Skip to main content
Cancers logoLink to Cancers
. 2022 Jul 26;14(15):3633. doi: 10.3390/cancers14153633

Variation in Treatment Patterns of Patients with Early-Onset Gastric Cancer

Michael LaPelusa 1,*,, Chan Shen 2,3,, Erin A Gillaspie 4, Christopher Cann 5, Eric Lambright 4, A Bapsi Chakravarthy 6, Michael K Gibson 5, Cathy Eng 5
Editors: Irit Ben Aharon, Savio George Barreto
PMCID: PMC9332417  PMID: 35892891

Abstract

Simple Summary

Gastric cancer is not routinely diagnosed in patients younger than 45. However, the incidence of gastric cancer in young patients is rising. Little is known about the demographic features of young patients diagnosed with gastric cancer. Additionally, the relationship between the therapies these patients receive and their socioeconomic characteristics has not been delineated. We showed that younger patients were more likely to be female, Asian/Pacific Islander, African American, Hispanic, and have advanced-stage disease compared to older patients with gastric cancer. After adjusting for disease stage, we identified differences in receipt of surgery, chemotherapy, and radiation among young patients with gastric cancer based on gender/sex, race/ethnicity, treatment center type, insurance status, and location of residence. Future work should focus on understanding whether these differences were driven by patient choice or alternative reasons.

Abstract

Background: Early-onset gastric cancer (EOGC), or gastric cancer in patients younger than 45 years old, is poorly understood and relatively uncommon. Similar to other gastrointestinal malignancies, the incidence of EOGC is rising in Western countries. It is unclear which populations experience a disproportionate burden of EOGC and what factors influence how patients with EOGC are treated. Methods: We conducted a retrospective, population-based study of patients diagnosed with gastric cancer from 2004 to 2018 using the National Cancer Database (NCDB). In addition to identifying unique demographic characteristics of patients with EOGC, we evaluated (using multivariable logistic regression controlling for year of diagnoses, primary site, and stage) how gender/sex, race/ethnicity, treatment facility type, payor status, and location of residence influenced the receipt of surgery, chemotherapy, and radiation. Results: Compared to patients 45–70 and >70 years of age with gastric cancer, patients with EOGC were more likely to be female, Asian/Pacific Islander (PI), African American (AA), Hispanic, uninsured, and present with stage IV disease. On multivariable analysis, several differences among subsets of patients with EOGC were identified. Female patients with EOGC were less likely to receive surgery and chemotherapy than male patients with EOGC. Asian/Pacific Islander patients with EOGC were more likely to receive chemotherapy and less likely to receive radiation than Caucasian patients with EOGC. African American patients were more likely to receive chemotherapy than Caucasian patients with EOGC. Hispanic patients were more likely to receive surgery and chemotherapy and less likely to receive radiation than Caucasian patients with EOGC. Patients with EOGC treated at community cancer centers were more likely to receive surgery and less likely to receive chemotherapy than patients with EOGC treated at academic centers. Uninsured patients with EOGC were more likely to receive surgery and less likely to receive chemotherapy than privately insured patients with EOGC. Patients with EOGC living in locations not adjacent to metropolitan areas were less likely to receive surgery compared to patients with EOGC who resided in metropolitan areas, Conclusions: Patients with EOGC are a demographically distinct population. Treatment of these patients varies significantly based on several demographic factors. Additional analysis is needed to elucidate why particular groups are more affected by EOGC and how treatment decisions are made for, and by, these patients.

Keywords: gastric cancer, early-onset, NCDB, incidence, treatment

1. Introduction

Globally, gastric cancer is a significant public health issue. In 2020, there were over one million new cases and 769,000 deaths, making it the fifth most common cancer and fourth most common cause of cancer-related death [1]. In the United States (US), there are projected to be 26,380 new cases of gastric cancer and 11,090 cancer-related deaths in 2022 [2].

Early-onset gastric cancer (EOGC) is a relatively uncommon phenomenon. One estimate concluded that anywhere between 10–30% of gastric cancer occurs in young patients [3]. However, similarly to several other early-onset gastrointestinal malignancies, the incidence of EOGC is increasing in Western countries [4,5,6,7,8,9].

Relative to older patients with gastric cancer, less data exist regarding the demographic makeup of young patients with gastric cancer. Additionally, the impact of socioeconomic factors on treatment patterns in this population is unknown. Our primary objective was to delineate how gender/sex, race/ethnicity, treatment center type, insurance status, and residence location contribute to the treatment of patients with EOGC.

2. Methods

2.1. Data Source

This large observational study utilized the National Cancer Database (NCDB) 2004–2018 data set. The NCDB is a national collaboration sponsored by the American Cancer Society and the American College of Surgeons. The NCDB captures approximately 70% of all new cancer diagnoses in the US and is widely accepted as a data source for cancer outcomes research [10]. Data on cancer patients were collected by Commission on Cancer accredited facilities.

