Nasopharyngeal cancer mortality in disaggregated Asian and non-Asian Americans.

BACKGROUND: Nasopharyngeal carcinoma (NPC) mortality varies based on multiple risk factors. While NPC mortality is higher in Asia, little is known about Asian subgroups in the United States (US). METHODS: Using the 2005-2020 National Vital Statistics System, we examined NPC mortality by age, race (non-Hispanic black, Hispanic white (HW), non-Hispanic white (NHW), Chinese, Filipino, Asian Indian, Japanese, Korean, Vietnamese), sex, and nativity (Untied States or foreign-born). RESULTS: Upon disaggregation, Chinese (1.96 [CI: 1.78-2.16]), Filipino (0.68 [0.68-1.11]), and Vietnamese Americans (0.68 [0.52-1.10]) had the top age-adjusted mortality rates (AAMR per 100 000 person-years). Foreign-born Chinese, Vietnamese, Filipinos, Asian Indians, and NHW had higher AAMRs compared to US-born persons. All male groups had higher AAMR compared to females. Stratifying for race, nativity, and sex, foreign-born Chinese males (4.09 [3.79-4.40]) had the highest AAMR. CONCLUSION: These findings demonstrate the importance of disaggregating NPC mortality data by Asian subgroups, providing valuable insights for targeted public health interventions in the United States.

Leading causes of death in Vietnamese Americans: An ecological study based on national death records from 2005-2020.

BACKGROUND: Disaggregated data is a cornerstone of precision health. Vietnamese Americans (VietAms) are the fourth-largest Asian subgroup in the United States (US), and demonstrate a unique burden of disease and mortality. However, most prior studies have aggregated VietAms under the broader Asian American category for analytic purposes. This study examined the leading causes of death among VietAms compared to aggregated Asian Americans and non-Hispanic Whites (NHWs) during the period 2005-2020. METHODS: Decedent data, including underlying cause of death, were obtained from the National Center for Health Statistics national mortality file from 2005 to 2020. Population denominator estimates were obtained from the American Community Survey one-year population estimates. Outcome measures included proportional mortality, age-adjusted mortality rates per 100,000 (AMR), and annual percent change (APC) in mortality over time. Data were stratified by sex and nativity status. Due to large differences in age structure, we report native- and foreign-born VietAms separately. FINDINGS: We identified 74,524 VietAm decedents over the study period (71,305 foreign-born, 3,219 native-born). Among foreign-born VietAms, the three leading causes of death were cancer (26.6%), heart disease (18.0%), and cerebrovascular disease (9.0%). Among native-born VietAms the three leading causes were accidents (19.0%), self-harm (12.0%), and cancer (10.4%). For every leading cause of death, VietAms exhibited lower mortality compared to both aggregated Asians and NHWs. Over the course of the study period, VietAms witnessed an increase in mortality in every leading cause. This effect was mostly driven by foreign-born, male VietAms. CONCLUSIONS AND RELEVANCE: While VietAms have lower overall mortality from leading causes of death compared to aggregated Asians and NHWs, these advantages have eroded markedly between 2005 and 2020. These data emphasize the importance of racial disaggregation in the reporting of public health measures.

Prevalence of Gastric Precursor Lesions in Countries With Differential Gastric Cancer Burden: A Systematic Review and Meta-analysis.

BACKGROUND & AIMS: The prevalence of precursor lesions for gastric cancer (GC) and the differential burden between countries of varying GC risk is not well-understood. We conducted a systematic review and meta-analysis to estimate the global prevalence of precursor lesions. METHODS: We estimated the prevalence of atrophic gastritis (AG), gastric intestinal metaplasia (IM), and dysplasia in regions with low, medium, and high GC incidence. Because IM is an advanced manifestation of AG, we assessed the prevalence of less advanced precursors, regardless of the presence of more advanced lesions. Prevalence was sub-stratified by Helicobacter pylori infection, symptomatology, and period (<2000, 2000-2010, and >2010). RESULTS: Among the 582 articles that underwent full-text review, 166 studies met inclusion criteria. The global prevalence estimates of AG, IM, and dysplasia were 25.4%, 16.2%, and 2.0%, respectively, on the basis of 126 studies that reported the prevalence of less advanced precursors, regardless of the presence of more advanced lesions. The prevalence of all precursor lesions was higher in high and medium compared with low GC incidence countries (P < .01). Prevalence of AG and IM was significantly higher among H pylori-infected individuals (P < .01) but not statistically different between symptomatic and asymptomatic individuals (P > .17). All precursors demonstrated a secular decrease in prevalence over time. CONCLUSIONS: Gastric precursor lesions have differences in prevalence in regions with differential GC incidence and are associated with H pylori infection. Because of the substantial prevalence of precursor lesions in both symptomatic and asymptomatic individuals, symptomatic evaluation may not be sufficient to identify individuals at risk. These estimates provide important insights for tailoring GC prevention strategies.

