Outcomes of patients with nonmetastatic gastric adenocarcinoma according to perioperative treatment strategy: a real-world, population-based study

2021 ◽  
Vol 10 (15) ◽  
pp. 1143-1151
Author(s):  
Omar Abdel-Rahman
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Adjuvant Chemotherapy ◽  
Treatment Strategy ◽  
Cox Regression ◽  
Population Based ◽  
Survival Outcomes ◽  
Perioperative Chemotherapy ◽  
Cox Regression Analysis ◽  
Perioperative Treatment

Aim: To assess the survival outcomes of patients with nonmetastatic gastric cancer according to the type of perioperative treatment strategy used (surgery-only, adjuvant chemo-radiotherapy, adjuvant chemotherapy, perioperative chemotherapy) in a population-based setting. Materials & methods: Surveillance, Epidemiology and End Results research-plus database was explored, and patients with nonmetastatic gastric cancer who were treated with an oncologic surgery were reviewed. Multivariable Cox regression analysis was used to examine the impact of treatment strategy on overall and cancer-specific survival. Results: A total of 11,526 patients were found to be eligible and they were included in the current analysis. Looking at the percentages of different treatment strategies throughout the study years (2006–2017), the use of the following strategies increased: adjuvant chemotherapy (20.1 vs 10.6%), and perioperative chemotherapy (21.3 vs 0.5%); while the use of the following strategies decreased: surgery only (36.2 vs 58.2%), and adjuvant chemo-radiotherapy (22.4 vs 30.6%). Using multivariable Cox regression analysis, the following factors were associated with worse overall survival: older age (hazard [HR]: 1.021; 95% CI: 1.018–1.023), males (HR: 1.09; 95% CI: 1.04–1.14), Black race (HR: 1.11; 95% CI: 1.04–1.19), cardia subsite (HR: 1.09; 95% CI: 1.02–1.17), grade 3–4 (HR:1.32; 95% CI: 1.25–1.40), diffuse histology (HR: 1.46; 95% CI: 1.35–1.58), clinically node positive (HR:1.43; 95% CI: 1.34–1.53), total gastrectomy (HR: 1.20; 95% CI: 1.13–1.28), and surgery-only approach (HR: 1.65; 95% CI: 1.55–1.75). Conclusion: Among patients with localized gastric cancer, patients who were treated with surgery-only, and to a less extent, patients who were treated with surgery followed by adjuvant chemotherapy have worse survival outcomes; while those treated with perioperative chemotherapy have the best survival outcomes.

scholarly journals Development and Validation of a Scoring System Based on 9 Glycolysis-Related Genes for Prognosis Prediction in Gastric Cancer

2020 ◽  
Vol 19 ◽  
pp. 153303382097167
Author(s):  
Tianqi Luo ◽  
Yufei Du ◽  
Jinling Duan ◽  
Chengcai Liang ◽  
Guoming Chen ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Adjuvant Chemotherapy ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Groups ◽  
Tumor Stage ◽  
Cox Regression Analysis ◽  
Gastric Cancer Patients

Gastric cancer is a malignant tumor with high morbidity and mortality worldwide. However, increasing evidences have revealed the correlation between the glycolysis process and tumorigenesis. This study is aim to develop a list of glycolysis-related genes for risk stratification in gastric cancer patients. We included 500 patients’ sample data from GSE62254 and GSE26942 datasets, and classified patients into training (n = 350) and testing sets (n = 150) at a ratio of 7: 3. Univariate and multivariate Cox regression analysis were performed to screen genes having prognostic value. Based on HALLMARK gene sets, we identified 9 glycolysis-related genes (BPNT1, DCN, FUT8, GMPPA, GPC3, LDHC, ME2, PLOD2, and UGP2). On the basis of risk score developed by the 9 genes, patients were classified into high- and low-risk groups. The survival analysis showed that the high-risk patients had a worse prognosis ( p < 0.001). Similar finding was observed in the testing cohort and 2 independent cohorts (GSE13861 and TCGA-STAD, all p < 0.001). The multivariate Cox regression analysis showed that the risk score was an independent prognostic factor for overall survival ( p < 0.001). Furthermore, we constructed a nomogram that integrated the risk score and tumor stage, age, and adjuvant chemotherapy. Through comparing the results of the receiver operating characteristic curves and decision curve analysis, we found that the nomogram had a superior predictive accuracy than conventional TNM staging system, suggesting that the risk score combined with other clinical factors (age, tumor stage, and adjuvant chemotherapy) can develop a robust prediction for survival and improve the individualized clinical decision making of the patient. In conclusion, we identified 9 glycolysis-related genes from hallmark glycolysis pathway. Based on the 9 genes, gastric cancer patients were separated into different risk groups related to survival.

