The prognostic impact of body mass index on patients with gastric adenocarcinoma and mucinous adenocarcinoma: a retrospective cohort study

Introduction

Gastric cancer (GC) is one of the most common malignancies globally and poses a serious threat to human lives and health, with its incidence rising significantly due to modern lifestyle and environmental factors (1-3). The latest data show that GC ranks 5^th in morbidity and fourth in mortality, with a 5-year overall survival rate of 35.1% (4-6). Beyond genetic and hereditary factors, which influence various cellular metabolism and signaling pathways, lifestyle factors, particularly excess weight, have been shown to significantly impact the risk of GC (3,7-13). The higher the body mass index (BMI), the worse the cancer prognosis is generally believed to be (14,15). However, the effect of excess weight on surgical outcomes in GC patients remains controversial (16,17). In GC patients, the “obesity paradox” describes the paradoxically “superior” outcomes for overweight and obese patients compared to non-overweight patients, contrary to popular belief that high BMI is associated with an increased risk of death in the general population (18-20). Current studies suggest that BMI is an important prognostic factor for multiple gastrointestinal tumors (21). Investigating the effect of BMI in patients with different types of GC on prognosis after radical GC surgery is meaningful to improve the 5-year survival rate in patients with different types of GC (22,23). However, the relationship between BMI and prognosis in GC remains complex and may differ based on histological subtypes.

Gastric adenocarcinoma is the most common type of GC, accounting for over 90% of all cases. It originates from the glandular cells of the gastric mucosa and can be further divided into intestinal and diffuse subtypes. Various risk factors are associated with this cancer, including Helicobacter pylori infection, chronic gastritis, poor dietary habits, smoking, and family history, among others. It may be asymptomatic in its early stages, but as the disease progresses, symptoms such as upper abdominal pain, indigestion, and weight loss may appear. Surgical resection is the primary treatment, possibly accompanied by chemotherapy and radiotherapy. The prognosis largely depends on the staging of the tumor, the treatment method used, and the patient’s overall health status.

Mucinous adenocarcinoma is a subtype of gastric adenocarcinoma, characterized by large amounts of mucus product ions. It accounts for about 10% of all GC cases. Similar to gastric adenocarcinoma, it may be related to certain specific changes in the gastric mucosa. This subtype may present as a large mass and can sometimes be accompanied by pseudomyxoma peritonei. While surgery remains the main treatment option, the potential for early metastasis in mucinous adenocarcinoma complicates treatment. The prognosis is generally poor because it is more likely to invade the serosa and metastasize to distant locations. This study focuses on two major subtypes of GC: gastric adenocarcinoma and mucinous adenocarcinoma. The mucinous subtype, characterized by abundant mucus production, is known for its poor prognosis (24). Understanding the role of BMI in these subtypes could provide critical insights into patient management and treatment strategies.

In this prospective study, we found that a total of 3,081 patients underwent radical GC surgery, including 2,883 adenocarcinoma patients and 198 mucinous adenocarcinoma patients. The patients were categorized into three groups based on their BMI (kg/m²): low BMI (<18.5), medium BMI (≥18.5, <24), and high BMI groups (≥24). Kaplan-Meier curve analysis of the survival period for adenocarcinoma patients showed that patients with high BMI had significantly better outcomes than those with low BMI. However, in the case of mucinous adenocarcinoma patients, there was no significant difference in prognosis among the BMI groups. Therefore, we hypothesize that this obesity paradox appears to exist only among adenocarcinoma patients, and not in those with mucinous adenocarcinoma. We present this article in accordance with the STROBE reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-593/rc).

Methods

Selection criteria and patients

The retrospective cohort study included GC patients undergoing radical surgical resection at the Zhejiang Cancer Hospital between April 2008 and December 2019. The inclusion criteria were as follows: (I) patients between 25 and 100 years of age; (II) patients undergoing radical surgical resection; (III) pathological diagnosis of gastric adenocarcinoma and mucinous adenocarcinoma; (IV) patients with or metastasizing from other tumors; (V) patients with residual GC; and (VI) pathological diagnosis of partial mucinous adenocarcinoma. Finally, the study included 3,081 patients.