2.2. Study Cohort Selection

We identified patients 18 to 90 years old who were diagnosed with gastric cancer from the NCDB 2004–2018 data set. Age cutoffs among population-based analyses of EOGC vary, ranging from 30 to 60 years old [9,11,12]. Given the heterogeneity in definitions of “early-onset”, we chose a cutoff of <45 years old. We stratified the sample into three age groups: <45 (EOGC), 45–70 (AOGC), and >70 years of age (LOGC).

2.3. Factors Considered

We considered the following patient demographics and characteristics: age, sex, race/ethnicity (non-Hispanic White hereto referred to as Caucasian, non-Hispanic Black hereto referred to as African American, Hispanic, Asian or Pacific Islander, and unknown), insurance status (uninsured, Medicaid, Medicare, other government, private, unknown), facility type (academic, comprehensive community, and community), location of residence (not metropolitan adjacent, metropolitan adjacent, metropolitan, unknown), and year of diagnosis. We also included the following tumor characteristics: disease stage (stage I, II, III, IV, unknown), tumor location (cardia, non-cardia), and histologic grade (well-differentiated, moderately-differentiated, poorly-differentiated, unknown) in our analysis. We examined the use of surgery, chemotherapy, or radiation individually since data were not available on receipt of bimodal or trimodal therapy.

2.4. Statistical Analysis

We used chi-square tests to examine whether the categorical variables (sex, race/ethnicity, facility type, year of diagnosis, primary payer, location of residence, primary site, stage, use of surgery, chemotherapy and radiation) varied significantly by age groups (EOGC, AOGC, LOGC). When evaluating the effect of specific demographic variables on treatment modality, the multivariable logistic regression models were always adjusted for year of diagnosis, primary site, and stage of cancer. We provide adjusted Odds Ratios (aOR) and 95% Confidence Interval (95% CI). p ≤ 0.05 was considered statistically significant. Analyses were conducted using SAS software, version 9.4 (SAS Institute, Inc., Cary, CA, USA).

3. Results

233,772 patients were identified from the NCDB between 2004 and 2018. Overall, 114,469 (49%) patients received surgery, 113,053 (48.4%) patients received chemotherapy, and 55,092 (23.6%) patients received radiation therapy.

As displayed in Table 1, females represented a higher proportion of patients with EOGC compared to patients with AOGC and LOGC. A greater percentage of patients with EOGC were Asian/Pacific Islander (PI), African American (AA), and Hispanic relative to patients with AOGC and LOGC. Patients with EOGC demonstrated a higher uninsurance rate than patients with AOGC and LOGC. Patients with EOGC presented with stage IV disease more frequently than patients with AOGC and LOGC.

Table 1.

Demographics.