Risk of Gastric Adenocarcinoma in a Multiethnic Population Undergoing Routine Care: An Electronic Health Records Cohort Study.

BACKGROUND: Gastric adenocarcinoma (GAC) is often diagnosed at advanced stages and portends a poor prognosis. We hypothesized that electronic health records (EHR) could be leveraged to identify individuals at highest risk for GAC from the population seeking routine care. METHODS: This was a retrospective cohort study, with endpoint of GAC incidence as ascertained through linkage to an institutional tumor registry. We utilized 2010 to 2020 data from the Palo Alto Medical Foundation, a large multispecialty practice serving Northern California. The analytic cohort comprised individuals ages 40-75 receiving regular ambulatory care. Variables collected included demographic, medical, pharmaceutical, social, and familial data. Electronic phenotyping was based on rule-based methods. RESULTS: The cohort comprised 316,044 individuals and approximately 2 million person-years (p-y) of observation. 157 incident GACs occurred (incidence 7.9 per 100,000 p-y), of which 102 were non-cardia GACs (incidence 5.1 per 100,000 p-y). In multivariable analysis, male sex [HR: 2.2, 95% confidence interval (CI): 1.6-3.1], older age, Asian race (HR: 2.5, 95% CI: 1.7-3.7), Hispanic ethnicity (HR: 1.9, 95% CI: 1.1-3.3), atrophic gastritis (HR: 4.6, 95% CI: 2.2-9.3), and anemia (HR: 1.9, 95% CI: 1.3-2.6) were associated with GAC risk; use of NSAID was inversely associated (HR: 0.3, 95% CI: 0.2-0.5). Older age, Asian race, Hispanic ethnicity, atrophic gastritis, and anemia were associated with non-cardia GAC. CONCLUSIONS: Routine EHR data can stratify the general population for GAC risk. IMPACT: Such methods may help triage populations for targeted screening efforts, such as upper endoscopy.

A spatially mapped gene expression signature for intestinal stem-like cells identifies high-risk precursors of gastric cancer.

Objective: Gastric intestinal metaplasia (GIM) is a precancerous lesion that increases gastric cancer (GC) risk. The Operative Link on GIM (OLGIM) is a combined clinical-histopathologic system to risk-stratify patients with GIM. The identification of molecular biomarkers that are indicators for advanced OLGIM lesions may improve cancer prevention efforts. Methods: This study was based on clinical and genomic data from four cohorts: 1) GAPS, a GIM cohort with detailed OLGIM severity scoring (N=303 samples); 2) the Cancer Genome Atlas (N=198); 3) a collation of in-house and publicly available scRNA-seq data (N=40), and 4) a spatial validation cohort (N=5) consisting of annotated histology slides of patients with either GC or advanced GIM. We used a multi-omics pipeline to identify, validate and sequentially parse a highly-refined signature of 26 genes which characterize high-risk GIM. Results: Using standard RNA-seq, we analyzed two separate, non-overlapping discovery (N=88) and validation (N=215) sets of GIM. In the discovery phase, we identified 105 upregulated genes specific for high-risk GIM (defined as OLGIM III-IV), of which 100 genes were independently confirmed in the validation set. Spatial transcriptomic profiling revealed 36 of these 100 genes to be expressed in metaplastic foci in GIM. Comparison with bulk GC sequencing data revealed 26 of these genes to be expressed in intestinal-type GC. Single-cell profiling resolved the 26-gene signature to both mature intestinal lineages (goblet cells, enterocytes) and immature intestinal lineages (stem-like cells). A subset of these genes was further validated using single-molecule multiplex fluorescence in situ hybridization. We found certain genes (TFF3 and ANPEP) to mark differentiated intestinal lineages, whereas others (OLFM4 and CPS1) localized to immature cells in the isthmic/crypt region of metaplastic glands, consistent with the findings from scRNAseq analysis. Conclusions: using an integrated multi-omics approach, we identified a novel 26-gene expression signature for high-OLGIM precursors at increased risk for GC. We found this signature localizes to aberrant intestinal stem-like cells within the metaplastic microenvironment. These findings hold important translational significance for future prevention and early detection efforts.

