The timing from perioperative chemotherapy and disease recurrence could have clinical impact on survival in bladder cancer patients treated with salvage chemotherapy.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 444-444
Author(s):  
Eiji Kikuchi ◽  
Nozomi Hayakawa ◽  
Koichirou Ogihara ◽  
Minami Omura ◽  
Ryuichi Mizuno ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Radical Cystectomy ◽  
Cox Regression ◽  
Prognostic Indicator ◽  
Disease Recurrence ◽  
Salvage Chemotherapy ◽  
Perioperative Chemotherapy ◽  
Cox Regression Analysis

444 Background: Our aim was to clarify whether the duration between perioperative chemotherapy and disease recurrence could affect therapeutic efficacy of salvage chemotherapy in bladder cancer patients treated with radical cystectomy. Methods: We retrospectively identified 201 patients treated with radical cystectomy and perioperative chemotherapy of neoadjuvant chemotherapy (NAC) and/or adjuvant chemotherapy (AC) for bladder cancer at our 7 institutions between 2003 and 2015. Of them 56 patients received salvage chemotherapy for disease recurrence and were included in the present analysis. We classified these patients according to the time from perioperative chemotherapy received to disease recurrence ( < 12 months, 12-24 months, and 24 < months) and compared their clinical characteristics and survival outcomes. Results: Overall, 33, 14, and 9 patients developed disease recurrence in < 12 months, 12-24 months, and < 24 months, respectively after perioperative chemotherapy. Patients in the 12-24 months group had a higher smoking rate compared to those in the other two groups, and were higher rate of female in comparison to the < 24 months group. Twenty-four (42.8%) patients received NAC alone, 23 (41.1%) received AC alone, and 9 (16.1%) received both NAC and AC. Twenty-two (66.7%), 9 (64%), and 4 (44.4%) patients received NAC in the < 12 months group, the 12-24 months group, and the < 24 months group, respectively. Furthermore, 19 (57.6%), 7 (50%), and 6 (66.7%) patients received AC in the < 12 months group, the 12-24 months group, and the < 24 months group, respectively. The 5 year overall survival in the < 12 months group was 26.6%, which was significantly lower than those in the 12-24 months group (51.1%, p < 0.001) and in the 24 months group (46.9%, p = 0.014). Multivariate Cox regression analysis revealed that disease recurrence after perioperative chemotherapy within 12 months was the only independent prognostic indicator for overall death (p = 0.032). Conclusions: Bladder cancer patients with disease recurrence within 12 months from their perioperative chemotherapy have a worse overall survival after salvage chemotherapy.

scholarly journals Development of a novel prognostic signature for predicting the overall survival of bladder cancer patients

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Huamei Tang ◽  
Lijuan Kan ◽  
Tong Ou ◽  
Dayang Chen ◽  
Xiaowen Dou ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Cox Regression ◽  
Test Group ◽  
Training Group ◽  
The Cancer Genome Atlas ◽  
Methylation Site ◽  
Cox Regression Analysis

Abstract Background: Bladder cancer is one of the most common malignancies. So far, no effective biomarker for bladder cancer prognosis has been identified. Aberrant DNA methylation is frequently observed in the bladder cancer and holds considerable promise as a biomarker for predicting the overall survival (OS) of patients. Materials and methods: We downloaded the DNA methylation and transcriptome data for bladder cancer from The Cancer Genome Atlas (TCGA), a public database, screened hypo-methylated and up-regulated genes, similarly, hyper-methylation with low expression genes, then retrieved the relevant methylation sites. Cox regression analysis was used to identify a nine-methylation site signature of a training group. Predictive ability was validated in a test group by receiver operating characteristic (ROC) analysis. Results: We identified nine bladder cancer-specific methylation sites as potential prognostic biomarkers and established a risk score system based on the methylation site signature to evaluate the OS. The performance of the signature was accurate, with area under curve was 0.73 in the training group and 0.71 in the test group. Taking clinical features into consideration, we constructed a nomogram consisting of the nine-methylation site signature and patients’ clinical variables, and found that the signature was an independent risk factor. Conclusions: Overall, the significant nine methylation sites could be novel prediction biomarkers, which could aid in treatment and also predict the overall survival likelihoods of bladder cancer patients.