Age Categories
EOGC
(n = 14,490)
AOGC
(n = 118,918)
LOGC
(n = 100,364)
Total
(n = 233,772)
p-Value
Age at Diagnosis
Mean (SD) 37.5 (5.80) 60.0 (6.92) 79.4 (5.73) 66.9 (13.63)
Median 39.0 61.0 79.0 68.0
Range 18.0, 44.0 45.0, 70.0 71.0, 90.0 18.0, 90.0
Sex, n (%) <0.0001
Male 7687
(53.1%)
77,902
(65.5%)
59,243
(59.0%)
144,832
(62.0%)
Female 6803
(46.9%)
41,016
(34.5%)
41,121
(41.0%)
88,940
(38.0%)
Race/Ethnicity, n (%) <0.0001
Hispanic 3600
(24.8%)
12,392
(10.4%)
7107(7.1%) 23,099
(9.9%)
White non-Hispanic 6351
(43.8%)
73,150
(61.5%)
68,427
(68.2%)
147,928
(63.3%)
Black non-Hispanic 2398
(16.5%)
18,846
(15.8%)
12,537(12.5%) 33,781
(14.5%)
Asian/PI non-Hispanic 1326
(9.2%)
7907
(6.6%)
6247
(6.2%)
15,480
(6.6%)
Unknown 815
(5.6%)
6623
(5.6%)
6046
(6.0%)
13,484
(5.8%)
Facility Type, n (%) <0.0001
Community Cancer Program 789
(5.4%)
7404
(6.2%)
7690
(7.7%)
15,883
(6.8%)
Comprehensive Community Cancer Program 4169
(28.8%)
39,110
(32.9%)
38,085
(37.9%)
81,364
(34.8%)
Academic/Research Program or Integrated Network Cancer Program 9532
(65.8%)
72,404
(60.9%)
54,589
(54.4%)
136,525
(58.4%)
Year of Diagnosis, n (%) <0.0001
2004–2008 4210
(29.1%)
31,212
(26.2%)
30,092
(30.0%)
65,514
(28.0%)
2009–2013 4783
(33.0%)
40,425
(34.0%)
33,425(33.3%) 78,633
(33.6%)
2014–2018 5497
(37.9%)
47,281
(39.8%)
36,847
(36.7%)
89,625
(38.3%)
Primary Payer, n (%) <0.0001
Not Insured 1695
(11.7%)
6448
(5.4%)
877
(0.9%)
9020
(3.9%)
Private Insurance 8560
(59.1%)
56,628
(47.6%)
9716
(9.7%)
74,904
(32.0%)
Medicaid 2961
(20.4%)
12,048
(10.1%)
2369
(2.4%)
17,378
(7.4%)
Medicare 613
(4.2%)
38,902
(32.7%)
84,847(84.5%) 124,362
(53.2%)
Other Government 184
(1.3%)
1969
(1.7%)
802
(0.8%)
2955
(1.3%)
Insurance Status Unknown 477
(3.3%)
2923
(2.5%)
1753
(1.7%)
5153
(2.2%)
Location of residence, n (%) <0.0001
Metro counties 12,494
(86.2%)
99,026
(83.3%)
84,832
(84.5%)
196,352
(84.0%)
Adjacent to metro area 1028
(7.1%)
11,057
(9.3%)
8749
(8.7%)
20,834
(8.9%)
Not adjacent to metro area 475
(3.3%)
4934
(4.1%)
3928
(3.9%)
9337
(4.0%)
Unknown 493
(3.4%)
3901(3.3%) 2855
(2.8%)
7249
(3.1%)
Primary Site, n (%) <0.0001
Cardia, NOS 3420
(23.6%)
44,808
(37.7%)
31,090
(31.0%)
79,318
(33.9%)
Non Cardia 11,070
(76.4%)
74,110
(62.3%)
69,274
(69.0%)
154,454
(66.1%)
Stage, n (%) <0.0001
Stage I 2341
(16.2%)
24,156
(20.3%)
22,923(22.8%) 49,420
(21.1%)
Stage II 1450
(10.0%)
15,814
(13.3%)
13,288
(13.2%)
30,552
(13.1%)
Stage III 2306
(15.9%)
21,550
(18.1%)
14,733
(14.7%)
38,589
(16.5%)
Stage IV 6229
(43.0%)
40,375
(34.0%)
27,258
(27.2%)
73,862
(31.6%)
Unknown 2164
(14.9%)
17,023
(14.3%)
22,162
(22.1%)
41,349
(17.7%)
Surgery, n (%) <0.0001
No surgery 7149
(49.3%)
54,716
(46.0%)
56,289
(56.1%)
118,154
(50.5%)
Surgery 7290
(50.3%)
63,596
(53.5%)
43,583
(43.4%)
114,469
(49.0%)
Unknown 51
(0.4%)
606
(0.5%)
492
(0.5%)
1149
(0.5%)
Chemotherapy, n (%) <0.0001
No chemotherapy 4831
(33.3%)
46,103
(38.8%)
62,392
(62.2%)
113,326
(48.5%)
Chemotherapy received 9242
(63.8%)
69,176
(58.2%)
34,635(34.5%) 113,053
(48.4%)
Unknown 417
(2.9%)
3639
(3.1%)
3337
(3.3%)
7393
(3.2%)
Radiation, n (%) <0.0001
No radiation 10,974
(75.7%)
83,467
(70.2%)
77,662
(77.4%)
172,103
(73.6%)
Radiation received 3127
(21.6%)
32,073
(27.0%)
19,892
(19.8%)
55,092
(23.6%)
Unknown 389
(2.7%)
3378
(2.8%)
2810
(2.8%)
6577
(2.8%)

As displayed in Table 2, female patients with EOGC were less likely to receive surgery and chemotherapy but more likely to receive radiation compared to male patients with EOGC. Compared to Caucasian patients, Asian/PI patients with EOGC were more likely to receive chemotherapy and less likely to receive radiation, AA patients with EOGC were more likely to receive chemotherapy, and Hispanic patients with EOGC were more likely to receive surgery and chemotherapy and less likely to receive radiation. Patients with EOGC treated at community cancer centers were more likely to receive surgery and less likely to receive chemotherapy than patients with EOGC treated at academic centers. Patients with EOGC treated at comprehensive community centers were more likely to receive surgery and less likely to receive radiation than patients with EOGC treated at academic centers. Compared to privately insured patients with EOGC, uninsured patients with EOGC were more likely to receive surgery and less likely to receive chemotherapy. Patients with EOGC who had Medicaid were more likely to receive surgery than privately insured patients. Patients with EOGC who resided in locations not adjacent to metropolitan areas were less likely to receive surgery than patients living in metropolitan areas.

Table 2.

Treatment patterns among patients with EOGC.