We looked at the medical records of all patients and collected data including demographic characteristics, tumor characteristics, treatment regimens, and survival rates. Patients were divided into low (<18.5), medium (≥18.5, <24), and high (≥24) BMI (kg/m²). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Zhejiang Cancer Hospital (approval No. IRB-2024-604) and informed consent was taken from all the patients.

Clinicopathological characteristics

We collected the following data: age, sex, BMI, pathological type, tumor location, surgical approach, type of resection, pathologic tumor-node-metastasis (pTNM) [American Joint Committee on Cancer tumor-node-metastasis, 8^th edition (AJCC-TNM 8^th)], degree of tumor differentiation, vascular tumor thrombus, nerve invasion, lymph node ratio (LNR), and tumor markers. Survival information was obtained through telephone follow-up and medical records. The final follow-up assessment was conducted in September 2021.

Statistical analysis

Categorical variables were compared using the Chi-squared test or Fisher’s exact test. Survival curves were estimated using the Kaplan-Meier method. Multivariate analysis was performed using Cox regression analyses (single variate Cox regression results inclusion factors of P<0.05). Hazard ratios (HRs) and 95% confidence intervals (CIs) were also calculated.

Statistical analysis was performed using IBM SPSS Statistics 25.0 (IBM Corp, Armonk, NY, USA) and GraphPad Prism8 version 8.3.0 (GraphPad Software, San Diego, CA, USA).

The ggstatsplot package was used for correlation plotting (25).

Results

Clinicopathological characteristics and clinical outcomes

Firstly, Figure 1 is the overall flowchart. As shown in Table 1, the majority of the 3,081 GC patients (63.9%) in the study population were over 60 years of age. Patients included 2,385 males (77.4%) and 696 females (22.6%). Analysis of tumor sites distribution revealed that 935 cases (30.3%) were upper GC, 487 cases (15.8%) were middle GC, 1,610 cases (52.2%) were lower GC, and only 49 cases (1.6%) were total GC.

Figure 1 Flowchart diagram. GC, gastric cancer; AFP, alpha-fetoprotein; BMI, body mass index.

Of the 3,081 GC patients, 1,634 (53.0%) were classified as pTNM stage III, 693 cases (22.5%) as stage II, 754 (24.5%) as stage I; 1,070 (34.7%) patients had poor differentiation, 1,206 (39.1%) were moderate-poor, 728 (23.6%) were moderate, 56 cases were moderate-well, and only 21 cases were well; 1,629 (52.9%) cases of vascular tumor thrombus were positive and 1,452 (47.1%) were negative; 1,468 (47.6%) cases of nerve invasion were positive and 1,613 (52.4%) were negative.

Independent risk factors for prognosis in GC patients

Univariate analysis showed that the gender (P=0.023), age (P<0.001), BMI (P<0.001), range of resection (P<0.001), surgery (P<0.001), tumor location (P=0.03), differentiation (P<0.001), vascular tumor thrombus (P<0.001), nerve invasion (P<0.001), maximum tumor diameter (P<0.001), pathologic tumor (pT) stage (P<0.001), pathologic node (pN) stage (P<0.001), pTNM (P<0.001) as well as the levels of carcinoembryonic antigen (CEA) (P<0.001), cancer antigen 19-9 (CA19-9) (P<0.001), cancer antigen 125 (CA125) (P<0.001), alpha-fetoprotein (AFP) (P<0.001), cancer antigen 242 (CA242) (P<0.001), and cancer antigen 724 (CA724) (P<0.001) were prognostic factors for GC. Subsequently, the factors with an index of P<0.05 by using univariate Cox regression analysis were subjected to multivariate Cox regression analysis. Furthermore, the multivariate analysis revealed that age (P<0.001; HR =1.40; 95% CI: 1.20–1.63), BMI (P<0.001; HR =0.82; 95% CI: 0.72–0.92), surgery methods (P<0.001; HR =0.64; 95% CI: 0.47–0.86), differentiation (P=0.03; HR =1.12; 95% CI: 1.01–1.23), pathological type (P<0.001; HR =0.80; 95% CI: 0.70–0.92), nerve invasion (P=0.01; HR =1.25; 95% CI: 1.06–1.48), maximum tumor diameter (P=0.05; HR =1.16; 95% CI: 1.00–1.35), pT (P<0.001; HR =1.31; 95% CI: 1.11–1.53), pN (P<0.001; HR =1.58; 95% CI: 1.41–1.76), CEA (P<0.001; HR =1.29; 95% CI: 1.10–1.52), and CA125 (P<0.001; HR =1.42; 95% CI: 1.10–1.83) were independent factors affecting the prognosis of GC patients.

