scholarly journals Independent Risk Factor Analysis for Major Cardiovascular Adverse Events in Patients with Mild Coronary Stenosis

2019 ◽  
Author(s):  
Wei Luo ◽  
Ru Zhao ◽  
YanQiu Song ◽  
Hui Zhao ◽  
WeiJun Ma ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Coronary Stenosis ◽  
Cox Regression ◽  
Risk Group ◽  
Adverse Cardiovascular Event ◽  
Cox Regression Analysis ◽  
Significant Difference ◽  
Independent Risk Factors ◽  
Hs Crp

Abstract Background: Independent risk factors for major adverse cardiovascular event (MACE) in patients with mild coronary stenosis are uncertain. This study aims to predict high-risk plaques detected by coronary computed tomographic angiography (CCTA) associated with indicative biomarkers.Methods: Totally 381 patients with mild coronary stenosis were included and MACE incidences were recorded through a 24-month follow-up. Totally 91 high-risk plaques are detected by CCTA, dividing into three plaque groups: high-risk group (HR), intermediate-risk group (IR) and low-risk group (LR). Specific blood biomarker measurements of hs-CRP, MMP-9, and MPO were taken simultaneously.Results: The mean age, levels of hs-CRP and MPO in HR and IR group were significantly higher than LR group. A considerably higher level of MMP-9 showed in HR group compared to LR group. The incidence rates of MACE were remarkably higher in HR group than LR group and IR group. Kaplan—Meier survival analysis demonstrated that the cumulative event—free survival rate of HR was significantly higher than that in LR and IR group and there were no significant difference between LR and IR group. The univariate COX regression analysis indicated that the age of patients, hs-CRP, MPO, and high-risk plaque scores≥2 were independent risk factors for MACE. Conclusion: Age, levels of hs-CRP and MPO, and high-risk plaque features informed by CCTA independently predicted MACE in patients with mild coronary stenosis. These results may improve the risk stratification in patients with mild coronary stenosis and suggest strategies for the individualized prevention programs.

scholarly journals Early and Midterm Outcome of TEVAR for Thoracic Aortic Pseudoaneurysm

2021 ◽  
Author(s):  
Hui Wang ◽  
Tun Wang ◽  
Hao He ◽  
Xin Li ◽  
Yuan Peng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Outcome ◽  
Cardiac Disease ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Aortic Pseudoaneurysm ◽  
Significant Difference ◽  
Independent Risk Factors ◽  
The Mean

Abstract Backgrounds: The prognosis of thoracic aortic pseudoaneurysm (TAP) after thoracic endovascular aortic repair (TEVAR) remains unclear. This study investigates the early and midterm clinical outcome as well as relevant risk factors of TAP patients following TEVAR therapy.Methods: From July 2010 to July 2020, 37 eligible TAP patients who underwent TEVAR were selected into our research. We retrospectively explored their baseline, perioperative and follow-up data. Fisher exact test and Kaplan-Meier method were applied for comparing difference between groups. Risk factors of late survival were discerned using Cox regression analysis.Results: There were 29 men and 12 women, with the mean age as 59.5±13.0 years (range, 30-82). The mean follow-up time was 30.7±28.3 months (range, 1-89). For early result, early mortality (≦30days) happened in 3(8.1%) zone 3 TAP patients versus 0 in zone 4 (p= 0.028); acute arterial embolism of lower extremity and type II endoleak respectively occurred in 1(2.7%) case. For midterm result, survival at 3 months, 1 year and 5 years was 88.8±5.3%, 75.9±7.5% and 68.3±9.9%, which showed significant difference between zone 2/3 versus zone 4 group (56.3±14.8% versus 72.9±13.2%, p= 0.013) and emergent versus elective TEVAR groups (0.0±0.0% versus 80.1±8.0%, p= 0.049). On multivariate Cox regression, lesions at zone 2/3 (HR 4.605, 95%CI 1.095-19.359), concomitant cardiac disease (HR 4.932, 95%CI 1.086-22.403) and emergent TEVAR (HR 4.196, 95%CI 1.042-16.891) were significant independent risk factors for worse late clinical outcome. Conclusions: TEVAR therapy is effective and safe with satisfactory early and midterm clinical outcome for TAP patients. Lesions at zone 2/3, concomitant cardiac disease and emergent TEVAR were independent risk factors for midterm survival outcome.