Variable Categories Odds Ratio; 95% CI; p-Value
Surgery Chemotherapy Radiation
Age (Continuous) 1.00; [0.99, 1.00]; 0.334 1.00; [0.99, 1.00]; 0.441 0.99; [0.98, 0.99]; 0.033
Gender/Sex Female 0.89; [0.81, 0.97]; 0.008 0.80; [0.74, 0.87]; <0.001 1.41; [1.29, 1.56]; <0.001
Male Reference
Race/Ethnicity Asian/PI 1.08; [0.93, 1.26]; 0.321 1.66; [1.43, 1.92]; <0.001 0.74; [0.63, 0.87]; <0.001
African American 1.07; [0.95, 1.21]; 0.274 1.21; [1.08, 1.36]; <0.001 0.94; [0.82, 1.08]; 0.385
Hispanic 1.42; [1.26, 1.59]; <0.001 1.52; [1.37, 1.69]; <0.001 0.82; [0.73, 0.93]; 0.002
Non-Hispanic White Reference
Facility Type Community 1.24; [1.02, 1.50]; 0.029 0.80; [0.67, 0.95]; 0.013 0.84; [0.69, 1.03]; 0.100
Comprehensive Community 1.15; [1.05, 1.27]; 0.003 1.02; [0.93, 1.12]; 0.662 0.78; [0.71, 0.86]; <0.001
Academic Reference
Payor Status Uninsured 1.92; [1.67, 2.22]; <0.001 0.78; [0.68, 0.88]; <0.001 1.07; [0.92, 1.25]; 0.132
Medicaid 1.69; [1.51, 1.89]; <0.001 0.90; [0.82, 1.00]; 0.061 1.01; [0.89, 1.13]; 0.906
Medicare 1.44; [1.17, 1.78]; <0.001 0.50; [0.41, 0.60]; <0.001 1.08; [0.86, 1.36]; 0.497
Other Government 1.61; [1.10, 2.35]; 0.014 0.94; [0.66, 1.36]; 0.759 0.58; [0.40, 0.85]; 0.005
Unknown 1.93; [1.49, 2.49]; <0.001 0.85; [0.67, 1.09]; 0.209 1.16; [0.88, 1.53]; 0.282
Private Reference
Location Not Metro Adjacent 0.69; [0.54, 0.89]; 0.004 1.03; [0.82, 1.30]; 0.781 1.00; [0.78, 1.29]; 0.974
Metro Adjacent 0.93; [0.79, 1.10]; 0.383 1.06; [0.91, 1.24]; 0.448 0.94; [0.79, 1.11]; 0.442
Metro Reference

Selected results are presented in this table. The multivariable logistic regression also controlled for year of diagnosis, primary site, and stage of cancer.

4. Discussion

4.1. Demographic Characteristics

Patients with EOGC display unique clinical features. We found that patients with EOGC were more likely to be female, Asian/PI, AA, Hispanic, uninsured, and present with stage IV disease versus patients with AOGC and LOGC. Our analysis was consistent with others that showed EOGC is more common in females, more likely to be diagnosed at an advanced stage and have a disproportionate effect on uninsured patients, African Americans, and Hispanic patients [13,14,15,16]. Others have shown that EOGC displays unique genomic features. For example, tumors of patients with EOGC are more likely to have a diffuse histologic subtype and include signet ring cells, more likely to contain mutated CDH1, BANP, MUC5B, and TGFBR1 genes, and less likely to contain microsatellite instability [9,17,18,19]. While smoking and alcohol use are known modifiable risk factors for the development of gastric cancer, particularly in the US, where the prevalence of Helicobacter pylori infection is relatively low, modifiable risk factors such as smoking and alcohol use were not found to be associated with the development of EOGC in an analysis of the Behavioral Risk Factor Surveillance System [9]. Some have speculated that EOGC is associated with proton pump inhibitor use via increased gastrin production and subsequent gastrin-induced carcinogenesis. However, conflicting data exist on this topic [20,21]. Others have purported there to be an association between Epstein Barr Virus and EOGC—however, these data are not consistent which may be secondary to variability between tumor samples in the Cancer Genome Atlas, Hong Kong Cancer Registry, and Asian Cancer Research Group cohorts [9,22,23,24]. Limited data exist on how patients with EOGC are treated compared to older patients. One previous analysis of SEER data showed that patients with EOGC who underwent surgery received more adjuvant radiation compared to older patients with gastric cancer [25]. Another analysis in China showed that patients with EOGC were more likely to receive chemotherapy than older patients, a finding possibly related to better performance status in younger patients [26].

4.2. Treatment by Gender/Sex

We found female patients with EOGC were less likely to receive surgery and chemotherapy but more likely to receive radiation than males with EOGC [Table 2]. Several epidemiological studies of gastric cancer treatment patterns have similarly identified an association between the receipt of less surgery and chemotherapy with female gender/sex. In an NCDB analysis of patients with stage Ib-III gastric cancer of all ages, female patients were less likely to receive perioperative chemotherapy than males [27]. Female patients of all ages that underwent surgery with curative intent in the Netherlands were also less likely than males to receive perioperative chemotherapy and were more likely to undergo partial gastrectomy (rather than total gastrectomy). However, these differences were not statistically significant after adjusting for clinicopathologic factors such as clinical stage [28]. In another Dutch study of treatment allocation, female patients with unresectable gastric cancer were less likely to receive chemotherapy compared to males [29].