From the univariate analysis of the prognosis of patients with GC, it can be seen that BMI is an important influencing factor, which was also consistent with previous studies, so we selected BMI as an influencing factor for the research (Table 2).

Correlation between BMI and clinicopathological characteristics

According to the BMI sub-criteria, 276 people were identified as having a low BMI, 1,956 as having a moderate BMI, and 849 as having a high BMI. There was a correlation between BMI and clinicopathological characteristics. Positive correlations between age (P<0.001), sex (P=0.048), pTNM stage (P<0.001), nerve invasion (P<0.001), and maximum diameter (P<0.001) were found in the Chi-squared assay (Table 3). In addition, we analyzed the association between tumor markers levels, suggesting a negative correlation between BMI and CEA levels (P=0.01), as well as AFP levels (P<0.001) (Table 4). From various serum tumor markers, only AFP showed a linear relationship with BMI (Figure 2).

Figure 2 The linear relationship between AFP and BMI. BMI, body mass index; AFP, alpha-fetoprotein.

Effect of BMI on prognosis in GC patients

In addition, analysis of survival curves of 3,081 GC patients using the life table and Kaplan-Meier methods revealed statistically significant differences in adenocarcinoma prognosis between different BMI groups (P<0.001): the higher the BMI, the better the prognosis (Figure 3A). P value in the high BMI group was higher than the medium BMI group (P<0.01) and the medium BMI group was higher than the low BMI group (P<0.01). However, in the mucinous adenocarcinoma group, different BMI markers had no significant impact on prognosis (Figure 3B). High BMI group vs. medium BMI group (P=0.40), medium BMI group vs. low BMI group (P=0.77), and high BMI group vs. low BMI group (P=0.39).

Figure 3 Gastric adenocarcinoma and mucinous adenocarcinoma patients’ survival curves. (A) Life table OS analysis for adenocarcinoma patients in different BMI groups; (B) The Kaplan-Meier OS analysis for mucinous adenocarcinoma patients in different BMI groups. BMI: low (<18.5 kg/m²); medium (≥18.5, <24 kg/m²), and high (≥24 kg/m²). BMI, body mass index; OS, overall survival.

Discussion

GC is one of the most common cancers in the world and its overall prognosis is relatively poor. At the same time, obesity is increasing globally, especially in developed countries (26-29). Obesity is associated with poor overall survival or advanced stage in various malignant tumors, including breast cancer, colorectal cancer, pancreatic cancer, and GC. The results showed that postoperative complications associated with high BMI were mainly minor. Conversely, patients with low BMI had more severe complications, leading to higher postoperative mortality. BMI has been proven to be an independent prognostic factor in multivariate Cox models (30). Chen et al. performed gastrectomy on 1,249 patients and classified them into low BMI (≤18.49 kg/m²), medium BMI (18.50–24.99 kg/m²), and high BMI (≥25.00 kg/m²) groups (31). They analyzed the impact of BMI on postoperative complications and overall survival rate. The results showed that the incidence rate was higher in the high BMI group than that in the low BMI group and the medium BMI group, but the average Charlson Comorbidity Index (CCI; which is used to assess the impact of the severity of comorbidities on long-term prognosis) was significantly higher in the low BMI group than that in the high BMI group. Compared to the medium BMI group, those with low BMI had the lowest survival outcomes and those with high BMI had the highest survival. Subgroup analysis showed that low BMI was associated with poor survival in patients with stage III–IV diseases to IV diseases. Low BMI is associated with more severe postoperative complications and poor prognosis. These findings, coupled with recent evidence that certain types of obesity can be considered “healthy”, provide some evidence for the “obesity paradox”. This may be due to low BMI, usually associated with low albumin and hemoglobin levels, and may be due to malnutrition. This finding is especially true in cancer patients because of energy disorders caused by cachexia. High BMI involves severe changes in endocrine and metabolic responses, leading to specific diseases collectively known as metabolic syndrome. Tokunaga et al. compared the clinicopathological characteristics and 5-year survival rates in overweight and non-overweight patients undergoing radical GC surgery (17). They found that the 5-year survival rate after radical gastrectomy in overweight Japanese patients was higher than in non-overweight Japanese patients, especially those with early GC. In general, patients with a higher BMI have higher postoperative incidence rate, and patients with a higher BMI have more difficulty with surgery, resulting in higher postoperative incidence rate. In addition, inadequate lymph node dissection during gastrectomy may affect long-term survival and may worsen the actual 5-year survival rate of overweight patients. However, the relationship between BMI and long-term prognosis needs to be further investigated. Oh et al. have reported that being overweight negatively affected the postoperative complication rate in GC patients, but not their long-term survival (30).