scholarly journals Expression of LOX Suggests Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Jinfeng Zhu ◽  
Chen Luo ◽  
Jiefeng Zhao ◽  
Xiaojian Zhu ◽  
Kang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Expression Level ◽  
Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p &lt; 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

scholarly journals Role of Disease Modifying Treatment in the Risk of Alloimmunization in Transfused Patients with Myelodysplastic Syndromes: A Population-Based Study

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4253-4253
Author(s):  
Hanne Rozema ◽  
Robby Kibbelaar ◽  
Nic Veeger ◽  
Mels Hoogendoorn ◽  
Eric van Roon
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Cox Regression ◽  
Population Based ◽  
Incidence Rates ◽  
Blood Products ◽  
Cox Regression Analysis ◽  
In The Beginning ◽  
Observation Period

The majority of patients with myelodysplastic syndromes (MDS) require regular red blood cell (RBC) transfusions. Alloimmunization (AI) against blood products is an adverse event, causing time-consuming RBC compatibility testing. The reported incidence of AI in MDS patients varies greatly. Even though different studies on AI in MDS patients have been performed, there are still knowledge gaps. Current literature has not yet fully identified the risk factors and dynamics of AI in individual patients, nor has the influence of disease modifying treatment (DMT) been explored. Therefore, we performed this study to evaluate the effect of DMT on AI. An observational, population-based study, using the HemoBase registry, was performed including all newly diagnosed MDS patients between 2005 and 2017 in Friesland, a province of the Netherlands. All available information about treatment and transfusions, including transfusion dates, types, and treatment regimens, was collected from the electronic health records and laboratory systems. Follow-up occurred through March 2019. For our patient cohort, blood products were matched for AB0 and RhD, and transfused per the 'type and screen' policy (i.e. electronic matching of blood group phenotype between patient and donor). After a positive antibody screening, antibody identification and Rh/K phenotyping was performed and subsequent blood products were (cross)matched accordingly. The observation period was counted from first transfusion until last transfusion or first AI event. Univariate analyses and cumulative frequency distributions were performed to study possible risk factors and dynamics of AI. DMT was defined as hypomethylating agents, lenalidomide, chemotherapy and monoclonal antibodies. The effect of DMT as a temporary risk period on the risk of AI was estimated with incidence rates, relative risks (RR) and hazard ratios (HR) using a cox regression analysis. Follow-up was limited to 24 months for the cox regression analysis to avoid possible bias by survival differences. Statistical analyses were performed using IBM SPSS 24 and SAS 9.4. Out of 292 MDS patients, 236 patients received transfusions and were included in this study, covering 463 years of follow-up. AI occurred in 24 patients (10%). AI occurred mostly in the beginning of the observation period: Eighteen patients (75%) were alloimmunized after receiving 20 units of RBCs, whereas 22 patients (92%) showed AI after 45 units of RBCs (Figure 1). We found no significant risk factors for AI in MDS patients at baseline. DMT was given to 67 patients (28%) during the observation period. Patients on DMT received more RBC transfusions than patients that did not receive DMT (median of 33 (range: 3-154) and 11 (range: 0-322) RBC units respectively, p<0,001). Four AI events (6%) occurred in patients on DMT and 20 AI events (12%) occurred in patients not on DMT. Cox regression analysis of the first 24 months of follow-up showed an HR of 0.30 (95% CI: 0.07-1.31; p=0.11). The incidence rates per 100 person-years were 3.19 and 5.92 respectively. The corresponding RR was 0.54 (95% CI: 0.16-1.48; p=0.26). Based on our results, we conclude that the incidence of AI in an unselected, real world MDS population receiving RBC transfusions is 10% and predominantly occurred in the beginning of follow-up. Risk factors for AI at baseline could not be identified. Our data showed that patients on DMT received significantly more RBC transfusions but were less susceptible to AI. Therefore, extensive matching of blood products may not be necessary for patients on DMT. Larger studies are needed to confirm the protective effect of DMT on AI. Disclosures Rozema: Celgene: Other: Financial support for visiting MDS Foundation conference.

