MRI-based Radiomics and ADC Values Are Related to Recurrence of Endometrial Carcinoma：A Preliminary Analysis 

2021 ◽  
Author(s):  
Kaiyue Zhang ◽  
Yu Zhang ◽  
Xin Fang ◽  
Jiangning Dong ◽  
Liting Qian
Keyword(s):  
Cox Regression ◽  
Myometrial Invasion ◽  
Inverse Correlation ◽  
Figo Stage ◽  
Clinicopathological Features ◽  
Prognostic Information ◽  
Adc Value ◽  
Kaplan Meier ◽  
Adc Values ◽  
Cox Analysis

Abstract Background: To identify predictive value of apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI)-based radiomics for all recurrences in patients with endometrial carcinoma (EC).Methods: One hundred and seventy-four EC patients who were treated with operation and followed up in our institution were retrospectively reviewed. Baseline clinicopathological features and ADC values were analyzed. Radiomic parameters were extracted on T2 weighted imaging and screened by logistic regression, and then a radiomics signature was developed to calculate the radiomic score (radscore). Kaplan–Meier analysis was performed and a Cox regression model was used to evaluate the correlation between clinicopathological features, ADC values and radiology with recurrence.Results: ADC values showed inverse correlation with recurrence, while radscore was positively associated with recurrence. In univariate analyses, FIGO stage, pathological types, myometrial invasion, lymphovascular space invasion (LVSI), ADC value and radscore were associated with recurrence. In multivariate Cox analysis, pathological types, ADC and radscore were independent risk factors for recurrence.Conclusions: ADC value and radscore were independent predictors of recurrence of EC, which can supplement prognostic information in addition to clinicopathological information and provide basis for individualized treatment and follow-up plan.

scholarly journals MRI-based radiomics and ADC values are related to recurrence of endometrial carcinoma: a preliminary analysis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kaiyue Zhang ◽  
Yu Zhang ◽  
Xin Fang ◽  
Jiangning Dong ◽  
Liting Qian
Keyword(s):  
Endometrial Carcinoma ◽  
Cox Regression ◽  
Myometrial Invasion ◽  
Test Group ◽  
Inverse Correlation ◽  
Training Group ◽  
Figo Stage ◽  
Clinicopathological Features ◽  
Prognostic Information ◽  
Adc Values

Abstract Background To identify predictive value of apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI)-based radiomics for all recurrences in patients with endometrial carcinoma (EC). Methods One hundred and seventy-four EC patients who were treated with operation and followed up in our institution were retrospectively reviewed, and the patients were divided into training and test group. Baseline clinicopathological features and mean ADC (ADCmean), minimum ADC (ADCmin), and maximum ADC (ADCmax) were analyzed. Radiomic parameters were extracted on T2 weighted images and screened by logistic regression, and then a radiomics signature was developed to calculate the radiomic score (radscore). In training group, Kaplan–Meier analysis was performed and a Cox regression model was used to evaluate the correlation between clinicopathological features, ADC values and radscore with recurrence, and verified in the test group. Results ADCmean showed inverse correlation with recurrence, while radscore was positively associated with recurrence. In univariate analyses, FIGO stage, pathological types, myometrial invasion, ADCmean, ADCmin and radscore were associated with recurrence. In the training group, multivariate Cox analysis showed that pathological types, ADCmean and radscore were independent risk factors for recurrence, which were verified in the test group. Conclusions ADCmean value and radscore were independent predictors of recurrence of EC, which can supplement prognostic information in addition to clinicopathological information and provide basis for individualized treatment and follow-up plan.

Right ventricular rather than left ventricular systolic dysfunction predicts outcome in patients undergoing transcatheter aortic valve implantation: insights from cardiac magnetic resonance imaging

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Koschutnik ◽  
C Nitsche ◽  
C Dona ◽  
V Dannenberg ◽  
A.A Kammerlander ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cox Regression ◽  
Systolic Dysfunction ◽  
Left Ventricular ◽  
Prognostic Information ◽  
Transcatheter Aortic Valve ◽  
Kaplan Meier ◽  
Lv Volumes ◽  
Valve Implantation ◽  
Rv Function

