scholarly journals Determinants of Preventive Behaviors for COVID-19 in Japan

2021 ◽  
Vol 18 (19) ◽  
pp. 9979
Author(s):  
Motoko Kosugi
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Risk Group ◽  
Age Groups ◽  
High Risk Group ◽  
Perceived Effectiveness ◽  
Preventive Behaviors ◽  
Risk Of Mortality ◽  
Main Factors ◽  
Using Data

As of June 2021, there have been more than 13,000 deaths in Japan due to the COVID-19 pandemic. Data from the Ministry of Health, Labor, and Welfare show that the mortality rate of COVID-19 greatly varies by age. In this study, using data from a questionnaire survey, an investigation was carried out to find differences in anxiety and risk perception, attitudes toward risk, and the frequency of implementation of countermeasures to infection among age groups that are prone to a greater risk of mortality, as well as the main factors that determine the frequency of implementation. Older people, who form a high-risk group, have a stronger tendency for anxiety and cautious attitudes toward COVID-19, and they more frequently implement preventive behaviors. The results of multiple regression analysis showed that the frequency of implementation of behaviors is determined not only by anxiety, cautious attitude, risk of aggravation to oneself, and perceived effectiveness of behaviors but also by regret, altruism, and conformity. In addition, almost no age-based gap was found between the determinants, suggesting that the motivation to take infection preventive behaviors is the same regardless of age.

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 A Novel Signature to Predict Thyroid Cancer Prognosis and Immune Landscape Using Immune-Related LncRNA Pairs

2021 ◽  
Author(s):  
BO SONG ◽  
Lijun Tian ◽  
Fan Zhang ◽  
Zheyu Lin ◽  
Boshen Gong ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Thyroid Cancer ◽  
High Risk ◽  
Small Molecule ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Immune Cell Infiltration ◽  
Cox Regression Analysis

Abstract Background: Thyroid cancer (TC) is the most common endocrine malignancy worldwide. The incidence of TC is high and increasing worldwide due to continuous improvements in diagnostic technology. TC is still often overtreated due to a lack of reliable diagnostic biomarkers. Therefore, determining accurate prognostic predictions to stratify TC patients is important.Methods: Raw data were downloaded from the TCGA database, and pairwise comparisons were applied to identify differentially expressed immune-related lncRNA (DEirlncRNA) pairs. Then, we used univariate Cox regression analysis and a modified Lasso algorithm on these pairs to construct a risk assessment model for TC. Next, TC patients were assigned to high- and low-risk groups based on the optimal cutoff score of the model for the 1-year ROC curve. We evaluated the signature in terms of prognostic independence, predictive value, immune cell infiltration, ICI-related molecules and small-molecule inhibitor efficacy. Results: We identified 30 DEirlncRNA pairs through Lasso regression, and 14 pairs served as the novel predictive signature. The high-risk group had a significantly poorer prognosis than the low-risk group. Cox regression analysis revealed that this immune-related signature can predict prognosis independently and reliably for TC. With the CIBERSORT algorithm, we found an association between the signature and immune cell infiltration. Additionally, several immune checkpoint inhibitor (ICI)-related molecules, such as PD-1 and PD-L1, showed a negative correlation with the high-risk group. We further found that some commonly used small-molecule inhibitors, such as sunitinib, were related to this new signature. Conclusions: We constructed a prognostic immune-related lncRNA signature that can predict TC patient survival without considering the technical bias of different platforms, and this signature also sheds light on TC overall prognosis and novel clinical treatments, such as ICB therapy and small molecular inhibitors.

scholarly journals A Hypoxia Signature for Predicting Prognosis and Tumor Immune Microenvironment in Adrenocortical Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xi Chen ◽  
Lijun Yan ◽  
Yu Lu ◽  
Feng Jiang ◽  
Ni Zeng ◽  
...  
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Adrenocortical Carcinoma ◽  
Risk Group ◽  
Gene Signature ◽  
High Risk Group ◽  
Immune Microenvironment ◽  
Gene Sets ◽  
Tumor Immune Microenvironment ◽  
Hypoxia Signature