scholarly journals Application value of nomogram and prognostic factors of gastric cancer patients who underwent D2 radical lymphadenectomy

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Guang-Chuan Mu ◽  
Yuan Huang ◽  
Zhi-Ming Liu ◽  
Xiang-Hua Wu ◽  
Xin-Gan Qin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Cancer Patients ◽  
Cox Regression ◽  
Term Survival ◽  
Long Term Survival ◽  
Cox Regression Analysis ◽  
Gastric Cancer Patients

Abstract Background The aim of this study was to explore the prognostic factors and establish a nomogram to predict the long-term survival of gastric cancer patients. Methods The clinicopathological data of 421 gastric cancer patients, who were treated with radical D2 lymphadenectomy by the same surgical team between January 2009 and March 2017, were collected. The analysis of long-term survival was performed using Cox regression analysis. Based on the multivariate analysis results, a prognostic nomogram was formulated to predict the 5-year survival rate probability. Results In the present study, the total overall 3-year and 5-year survival rates were 58.7 and 45.8%, respectively. The results of the univariate Cox regression analysis revealed that tumor staging, tumor location, Borrmann type, the number of lymph nodes dissected, the number of lymph node metastases, positive lymph nodes ratio, lymphocyte count, serum albumin, CEA, CA153, CA199, BMI, tumor size, nerve invasion, and vascular invasion were prognostic factors for gastric cancer (all, P < 0.05). However, merely tumor staging, tumor location, positive lymph node ratio, CA199, BMI, tumor size, nerve invasion, and vascular invasion were independent risk factors, based on the results of the multivariate Cox regression analysis (all, P < 0.05). The nomogram based on eight independent prognostic factors revealed a well-degree of differentiation with a concordance index of 0.76 (95% CI: 0.72–0.79, P < 0.001), which was better than the AJCC-7 staging system (concordance index = 0.68). Conclusion The present study established a nomogram based on eight independent prognostic factors to predict long-term survival in gastric cancer patients. The nomogram would be beneficial for more accurately predicting the prognosis of gastric cancer, and provide important basis for making individualized treatment plans following surgery.

Effect of combined consideration of distinct signatures of VEGF and soluble VEGFR2 on prognostic implication in gastric cancer.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 56-56
Author(s):  
Chan-Young Ock ◽  
Ah-Rong Nam ◽  
Ju-Hee Bang ◽  
Tae-Yong Kim ◽  
Kyung-Hun Lee ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Growth Factor ◽  
Cox Regression ◽  
Linear Regression Analysis ◽  
Vegf Receptor ◽  
Prognostic Impact ◽  
Prognostic Implication ◽  
Cox Regression Analysis ◽  
Fibroblast Growth Factor Basic