4.3. Treatment by Race/Ethnicity

We found Asian/PI patients with EOGC and AOGC were more likely to receive chemotherapy than Caucasian patients with EOGC and AOGC, respectively (Table 2 and Table S1), and Asian/PI patients with EOGC, AOGC, and LOGC were less likely to receive radiation compared to Caucasian patients with EOGC, AOGC, and LOGC, respectively (Table 2 and Tables S1 and S2). AA patients with EOGC and AOGC were more likely than Caucasian patients with EOGC and AOGC to receive chemotherapy, respectively (Table 2 and Table S1). Hispanic patients with EOGC and AOGC were more likely to receive surgery and chemotherapy than Caucasian patients with EOGC and AOGC, respectively (Table 2 and Table S1). Previous analyses of treatment differences of gastric cancer by race/ethnicity are not stratified by age. With this limitation, others have consistently found that Asian/PI patients with gastric cancer are more likely to receive therapy than other groups [30,31,32,33]. In the aforementioned NCDB analysis of patients of all ages with stage Ib-III gastric cancer undergoing surgery, Asian/PI and AA patients were less likely than Caucasian patients to receive perioperative chemotherapy while no difference was found among Hispanic patients [27]. It is known that Asian American, African American, and Hispanic patients receive hospice and palliative care at lower rates compared to Caucasian patients which some have theorized is related to differences in knowledge, cultural beliefs, and treatment preferences [34,35]. Assuming the utilization of hospice and palliative care is a surrogate for the receipt of less treatment, it is possible that this disparity in hospice and palliative care utilization is an explanation for our findings (regarding increased receipt of treatment among patients who are Asian/PI, African American, and Hispanic compared to Caucasian patients). Communication barriers and assumptions made by patients and their oncologists likely also play a role in the differences we observed.

4.4. Treatment by Center Type

We found patients with EOGC, AOGC, and LOGC treated at community cancer centers were more likely to receive surgery and less likely to receive chemotherapy than patients with EOGC, AOGC, and LOGC, treated at academic centers, respectively (Table 2 and Tables S1 and S2). In England, patients diagnosed with esophageal and gastric cancers in non-academic hospitals did not have a lower chance of having surgery than those diagnosed in an academic hospital [36]. Several studies in the Netherlands have identified patterns in the treatment of gastric cancer by hospital type and found that patients with gastric cancer treated at high-volume hospitals were more likely to receive systemic therapy and surgery compared to hospitals with lower volume [37,38]. Academic centers are more likely to have enroll patients on clinical trials and offer treatment options that are not available in community cancer centers, which may help explain our findings.

4.5. Treatment by Payor Status

We found patients with EOGC, AOGC, and LOGC who were uninsured or had Medicaid were more likely to receive surgery and less likely to receive chemotherapy than insured patients with EOGC, AOGC, and LOGC, respectively (Table 2 and Tables S1 and S2). In the Netherlands, younger age and higher socioeconomic status (SES) were independent factors for receiving treatment in patients with esophageal and gastric cancer [38,39]. Notably, patients with gastric cancer who lack insurance have been shown to have worse survival outcomes and receive less therapy compared to insured patients [40,41]. Insurance status plays a role in the type of treatment patients can receive (as well as where they can receive it).

4.6. Treatment by Location

We found patients with EOGC and LOGC residing in locations that were not adjacent to metropolitan areas were less likely to receive surgery than those residing in metropolitan areas (Table 2 and Table S2). In analyses of SEER and California Cancer Registry data, patients of all ages with gastric cancer residing in rural areas were also less likely to receive surgery compared to those in urban areas, which was attributed to lower levels of educational attainment, lower median household income, longer commute times, less contact with oncology providers, and less access to health insurance [42,43].

5. Conclusions

Our study represents the most comprehensive to date regarding the unique treatment patterns of patients with EOGC. As an entity, EOGC displays many alarming features—the incidence of this entity is increasing, these patients tend to present with late-stage disease, and risk factors are not well defined.

Our study had several important limitations. Most notably, individual-level data regarding the treatment sequence for each patient are not available in the NCDB, nor are data regarding environmental risk factors and tumor genomic information.

We found dramatic, statistically significant differences regarding how patients with EOGC are treated after adjusting for stage, tumor location, and year of diagnosis. However, the reasons why subgroups of patients with EOGC were treated differently is unclear. Ultimately, the complex interplay between intrinsic patient perceptions of treatment combined with external forces such as residence in a resource-limited setting, inadequate health insurance, and bias on the part of providers are likely intertwined. More research to untangle this complex narrative is warranted to characterize which factors play a role in the pursuit and receipt of treatment from both the patient and oncologist perspectives. Additionally, developing effective cultural awareness, minimizing assumptions, and recognizing differences in communication preferences are important to mitigate discrimination against, and implicit bias towards, marginalized patient populations. Investing in educational programs and healthcare systems to ensure patients have every opportunity to access high-quality care, as well as clinical trials, is imperative.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers14153633/s1, Table S1: Treatment Patterns Among Patients with AOGC; Table S2: Treatment Patterns Among Patients with LOGC.