scholarly journals Identification of Seven-Gene Hypoxia Signature for Predicting Overall Survival of Hepatocellular Carcinoma

2020 ◽  
Author(s):  
YuPing Bai ◽  
Wenbo Qi ◽  
Le Liu ◽  
Jing Zhang ◽  
Lan Pang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Prognostic Models ◽  
Cox Regression Analysis ◽  
Significant Difference

Abstract Background: Hepatocellular carcinoma is ranked fifth among the most common cancer worldwide. Hypoxia can induce tumor growth, but the relationship with HCC prognosis remains unclear. Our study aims to construct a hypoxia-related multigene model to predict the prognosis of HCC. Methods: RNA-seq expression data and related clinical information were download from TCGA database and ICGC database, respectively. Univariate/multivariate Cox regression analysis was used to construct prognostic models. KM curve analysis, and ROC curve were used to evaluate the prognostic models, which were further verified in the clinical traits and ICGC database. GSEA analyzed pathway enrichment in high-risk groups. Nomogram was constructed to predict the personalized treatment of patients. Finally, real-time fluorescence quantitative PCR(RT-qPCR) was used to detect the expressions of KDELR3 and SCARB1 in normal hepatocytes and 4 hepatocellular carcinoma cells. Results: Through a series of analyses, 7 prognostic markers related to HCC survival were constructed. HCC patients were divided into the high and low risk group, and the results of KM curve showed that there was a significant difference between the two groups. Stratified analysis，found that there were significant differences in risk values of different ages, genders, stages and grades, which could be used as independent predictors. In addition, we assessed the risk value in the clinical traits analysis and found that it could accelerate the progression of cancer, while the results of GSEA enrichment analysis showed that the high-risk group patients were mainly distributed in the cell cycle and other pathways. Then, Nomogram was constructed to predict the overall survival of patients. Finally, RT-qPCR showed that KDELR3 and SCARB1 were highly expressed in HepG2 and L02, respectively. Conclusion: This study provides a potential diagnostic indicator for HCC patients, and help clinicians to deepen the comprehension in HCC pathogenesis so as to make personalized medical decisions.

scholarly journals Identification of Seven-Gene Hypoxia Signature for Predicting Overall Survival of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuping Bai ◽  
Wenbo Qi ◽  
Le Liu ◽  
Jing Zhang ◽  
Lan Pang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Disease Free Survival ◽  
High Risk Group ◽  
Prognostic Models ◽  
Cox Regression Analysis ◽  
Significant Difference

BackgroundHepatocellular carcinoma (HCC) is ranked fifth among the most common cancer worldwide. Hypoxia can induce tumor growth, but the relationship with HCC prognosis remains unclear. Our study aims to construct a hypoxia-related multigene model to predict the prognosis of HCC.MethodsRNA-seq expression data and related clinical information were download from TCGA database and ICGC database, respectively. Univariate/multivariate Cox regression analysis was used to construct prognostic models. KM curve analysis, and ROC curve were used to evaluate the prognostic models, which were further verified in the clinical traits and ICGC database. GSEA analyzed pathway enrichment in high-risk groups. Nomogram was constructed to predict the personalized treatment of patients. Finally, real-time fluorescence quantitative PCR (RT-qPCR) was used to detect the expressions of KDELR3 and SCARB1 in normal hepatocytes and 4 HCC cells. The expressions of SCARB1 in hepatocellular carcinoma tissue in 46 patients were detected by immunohistochemistry, and the correlation between its expressions and disease free survival of patient was calculated.ResultsThrough a series of analyses, seven prognostic markers related to HCC survival were constructed. HCC patients were divided into the high and low risk group, and the results of KM curve showed that there was a significant difference between the two groups. Stratified analysis, found that there were significant differences in risk values of different ages, genders, stages and grades, which could be used as independent predictors. In addition, we assessed the risk value in the clinical traits analysis and found that it could accelerate the progression of cancer, while the results of GSEA enrichment analysis showed that the high-risk group patients were mainly distributed in the cell cycle and other pathways. Then, Nomogram was constructed to predict the overall survival of patients. Finally, RT-qPCR showed that KDELR3 and SCARB1 were highly expressed in HepG2 and L02, respectively. Results of IHC staining showed that SCARB1 was highly expressed in cancer tissues compared to adjacent normal liver tissues and its expression was related to hepatocellular carcinoma differentiation status. The Kaplan-Meier survival showed a poor percent survival in the SCARB1 high group compared to that in the SCARB1 low group.ConclusionThis study provides a potential diagnostic indicator for HCC patients, and help clinicians to deepen the comprehension in HCC pathogenesis so as to make personalized medical decisions.