scholarly journals Identification of an 11-Autophagy-Related-Gene Signature as Promising Prognostic Biomarker for Bladder Cancer Patients

Biology ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 375
Author(s):  
Chaoting Zhou ◽  
Alex Heng Li ◽  
Shan Liu ◽  
Hong Sun
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Related Gene ◽  
Training Cohort ◽  
Cox Regression Analysis ◽  
Therapeutic Decisions

Background: Survival rates for highly invasive bladder cancer (BC) patients have been very low, with a 5-year survival rate of 6%. Accurate prediction of tumor progression and survival is important for diagnosis and therapeutic decisions for BC patients. Our study aims to develop an autophagy-related-gene (ARG) signature that helps to predict the survival of BC patients. Methods: RNA-seq data of 403 BC patients were retrieved from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) database. Univariate Cox regression analysis was performed to identify overall survival (OS)-related ARGs. The Lasso Cox regression model was applied to establish an ARG signature in the TCGA training cohort (N = 203). The performance of the 11-gene ARG signature was further evaluated in a training cohort and an independent validation cohort (N = 200) using Kaplan-Meier OS curve analysis, receiver operating characteristic (ROC) analysis, as well as univariate and multivariate Cox regression analysis. Results: Our study identified an 11-gene ARG signature that is significantly associated with OS, including APOL1, ATG4B, BAG1, CASP3, DRAM1, ITGA3, KLHL24, P4HB, PRKCD, ULK2, and WDR45. The ARGs-derived high-risk bladder cancer patients exhibited significantly poor OS in both training and validation cohorts. The prognostic model showed good predictive efficacy, with the area under the ROC curve (AUCs) for 1-year, 3-year, and 5-year overall survival of 0.702 (0.695), 0.744 (0.640), and 0.794 (0.658) in the training and validation cohorts, respectively. A prognostic nomogram, which included the ARGs-derived risk factor, age and stage for eventual clinical translation, was established. Conclusion: We identified a novel ARG signature for risk-stratification and robust prediction of overall survival for BC patients.

scholarly journals Associations between body mass index and bladder cancer survival: Is the obesity paradox short-lived?

2021 ◽  
Vol 16 (5) ◽  
Author(s):  
Fernanda Arthuso ◽  
Adrian S. Fairey ◽  
Normand G. Boule ◽  
Kerry S. Courneya
Keyword(s):  
Body Mass Index ◽  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Radical Cystectomy ◽  
Body Mass ◽  
Cox Regression ◽  
Obesity Paradox ◽  
Step Function ◽  
Time Segment

Introduction: We investigated the associations of pre-surgical body mass index (BMI) with bladder cancer outcomes in patients treated with radical cystectomy. Methods: We retrospectively analyzed data from 488 bladder cancer patients treated with radical cystectomy between 1994 and 2007 and followed up until 2016. Cox regression with step function (time-segment analysis) was conducted for overall survival because the proportional hazard assumption was violated. Results: Of 488 bladder cancer patients, 155 (31.8%) were normal weight, 186 (38.1%) were overweight, and 147 (30.1%) were obese. During the median followup of 59.5 months, 363 (74.4%) patients died, including 197 (40.4%) from bladder cancer. In adjusted Cox regression analyses, BMI was not significantly associated with bladder cancer-specific survival for overweight (hazard ratio [HR] 0.79, 95% confidence interval [CI] 0.57–1.10, p=0.16) or obese (HR 0.76, 95% CI 0.52–1.09, p=0.13) patients. In the Cox regression with step function for overall survival, the time interaction was significant overall (p=0.020) and specifically for overweight patients (p=0.006). In the time-segment model, the HR for overweight during the first 63 months was 0.66 (95% CI 0.49–0.90, p=0.008), whereas it was 1.41 (95% CI 0.89–2.23, p=0.14) after 63 months. Although not statistically significant, a similar pattern was observed for obese patients. Conclusions: Our findings suggest that overweight and obese bladder cancer patients had better outcomes within the first five years after radical cystectomy; however, there were no differences in longer-term survival. These data suggest that the obesity paradox in bladder cancer patients treated with radical cystectomy may be short-lived.