56 Background: Anti-angiogenic strategy in gastric cancer (GC) has been highlighted again due to the recent success of ramucirumab and apatinib. Therefore, the comprehensive network of VEGF, soluble VEGF receptor-2 (sVEGFR2) and cytokines and other angiogenic factors (CAF) in GC and their prognostic impact would be of importance, although they have been poorly understood. We aimed to find out the CAF signature associated with VEGF and sVEGFR2, and to explore their prognostic implication in GC. Methods: We measured pretreatment serum levels of 52 CAFs, including VEGF and sVEGFR2, using multiplex bead immunoassays and ELISA, in 70 patients who were diagnosed with GC in Seoul National University Hospital, and treated with palliative chemotherapy. Linear regression analysis for correlating CAFs with VEGF and sVEGFR2, and survival analysis by log rank test and Cox regression analysis were performed. Results: The VEGF signature was shown to be associated with seven CAFs (interluekin [IL]-7, IL-12p70, IL-2Ra, IL-10, stem cell factor, Fibroblast growth factor-basic, IL-3). The sVEGFR2 signature was associated with IL-4 and platelet-derived growth factor beta, but VEGF and sVEGFR2 showed no association with each other. Patients with high VEGF had a tendency to have worse overall survival (OS) than those with low VEGF (11.2 months versus 16.7 months; P = 0.061). However, among patients with high-sVEGFR2, OS was not different according to VEGF (12.1 months, high-VEGF versus 15.1 months, low-VEGF; P = 0.546). Interestingly, the poor prognostic impact of high-VEGF was far significant in patients with low-sVEGFR2 (10.9 months versus 16.8 months; P = 0.036). With this perspective, VEGF/sVEGFR2 ratio was significantly correlated with worse OS in univariate as well as multivariate analysis (HR 1.78 [95% CI 1.08-2.94], P= 0.024). Conclusions: Based on the comprehensive network analysis of CAF, VEGF and sVEGFR2 had distinct CAF signatures in GC. Consideration of both VEGF and sVEGFR2 confers more accurate prognostic implication compared with VEGF alone in GC. Regarding the angiogenic aspect, VEGF/sVEGFR2 ratio is significantly correlated with survival outcome in GC.

scholarly journals High Expression of PABPC1 Predicts Worse Survival of Gastric Cancer Patients

2020 ◽  
Author(s):  
Tailai An ◽  
Lingna Deng ◽  
Zheng Yang ◽  
Cuicui Chai ◽  
Yan Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Mrna Translation ◽  
High Expression ◽  
Depth Of Invasion ◽  
Cox Regression Analysis

Abstract Background: Gastric cancer (GC) is one of the most common cancers with one of the highest mortality rates. Unfortunately, underlying molecular mechanisms contributing to GC have not been fully illuminated. PABPC1 is involved in a series of processes, such as mRNA translation, and mRNA deadenylation and decay. We performed this study to clarify the role of PABPC1 in GC. Methods: To evaluate PABPC1 expressions in GC and normal tissues, we performed bioinformatics analysis of data from TCGA. PABPC1 expressions were evaluated by immunohistochemical (IHC) staining of 170 GC specimens. Associations between PABPC1 expression and clinicopathological variables were analyzed. Independent predictive factors for survival of GC patients were determined by Cox regression analysis. Results: It was revealed by bioinformatics analysis that compared with normal gastric tissues, PABPC1 expressions in GC tissues were significantly higher (P=0.002, paired) (P=3.605e^-9, unpaired). It was revealed that PABPC1 expression was significantly associated with tumor size (P=0.008), Borrmann classification (P=0.003), vessel invasion (P=0.017), depth of invasion (P=0.032), lymph node metastasis (P=0.001), and TNM stage (P=0.019). It was demonstrated through Cox regression analysis that PABPC1 expression was a predictive factor for both overall survival (OS) (P<0.001) and disease-free survival (DFS) (P<0.001) of GC patients. Conclusions: Compared with that of normal gastric tissue, expression level of PABPC1 in GC tissue was significantly higher and PABPC1,s high expression was significantly associated with poorer survival, suggesting its potential as a therapeutic biomarker for GC.

scholarly journals Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

2021 ◽  
Vol 27 ◽  
Author(s):  
Weijun Ma ◽  
Weidong Li ◽  
Lei Xu ◽  
Lu Liu ◽  
Yu Xia ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Model ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Survival Outcomes ◽  
Activated T Cells ◽  
Single Nucleotide ◽  
Cox Regression Analysis ◽  
Immune Infiltration ◽  
Surgical Methods

Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.Results: Single nucleotide polymorphism (SNP), C &gt; T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4+ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

scholarly journals Integrated analysis of 1804 samples of six centers to construct and validate a robust immune-related prognostic signature associated with stromal cell abundance in tumor microenvironment for gastric cancer

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Junyu Huo ◽  
Ge Guan ◽  
Jinzhen Cai ◽  
Liqun Wu
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Risk Score ◽  
Stromal Cell ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
Integrated Analysis ◽  
Prognostic Signature ◽  
Cox Regression Analysis

Abstract Background Stromal cells in tumor microenvironment could promote immune escape through a variety of mechanisms, but there are lacking research in the field of gastric cancer (GC). Methods We identified differential expressed immune-related genes (DEIRGs) between the high- and low-stromal cell abundance GC samples in The Cancer Genome Atlas and GSE84437 datasets. A risk score was constructed basing on univariate cox regression analysis, LASSO regression analysis, and multivariate cox regression analysis in the training cohort (n=772). The median value of the risk score was used to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE26253, n=432; GSE62254, n=300; GSE15459, n=191; GSE26901, n=109) from the Gene Expression Omnibus (GEO) database. The immune cell infiltration was quantified by the CIBERSORT method. Results The risk score contained 6 genes (AKT3, APOD, FAM19A5, LTBP3, NOV, and NOX4) showed good performance in predicting 5-year overall survival (OS) rate and 5-year recurrence-free survival (RFS) rate of GC patients. The risk death and recurrence of GC patients growing with the increasing risk score. The patients were clustered into three subtypes according to the infiltration of 22 kinds of immune cells quantified by the CIBERSORT method. The proportion of cluster A with the worst prognosis in the high-risk group was significantly higher than that in the low-risk group; the risk score of cluster C subtype with the best prognosis was significantly lower than that of the other two subtypes. Conclusion This study established and validated a robust prognostic model for gastric cancer by integrated analysis 1804 samples of six centers, and its mechanism was explored in combination with immune cell infiltration characterization.

Benefit of adjuvant chemotherapy in patients with T4, UICC II colon cancer.

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 700-700
Author(s):  
Andreas Teufel ◽  
Michael Gerken ◽  
Janine Hartl ◽  
Timo Itzel ◽  
Stefan Fichtner-Feigl ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Adjuvant Chemotherapy ◽  
Cox Regression ◽  
Standard Of Care ◽  
Population Based ◽  
Postoperative Chemotherapy ◽  
R0 Resection ◽  
Uicc Stage ◽  
Cox Regression Analysis ◽  
High Risk Situation

700 Background: Colorectal cancer is the third most common cancer and a major cause of morbidity and mortality worldwide. Adjuvant chemotherapy is considered standard of care in patients with UICC stage III colon cancer after R0-resection. For patients with UICC stage II colon cancer, a benefit of adjuvant therapy was not demonstrated. However, there is an ongoing discussion whether adjuvant chemotherapy may be beneficial for a subgroup of UICC II patients with "high-risk situation" (e.g., T4 situation). Methods: We investigated our Bavarian, population based (2.1 million inhabitants) cohort of 1,937 patients with UICC II CRC for a benefit of adjuvant chemotherapy in patients with larger (T4) tumors. Patients over 80 years were excluded. Of these patients, 240 patients had a T4 tumor (12%). 77 of all T4 patients received postoperative chemotherapy (33%). Survival analyses were performed using Kaplan Meier analysis and Cox regression models. Results: Patients with a T4 tumor who received postoperative chemotherapy had a highly significant survival benefit with respect to overall survival (p<0.001) and recurrence free survival (p=0.008). However, no difference was seen between oxaliplatin containing or non-oxaliplatin containing treatment regimens. Finally, G2 and G3 tumors were demonstrated to particularly benefit from adjuvant treatment. Chemotherapy, age at diagnosis and tumor grading remained independent risk factors in multivariable cox regression analysis. Conclusions: Overall, our retrospective study demonstrated a significant benefit of an adjuvant chemotherapy in the T4 UICC II subgroup of patients with colon cancer. Based on our data adjuvant chemotherapy should strongly be considered in these patients.

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