The association between local area immigrant fraction and prevalence of cardiovascular diseases in the United States: an observational study.

Background: Local area immigrant fraction is strongly and positively correlated with local life expectancy in the United States. The aim of the study was to determine the relationship between local area immigrant fraction and local prevalence of coronary heart disease (CHD) and stroke. Methods: Cross-sectional study design, with ZIP code as the unit of observation. Demographic data was obtained from the American Community Survey, and linked to indicators of health access (e.g., insurance, annual check-ups, cholesterol screening), obesity, behavior (smoking, exercise), and cardiovascular outcomes data from the 2020 Population Level Analysis and Community Estimates. Multivariable regression and path analyses were used to assess both direct and indirect relationships among variables. Findings: CHD prevalence was lower in the second (3.9% relative difference, 95% CI: 3.1-4.5%), third (6.5%, 95% CI: 5.8-7.1%), and fourth (14.8%, 95% CI: 14.1-15.8%) quartiles of immigrant fraction compared to the lowest (p-trend <0.001). These effects remained robust in multivariable analysis following adjustment for indicators of access, obesity, and behavioral variables (p-trend <0.0001). For stroke, only the highest quartile demonstrated a significant difference in prevalence (2.1%, 95% CI: 1.2-3.0% with full adjustment). In CHD path analysis, ∼45% of the association of immigrant fraction was direct, and ∼55% was mediated through lower prevalence of deleterious behaviors (e.g., smoking). In stroke path analysis, the effect was entirely mediated through indirect effects. Interpretation: In the United States, ZIP codes with higher immigrant fractions have lower prevalence of cardiovascular diseases. These associations are partially mediated through differences in health behaviors at the community level. Funding: NIH (K08CA252635, P30AG0059304, K24HL150476), Stanford University, Rutgers University.

Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks.

MOTIVATION: Providing a dynamic assessment of prognosis is essential for improved personalized medicine. The landmark model for survival data provides a potentially powerful solution to the dynamic prediction of disease progression. However, a general framework and a flexible implementation of the model that incorporates various outcomes, such as competing events, have been lacking. We present an R package, dynamicLM, a user-friendly tool for the landmark model for the dynamic prediction of survival data under competing risks, which includes various functions for data preparation, model development, prediction and evaluation of predictive performance. IMPLEMENTATION: dynamicLM as an R package. GENERAL FEATURES: The package includes options for incorporating time-varying covariates, capturing time-dependent effects of predictors and fitting a cause-specific landmark model for time-to-event data with or without competing risks. Tools for evaluating the prediction performance include time-dependent area under the ROC curve, Brier Score and calibration. AVAILABILITY: Available on GitHub [https://github.com/thehanlab/dynamicLM].

Controlling Gastric Cancer in a World of Heterogeneous Risk.

Gastric cancer (GC) is a leading cause of global mortality but also a cancer whose footprint is highly unequal. This review aims to define global disease epidemiology, critically appraise strategies of prevention and disease attenuation, and assess how these strategies could be applied to improve outcomes from GC in a world of variable risk and disease burden. Strategies of primary prevention focus on improving the detection and eradication of the main environmental risk factor, Helicobacter pylori. In certain countries of high incidence, endoscopic or radiographic screening of the asymptomatic general population has been adopted as a means of secondary prevention. By contrast, identification and targeted surveillance of individuals with precancerous lesions (such as intestinal metaplasia) is being increasingly embraced in nations of low incidence. This review also highlights existing knowledge gaps in GC prevention as well as the role of emerging technologies for early detection and risk stratification.