Abstract Background Right ventricular (RV) function is strongly associated with outcome in heart failure. Whether it also adds important prognostic information in patients undergoing transcatheter aortic valve implantation (TAVI) is unknown. Methods We consecutively enrolled patients with severe aortic stenosis (AS) scheduled for TAVI and preprocedural cardiac magnetic resonance (CMR) imaging. Kaplan-Meier estimates and multivariate Cox regression analyses were used to identify factors associated with outcome. A composite of heart failure hospitalization and/or cardiovascular death was selected as primary study endpoint. Results 423 consecutive patients (80.7±7.3 years; 48% female) were prospectively included, 201 (48%) underwent CMR imaging. 55 (27%) patients presented with RV systolic dysfunction (RVSD) defined by RV ejection fraction (RVEF) <45%. RVSD was associated with male sex (69 vs. 40%; p<0.001), New York Heart Association (NYHA) functional status (NYHA ≥ III: 89 vs. 57%; p<0.001), NT-proBNP serum levels (9365 vs. 2715 pg/mL; p<0.001), and history of atrial fibrillation (AF: 51 vs. 30%; p=0.005). On CMR, RVSD was associated with left ventricular (LV) volumes (end-diastolic: 187 vs. 137 mL, end-systolic: 119 vs. 53 mL; p<0.001) and EF (39 vs. 64%; p<0.001). A total of 51 events (37 deaths, 14 hospitalizations for heart failure) occurred during follow-up (9.8±9 months). While LVSD (LVEF <50%) was not significantly associated with outcome (HR 0.83, 95% CI: 0.33 – 2.11; p=0.694), RVSD showed a strong and independent association with event-free survival by multivariate Cox regression analysis (HR 2.47, 95% CI: 1.07–5.73; p=0.035), which was adjusted for all relevant CMR parameters (LV volumes and EF), cardiovascular risk factors (sex, NYHA, AF, diabetes mellitus type II, use of diuretics), and routine biomarkers (NT-proBNP, creatinine). Conclusions RVSD rather than LVSD, as determined on CMR, is an important predictor of outcome in patients undergoing TAVI. RV function might thus add useful prognostic information on top of established risk factors. Figure 1. Kaplan-Meier survival curves Funding Acknowledgement Type of funding source: None

scholarly journals Immune Cell Infiltration in the Microenvironment of Liver Oligometastasis from Colorectal Cancer: Intratumoural CD8/CD3 Ratio Is a Valuable Prognostic Index for Patients Undergoing Liver Metastasectomy

Cancers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1922 ◽  
Author(s):  
Jianhong Peng ◽  
Yongchun Wang ◽  
Rongxin Zhang ◽  
Yuxiang Deng ◽  
Binyi Xiao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastases ◽  
Immune Cell ◽  
Cox Regression ◽  
Simultaneous Detection ◽  
Prognostic Index ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Information ◽  
Kaplan Meier

Background: A comprehensive investigation into immune cell infiltration provides more accurate and reliable prognostic information for patients with colorectal liver oligometastases (CLO) after liver metastasectomy. Methods: Simultaneous detection of the immune constituents CD3+, CD8+, Foxp3+ T, and α-SMA+ cells in the liver oligometastasis of 133 patients was conducted using a four-colour immunohistochemical multiplex technique. Immune cells were quantified, and tumour-infiltrating lymphocyte (TIL) ratios were subsequently calculated. Correlation analysis was performed using Pearson’s correlation. Recurrence-free survival (RFS) and overall survival (OS) for TIL ratios were analysed using the Kaplan–Meier method and Cox regression models. Results: Significantly fewer CD3+, CD8+, and Foxp3+ T cells were observed in the intratumoural region than in the peritumoural region of liver metastases. CD3+, CD8+, Foxp3+ T, and α-SMA+ cells showed significantly positive correlations with each other both in the intratumoural and peritumoural regions of liver metastases. Only the CD8/CD3 TIL ratio demonstrated a positive correlation between intratumoural and peritumoural regions of liver metastases (r = 0.541, p < 0.001). Patients with high intratumoural CD8/CD3 ratios had significantly longer 3-year RFS (59.0% vs. 47.4%, p = 0.035) and 3-year OS rates (83.3% vs. 65.8%, p = 0.007) than those with low intratumoural CD8/CD3 ratios. Multivariate analyses revealed that the intratumoural CD8/CD3 ratio was independently associated with RFS (HR = 0.593; 95% CI = 0.357–0.985; p = 0.043) and OS (HR = 0.391; 95% CI = 0.193–0.794; p = 0.009). Conclusion: These findings offer a better understanding of the prognostic value of immune cell infiltration on liver oligometastasis from colorectal cancer.