scholarly journals A robust eleven-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts

2020 ◽  
Author(s):  
Jiaxing Lin ◽  
Jieping Yang ◽  
Xiao Xu ◽  
Yutao Wang ◽  
Meng Yu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
High Risk ◽  
B Cell ◽  
Cancer Patients ◽  
Prognostic Model ◽  
Cox Regression ◽  
Cell Memory ◽  
Cox Regression Analysis ◽  
B Cell Memory

Abstract Background: Bladder cancer is the tenth most common cancer in the world, but existing biomarkers and prognostic models are limited.Method: In this study, we used four bladder cancer cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases to perform univariate Cox regression analysis to identify common prognostic genes. We used selected genes to construct a prognostic model. Kaplan-Meier analysis, Receiver Operating Characteristic curve, and univariate and multivariate Cox analysis were used to evaluate the prognostic model for the four cohorts. Finally, a co-expression network, CIBERSORT, and ESTIMATE algorithm were used to explore the mechanism related to the model.Results: A total of 11 genes were identified from the four cohorts to construct the prognostic model, including eight risk genes (SERPINE2, PRR11, DSEL, DNM1, COMP, ELOVL4, RTKN, and MAPK12) and three protective genes (FABP6, C16orf74, and TNK1). The model and the 11 genes have excellent performance in predicting overall survival and have been confirmed in 5 cohorts. The model's predictive ability is stronger than other clinical features and has practical significance in clinical application.Through the analysis of the weighted co-expression network, the gene module related to the model was found, and the key genes in this module were mainly enriched in the items related to the tumor microenvironment. When comparing the level of immune cell infiltration in high-risk samples, B cell memory showed low infiltration in high-risk patients. Furthermore, in the case of low B cell memory infiltration and high-risk score, the prognosis of the patients was the worst.Conclusion: The model we developed has strong stability and good performance and can stratify the risk of bladder cancer patients, to achieve individualized treatment.

scholarly journals Efficacy and Safety of FLOT regimen vs. DCF, FOLFOX, and ECF regimens as Perioperative Chemotherapy Treatments for Resectable Gastric Cancer Patients

2021 ◽  
Author(s):  
Pegah Farrokhi ◽  
Alireza Sadeghi ◽  
Mehran sharifi ◽  
Payam Dadvand ◽  
Rachel Riechelmann ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Cox Regression ◽  
Progression Free Survival ◽  
R0 Resection ◽  
P Value ◽  
Perioperative Chemotherapy ◽  
Resectable Gastric Cancer ◽  
Gastric Cancer Patients

AbstractAimThis study aimed to evaluate and compare the efficacy and toxicity of common regimens used as perioperative chemotherapy including ECF, DCF, FOLFOX, and FLOT to identify the most effective chemotherapy regimen with less toxicity.Material and MethodsThis retrospective cohort study was based on 152 eligible gastric cancer patients recruited in a tertiary oncology hospital in Isfahan, Iran (2014-2019). All resectable gastric cancer patients who had received one of the four chemotherapy regimens including ECF, DCF, FOLFOX, or FLOT, and followed for at least one year (up to five years) were included. The primary endpoint of this study was Overall Survival (OS), Progression-Free Survival (PFS), Overall Response Rate (ORR), and R0 resection. We also considered toxicity according to CTCAE (v.4.0) criteria as a secondary endpoint. Cox -regression models were used applied to estimate OS and PFS time, controlled for relevant covariates.ResultsOf included patients, 32(21%), 51(33.7%), 37(24.3%), and 32(21%) had received ECF, DCF, FOLFOX and FLOT, respectively. After the median 25 months follow-up, overall survival was higher with the FLOT regimen in comparison with other regimens (hazard ratio [HR] = 0. 052). The median OS of the FLOT regimen was not reachable in Kaplan-Meier analysis and the median OS was 28, 26, and 23 months for DCF, FOLOFX, and ECF regimens, respectively. On the other hand, a median PFS of 25, 17, 15, and 14 months was observed for FLOT, DCF, FOLFOX, and ECF regimens, respectively (Log-rank = 0. 021). FLOT regimen showed 84. 4% ORR which was notably higher than other groups (p-value<0. 01).ConclusionsFor resectable gastric cancer patients, the perioperative FLOT regimen seemed to lead to a significant improvement in patients’ OS and PFS in comparison with ECF, DCF, and FOLFOX regimens. As such, the FLOT regimen could be considered as the optimal option for managing resectable gastric cancer patients.

