scholarly journals Validation of the Canadian syncope risk score in a large prospective international multicenter study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
T Zimmermann ◽  
J Du Fay De Lavallaz ◽  
D Florez ◽  
V Widmer ◽  
M Freese ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Multicenter Study ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Funding Source ◽  
International Multicenter Study ◽  
International Multicenter ◽  
Very High

Abstract Background Management and risk stratification of patients with syncope in the emergency department (ED) is often challenging. In an effort to support ED physicians in disposition decisions, the Canadian Syncope Risk Score (CSRS) was developed to predict 30-day serious outcomes. Methods The CSRS was developed in a Canadian multicenter study and contains nine predictors: predisposition to vasovagal syncope, heart disease, systolic pressure <90 or >180mmHg in the ED, troponin level >99th percentile, abnormal QRS axis, QRS duration >130ms, QTc interval >480ms and an ED diagnosis of vasovagal or cardiac syncope. Patients can achieve a CSRS score between −3 and +11 points. We validated the CSRS in a large prospective international multicenter study recruiting patients 40 years or older presenting to the ED with a syncopal event within the last 12 hours. Recruitment centers contained smaller provincial hospitals, as well as big University Hospitals in eight countries on three continents. Primary outcome measure were 30-day serious arrhythmic and non-arrhythmic adverse events, as defined by the authors of the original score. Results 1581 patients were eligible for this analysis. The population in this validation cohort was older (mean age 68 vs 54 years) and had a considerably higher rate of serious outcomes compared to the derivation cohort (n=186 (11.8%) vs n=147 (3.6%)). The area under the receiver operating characteristic curve (AUC) for the CSRS was 0.88 (95% confidence interval (CI) 0.86–0.91) and significantly higher compared to the validated OESIL score (AUC 0.75, 95% CI 0.71–0.78, p<0.001). Calibration curve analysis showed an underestimation of risk in patients with a low CSRS and an overestimation in patients with a high CSRS. The rate of observed serious outcomes within 30d increased from 0.8% in the very low risk group (CSRS equal to or below −2) to 48% in the (very) high risk group (CSRS equal to or above 4, Hazard ratio 79.4, 95% CI 11.1–570.9). A Kaplan-Meier plot was used to visualize rates of serious outcomes in three different risk groups (Figure). Conclusion This is the first validation of the Canadian Syncope Risk Score in a large international syncope cohort. The prognostic discrimination of the CSRS for 30-day serious outcomes was very good in our validation cohort and comparable to that of the Canadian derivation study. Despite suboptimal calibration, prognostic analysis showed a high rate of serious outcomes in the CSRS (very) high risk group and a low rate of serious outcomes in the very low risk group. Allowing the clinical judgement of the ED physician in the form of suspected syncope etiology to be a part of the score seems to largely contribute to the high performance of the CSRS. Additional validation studies might be needed to further increase the accuracy of the CSRS in different patient populations with a different incidence of outcomes in settings outside of Canada. Figure 1 Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Swiss National Science Foundation; Swiss Heart Foundation

scholarly journals Development and Validation of a Lncrnas-Based Nomogram for Survival Prediction in Neuroblastoma Patients

2021 ◽  
Author(s):  
Yong Lv ◽  
ShuGuang Jin ◽  
Bo Xiang
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment

Abstract BackgroundTreatment of neuroblastoma is evolving toward precision medicine. LncRNAs can be used as prognostic biomarkers in many types of cancer.MethodsBased on the RNA-seq data from GSE49710, we built a lncRNAs-based risk score using the least absolute shrinkage and selection operation (LASSO) regression. Cox regression, receiver operating characteristic curves were used to evaluate the association of the LASSO risk score with overall survival. Nomograms were created and then validated in an external cohort from TARGET database. Gene set enrichment analysis was performed to identify the significantly changed biological pathways. ResultsThe 16-lncRNAs-based LASSO risk score was used to separate patients into high-risk and low-risk groups. In GSE49710 cohort, the high-risk group exhibited a poorer OS than those in the low-risk group (P<0.001). Moreover, multivariate Cox regression analysis demonstrated that LASSO risk score was an independent risk factor (HR=6.201;95%CI:2.536-15.16). The similar prognostic powers of the 16-lncRNAs were also achieved in the external cohort and in stratified analysis. In addition, a nomogram was established and worked well both in the internal validation cohort (C-index=0.831) and external validation cohort (C-index=0.773). The calibration plot indicated the good clinical utility of the nomogram. Gene set enrichment analysis (GSEA) indicated that high-risk group was related with cancer recurrence, metastasis and inflammatory associated pathways.ConclusionThe lncRNA-based LASSO risk score is a promising and potential prognostic tool in predicting the survival of patients with neuroblastoma. The nomogram combined the lncRNAs and clinical parameters allows for accurate risk assessment in guiding clinical management.

scholarly journals Four Immune-Related Long Non-coding RNAs for Prognosis Prediction in Patients With Hepatocellular Carcinoma

2020 ◽  
Vol 7 ◽  
Author(s):  
Muqi Li ◽  
Minni Liang ◽  
Tian Lan ◽  
Xiwen Wu ◽  
Wenxuan Xie ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Rate ◽  
High Risk ◽  
Risk Score ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Lasso Regression ◽  
Gene Set

BackgroundLong non-coding RNA (LncRNA) plays an important role in the occurrence and development of hepatocellular carcinoma (HCC). This study aims to establish an immune-related LncRNA model for risk assessment and prognosis prediction in HCC patients.MethodsHepatocellular carcinoma patient samples with complete clinical data and corresponding whole transcriptome expression were obtained from the Cancer Genome Atlas (TCGA). Immune-related genes were acquired from the Gene Set Enrichment Analysis (GSEA) website and matched with LncRNA in the TCGA to get immune-related LncRNA. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for screening the candidate LncRNAs and calculating the risk coefficient to establish the prognosis model. Patients were divided into a high-risk group and a low-risk group depending on the median risk score. The reliability of the prediction was evaluated in the validation cohort and the whole cohort. GSEA and principal component analysis were used for function evaluation.ResultsA total of 319 samples met the screening criteria and were randomly distributed across the training cohort and the validation cohort. After comparison with the IMMUNE_RESPONSE gene set and the IMMUNE_SYSTEM_PROCESS gene set, a total of 3094 immune-related LncRNAs were screened. Ultimately, four immune-related LncRNAs were used to construct a formula using LASSO regression. According to the formula, the low-risk group showed a higher survival rate than the high-risk group in the validation cohort and the whole cohort. The receiver operating characteristic curves data demonstrated that the risk score was more specific than other traditional clinical characteristics in predicting the 5-year survival rate for HCC.ConclusionThe four-immune-related-LncRNA model can be used for survival prediction in HCC and guide clinical therapy.

scholarly journals Multiple Myeloma Patients Undergoing Carfilzomib: Development and Validation of a Risk Score for Cardiovascular Adverse Events Prediction

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1631
Author(s):  
Anna Astarita ◽  
Giulia Mingrone ◽  
Lorenzo Airale ◽  
Fabrizio Vallelonga ◽  
Michele Covella ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Risk Assessment ◽  
Multiple Myeloma ◽  
Cardiovascular Risk ◽  
High Risk ◽  
Adverse Events ◽  
Risk Score ◽  
Risk Group ◽  
High Risk Group ◽  
Cardiovascular Risk Assessment