Adrenocortical carcinoma (ACC) is a rare malignancy with dismal prognosis. Hypoxia is one of characteristics of cancer leading to tumor progression. For ACC, however, no reliable prognostic signature on the basis of hypoxia genes has been built. Our study aimed to develop a hypoxia-associated gene signature in ACC. Data of ACC patients were obtained from TCGA and GEO databases. The genes included in hypoxia risk signature were identified using the Cox regression analysis as well as LASSO regression analysis. GSEA was applied to discover the enriched gene sets. To detect a possible connection between the gene signature and immune cells, the CIBERSORT technique was applied. In ACC, the hypoxia signature including three genes (CCNA2, COL5A1, and EFNA3) was built to predict prognosis and reflect the immune microenvironment. Patients with high-risk scores tended to have a poor prognosis. According to the multivariate regression analysis, the hypoxia signature could be served as an independent indicator in ACC patients. GSEA demonstrated that gene sets linked to cancer proliferation and cell cycle were differentially enriched in high-risk classes. Additionally, we found that PDL1 and CTLA4 expression were significantly lower in the high-risk group than in the low-risk group, and resting NK cells displayed a significant increase in the high-risk group. In summary, the hypoxia risk signature created in our study might predict prognosis and evaluate the tumor immune microenvironment for ACC.

scholarly journals Comprehensive Analysis of Inflammatory Response–Related Genes, and Prognosis and Immune Infiltration in Patients With Low-Grade Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Han ◽  
Zhifan Zuo ◽  
Meilin Qu ◽  
Yinghui Zhou ◽  
Qing Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Grade ◽  
Immune Microenvironment ◽  
Cox Regression Analysis

Background: Although low-grade glioma (LGG) has a good prognosis, it is prone to malignant transformation into high-grade glioma. It has been confirmed that the characteristics of inflammatory factors and immune microenvironment are closely related to the occurrence and development of tumors. It is necessary to clarify the role of inflammatory genes and immune infiltration in LGG.Methods: We downloaded the transcriptome gene expression data and corresponding clinical data of LGG patients from the TCGA and GTEX databases to screen prognosis-related differentially expressed inflammatory genes with the difference analysis and single-factor Cox regression analysis. The prognostic risk model was constructed by LASSO Cox regression analysis, which enables us to compare the overall survival rate of high- and low-risk groups in the model by Kaplan–Meier analysis and subsequently draw the risk curve and survival status diagram. We analyzed the accuracy of the prediction model via ROC curves and performed GSEA enrichment analysis. The ssGSEA algorithm was used to calculate the score of immune cell infiltration and the activity of immune-related pathways. The CellMiner database was used to study drug sensitivity.Results: In this study, 3 genes (CALCRL, MMP14, and SELL) were selected from 9 prognosis-related differential inflammation genes through LASSO Cox regression analysis to construct a prognostic risk model. Further analysis showed that the risk score was negatively correlated with the prognosis, and the ROC curve showed that the accuracy of the model was better. The age, grade, and risk score can be used as independent prognostic factors (p < 0.001). GSEA analysis confirmed that 6 immune-related pathways were enriched in the high-risk group. We found that the degree of infiltration of 12 immune cell subpopulations and the scores of 13 immune functions and pathways in the high-risk group were significantly increased by applying the ssGSEA method (p < 0.05). Finally, we explored the relationship between the genes in the model and the susceptibility of drugs.Conclusion: This study analyzed the correlation between the inflammation-related risk model and the immune microenvironment. It is expected to provide a reference for the screening of LGG prognostic markers and the evaluation of immune response.

scholarly journals Prognostic Significance of Severe Thrombocytopenia in Overall Survival of Patients with Myelodysplastic Syndromes Treated with Azacytidine. a Multicenter Study By the Hellenic MDS Study Group

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1822-1822
Author(s):  
Athanasios Galanopoulos ◽  
Evdoxia Kamouza ◽  
Christos K. Kontos ◽  
Argiris Symeonidis ◽  
Vassiliki Pappa ◽  
...  
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
High Risk ◽  
Myelodysplastic Syndromes ◽  
Cox Regression ◽  
Risk Group ◽  
Prognostic Significance ◽  
High Risk Group ◽  
Severe Thrombocytopenia ◽  
Kaplan Meier