scholarly journals Analysis of the Differential Expression and Prognostic Relationship of DEGs in AML based on TCGA Database

2020 ◽  
Author(s):  
Hang Zhang ◽  
Qian Li ◽  
Lan Li ◽  
Yue Gao ◽  
Rong Rong ◽  
...  
Keyword(s):  
Cox Regression ◽  
Differentially Expressed Gene ◽  
Clinical Information ◽  
Enrichment Score ◽  
Clinical Samples ◽  
Rna Seq ◽  
Survival Group ◽  
Hematopoietic Stem ◽  
Kaplan Meier ◽  
Cox Analysis

Abstract Background: Acute myeloid leukemia (AML) is a common and lethal hematological malignant hyperplastic disease originating from hematopoietic stem cells. The purpose of this study is to obtain the key AML survival-related differentially expressed gene. Methods: RNA sequencing (RNA-Seq) data and clinical information of patients were downloaded from the TCGA-LAML database. We focused the intersectional genes of survival-related DEGs, cytogenetics risk related-DEGs, and the top 10 pathways of both up- and down-regulated of Normalization Enrichment Score (NES). Multivariate Cox regression analyses were performed to analyze the independent factors for AML. The Kaplan–Meier and Nomogram analyses were plotted to predict and compare survival of AML patients. The validation of DEGs were performed by a clinical follow-up investigation.Results: 151 RNA-Seq samples for 60,488 genes and 200 clinical samples were selected from the TCGA-database. After filtering with the conditions about survival-related DEGs, cytogenetics-risk associated, and predicted in top 10 pathways, IGHM was the only remaining gene. Cox analysis showed that IGHM expression and age displayed were intendent factors to the patients’ survival (P<0.05). Higher IGHM expression was identified in poor survival group (P<0.05), with 68%, 43%, and 30% in 1, 3, and 5-year survival investigation. GSEA analysis revealed that IGHM were mainly enriched in the immune response. In Chinese population, IGHM displayed its significance not in the childhood AML patients but in adult ones. Conclusion: High expression of IHGM gene is an independent risky factor for the survival of patients with AML, which can be an important molecular marker for AML prognosis.

scholarly journals A Novel Ferroptosis-Related Long Non-coding RNA Prognostic Risk Model for Gastric Cancer

2021 ◽  
Author(s):  
Shenglan Huang ◽  
Dan Li ◽  
Lingling Zhuang ◽  
Liying Sun ◽  
Jianbing Wu
Keyword(s):  
Gastric Cancer ◽  
Risk Score ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Clinical Stage ◽  
Curve Analysis ◽  
Clinicopathological Features ◽  
Roc Curve Analysis ◽  
Kaplan Meier

Abstract Background：Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is a novel and distinct type of non-apoptotic cell death that is closely associated with metabolism, redox biology, and tumor prognosis. Recently, ferroptosis-related long non-coding RNAs (lncRNAs) have received increasing attention in predicting cancer prognosis. Thus, we aimed to construct an ferroptosis-related lncRNAs signature for predicting the prognosis of patients with gastric cancer.Methods：We built an ferroptosis-related lncRNA risk signature by using Cox regression based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. Cox regression was performed to explore whether the signature could be used as an independent factor. A nomogram was built involving the risk score and clinicopathological features. Furthermore, we explored the biological functions and immune states in two groups.Results：Eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in gastric cancer. Kaplan–Meier curve analysis revealed that patients in the high-risk group had worse survival than those in the low-risk group. The survival outcome was also appropriate for subgroup analysis, including age, sex, grade, and clinical stage. Multivariate Cox regression analysis and receiver operating characteristic (ROC) curve analysis demonstrated that the risk score was an independent prognostic factor and superior to traditional clinicopathological features in predicting GC prognosis. Next, we established a nomogram according to clinical parameters (age, sex, grade, and clinical stage) and risk score. All the verified results, including ROC curve analysis, calibration curve, and decision curve analysis, demonstrated that the nomogram could accurately predict the survival of patients with gastric cancer. Gene set enrichment analysis revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation.Conclusion: We established a novel ferroptosis-related prognostic risk signature including eight lncRNAs and constructed a nomogram to predict the prognosis of gastric cancer patients, which may improve prognostic predictive accuracy and guide individualized treatment for patients with GC.

