23.García-González MA, Lanas A, Quintero E, et al. (2007). Gastric cancer susceptibility is not linked to pro-and anti-inflammatory cytokine gene polymorphisms in whites: a Nationwide Multicenter Study in Spain. Am J Gastroenterol, 102(9):1878–92. [DOI] [PubMed] [Google Scholar]
- 24.Nagase H, Ogino K, Yoshida I, et al. (1996). Family history-related risk of gastric cancer in Japan: a hospital-based case-control study. Jpn J Cancer Res, 87(10):1025–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Song H, Ekheden I, Ploner A, et al. (2018). Family history of gastric mucosal abnormality and the risk of gastric cancer: a population-based observational study. Int J Epidemiol, 47(2):440–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Foschi R, Lucenteforte E, Bosetti C, et al. (2008). Family history of cancer and stomach cancer risk. Int J Cancer, 123(6):1429–32. [DOI] [PubMed] [Google Scholar]
- 27.Dhillon P, Farrow D, Vaughan T, et al. (2001). Family history of cancer and risk of esophageal and gastric cancers in the United States. Int J Cancer, 93(1):148–52. [DOI] [PubMed] [Google Scholar]
- 28.Hassan M, Phan A, Li D, et al. (2008). Family history of cancer and associated risk of developing neuroendocrine tumors: a case-control study. Cancer Epidemiol Biomarkers Prev, 17(4):959–65. [DOI] [PubMed] [Google Scholar]
- 29.Safaee A, Moghimi Dehkordi B, Fatemi S, et al. (2011). Family History as a Risk for Upper Gastrointestinal Tract Cancer: A Case Control Study. Iran J Cancer Prev, 4(3):114–8. [PMC free article] [PubMed] [Google Scholar]
- 30.La Vecchia C, Negri E, Franceschi S, et al. (1992). Family history and the risk of stomach and colorectal cancer. Cancer, 70(1):50–5. [DOI] [PubMed] [Google Scholar]
- 31.Lissowska J, Groves F, Sobin L, et al. (1999). Family history and risk of stomach cancer in Warsaw, Poland. Eur J Cancer Prev, 8(3):223–7. [DOI] [PubMed] [Google Scholar]
- 32.Hagy GW. (1954). A familial study of gastric carcinoma. Am J Hum Genet, 6(4):434–47. [PMC free article] [PubMed] [Google Scholar]
- 33.Zanghieri G, Di Gregorio C, Sacchetti C, et al. (1990). Familial occurrence of gastric cancer in the 2-year experience of a population-based registry. Cancer, 66(9):2047–51. [DOI] [PubMed] [Google Scholar]
- 34.Toyoshima H, Hayashi S, Hashimoto S, et al. (1997). Familial aggregation and covariation of diseases in a Japanese rural community: comparison of stomach cancer with other diseases. Ann Epidemiol, 7(7):446–51. [DOI] [PubMed] [Google Scholar]
- 35.Huang X, Tajima K, Hamajima N, et al. (1999). Effect of life styles on the risk of subsite-specific gastric cancer in those with and without family history. J Epidemiol, 9(1):40–5. [DOI] [PubMed] [Google Scholar]
- 36.Palli D, Russo A, Saieva C, et al. (2000). Dietary and familial determinants of 10-year survival among patients with gastric carcinoma. Cancer, 89(6):1205–13. [DOI] [PubMed] [Google Scholar]
- 37.Huang X, Hirose K, Wakai K, et al. (2004). Comparison of lifestyle risk factors by family history for gastric, breast, lung and colorectal cancer. Asian Pac J Cancer Prev, 5(4):419–27. [PubMed] [Google Scholar]
- 38.Ikeguchi M, Fukuda K, Oka S, et al. (2001). Clinicopathological findings in patients with gastric adenocarcinoma with familial aggregation. Dig Surg, 18(6):439–43. [DOI] [PubMed] [Google Scholar]
- 39.Ihamäki T, Sipponen P, Varis K, et al. (1991). Characteristics of gastric mucosa which precede occurrence of gastric malignancy: results of long-term follow-up of three family samples. Scand J Gastroenterol Suppl, 186:16–23. [DOI] [PubMed] [Google Scholar]
- 40.Muñoz N, Plummer M, Vivas J, et al. (2001). A case-control study of gastric cancer in Venezuela. Int J Cancer, 93(3):417–23. [DOI] [PubMed] [Google Scholar]
- 41.Palli D, Bianchi S, Decarli A, et al. (1992). A case-control study of cancers of the gastric cardia in Italy. Br J Cancer, 65(2):263–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Minami Y, Tateno HJCs. (2003). Associations between cigarette smoking and the risk of four leading cancers in Miyagi Prefecture, Japan: a multi-site case-control study. Cancer Sci, 94(6):540–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Group HaCC (2001). Gastric cancer and Helicobacter pylori: a combined analysis of 12 case control studies nested within prospective cohorts. Gut, 49(3):347–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Sung JJY. (2020). Population-based screening and mass eradication of Helicobacter pylori infection to prevent gastric cancer: There are more questions than answers. J Gastroenterol Hepatol, 35(4):521–2. [DOI] [PubMed] [Google Scholar]
- 45.Choi IJ, Kim CG, Lee JY, et al. (2020). Helicobacter pylori Family History of Gastric Cancer and Treatment. N Engl J Med, 382(5):427–36. [DOI] [PubMed] [Google Scholar]
- 46.Yaghoobi M, McNabb-Baltar J, Bijarchi R, et al. (2017). What is the quantitative risk of gastric cancer in the first-degree relatives of patients? A meta-analysis. World J Gastroenterol, 23(13):2435–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Kim N. (2019). Chemoprevention of gastric cancer by Helicobacter pylori eradication and its underlying mechanism. J Gastroenterol Hepatol, 34(8):1287–95. [DOI] [PubMed] [Google Scholar]
- 48.Li H, Zang J, Wang P, et al. (2012). Gastric cancer susceptibility in gastric cancer relatives: attributable risks of Macrophage migration inhibitory factor promoter polymorphism and Helicobacter pylori. Cytokine, 60(2):346–51. [DOI] [PubMed] [Google Scholar]
- 49.Weyermann M, Rothenbacher D, Brenner H. (2009). Acquisition of Helicobacter pylori infection in early childhood: independent contributions of infected mothers, fathers, and siblings. Am J Gastroenterol, 104(1):182–9. [DOI] [PubMed] [Google Scholar]
- 50.Imsland AK, Eldon BJ, Arinbjarnarson S, et al. (2002). Genetic epidemiologic aspects of gastric cancer in Iceland. J Am Coll Surg, 195(2):181–6; discussion 6–7. [DOI] [PubMed] [Google Scholar]