Prognostic Nomogram Incorporating Immunohistochemical Results for the Overall Survival of Patients with Bladder Cancer.

2020 ◽  
Author(s):  
Tianwei Wang ◽  
Yunyan Wang
Keyword(s):  
Risk Factors ◽  
Overall Survival ◽  
Bladder Cancer ◽  
Risk Model ◽  
Cox Regression ◽  
Validation Cohort ◽  
Multivariable Analysis ◽  
Clinical Information ◽  
Internal Validation ◽  
Cox Regression Analysis

Abstract Objectives: In this study, we want to combine GATA3, VEGF, EGFR and Ki67 with clinical information to develop and validate a prognostic nomogram for bladder cancer.Methods: A total of 188 patients with clinical information and immunohistochemistry were enrolled in this study, from 1996 to 2018. Univariable and multivariable cox regression analysis was applied to identify risk factors for nomogram of overall survival (OS). The calibration of the nomogram was performed and the Area Under Curve (AUC) was calculated to assess the performance of the nomogram. Internal validation was performed with the validation cohort., the calibration curve and the AUC were calculated simultaneously.Results: Univariable and multivariable analysis showed that age (HR: 2.229; 95% CI: 1.162-4.274; P=0.016), histology (HR: 0.320; 95% CI: 0.136-0.751; P=0.009), GATA3 (HR: 0.348; 95% CI: 0.171-0.709; P=0.004), VEGF (HR: 2.295; 95% CI: 1.225-4.301; P=0.010) and grade (HR: 4.938; 95% CI: 1.339-18.207; P=0.016) remained as independent risk factors for OS. The age, histology, grade, GATA3 and VEGF were included to build the nomogram. The accuracy of the risk model was further verified with the C-index. The C-index were 0.65 (95% CI, 0.58-0.72) and 0.58 (95% CI, 0.46-0.70) in the training and validation cohort respectively. Conclusions: A combination of clinical variables with immunohistochemical results based nomogram would predict the overall survival of patients with bladder cancer.

scholarly journals Neutrophil to Lymphocyte Ratio as Prognostic Indicator for Patients with Esophageal Squamous Cell Cancer

2017 ◽  
Vol 32 (4) ◽  
pp. 409-414 ◽  
Author(s):  
Guo-Dong Gao ◽  
Bo Sun ◽  
Xian-Bin Wang ◽  
Shi-Meng Wang
Keyword(s):  
Overall Survival ◽  
Squamous Cell ◽  
Cox Regression ◽  
Cell Cancer ◽  
Prognostic Indicator ◽  
Neutrophil To Lymphocyte Ratio ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Leukocyte Counts ◽  
Clinical Records

Background This study aimed to evaluate the correlation between neutrophil to lymphocyte ratio (NLR) with overall survival (OS) of esophageal squamous cell carcinoma (ESCC) patients. Method Records of patients with diagnosed ESCC were reviewed. Leukocyte counts and patients' characteristics were extracted from their clinical records to calculate NLR. Correlation between NLR and baseline characteristics with overall survival (OS) was then analyzed using Cox regression. The patients were then separated into higher and lower NLR groups according to median NLR. OS was further compared between the 2 groups. Results A total of 1281 patients were included in the study. Cox regression analysis showed a significant correlation of NLR with OS of ESCC patients. The median pretreatment NLR was identified as 2.86. Higher NLR was associated with worse prognosis in terms of OS. Conclusions Pretreatment NLR is independently associated with OS of ESCC patients. Therefore, NLR may be used as a predictive indicator for pretreatment evaluation and adjustment of treatment regimen.

scholarly journals A robust eleven-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts

2020 ◽  
Author(s):  
Jiaxing Lin ◽  
Jieping Yang ◽  
Xiao Xu ◽  
Yutao Wang ◽  
Meng Yu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
High Risk ◽  
B Cell ◽  
Cancer Patients ◽  
Risk Score ◽  
Prognostic Model ◽  
Cell Memory ◽  
Cox Regression Analysis ◽  
B Cell Memory

Abstract Background: Bladder cancer is the tenth most common cancer globally, but existing biomarkers and prognostic models are limited. Method: In this study, we used four bladder cancer cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases to perform univariate Cox regression analysis to identify common prognostic genes. We used the least absolute shrinkage and selection operator regression to construct a prognostic Cox model. Kaplan-Meier analysis, receiver operating characteristic curve, and univariate / multivariate Cox analysis were used to evaluate the prognostic model for the four cohorts. Finally, a co-expression network, CIBERSORT, and ESTIMATE algorithm were used to explore the mechanism related to the model. Results: A total of 11 genes were identified from the four cohorts to construct the prognostic model, including eight risk genes (SERPINE2, PRR11, DSEL, DNM1, COMP, ELOVL4, RTKN, and MAPK12) and three protective genes (FABP6, C16orf74, and TNK1). The 11-genes model could stratify the risk of patients in all five cohorts, and the prognosis was worse in the group with a high-risk score. The area under the curve values of the five cohorts in the first year are all greater than 0.65. Furthermore, this model's predictive ability is stronger than that of age, gender, grade, and T stage. Through the weighted co-expression network analysis, the gene module related to the model was found, and the key genes in this module were mainly enriched in the tumor microenvironment. B cell memory showed low infiltration in high-risk patients. Furthermore, in the case of low B cell memory infiltration and high-risk score, the prognosis of the patients was the worst. Conclusion: The proposed eleven-genes model is a promising biomarker for estimating overall survival in bladder cancer. This model can be used to stratify the risk of bladder cancer patients, which is beneficial to the realization of individualized treatment.

scholarly journals A robust eleven-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts

2020 ◽  
Author(s):  
Jiaxing Lin ◽  
Jieping Yang ◽  
Xiao Xu ◽  
Yutao Wang ◽  
Meng Yu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
High Risk ◽  
B Cell ◽  
Cancer Patients ◽  
Risk Score ◽  
Prognostic Model ◽  
Cell Memory ◽  
Cox Regression Analysis ◽  
B Cell Memory

Abstract Background: Bladder cancer is the tenth most common cancer globally, but existing biomarkers and prognostic models are limited. Method: In this study, we used four bladder cancer cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases to perform univariate Cox regression analysis to identify common prognostic genes. We used the least absolute shrinkage and selection operator regression to construct a prognostic Cox model. Kaplan-Meier analysis, receiver operating characteristic curve, and univariate / multivariate Cox analysis were used to evaluate the prognostic model for the four cohorts. Finally, a co-expression network, CIBERSORT, and ESTIMATE algorithm were used to explore the mechanism related to the model.Results: A total of 11 genes were identified from the four cohorts to construct the prognostic model, including eight risk genes (SERPINE2, PRR11, DSEL, DNM1, COMP, ELOVL4, RTKN, and MAPK12) and three protective genes (FABP6, C16orf74, and TNK1). The 11-genes model could stratify the risk of patients in all five cohorts, and the prognosis was worse in the group with a high-risk score. The area under the curve values of the five cohorts in the first year are all greater than 0.65. Furthermore, this model's predictive ability is stronger than that of age, gender, grade, and T stage. Through the weighted co-expression network analysis, the gene module related to the model was found, and the key genes in this module were mainly enriched in the tumor microenvironment. B cell memory showed low infiltration in high-risk patients. Furthermore, in the case of low B cell memory infiltration and high-risk score, the prognosis of the patients was the worst.Conclusion: The proposed eleven-genes model is a promising biomarker for estimating overall survival in bladder cancer. This model can be used to stratify the risk of bladder cancer patients, which is beneficial to the realization of individualized treatment.

Sign in / Sign up

Export Citation Format

Share Document