Low rates of structured advance care planning documentation in electronic health records: results of a single-center observational study.

BACKGROUND: Proper advance care planning (ACP) documentation both improves patient care and is increasingly seen as a marker of high quality by governmental payers. The transition of most medical documentation to electronic health records (EHR) allows for ACP documents to be rapidly disseminated across diverse ambulatory practice settings. At the same time, the complexity and heterogeneity of the EHR, as well as the multiple potential storage locations for documentation, may lead to confusion and inaccessibility. There has been movement to promote structured ACP (S-ACP) documentation within the EHR. METHODS: We performed a retrospective cohort study at a single, large university medical center in California to analyze rates of S-ACP documentation. S-ACP was defined as ACP documentation contained in standardized locations, auditable, and not in free-text format. The analytic cohort composed of all patients 65 and older with at least one ambulatory encounter at Stanford Health Care between 2012 and 2020, and without concurrent hospice care. We then analyzed clinic-level, provider-level, insurance, and temporal factors associated with S-ACP documentation rate. RESULTS: Of 187,316 unique outpatient encounters between 2012 and 2020, only 7,902 (4.2%) contained S-ACP documentation in the EHR. The most common methods of S-ACP documentation were through problem list diagnoses (3,802; 40.3%) and scanned documents (3,791; 40.0%). At the clinic level, marked variability in S-ACP documentation was observed, with Senior Care (46.6%) and Palliative Care (25.0%) demonstrating highest rates. There was a temporal trend toward increased S-ACP documentation rate (p < 0.001). CONCLUSION: This retrospective, single-center study reveals a low rate of S-ACP documentation irrespective of clinic and specialty. While S-ACP documentation rate should not be construed as a proxy for ACP documentation rate, it nonetheless serves as an important quality metric which may be reported to payers. This study highlights the need to both centralize and standardize reporting of ACP documentation in complex EHR systems.

Leading causes of death in Asian Indians in the United States (2005-2017).

OBJECTIVE: Asian Indians are among the fastest growing United States (US) ethnic subgroups. We characterized mortality trends for leading causes of death among foreign-born and US-born Asian Indians in the US between 2005-2017. STUDY DESIGN AND SETTING: Using US standardized death certificate data, we examined leading causes of death in 73,470 Asian Indians and 20,496,189 non-Hispanic whites (NHWs) across age, gender, and nativity. For each cause, we report age-standardized mortality rates (AMR), longitudinal trends, and absolute percent change (APC). RESULTS: We found that Asian Indians' leading causes of death were heart disease (28% mortality males; 24% females) and cancer (18% males; 22% females). Foreign-born Asian Indians had higher all-cause AMR compared to US-born (AMR 271 foreign-born, CI 263-280; 175.8 US-born, CI 140-221; p<0.05), while Asian Indian all-cause AMR was lower than that of NHWs (AMR 271 Indian, CI 263-278; 754.4 NHW, CI 753.3-755.5; p<0.05). All-cause AMR increased for foreign-born Asian Indians over time, while decreasing for US-born Asian Indians and NHWs. CONCLUSIONS: Foreign-born Asian Indians were 2.2 times more likely to die of heart disease and 1.6 times more likely to die of cancer. Asian Indian male AMR was 49% greater than female on average, although AMR was consistently lower for Asian Indians when compared to NHWs.

Catching Up with the World: Pepsinogen Screening for Gastric Cancer in the United States.

Gastric cancer remains a deadly cancer with poor outcomes in the United States. There is a need for screening strategies for gastric cancer in the U.S. population. With progressive Helicobacter pylori-mediated inflammation of the gastric mucosa, pepsinogen I levels decrease and the pepsinogen I/II ratio decreases. Pepsinogen test positivity (PG+) has been evaluated as a promising screening test among Asian and European populations; however, its utility in multiethnic U.S. populations is poorly described. In this case-control study nested within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, In and colleagues evaluate the discrimination of PG+ in serum collected from individuals prior to the development of gastric cancer. The authors find that PG+ individuals were at nearly 10-fold increased risk for developing gastric cancer, and this effect remained robust after adjusting for Helicobacter pylori status, family history, education, smoking, and obesity. In subgroup analysis, the predictive ability of the test was particularly robust for noncardia gastric cancers, and nonpredictive of cardia gastric cancers. Serum pepsinogen testing holds promise as a noninvasive screening strategy to triage individuals at heightened risk for gastric cancer, and may help to improve early diagnosis in the United States. See related article by In et al., p. 1426.