scholarly journals A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110279
Author(s):  
Qinping Guo ◽  
Yinquan Wang ◽  
Jie An ◽  
Siben Wang ◽  
Xiushan Dong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Cox Regression ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Signet Ring ◽  
Ring Cell ◽  
Independent Risk Factors

Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions.

scholarly journals Constructing the Logical Regression Model to Predict the Target of Jianpi Jiedu Decoction in the Treatment of Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Rongjie Zhang ◽  
Yan Chen ◽  
Ge Zhou ◽  
Baoguo Sun ◽  
Yue Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Regression Model ◽  
Target Genes ◽  
Cox Regression ◽  
Risk Group ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Prognostic Analysis ◽  
Significant Difference

Objectives. The purpose of this study was to identify the molecular mechanism and prognosis-related genes of Jianpi Jiedu decoction in the treatment of hepatocellular carcinoma. Methods. The gene expression data of hepatocellular carcinoma samples and normal tissue samples were downloaded from TCGA database, and the potential targets of drug composition of Jianpi Jiedu decoction were obtained from TCMSP database. The genes were screened out in order to obtain the expression of these target genes in patients with hepatocellular carcinoma. The differential expression of target genes was analyzed by R software, and the genes related to prognosis were screened by univariate Cox regression analysis. Then, the LASSO model was constructed for risk assessment and survival analysis between different risk groups. At the same time, independent prognostic analysis, GSEA analysis, and prognostic analysis of single gene in patients with hepatocellular carcinoma were performed. Results. 174 compounds of traditional Chinese medicine were screened by TCMSP database, corresponding to 122 potential targets. 39 upregulated genes and 9 downregulated genes were screened out. A total of 20 candidate prognostic related genes were screened out by univariate Cox analysis, of which 12 prognostic genes were involved in the construction of the LASSO regression model. There was a significant difference in survival time between the high-risk group and low-risk group ( p < 0.05 ). Among the genes related to prognosis, the expression levels of CCNB1, NQO1, NUF2, and CHEK1 were high in tumor tissues ( p < 0.05 ). Survival analysis showed that the high expression levels of these four genes were significantly correlated with poor prognosis of HCC ( p < 0.05 ). GSEA analysis showed that the main KEGG enrichment pathways were lysine degradation, folate carbon pool, citrate cycle, and transcription factors. Conclusions. In the study, we found that therapy target genes of Jianpi Jiedu decoction were mainly involved in metabolism and apoptosis in hepatocellular carcinoma, and there was a close relationship between the prognosis of hepatocellular carcinoma and the genes of CCNB1, NQO1, NUF2, and CHEK1.

scholarly journals A Risk Signature of Nine Autophagy-Related Genes Associated With Immune Microenvironment and Clinical Prognosis in Wilms Tumor

2021 ◽  
Author(s):  
Shaopei Ye ◽  
Wenbin Tang ◽  
Ke Huang
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Wilms Tumor ◽  
Risk Group ◽  
High Risk Group ◽  
Differentially Expressed ◽  
Clinical Prognosis ◽  
Cox Regression Analysis

Abstract Background: Autophagy is a biological process to eliminate dysfunctional organelles, aggregates or even long-lived proteins. . Nevertheless, the potential function and prognostic values of autophagy in Wilms Tumor (WT) are complex and remain to be clarifed. Therefore, we proposed to systematically examine the roles of autophagy-associated genes (ARGs) in WT.Methods: Here, we obtained differentially expressed autophagy-related genes (ARGs) between healthy and Wilms tumor from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology. Then univariate COX regression analysis and multivariate COX regression analysis were performed to acquire nine autophagy genes related to WT patients’ survival. According to the risk score, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis.Results: Eighteen DEARGs were identifed, and nine ARGs were fnally utilized to establish the FAGs based signature in the TCGA cohort. we found that patients in the high-risk group were associated with mutations in TP53. We further conducted CIBERSORT analysis, and found that the infiltration of Macrophage M1 was increased in the high-risk group. Finally, the expression levels of crucial ARGs were verifed by the experiment, which were consistent with our bioinformatics analysis.Conclusions: we emphasized the clinical significance of autophagy in WT, established a prediction system based on autophagy, and identified a promising therapeutic target of autophagy for WT.