A total of 3,081 patients underwent radical GC surgery in this study, including 2,883 with adenocarcinoma and 198 with mucinous adenocarcinoma, divided into groups with low BMI (<18.5 kg/m²), medium BMI (≥18.5, <24 kg/m²), and high BMI groups (≥24 kg/m²). Kaplan-Meier curve analysis of survival period adenocarcinoma patients revealed that patients with high BMI had significantly better outcomes than those with low BMI and those with high BMI. However, in patients with mucinous adenocarcinoma, there was no significant difference in prognosis between these BMI groups.

Therefore, we can assume that this “obesity paradox” exists only in adenocarcinoma patients and not in mucinous adenocarcinoma patients. In other words, the prognosis of patients with adenocarcinoma usually improves with an increase in BMI, while that of patients with mucinous adenocarcinoma does not. We hypothesized that previous prognostic findings were consistent with the adenocarcinoma cohort, possibly because the majority of GC patients have adenocarcinoma. The lack of correlation between BMI and prognosis in mucinous adenocarcinoma may be attributed to the inherently poor prognosis of this pathological subtype. Mucinous adenocarcinoma is characterized by aggressive biological behavior, advanced disease stages at diagnosis, and limited therapeutic options. These factors likely overshadow the potential prognostic impact of BMI, making it less influential compared to adenocarcinoma. Additionally, the distinct biological features of mucinous adenocarcinoma, such as high mucin content and unique tumor microenvironment, may reduce the relevance of BMI in influencing patient outcomes.

However, we also know that postoperative complications and difficulties in caring for GC patients increase with weight gain (32). Therefore, we suggest that patients with mucinous adenocarcinoma should still maintain a healthy weight, as low BMI may further contribute to frailty and reduced treatment tolerance. In contrast, adenocarcinoma patients should focus on improving their nutritional status to optimize body weight, as higher BMI appears to confer a survival advantage. Future research should stratify patients by tumor stage and treatment modality to investigate the interplay between BMI and prognosis in these subtypes, particularly in mucinous adenocarcinoma.

Interestingly, a low BMI was associated with higher AFP levels in mucinous adenocarcinoma patients, indicating a negative correlation. This finding suggests that patients with lower BMI, potentially reflecting malnutrition or advanced disease stages, may have elevated AFP levels due to more aggressive tumor biology or greater tumor burden. This relationship highlights the potential use of AFP as a complementary marker in predicting poor prognosis in low-BMI patients. However, further studies are required to elucidate the underlying mechanisms of this association and its implications for patient management.

In summary, in this prospective study, we found that, unlike previous studies, BMI was not associated with prognosis in patients with mucinous adenocarcinoma. However, there are some notable drawbacks in the study. First, the number of samples from patients with mucinous adenocarcinoma is much smaller than those from adenocarcinoma, and further study of the larger sample size is recommended. Secondly, the patients included were followed up for a long period of time, with survival as the only prognostic indicator.

Conclusions

The BMI index has a certain reference value for the prognosis of GC patients. Among adenocarcinoma patients, the prognosis was significantly better in the high BMI group than in the low BMI group, but no significant prognostic difference was found among BMI groups in mucinous adenocarcinoma.