Author Contributions

M.L., C.S. and C.E. were involved with study conception and design. M.L., C.S., E.A.G., C.C. and A.B.C. were involved with draft manuscript preparation. E.L., M.K.G. and C.E. were involved with editing. All authors were involved with interpreting results. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to the utilization of a publicly available, de-identified database.

Informed Consent Statement

Not applicable.

Data Availability Statement

A publicly available dataset was analyzed in this study. This data can be found here: https://www.facs.org/quality-programs/cancer-programs/national-cancer-database/publicaccess/, accessed on 3 June 2022.

Conflicts of Interest

The authors have no conflict to disclose in relation to this study.

Funding Statement

This research received no external funding.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Sung H., Ferlay J., Siegel R.L., Laversanne M., Soerjomataram I., Jemal A., Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2021;71:209–249. doi: 10.3322/caac.21660. [DOI] [PubMed] [Google Scholar]
  • 2.Siegel R.L., Miller K.D., Fuchs H.E., Jemal A. Cancer statistics, 2022. CA Cancer J. Clin. 2022;72:7–33. doi: 10.3322/caac.21708. [DOI] [PubMed] [Google Scholar]
  • 3.Kokkola A., Sipponen P. Gastric carcinoma in young adults. Hepato-Gastroenterology. 2001;48:1552–1555. [PubMed] [Google Scholar]
  • 4.Arnold M., Park J.Y., Camargo M.C., Lunet N., Forman D., Soerjomataram I. Is gastric cancer becoming a rare disease? A global assessment of predicted incidence trends to 2035. Gut. 2020;69:823–829. doi: 10.1136/gutjnl-2019-320234. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Heer E.V., Harper A.S., Sung H., Jemal A., Fidler-Benaoudia M.M. Emerging cancer incidence trends in Canada: The growing burden of young adult cancers. Cancer. 2020;126:4553–4562. doi: 10.1002/cncr.33050. [DOI] [PubMed] [Google Scholar]
  • 6.LaPelusa M., Shen C., Arhin N.D., Cardin D., Tan M., Idrees K., Geevarghese S., Chakravarthy B., Berlin J., Eng C. Trends in the Incidence and Treatment of Early-Onset Pancreatic Cancer. Cancers. 2022;14:283. doi: 10.3390/cancers14020283. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Codipilly D.C., Sawas T., Dhaliwal L., Johnson M.L., Lansing R., Wang K.K., Leggett C.L., Katzka D.A., Iyer P.G. Epidemiology and outcomes of young-onset esophageal adenocarcinoma: An analysis from a population-based database. Cancer Epidemiol. Prev. Biomark. 2021;30:142–149. doi: 10.1158/1055-9965.EPI-20-0944. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Siegel R.L., Fedewa S.A., Anderson W.F., Miller K.D., Ma J., Rosenberg P.S., Jemal A. Colorectal cancer incidence patterns in the United States, 1974–2013. JNCI J. Natl. Cancer Inst. 2017;109:djw322. doi: 10.1093/jnci/djw322. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Bergquist J.R., Leiting J.L., Habermann E.B., Cleary S.P., Kendrick M.L., Smoot R.L., Nagorney D.M., Truty M.J., Grotz T.E. Early-onset gastric cancer is a distinct disease with worrisome trends and oncogenic features. Surgery. 2019;166:547–555. doi: 10.1016/j.surg.2019.04.036. [DOI] [PubMed] [Google Scholar]
  • 10.Boffa D.J., Rosen J.E., Mallin K., Loomis A., Gay G., Palis B., Thoburn K., Gress D., McKellar D.P., Shulman L.N. Using the National Cancer Database for outcomes research: A review. JAMA Oncol. 2017;3:1722–1728. doi: 10.1001/jamaoncol.2016.6905. [DOI] [PubMed] [Google Scholar]
  • 11.Theuer C.P., de Virgilio C., Keese G., French S., Arnell T., Tolmos J., Klein S., Powers W., Oh T., Stabile B.E. Gastric adenocarcinoma in patients 40 years of age or younger. Am. J. Surg. 1996;172:473–477. doi: 10.1016/S0002-9610(96)00223-1. [DOI] [PubMed] [Google Scholar]
  • 12.Rona K.A., Schwameis K., Zehetner J., Samakar K., Green K., Samaan J., Sandhu K., Bildzukewicz N., Katkhouda N., Lipham J.C. Gastric cancer in the young: An advanced disease with poor prognostic features. J. Surg. Oncol. 2017;115:371–375. doi: 10.1002/jso.24533. [DOI] [PubMed] [Google Scholar]
  • 13.Torrejon N.V., Deshpande S., Wei W., Tullio K., Kamath S.D. Proportion of early-onset gastric and esophagus cancers has changed over time with disproportionate impact on Black and Hispanic patients. JCO Oncol. Pract. 2022;18:e759–e769. doi: 10.1200/OP.21.00692. [DOI] [PubMed] [Google Scholar]
