scholarly journals A quantified risk-scoring system including the visceral fat area for peritoneal metastasis of gastric cancer

2019 ◽  
Vol Volume 11 ◽  
pp. 2903-2913 ◽  
Author(s):  
Xiaodong Chen ◽  
Weisheng Chen ◽  
Yunshi Huang ◽  
Jingxuan Xu ◽  
Yunpeng Zeng ◽  
...  
2020 ◽  
Author(s):  
Chenchen Mao ◽  
Mingming Shi ◽  
Hui Chen ◽  
Libin Xu ◽  
He Huang ◽  
...  

Abstract Background Although peritoneal metastasis (PM) is associated with poor prognosis in gastric cancer (GC) patients, it is difficult to discriminate preoperatively. Our previous study has demonstrated visceral fat area (VFA) is a better obesity index than body mass index (BMI) in predicting abdominal metastasis. Aim This study aimed to further explore the relationship between obesity and PM. Methods VFA was retrieved for 859 consecutive patients undergoing radical gastrectomy between January 1, 2009 and December 31, 2013. A receiver operating characteristic curve analysis was used to determine the BMI-specific cutoff values for VFA. Univariate and multivariate analyses evaluating the risk factors for PM at different BMI levels were performed. Results The optimal cutoff values for VFA were 67.28, 88.03, and 175.32 cm 2 for low, normal, and high BMI patients, respectively, and 18 (15.52%), 220 (40.15%), and 61 (31.28%) patients were classified as having high VFA in each group. Univariate logistic regression revealed that the association between high VFA and PM was not dependent on BMI (odds ratio [OR]=9.048, P=0.007 for low BMI, OR=3.827, P<0.001 for normal BMI, and OR=2.460, P=0.049 for high BMI). In multivariate logistic regression analysis, high VFA (OR=3.816, P<0.001) and vascular invasion (OR=1.951, P=0.039) were independent risk factors for PM only in the normal BMI group. Conclusions VFA only effectively predicted PM for GC patients with normal BMI, rather than those with low and high BMI. More attentions should be paid to those GC patients with high VFA and normal BMI.


2017 ◽  
Vol 116 (4) ◽  
pp. 533-544 ◽  
Author(s):  
Xiao-dong Chen ◽  
Chen-chen Mao ◽  
Wei-teng Zhang ◽  
Ji Lin ◽  
Rui-sen Wu ◽  
...  

2020 ◽  
Author(s):  
Yuzhi Wang ◽  
Yu Zou ◽  
Yi Zhang ◽  
Chengwen Li

The immune system and the tumor interact closely during tumor development. Aberrantly-expressed long non-coding RNAs (lncRNAs) may be potentially applied as diagnostic and prognostic markers for gastric cancer (GC). At present, the diagnosis and treatment of GC patients remain a formidable clinical challenge. This study aimed to build a risk scoring system to improve the prognosis of GC patients. In this study, ssGSEA was used to evaluate the infiltration of immune cells in GC tumor tissue samples, and the samples were split into a high immune cell infiltration group and a low immune cell infiltration group. 1262 differentially expressed lncRNAs between the high immune cell infiltration group and the low immune cell infiltration group. 3204 differentially expressed lncRNAs between GC tumor tissues and paracancerous tissues were identified. Then, 621 immune-related lncRNAs were screened using a Venn analysis based on the above results, and 85 prognostic lncRNAs were identified using a univariate Cox analysis. We constructed a prognostic signature using LASSO analysis and evaluated the predictive performance of the signature using ROC analysis. GO and KEGG enrichment analyses were performed on the lncRNAs using the R package, “clusterProfiler.” The TIMER online database was used to analyze correlations between the risk score and the abundances of the six types of immune cells. In conclusion, our study found that specific immune-related lncRNAs were clinically significant. These lncRNAs were used to construct a reliable prognostic signature and analyzed immune infiltrates, which may assist clinicians in developing individualized treatment strategies for GC patients.


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