Acknowledgments

The authors would like to thank the patients, nurses, and clinicians for their participation in this study. The authors also would like to thank Albino Bacolla for the help in polishing the paper.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-593/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-593/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-593/prf

Funding: This study was supported by the National Natural Science Foundation of China (No. 82473195), the Natural Science Foundation of Zhejiang Province of China (No. LTGY23H160018), the Zhejiang Medical and Health Science and Technology Program (No. 2024KY789), the Beijing Science and Technology Innovation Medical Development Foundation (No. KC2023-JX-0270-07 to Z.Y.), the National Research Center for Translational Medicine at Shanghai Program [No. NRCTM(SH)-2025-07], and the Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province (No. 2022E10021 to X.D.C.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-593/coif). C.L., H.D.L., H.Y.H., K.C., Y.X.H., D.Z., Q.M.B., Y.C.H., G.X.L., C.K.Z., Y.K.Z., M.C.D., Y.H.H., J.J., Y.S., and Z.Y. report this research was supported by the National Natural Science Foundation of China (No. 82473195), the Natural Science Foundation of Zhejiang Province of China (No. LTGY23H160018), the Zhejiang Medical and Health Science and Technology Program (No. 2024KY789), and the National Research Center for Translational Medicine at Shanghai Program [No. NRCTM(SH)-2025-07]. Z.Y. reports this study was supported by the Beijing Science and Technology Innovation Medical Development Foundation (No. KC2023-JX-0270-07). X.D.C. reports funding from the Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province (No. 2022E10021). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are responsible for all aspects of this work and have ensured that any issues related to the accuracy or integrity of the study have been thoroughly investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Zhejiang Cancer Hospital (approval No. IRB-2024-604) and informed consent was taken from all the patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Zhang X, Fang H, Zeng Z, et al. Preoperative Prognostic Nutrition Index as a Prognostic Indicator of Survival in Elderly Patients Undergoing Gastric Cancer Surgery. Cancer Manag Res 2021;13:5263-73. [Crossref] [PubMed]
2. Li X, Huang Y, Zu D, et al. PMMA nanoplastics induce gastric epithelial cellular senescence and cGAS-STING-mediated inflammation via ROS overproduction and NHEJ suppression. Ecotoxicol Environ Saf 2024;287:117284. [Crossref] [PubMed]
3. Huang YX, He HY, Chen K, et al. Prognostic impact and reasons for variability by tumor location in gastric cancer. World J Gastroenterol 2024;30:4709-24. [Crossref] [PubMed]
4. Wang FH, Zhang XT, Li YF, et al. The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021. Cancer Commun (Lond) 2021;41:747-95. [Crossref] [PubMed]
5. Zeng H, Chen W, Zheng R, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries. Lancet Glob Health 2018;6:e555-67. [Crossref] [PubMed]
6. Chen H, Hu Y, Zhuang Z, et al. Advancements and Obstacles of PARP Inhibitors in Gastric Cancer. Cancers (Basel) 2023;15:5114. [Crossref] [PubMed]
7. Ejaz A, Spolverato G, Kim Y, et al. Impact of body mass index on perioperative outcomes and survival after resection for gastric cancer. J Surg Res 2015;195:74-82. [Crossref] [PubMed]
8. Eom BW, Joo J, Yoon HM, et al. A body shape index has a good correlation with postoperative complications in gastric cancer surgery. Ann Surg Oncol 2014;21:1115-22. [Crossref] [PubMed]
9. McCaffrey DF, Griffin BA, Almirall D, et al. A tutorial on propensity score estimation for multiple treatments using generalized boosted models. Stat Med 2013;32:3388-414. [Crossref] [PubMed]
10. Liu H, Li X, Shi Y, et al. Protein Tyrosine Phosphatase PRL-3: A Key Player in Cancer Signaling. Biomolecules 2024;14:342. [Crossref] [PubMed]