  • 14.Holowatyj A.N., Ulrich C.M., Lewis M.A. Racial/ethnic patterns of young-onset noncardia gastric cancer. Cancer Prev. Res. 2019;12:771–780. doi: 10.1158/1940-6207.CAPR-19-0200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Giryes A., Oweira H., Mannhart M., Decker M., Abdel-Rahman O. Exploring the differences between early-onset gastric cancer and traditional-onset gastric cancer. J. Gastrointest. Oncol. 2018;9:1157. doi: 10.21037/jgo.2018.06.11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.De B., Rhome R., Jairam V., Özbek U., Holcombe R.F., Buckstein M., Ang C. Gastric adenocarcinoma in young adult patients: Patterns of care and survival in the United States. Gastric Cancer. 2018;21:889–899. doi: 10.1007/s10120-018-0826-x. [DOI] [PubMed] [Google Scholar]
  • 17.Cho S.Y., Park J.W., Liu Y., Park Y.S., Kim J.H., Yang H., Um H., Ko W.R., Lee B.I., Kwon S.Y. Sporadic early-onset diffuse gastric cancers have high frequency of somatic CDH1 alterations, but low frequency of somatic RHOA mutations compared with late-onset cancers. Gastroenterology. 2017;153:536–549.e526. doi: 10.1053/j.gastro.2017.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Huang Q., Zheng X., Jiao Y., Lei Y., Li X., Bi F., Guo F., Wang G., Liu M. A Distinct Clinicopathological Feature and Prognosis of Young Gastric Cancer Patients Aged ≤ 45 Years Old. Front. Oncol. 2021;11:674224. doi: 10.3389/fonc.2021.674224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Ma Z., Liu X., Paul M.E., Chen M., Zheng P., Chen H. Comparative investigation of early-onset gastric cancer. Oncol. Lett. 2021;21:374. doi: 10.3892/ol.2021.12635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Waldum H.L. The increase in early-onset gastric carcinomas from 1995 is probably due to the introduction of proton pump inhibitors. Surgery. 2020;168:568–569. doi: 10.1016/j.surg.2020.01.016. [DOI] [PubMed] [Google Scholar]
  • 21.MacArthur T.A., Harmsen W.S., Mandrekar J., Abraha F., Grotz T.E. Association of Common Medications and the Risk of Early-Onset Gastric Cancer: A Population-Based Matched Study. J. Cancer Epidemiol. 2021;2021:2670502. doi: 10.1155/2021/2670502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Wang K., Yuen S.T., Xu J., Lee S.P., Yan H.H., Shi S.T., Siu H.C., Deng S., Chu K.M., Law S. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat. Genet. 2014;46:573–582. doi: 10.1038/ng.2983. [DOI] [PubMed] [Google Scholar]
  • 23.Cristescu R., Lee J., Nebozhyn M., Kim K.-M., Ting J.C., Wong S.S., Liu J., Yue Y.G., Wang J., Yu K. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes. Nat. Med. 2015;21:449–456. doi: 10.1038/nm.3850. [DOI] [PubMed] [Google Scholar]
  • 24.Zhao L.-Y., Hu J.-K. Early-onset gastric cancer is quite distinct from late-onset gastric cancer. Surgery. 2020;167:883. doi: 10.1016/j.surg.2019.08.018. [DOI] [PubMed] [Google Scholar]
  • 25.Al-Refaie W.B., Hu C.-Y., Pisters P.W., Chang G.J. Gastric adenocarcinoma in young patients: A population-based appraisal. Ann. Surg. Oncol. 2011;18:2800–2807. doi: 10.1245/s10434-011-1647-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Jiang Y., Xie J., Huang W., Chen H., Xi S., Li T., Chen C., Sun Z., Hu Y., Liu W. Chemotherapy Use and Survival Among Young and Middle-Aged Patients With Gastric Cancer. Clin. Transl. Gastroenterol. 2020;11:e00253. doi: 10.14309/ctg.0000000000000253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Sherman K.L., Merkow R.P., Bilimoria K.Y., Wang C.E., Mulcahy M.F., Benson A.B., Bentrem D.J. Treatment trends and predictors of adjuvant and neoadjuvant therapy for gastric adenocarcinoma in the United States. Ann. Surg. Oncol. 2013;20:362–370. doi: 10.1245/s10434-012-2552-7. [DOI] [PubMed] [Google Scholar]
  • 28.Kalff M.C., Wagner A.D., Verhoeven R.H., Lemmens V.E., van Laarhoven H.W., Gisbertz S.S., van Berge Henegouwen M.I. Sex differences in tumor characteristics, treatment, and outcomes of gastric and esophageal cancer surgery: Nationwide cohort data from the Dutch Upper GI Cancer Audit. Gastric Cancer. 2021;25:22–32. doi: 10.1007/s10120-021-01225-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Dijksterhuis W.P.M., Kalff M.C., Wagner A.D., Verhoeven R.H.A., Lemmens V.E.P.P., van Oijen M.G.H., Gisbertz S.S., van Berge Henegouwen M.I., van Laarhoven H.W.M. Gender Differences in Treatment Allocation and Survival of Advanced Gastroesophageal Cancer: A Population-Based Study. JNCI J. Natl. Cancer Inst. 2021;113:1551–1560. doi: 10.1093/jnci/djab075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Gill S., Shah A., Le N., Cook E.F., Yoshida E.M. Asian ethnicity–related differences in gastric cancer presentation and outcome among patients treated at a Canadian Cancer Center. J. Clin. Oncol. 2003;21:2070–2076. doi: 10.1200/JCO.2003.11.054. [DOI] [PubMed] [Google Scholar]