scholarly journals Impact of Metabolic Syndrome on the Development of Cardiovascular Disease among Kazakhs in Remote Rural Areas of Xinjiang, China: A Cohort Study

2020 ◽  
Author(s):  
Wenwen Yang ◽  
Shuxia Guo ◽  
Haixia Wang ◽  
Yu Li ◽  
Xianghui Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Metabolic Syndrome ◽  
Rural Areas ◽  
Cox Regression ◽  
Baseline Survey ◽  
Minority Populations ◽  
Cox Regression Analysis ◽  
Independent Risk Factors

Abstract Background: Metabolic syndrome (MS) could promote the development of cardiovascular disease(CVD). The aim of this study was to examine the association of MS and its components with CVD among Kazakhs in Xinjiang. Methods: According to the geographical distribution of the minority populations in Xinjiang, we selected the representative prefecture (Yili). A total of 2,644 participants completed the baseline survey between April 2010 and December 2012. The follow-up survey was conducted from April 2016 to December 2016. Only 2,286 out of 2,644 participants were followed-up on, with a follow-up rate of 86.46%. Cox regression was used to evaluate the association of each component and the number of combinations of MS components on the development of CVD. Results: Multivariate Cox regression analysis showed that blood pressure (BP), waist circumference (WC), and triglycerides (TG) were independently associated with CVD. Participants with 1–5 MS components had an increased hazard ratio for developing CVD, from 1.82 to 8.59 (trend P<0.001), compared with those without any MS components. This trend persisted after adjusting for other general risk factors. The risk of developing CVD increased when TG and WC coexisted, or when TG/WC and BP coexisted. However, no significant interactions were found between BP , WC , and TG. Conclusions: BP , WC, and TG were independent risk factors for CVD in Kazakhs. In clinical practice, a more informative assessment may be obtained by taking into account the number of MS components.

scholarly journals Discovery and validation of immune- related long non-coding RNA biomarkers associated with prognosis in hepatocellular carcinoma

2020 ◽  
Author(s):  
Li Liu ◽  
She Tian ◽  
Zhu Li ◽  
Yongjun Gong ◽  
Hao Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Survival Curve ◽  
Principal Component ◽  
High Risk Group ◽  
Low Risk ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Background : Hepatocellular carcinoma (HCC) is one of the most common clinical malignant tumors, resulting in high mortality and poor prognosis. Studies have found that LncRNA plays an important role in the onset, metastasis and recurrence of hepatocellular carcinoma. The immune system plays a vital role in the development, progression, metastasis and recurrence of cancer. Therefore, immune-related lncRNA can be used as a novel biomarker to predict the prognosis of hepatocellular carcinoma. Methods : The transcriptome data and clinical data of HCC patients were obtained by using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA‑LIHC), and immune-related genes were extracted from the Molecular Signatures Database (IMMUNE RESPONSE M19817 and IMMUNE SYSTEM PROCESS M13664). By constructing the co-expression network and Cox regression analysis, 13 immune-lncRNAs was identified to predict the prognosis of HCC patients. Patients were divided into high risk group and low risk group by using the risk score formula, and the difference in overall survival (OS) between the two groups was reflected by Kaplan-Meier survival curve. The time - dependent receiver operating characteristics (ROC) analysis and principal component analysis (PCA) were used to evaluate 13 immune -lncRNAs signature. Results : Through TCGA - LIHC extracted from 343 cases of patients with hepatocellular carcinoma RNA - Seq data and clinical data, 331 immune-related genes were extracted from the Molecular Signatures Database , co-expression networks and Cox regression analysis were constructed, 13 immune-lncRNAs signature was identified as biomarkers to predict the prognosis of patients. At the same time using the risk score median divided the patients into high risk and low risk groups, and through the Kaplan-Meier survival curve analysis found that high-risk group of patients' overall survival (OS) less low risk group of patients. The AUC value of the ROC curve is 0.828, and principal component analysis (PCA) results showed that patients could be clearly divided into two parts by immune-lncRNAs, which provided evidence for the use of 13 immune-lncRNAs signature as prognostic markers. Conclusion : Our study identified 13 immune-lncRNAs signature that can effectively predict the prognosis of HCC patients, which may be a new prognostic indicator for predicting clinical outcomes.

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