scholarly journals Histopathological and Genomic Grading Provide Complementary Prognostic Information in Breast Cancer: A Study on Publicly Available Datasets

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Nilotpal Chowdhury
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Indicator ◽  
Rank Test ◽  
Prognostic Impact ◽  
Prognostic Information ◽  
Free Survival ◽  
Kaplan Meier ◽  
Hazard Ratios ◽  
Significant Prognostic Indicator

The genomic grade (GG) for breast cancer is thought to be the genomic counterpart of histopathological grade (HG). The motivation behind this study was to see whether HG retains its prognostic impact even when adjusted for GG, or whether it can be replaced by the latter. Four publicly available gene expression datasets were analyzed. Kaplan-Meier curves, log rank test, and Cox regression were used to study recurrence-free survival (RFS) and distant metastasis-free survival (DMFS). HG remained a significant prognostic indicator in low GG tumors (P = 0.003 for DMFS, P< 0.001 for RFS) but not in high GG tumors. HG grade 2 tumors differed significantly from HG grade 1 tumors, underlining the prognostic role of intermediate HG tumors. Additionally, GG could stratify HG 1 as well as HG 2 tumors into distinct prognostic groups. HG and GG add independent prognostic information to each other. However, the prognostic effects of both HG and GG are time varying, with the hazard ratios of high HG and GG tumors being markedly attenuated over time.

scholarly journals Gene Expression Profiling for Survival Prediction in Pediatric Rhabdomyosarcomas: A Report From the Children's Oncology Group

2010 ◽  
Vol 28 (7) ◽  
pp. 1240-1246 ◽  
Author(s):  
Elai Davicioni ◽  
James R. Anderson ◽  
Jonathan D. Buckley ◽  
William H. Meyer ◽  
Timothy J. Triche
Keyword(s):  
Gene Expression ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Expression Patterns ◽  
Good Prognosis ◽  
Survival Prediction ◽  
Oncology Group ◽  
Prognostic Information ◽  
Kaplan Meier ◽  
Highly Correlated

Purpose We investigated whether tumors from diagnostic biopsies of primary rhabdomyosarcoma (RMS) contain relevant prognostic information in the form of gene expression signatures that can be used to model and predict outcome of patients. Patients and Methods A 22,000-probe set microarray was used to evaluate 120 RMS specimens and correlate gene expression patterns to survival. Multivariate gene expression models or metagenes were developed using cross-validated Cox regression proportional hazards modeling and were evaluated using Kaplan-Meier analysis. Results A 34-metagene, based on expression patterns of 34 genes, was highly predictive of outcome. It was not highly correlated with individual clinical risk factors such as patient age, stage, tumor size, or histology. However, it was correlated with a risk classification used by the Children's Oncology Group and the biologic subsets of alveolar histology tumors. Conclusion These data support further evaluation of RMS metagenes to discriminate patients with good prognosis from those with poor prognosis, with the potential to direct risk-adapted therapy.

scholarly journals A Novel Four-Gene Prognostic Signature as a Risk Biomarker in Cervical Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jun Wang ◽  
Hua Zheng ◽  
Yatian Han ◽  
Geng Wang ◽  
Yanbin Li
Keyword(s):  
Cervical Cancer ◽  
Cox Regression ◽  
Treatment Options ◽  
Treatment Strategies ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Prognostic Signature ◽  
Tissue Samples ◽  
Kaplan Meier ◽  
Cox Analysis

Background. Cervical cancer (CC) is a major malignancy affecting women worldwide, with limited treatment options for patients with advanced disease. The aim of this study was to identify novel prognostic biomarkers for CC. Methods. RNA-Seq data from four Gene Expression Omnibus datasets (GSE5787, GSE6791, GSE26511, and GSE63514) were used to identify differentially expressed genes (DEGs) between CC and normal cervical tissues. Functional and enrichment analyses of the DEGs were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Oncomine database, Cytoscape software, and Kaplan-Meier survival analyses were used for in-depth screening of hub DEGs. The Cox regression was then used to develop a prognostic signature, which was in turn used to create a nomogram. Results. A total of 207 DEGs were identified in the tissue samples, eight of which were prognostically significant in terms of overall survival (OS). Thereafter, a novel four-gene signature consisting of DSG2, MMP1, SPP1, and MCM2 was developed and validated using stepwise Cox analysis. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.785, 0.609, and 0.686 in the training, verification, and combination groups, respectively. The protein expression levels of the four genes were well validated by the western blotting. Moreover, the nomogram analysis showed that a combination of this four-gene signature plus lymph node metastasis (LNM) status effectively predicted the 1- and 3-year OS probabilities of CC patients with accuracies of 69.01% and 83.93%, respectively. Conclusions. We developed a four-gene signature that can accurately predict the prognosis in terms of OS, of CC patients, and could be a valuable tool for designing treatment strategies.