  • 31.Kim J., Sun C.-L., Mailey B., Prendergast C., Artinyan A., Bhatia S., Pigazzi A., Ellenhorn J. Race and ethnicity correlate with survival in patients with gastric adenocarcinoma. Ann. Oncol. 2010;21:152–160. doi: 10.1093/annonc/mdp290. [DOI] [PubMed] [Google Scholar]
  • 32.Klapheke A.K., Carvajal-Carmona L.G., Cress R.D. Racial/ethnic differences in survival among gastric cancer patients in california. Cancer Causes Control. 2019;30:687–696. doi: 10.1007/s10552-019-01184-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Zhang G., Zhao X., Li J., Yuan Y., Wen M., Hao X., Li P., Zhang A. Racial disparities in stage-specific gastric cancer: Analysis of results from the Surveillance Epidemiology and End Results (SEER) program database. J. Investig. Med. 2017;65:991–998. doi: 10.1136/jim-2017-000413. [DOI] [PubMed] [Google Scholar]
  • 34.Johnson K.S. Racial and ethnic disparities in palliative care. J. Palliat. Med. 2013;16:1329–1334. doi: 10.1089/jpm.2013.9468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Medicare Payment Advisory Commission (US) Report to the Congress, Medicare Payment Policy. Medicare Payment Advisory Commission; Washington, DC, USA: 2003. [Google Scholar]
  • 36.Bachmann M., Alderson D., Edwards D., Wotton S., Bedford C., Peters T., Harvey I. Cohort study in South and West England of the influence of specialization on the management and outcome of patients with oesophageal and gastric cancers. J. Br. Surg. 2002;89:914–922. doi: 10.1046/j.1365-2168.2002.02135.x. [DOI] [PubMed] [Google Scholar]
  • 37.Dijksterhuis W.P., Verhoeven R.H., Pape M., Slingerland M., Mohammad N.H., de Vos-Geelen J., Beerepoot L.V., van Voorthuizen T., Creemers G.-J., Lemmens V.E. Hospital volume and beyond first-line palliative systemic treatment in metastatic oesophagogastric adenocarcinoma: A population-based study. Eur. J. Cancer. 2020;139:107–118. doi: 10.1016/j.ejca.2020.08.010. [DOI] [PubMed] [Google Scholar]
  • 38.Bus P., Aarts M.J., Lemmens V.E., van Oijen M.G., Creemers G.-J., Nieuwenhuijzen G.A., van Baal J.W., Siersema P.D. The effect of socioeconomic status on staging and treatment decisions in esophageal cancer. J. Clin. Gastroenterol. 2012;46:833–839. doi: 10.1097/MCG.0b013e31824e8ff8. [DOI] [PubMed] [Google Scholar]
  • 39.Trip A.K., Stiekema J., Visser O., Dikken J.L., Cats A., Boot H., Van Sandick J.W., Jansen E.P., Verheij M. Recent trends and predictors of multimodality treatment for oesophageal, oesophagogastric junction, and gastric cancer: A Dutch cohort-study. Acta Oncol. 2015;54:1754–1762. doi: 10.3109/0284186X.2015.1009638. [DOI] [PubMed] [Google Scholar]
  • 40.Findakly D., Forlemu A., Kosa D., Amar S. The Impact of Sociodemographic Characteristics on Gastric Cancer Outcomes: A Retrospective Review of a Large Single Center Study. American Society of Clinical Oncology; Alexandria, VA, USA: 2021. [Google Scholar]
  • 41.Parikh-Patel A., Morris C.R., Kizer K.W. Disparities in quality of cancer care: The role of health insurance and population demographics. Medicine. 2017;96:e9125. doi: 10.1097/MD.0000000000009125. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Minhas A.A., Fatima Z., Kommineni S.K., Ahmad Z., Minhas S.A. The Association of Rural-Urban Inhabitation With Gastric Adenocarcinoma Mortality and Treatment: A Surveillance, Epidemiology, and End Results (SEER)-Based Study. Cureus. 2021;13:e18571. doi: 10.7759/cureus.18571. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Parikh-Patel A., Morris C.R., Kizer K.W., Wun T., Keegan T.H. Urban–Rural Variations in Quality of Care Among Patients With Cancer in California. Am. J. Prev. Med. 2021;61:e279–e288. doi: 10.1016/j.amepre.2021.05.021. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data Availability Statement

A publicly available dataset was analyzed in this study. This data can be found here: https://www.facs.org/quality-programs/cancer-programs/national-cancer-database/publicaccess/, accessed on 3 June 2022.


Articles from Cancers are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)

RESOURCES