Abstract INTRODUCTION: The hypomethylating agents 5-azacitidine (5-AZA) and decitabine are recently considered the most preferable treatment option for patients with intermediate-2 and high-risk myelodysplastic syndromes (MDS), by International Prognostic Scoring System (IPSS). 5-AZA responders experience improved survival both in clinical trials (AZA 001) and in the real-life setting. Thrombocytopenia is a common event in MDS, during the course of the disease; recently, severe thrombocytopenia (≤30,000 platelets/μL) has been suggested as an important factor regarding the survival of MDS patients. In the present study, we examined the potential prognostic significance of severe thrombocytopenia, in intermediate-2- and high-risk MDS patients, being treated with 5-AZA, during the first 3 years of treatment. METHODS: This retrospective study included 850 higher-risk patients (intermediate-2- and high-risk), registered in the the Hellenic MDS Registry, treated with 5-AZA from 2010 to 2018 and were followed up for a time period up to 3 years. Complete patient data were available for 225 patients. Biostatistical analysis performed in this study included Kaplan-Meier survival analysis and Cox regression. The level of statistical significance was set at a probability value of less than 0.050 (P<0.050). RESULTS: The current study included 225 patients (159 male and 66 women) with intermediate-2- or high-risk MDS treated with 5-AZA, with a median age of 74 years (range: 47 - 89). WHO diagnosis included 1 (0.4%) case of RCUD, 8 (3.6%) cases of RCMD, 3 (1.3%) cases of RCMD-RS, 43 (19.1%) cases of RAEB-1, and 170 (75.6%) cases of RAEB-2. According to IPSS, 174 (77.3%) patients were classified in the intermediate-2 risk group and 51 (22.7%) patients in the high-risk group. In addition, according to IPSS-R, 24 (10.7%) patients were categorized in the intermediate risk group, 106 (47.1%) patients in the high-risk group, and 95 (42.2%) patients in the very-high risk group. All patients were evaluated regarding response to 5-AZA treatment. The initial response at 6 months was: complete remission (CR) in 40 (18.4%) patients, partial remission (PR) in 24 (11.1%) patients, hematological improvement (HI) in 35 (16.1%) patients; therefore, the initial overall response rate (CR, PR, and HI) was 45.6%. Stable disease (SD) was achieved by 56 (25.8%) MDS patients, while 62 (28.5%) patients showed progression of disease (PD) or treatment failure. Severe thrombocytopenia was not predictive of response, as shown using logistic regression analysis. However, severe thrombocytopenia predicted poor overall survival (OS) in the first 3 years of treatment with 5-AZA, as shown by the Kaplan-Meier analysis (Figure 1; P=0.016). Regarding AML-free survival, a strong trend was observed for thy unfavorable prognostic role of this severe cytopenia (P=0.096). Univariate Cox regression analysis for OS revealed a statistically significant hazard ratio (HR) of 1.6 for MDS patients with severe thrombocytopenia (HR=1.6, 95% CI=1.08, P=0.019). CONCLUSIONS: Our study showed that severe thrombocytopenia (≤ 30,000 platelets/μL) in intermediate-2- and high-risk MDS patients, treated with 5-AZA, predicts lower OS rates during the first 3 years of treatment. Figure 1. Figure 1. Disclosures No relevant conflicts of interest to declare.

Identification of a novel CpG methylation signature to predict prognosis in lung squamous cell carcinoma

2020 ◽  
pp. 1-11
Author(s):  
Nan Lee ◽  
Xuelian Xia ◽  
Hui Meng ◽  
Weiliang Zhu ◽  
Xiankai Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk ◽  
Risk Patients

BACKGROUND: DNA methylation plays a vital role in modulating genomic function and warrants evaluation as a biomarker for the diagnosis and treatment of lung squamous cell carcinoma (LUSC). OBJECTIVE: In this study, we aimed to identify effective potential biomarkers for predicting prognosis and drug sensitivity in LUSC. METHODS: A univariate Cox proportional hazards regression analysis, a random survival forests-variable hunting (RSFVH) algorithm, and a multivariate Cox regression analysis were adopted to analyze the methylation profile of patients with LUSC included in public databases: The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO). RESULTS: A methylated region consisting of 3 sites (cg06675147, cg07064331, cg20429172) was selected. Patients were divided into a high-risk group and a low-risk group in the training dataset. High-risk patients had shorter overall survival (OS) (hazard ratio [HR]: 2.72, 95% confidence interval [CI]: 1.82–4.07, P< 0.001) compared with low-risk patients. The accuracy of the prognostic signature was validated in the test and validation cohorts (TCGA, n= 94; GSE56044, n= 23). Gene set variation analysis (GSVA) showed that activity in the cell cycle/mitotic, ERBB, and ERK/MAPK pathways was higher in the high-risk compared with the low-risk group, which may lead to differences in OS.Interestingly, we observed that patients in the high-risk group were more sensitive to gemcitabine and docetaxel than the low-risk group, which is consistent with results of the GSVA. CONCLUSION: We report novel methylation sites that could be used as powerful tools for predicting risk factors for poorer survival in patients with LUSC.

scholarly journals Perioperative outcomes of segmentectomies versus lobectomies in high-risk patients: an ESTS database analysis