The Gastric Cancer Registry: A Genomic Translational Resource for Multidisciplinary Research in Gastric Cancer.

BACKGROUND: Gastric cancer is a leading cause of cancer morbidity and mortality. Developing information systems which integrate clinical and genomic data may accelerate discoveries to improve cancer prevention, detection, and treatment. To support translational research in gastric cancer, we developed the Gastric Cancer Registry (GCR), a North American repository of clinical and cancer genomics data. METHODS: Participants self-enrolled online. Entry criteria into the GCR included the following: (i) diagnosis of gastric cancer, (ii) history of gastric cancer in a first- or second-degree relative, or (iii) known germline mutation in the gene CDH1. Participants provided demographic and clinical information through a detailed survey. Some participants provided specimens of saliva and tumor samples. Tumor samples underwent exome sequencing, whole-genome sequencing, and transcriptome sequencing. RESULTS: From 2011 to 2021, 567 individuals registered and returned the clinical questionnaire. For this cohort 65% had a personal history of gastric cancer, 36% reported a family history of gastric cancer, and 14% had a germline CDH1 mutation. 89 patients with gastric cancer provided tumor samples. For the initial study, 41 tumors were sequenced using next-generation sequencing. The data was analyzed for cancer mutations, copy-number variations, gene expression, microbiome, neoantigens, immune infiltrates, and other features. We developed a searchable, web-based interface (the GCR Genome Explorer) to enable researchers' access to these datasets. CONCLUSIONS: The GCR is a unique, North American gastric cancer registry which integrates clinical and genomic annotation. IMPACT: Available for researchers through an open access, web-based explorer, the GCR Genome Explorer will accelerate collaborative gastric cancer research across the United States and world.

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams.

PURPOSE: Noncardia gastric cancer (NCGC) is a leading cause of global cancer mortality, and is often diagnosed at advanced stages. Development of NCGC risk models within electronic health records (EHR) may allow for improved cancer prevention. There has been much recent interest in use of machine learning (ML) for cancer prediction, but few studies comparing ML with classical statistical models for NCGC risk prediction. METHODS: We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of Washington (UW). The LR model contained well-established NCGC risk factors (intestinal metaplasia histology, prior Helicobacter pylori infection, race, ethnicity, nativity status, smoking history, anemia), whereas ML models agnostically selected variables from the EHR. Models were developed and internally validated in the Stanford data, and externally validated in the UW data. Hyperparameter tuning of models was achieved using cross-validation. Model performance was compared by accuracy, sensitivity, and specificity. RESULTS: In internal validation, LR performed with comparable accuracy (0.732; 95% CI, 0.698 to 0.764), sensitivity (0.697; 95% CI, 0.647 to 0.744), and specificity (0.767; 95% CI, 0.720 to 0.809) to penalized lasso, support vector machine, K-nearest neighbor, and random forest models. In external validation, LR continued to demonstrate high accuracy, sensitivity, and specificity. Although K-nearest neighbor demonstrated higher accuracy and specificity, this was offset by significantly lower sensitivity. No ML model consistently outperformed LR across evaluation criteria. CONCLUSION: Drawing data from two independent EHRs, we find LR on the basis of established risk factors demonstrated comparable performance to optimized ML algorithms. This study demonstrates that classical models built on robust, hand-chosen predictor variables may not be inferior to data-driven models for NCGC risk prediction.

ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo.

To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue's cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN's scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown.

The risk of diffuse-type gastric cancer following diagnosis with gastric precancerous lesions: a systematic review and meta-analysis.