11. Shi Y, Xu S, Ngoi NYL, et al. PRL-3 dephosphorylates p38 MAPK to promote cell survival under stress. Free Radic Biol Med 2021;177:72-87. [Crossref] [PubMed]
12. Ye Z, Xu S, Shi Y, et al. GRB2 stabilizes RAD51 at reversed replication forks suppressing genomic instability and innate immunity against cancer. Nat Commun 2024;15:2132. [Crossref] [PubMed]
13. Ye Z, Ng CP, Liu H, et al. PRL1 and PRL3 promote macropinocytosis via its lipid phosphatase activity. Theranostics 2024;14:3423-38. [Crossref] [PubMed]
14. Bickenbach KA, Denton B, Gonen M, et al. Impact of obesity on perioperative complications and long-term survival of patients with gastric cancer. Ann Surg Oncol 2013;20:780-7. [Crossref] [PubMed]
15. Sun Y, Liu S. Metastasis of papillary thyroid cancer: does body mass index (BMI) is the key factor? Gland Surg 2022;11:1439-40. [Crossref] [PubMed]
16. Després JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature 2006;444:881-7. [Crossref] [PubMed]
17. Tokunaga M, Hiki N, Fukunaga T, et al. Better 5-year survival rate following curative gastrectomy in overweight patients. Ann Surg Oncol 2009;16:3245-51. [Crossref] [PubMed]
18. Mullen JT, Moorman DW, Davenport DL. The obesity paradox: body mass index and outcomes in patients undergoing nonbariatric general surgery. Ann Surg 2009;250:166-72. [Crossref] [PubMed]
19. Wong J, Rahman S, Saeed N, et al. Effect of body mass index in patients undergoing resection for gastric cancer: a single center US experience. J Gastrointest Surg 2014;18:505-11. [Crossref] [PubMed]
20. Yasunaga H, Horiguchi H, Matsuda S, et al. Body mass index and outcomes following gastrointestinal cancer surgery in Japan. Br J Surg 2013;100:1335-43. [Crossref] [PubMed]
21. Xu X, Shen W, Wang D, et al. Clinical features and prognosis of resectable pulmonary primary invasive mucinous adenocarcinoma. Transl Lung Cancer Res 2022;11:420-31. [Crossref] [PubMed]
22. Calderillo-Ruíz G, Díaz-Romero MC, Carbajal-López B, et al. Latin American young patients with gastric adenocarcinoma: worst prognosis and outcomes. J Gastrointest Oncol 2023;14:2018-27. [Crossref] [PubMed]
23. Tao W, Lagergren J. Clinical management of obese patients with cancer. Nat Rev Clin Oncol 2013;10:519-33. [Crossref] [PubMed]
24. Shen Y, Chen K, Gu C. Identification of a chemotherapy-associated gene signature for a risk model of prognosis in gastric adenocarcinoma through bioinformatics analysis. J Gastrointest Oncol 2022;13:2219-33. [Crossref] [PubMed]
25. Patil I. Visualizations with statistical details: The'ggstatsplot'approach. J Open Source Softw 2021;6:3167. [Crossref]
26. Roukos DH, Kappas AM. Perspectives in the treatment of gastric cancer. Nat Clin Pract Oncol 2005;2:98-107. [Crossref] [PubMed]
27. Strong VE, Song KY, Park CH, et al. Comparison of gastric cancer survival following R0 resection in the United States and Korea using an internationally validated nomogram. Ann Surg 2010;251:640-6. [Crossref] [PubMed]
28. Qiu L, Kang H, Yang J, et al. Accurate prediction of stomach adenocarcinomas of poorest and best prognosis with a combination of gene expression and clinical signatures. Genome Instability & Disease 2022;3:227-37. [Crossref]
29. Liu X, Irfan M, Xu X, et al. Helicobacter pylori infection induced genome instability and gastric cancer. Genome Instability & Disease 2020;1:129-42. [Crossref]
30. Oh SJ, Hyung WJ, Li C, et al. Effect of being overweight on postoperative morbidity and long-term surgical outcomes in proximal gastric carcinoma. J Gastroenterol Hepatol 2009;24:475-9. [Crossref] [PubMed]
31. Chen HN, Chen XZ, Zhang WH, et al. The Impact of Body Mass Index on the Surgical Outcomes of Patients With Gastric Cancer: A 10-Year, Single-Institution Cohort Study. Medicine (Baltimore) 2015;94:e1769. [Crossref] [PubMed]
32. Lin YS, Huang KH, Lan YT, et al. Impact of body mass index on postoperative outcome of advanced gastric cancer after curative surgery. J Gastrointest Surg 2013;17:1382-91. [Crossref] [PubMed]