scholarly journals Role of diffusion weighted MRI in characterization of renal diseases

2018 ◽  
Vol 5 (6) ◽  
pp. 1485
Author(s):  
Pankaj Kumar ◽  
Yashpaul . ◽  
P. K. Soni ◽  
Dhiraj Kapoor ◽  
Rajesh Kumar ◽  
...  
Keyword(s):  
Renal Failure ◽  
Renal Function ◽  
Inverse Correlation ◽  
Renal Diseases ◽  
Significant Inverse Correlation ◽  
Adc Value ◽  
Adc Values ◽  
The Mean

Background: MRI has the unique ability to show both structure and function objectively without any radiation exposure to the patient. Apparent diffusion coefficient (ADC) is a quantitative parameter that combines the effects of capillary perfusion and water diffusion. Renal parameters have shown inverse relationship with the ADC values in these studies. So, ADC values have a potential to serve as a marker of renal function. The aim of the present endeavor was to study the role of DW MRI in characterization of renal function and to find out the clinical use of DW MRI in renal diseases; and establish the relationship between renal function assessed by eGFR and that by DW MRI calculated in terms of ADC values in various renal diseasesMethods: Total 30 patients were included in the study. The study was carried out in department of radiodiagnosis at Dr. RPMGC Kangra. 1.5 Tesla MRI machine was used. The ADC value was calculated at upper, mid and lower pole of each kidney and the mean was taken. Then the mean of right and left kidneys was taken to calculate the mean ADC of the patient.Results: Serum creatinine in present study ranged from 0.67 to 13.9mg/dl, with mean value of 7.28mg/d. Serum urea ranged from 22 to 293mg/dl with the mean of 119.6mg/dl. There was significant inverse correlation occurred between ADC values and serum urea (r=-0.43, p=0.02). There was significant inverse correlation between ADC values and serum creatinine (p=0.01) and a positive correlation between eGFR and ADC values (r=0.14, p=0.47).Conclusions: ADC values consistently decreased with increasing stage of renal failure, so these can be used as an indirect maker of renal function. Authors conclude that lower would be the ADC value more advanced would be the stage of renal failure. DW MRI can also be detect early stages of renal failure even when the serum maker are within normal range.

scholarly journals Pseudogene HSPA7 is a Poor Prognostic Biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) and Correlated With Immune Infiltrates

2021 ◽  
Author(s):  
Chunjin Ding ◽  
Rundong He ◽  
Jinghan Zhang ◽  
Zhan Dong ◽  
Jun Wu
Keyword(s):  
Cox Regression ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Renal Clear Cell Carcinoma ◽  
Database Analysis ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
Infiltrating Cells ◽  
Cox Analysis

Abstract Background: Pseudogenes played important roles in tumorigenesis, while there are nearly no reports about the expression and roles of HSPA7 in the cancer. Methods: Firstly,we used Logistic regression,the KS test, the GEPIA database, UALCAN database and qRT-PCR to analyze the level of HSPA7 expressed in KIRC,then we used the Cox regression and the Kaplan-Meier curve to analyze the overall survival(OS) of KIRC patients with different Clinico-pathological parameters. Thirdly, we used the multivariate Cox analysis of influencing factors to compare the correlation between the HSPA7 expression level and the clinical parameters. Finally, we used multi-GSEA analysis and the Tumor Immunoassay Resource (TIMER) database to explore the functional role of HSPA7 in KIRC. Results: The HSPA7 is highly expressed in KIRC tumor tissues, and its expression is related to clinico-pathological features and survival in KIRCpatints.GSEA analysis displayed the high expression of HSPA7 in KIRC were related to several tumor-related and immune-related pathways. With the TIMER database analysis we showed that HSPA7 levels were correlated with the CD4+ T cells, neutrophils and Dendritic Cell.Conclusions: Our study showed that HSPA7 is very important in the tumor progression and may act as a poor prognostic biomarker for KIRC tumor by modulating immune infiltrating cells.

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