PURPOSE: Gastric cancers are classified as diffuse-type (DTGC) or intestinal-type (ITGC). DTGCs have distinct clinical and histopathologic features, and carry a worse overall prognosis compared to ITGCs. Atrophic gastritis (AG) and intestinal metaplasia (IM) are known precursors to ITGC. It is unknown if AG and IM increase risk for DTGC. METHODS: We performed a systematic review to identify studies reporting on the association of AG/IM and DTGC. We extracted the odds ratio (OR) of the association from studies, and performed pool analysis. Subgroup analysis was performed on studies reporting histologic severity (using operative link systems) to assess if histologic severity of AG/IM was associated with higher risk. RESULTS: We identified six case-control and eight cohort studies for inclusion. Both AG (pooled OR = 1.9, 95% CI 1.5 to 2.4, p < 0.001) and IM (pooled OR = 2.3, 95% CI 1.9 to 2.9, p < 0.001) demonstrated an association with DTGC. High AG severity was associated with increased risk for DTGC compared to low AG severity (OR = 1.7, 95% CI 1.2 to 2.3, p = 0.002). Similarly, high IM severity was associated with increased risk compared to low IM severity (OR = 1.9, 95% CI 1.3 to 2.7, p = 0.001). CONCLUSION: Both AG and IM are associated with DTGC. Increasing histologic severity of both AG and IM increases risk for DTGC. There may exist a common pathway between ITGC and some DTGCs mediated through mucosal precursor lesions. These data may inform future strategies of cancer risk attenuation and control.

Pepsinogens and Gastrin Demonstrate Low Discrimination for Gastric Precancerous Lesions in a Multi-Ethnic United States Cohort.

Early identification of gastric precancerous lesions, including atrophic gastritis (AG) and intestinal metaplasia (IM), may improve gastric cancer detection and prevention. Because AG and IM are generally asymptomatic, many of the estimated 15 million Americans who carry these lesions remain undiagnosed.1 AG and IM are associated with either active or prior Helicobacter pylori (Hp) infection. Hp infection leads to perturbations in the serum concentration of gastric hormones pepsinogen I (PGI), pepsinogen II, the pepsinogen I/II ratio (PGR), gastrin-17 (G-17), and Hp IgG.2,3 In East Asia and other regions with high burden of Hp infection and gastric cancer, these biomarkers have been used as screening tools for AG and IM.4 However, there exists limited data on the sensitivity and discrimination of these serologic markers in low-Hp-prevalence populations, such as the United States.

An Approach to the Primary and Secondary Prevention of Gastric Cancer in the United States.

BACKGROUND & AIMS: Gastric cancer (GC) remains a leading cause of mortality among certain racial, ethnic, and immigrant groups in the United States (US). The majority of GCs are diagnosed at advanced stages, and overall survival remains poor. There exist no structured national strategies for GC prevention in the US. METHODS: On March 5-6, 2020 a summit of researchers, policy makers, public funders, and advocacy leaders was convened at Stanford University to address this critical healthcare disparity. After this summit, a writing group was formed to critically evaluate the effectiveness, potential benefits, and potential harms of methods of primary and secondary prevention through structured literature review. This article represents a consensus statement prepared by the writing group. RESULTS: The burden of GC is highly inequitably distributed in the US and disproportionately falls on Asian, African American, Hispanic, and American Indian/Alaskan Native populations. In randomized controlled trials, strategies of Helicobacter pylori testing and treatment have been demonstrated to reduce GC-specific mortality. In well-conducted observational and ecologic studies, strategies of endoscopic screening have been associated with reduced GC-specific mortality. Notably however, all randomized controlled trial data (for primary prevention) and the majority of observational data (for secondary prevention) are derived from non-US sources. CONCLUSIONS: There exist substantial, high-quality data supporting GC prevention derived from international studies. There is an urgent need for cancer prevention trials focused on high-risk immigrant and minority populations in the US. The authors offer recommendations on how strategies of primary and secondary prevention can be applied to the heterogeneous US population.

Improving the Early Diagnosis of Gastric Cancer.

Gastric cancer (GC) remains a leading cause of cancer morbidity and mortality worldwide. Outcomes from GC remain poor, especially in Western nations where cancer diagnosis is usually at advanced stages where curative resection is not possible. By contrast, nations of East Asia have adopted methods of population-level screening with improvements in stage of diagnosis and survival. In this review, the authors discuss the epidemiology of GC in Western populations, highlight at-risk populations who may benefit from screening, overview screening modalities, and discuss promising approaches to early GC detection.