2020 ◽  
Author(s):  
Alessandro Brunelli ◽  
Herbert Decaluwe ◽  
Dominique Gossot ◽  
Francesco Guerrera ◽  
Zalan Szanto ◽  
...  
Keyword(s):  
High Risk ◽  
Mortality Rate ◽  
Risk Group ◽  
Mortality Rates ◽  
High Risk Group ◽  
Low Risk ◽  
Perioperative Outcomes ◽  
Database Analysis ◽  
Risk Of Mortality ◽  
Risk Patients

Abstract OBJECTIVES We queried the European Society of Thoracic Surgeons (ESTS) database with the aim to assess cardiopulmonary morbidity and 30-day mortality of segmentectomies and lobectomies in patients with a Eurolung-predicted mortality above the upper interquartile and classified as high risk. METHODS A total of 61 492 patients registered in the ESTS database (2007–2018) and submitted to lobectomy (55 353) or segmentectomy (6139) were divided into high risk or low risk according to a Eurolung-predicted mortality cut-off of 2.5% (corresponding in our population to the upper interquartile). Predicted versus observed mortalities were compared within each type of operation by using binomial test of proportion. Observed morbidity and mortality rates were compared between the 2 procedures using the χ2 test. RESULTS A total of 14 007 lobectomies and 1251 segmentectomies were classified as high risk. In the high-risk group, the cardiopulmonary morbidity and 30-day mortality rates observed in segmentectomies were lower than in lobectomies (morbidity: 12% vs 17%, P &lt; 0.0001; mortality: 2.4% vs 3.7%, P = 0.018). In segmentectomy patients, the observed mortality rate was lower than the Eurolung-predicted one (2.4% vs 3.8%, P = 0.009), while in the lobectomy patients, there was no difference between observed and predicted mortality (3.7% vs 3.8%, P = 0.9). In the low-risk group, the cardiopulmonary morbidity and 30-day mortality rates observed in segmentectomies were lower than in lobectomies (morbidity: 4.5% vs 7.8%, P &lt; 0.0001; mortality: 0.6% vs 1.0%, P = 0.01). In segmentectomy patients, the observed mortality rate was lower than the Eurolung-predicted one (0.6% vs 1.0%, P = 0.0003), while in the lobectomy patients, there was no difference between observed and predicted mortality (1.0% vs 1.1%, P = 0.06). CONCLUSIONS Segmentectomy was found associated with a 0.65 relative risk of mortality rate compared to lobectomy in patients deemed at higher surgical risk.

scholarly journals Immune-Related lncRNA Signature for Predicting the Immune Landscape of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Ji Yin ◽  
Xiaohui Li ◽  
Caifeng Lv ◽  
Xian He ◽  
Xiaoqin Luo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
High Risk ◽  
Cell Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Survival Prediction ◽  
Cox Regression Analysis

Background: Long non-coding RNA (lncRNA) plays a significant role in the development, establishment, and progression of head and neck squamous cell carcinoma (HNSCC). This article aims to develop an immune-related lncRNA (irlncRNA) model, regardless of expression levels, for risk assessment and prognosis prediction in HNSCC patients.Methods: We obtained clinical data and corresponding full transcriptome expression of HNSCC patients from TCGA, downloaded GTF files to distinguish lncRNAs from Ensembl, discerned irlncRNAs based on co-expression analysis, distinguished differentially expressed irlncRNAs (DEirlncRNAs), and paired these DEirlncRNAs. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multivariate Cox regression analysis were then performed to screen lncRNA pairs, calculate the risk coefficient, and establish a prognosis model. Finally, the predictive power of this model was validated through the AUC and the ROC curves, and the AIC values of each point on the five-year ROC curve were calculated to select the maximum inflection point, which was applied as a cut-off point to divide patients into low- or high-risk groups. Based on this methodology, we were able to more effectively differentiate between these groups in terms of survival, clinico-pathological characteristics, tumor immune infiltrating status, chemotherapeutics sensitivity, and immunosuppressive molecules.Results: A 13-irlncRNA-pair signature was built, and the ROC analysis demonstrated high sensitivity and specificity of this signature for survival prediction. The Kaplan–Meier analysis indicated that the high-risk group had a significantly shorter survival rate than the low-risk group, and the chi-squared test certified that the signature was highly related to survival status, clinical stage, T stage, and N stage. Additionally, the signature was further proven to be an independent prognostic risk factor via the Cox regression analyses, and immune infiltrating analyses showed that the high-risk group had significant negative relationships with various immune infiltrations. Finally, the chemotherapeutics sensitivity and the expression level of molecular markers were also significantly different between high- and low-risk groups.Conclusion: The signature established by paring irlncRNAs, with regard to specific expression levels, can be utilized for survival prediction and to guide clinical therapy in HNSCC.

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