Attributable fraction for the risk of death in patients with clinically localized muscle-invasive bladder cancer

2019 ◽  
Vol 18 (1) ◽  
pp. e809
Author(s):  
F. Audenet ◽  
B.S. Ferket ◽  
N. Waingankar ◽  
R. Jia ◽  
M.D. Galsky ◽  
...  
2021 ◽  
Author(s):  
Ruiliang Wang ◽  
Zongtai Zheng ◽  
Shiyu Mao ◽  
Wentao Zhang ◽  
Ji Liu ◽  
...  

Abstract Background: The progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) increases the risk of death. It is therefore important to find new relevant molecular models that will allow for effective prediction of the progression and prognosis of bladder cancer (BC).Methods: Using RNA-Sequence data of 49 BC patients in our center and weighted gene co-expression network analysis methods, a co-expression network of genes was developed and three key modules associated with malignant progression were selected. Based on the genes in three key modules, an eight-gene risk score was established using univariate Cox regression and the Least absolute shrinkage and selection operator Cox model in The Cancer Genome Atlas Program (TCGA) and validated in validation sets. Subsequently, a nomogram based on the risk score was constructed for prognostic prediction. The mRNA and protein expression levels of eight genes in cell lines and tissues were further investigated.Results: A novel eight-gene risk score was closely related to the malignant clinical features of BC and could predict the prognosis of patients in the training dataset (TCGA) and three validation sets (GSE3289 , GSE13507 and IMvigor210 trial). The nomogram showed good prognostic prediction and calibration. The mRNA and protein expression level of the eight genes were differentially expressed in cell lines and tissues.Conclusions: In our study, we established a novel eight-gene risk score which could predict the progression and prognoses of BC patients.


2021 ◽  
Author(s):  
Ruiliang Wang ◽  
Zongtai Zheng ◽  
Shiyu Mao ◽  
Wentao Zhang ◽  
Ji Liu ◽  
...  

Abstract Background: The progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) increases the risk of death. It is therefore important to find new relevant molecular models that will allow for effective prediction of the progression of bladder cancer (BC).Methods: Using RNA-Sequence data of 49 BC patients in our center and weighted gene co-expression network analysis methods, a co-expression network of genes was developed from which three key modules with prognostic value were selected using Univariate Cox regression in The Cancer Genome Atlas Program (TCGA). Subsequently, an eight-gene risk score was established using the Least absolute shrinkage and selection operator Cox model. Results: A novel eight-gene risk score was closely related to the malignant clinical features of BC and could predict the prognosis of patients in the training dataset (TCGA) and two validation sets (GSE3289 and GSE13507). Further, a nomogram for predicting the overall survival of patients was designed. The nomogram showed good calibration with clinical value through decision curve analysis. Lastly, we found that the mRNA and protein expression level of the eight genes were found to be differentially expressed in cell lines and tissue.Conclusions: In our study, we established a novel eight-gene risk score which could predict the progression and prognoses of BC patients.


2021 ◽  
Vol 11 ◽  
Author(s):  
Ruiliang Wang ◽  
Zongtai Zheng ◽  
Shiyu Mao ◽  
Wentao Zhang ◽  
Ji Liu ◽  
...  

The progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) increases the risk of death. It is therefore important to find new relevant molecular models that will allow for effective prediction of the progression and prognosis of bladder cancer (BC). Using RNA-Sequence data of 49 BC patients in Shanghai tenth people’s hospital (STPH) and weighted gene co-expression network analysis methods, a co-expression network of genes was developed and three key modules associated with malignant progression were selected. Based on the genes in three key modules, an eight-gene risk signature was established using univariate Cox regression and the Least absolute shrinkage and selection operator Cox model in The Cancer Genome Atlas Program (TCGA) and validated in validation sets. Subsequently, a nomogram based on the risk signature was constructed for prognostic prediction. The mRNA and protein expression levels of eight genes in cell lines and tissues were further investigated. The novel eight-gene risk signature was closely related to the malignant clinical features of BC and could predict the prognosis of patients in the training dataset (TCGA) and four validation sets (GSE32894, GSE13507, IMvigor210 trial, and STPH). The nomogram showed good prognostic prediction and calibration. The mRNA and protein expression levels of the eight genes were differentially expressed in cell lines and tissues. In our study, we established a novel eight-gene risk signature that could predict the progression and prognoses of BC patients.


Author(s):  
Jessica Marinaro ◽  
Alexander Zeymo ◽  
Jillian Egan ◽  
Filipe Carvalho ◽  
Ross Krasnow ◽  
...  

2007 ◽  
Vol 177 (4S) ◽  
pp. 114-115
Author(s):  
Young Deuk Choi ◽  
Kang Su Cho ◽  
Soung Yong Cho ◽  
Hyun Min Choi ◽  
Nam Hoon Cho

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