Cardiovascular adverse events (CVAEs) are linked to Carfilzomib (CFZ) therapy in multiple myeloma (MM); however, no validated protocols on cardiovascular risk assessment are available. In this prospective study, the effectiveness of the European Myeloma Network protocol (EMN) in cardiovascular risk assessment was investigated, identifying major predictors of CVAEs. From January 2015 to March 2020, 116 MM patients who had indication for CFZ therapy underwent a baseline evaluation (including blood pressure measurements, echocardiography and arterial stiffness estimation) and were prospectively followed. The median age was 64.53 ± 8.42 years old, 56% male. Five baseline independent predictors of CVAEs were identified: office systolic blood pressure, 24-h blood pressure variability, left ventricular hypertrophy, pulse wave velocity value and global longitudinal strain. The resulting ‘CVAEs risk score’ distinguished a low- and a high-risk group, obtaining a negative predicting value for the high-risk group of 90%. 52 patients (44.9%) experienced one or more CVAEs: 17 (14.7%) had major and 45 (38.7%) had hypertension-related events. In conclusion, CVAEs are frequent and a specific management protocol is crucial. The EMN protocol and the risk score proved to be useful to estimate the baseline risk for CVAEs during CFZ therapy, allowing the identification of higher-risk patients.

Identifying an immune-related gene-pair for prognosis prediction of metastatic colorectal cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15565-e15565
Author(s):  
Qiqi Zhu ◽  
Du Cai ◽  
Wei Wang ◽  
Min-Er Zhong ◽  
Dejun Fan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Prognostic Value ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Related Gene ◽  
Training Cohort ◽  
Gene Pairs ◽  
Immune Related Gene

e15565 Background: Few robust predictive biomarkers have been applied in clinical practice due to the heterogeneity of metastatic colorectal cancer (mCRC) . Using the gene pair method, the absolute expression value of genes can be converted into the relative order of genes, which can minimize the influence of the sequencing platform difference and batch effects, and improve the robustness of the model. The main objective of this study was to establish an immune-related gene pairs signature (IRGPs) and evaluate the impact of the IRGPs in predicting the prognosis in mCRC. Methods: A total of 205 mCRC patients containing overall survival (OS) information from the training cohort ( n = 119) and validation cohort ( n = 86) were enrolled in this study. LASSO algorithm was used to select prognosis related gene pairs. Univariate and multivariate analyses were used to validate the prognostic value of the IRGPs. Gene sets enrichment analysis (GSEA) and immune infiltration analysis were used to explore the underlying biological mechanism. Results: An IRGPs signature containing 22 gene pairs was constructed, which could significantly separate patients of the training cohort ( n = 119) and validation cohort ( n = 86) into the low-risk and high-risk group with different outcomes. Multivariate analysis with clinical factors confirmed the independent prognostic value of IRGPs that higher IRGPs was associated with worse prognosis (training cohort: hazard ratio (HR) = 10.54[4.99-22.32], P < 0.001; validation cohort: HR = 3.53[1.24-10.08], P = 0.012). GSEA showed that several metastasis and immune-related pathway including angiogenesis, TGF-β-signaling, epithelial-mesenchymal transition and inflammatory response were enriched in the high-risk group. Through further analysis of the immune factors, we found that the proportions of CD4+ memory T cell, regulatory T cell, and Myeloid dendritic cell were significantly higher in the low-risk group, while the infiltrations of the Macrophage (M0) and Neutrophil were significantly higher in the high-risk group. Conclusions: The IRGPs signature could predict the prognosis of mCRC patients. Further prospective validations are needed to confirm the clinical utility of IRGPs in the treatment decision.

A Hypoxia-related LncRNA Signature Predicts Survival of Primary Lower-grade glioma

2021 ◽  
Author(s):  
Yanjia Hu ◽  
Jing Zhang ◽  
Jing Chen
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Gene Set Enrichment

Abstract Background Hypoxia-related long non-coding RNAs (lncRNAs) have been proven to play a role in multiple cancers and can serve as prognostic markers. Lower-grade gliomas (LGGs) are characterized by large heterogeneity. Methods This study aimed to construct a hypoxia-related lncRNA signature for predicting the prognosis of LGG patients. Transcriptome and clinical data of LGG patients were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LGG cohort in TCGA was chosen as training set and LGG cohorts in CGGA served as validation sets. A prognostic signature consisting of fourteen hypoxia-related lncRNAs was constructed using univariate and LASSO Cox regression. A risk score formula involving the fourteen lncRNAs was developed to calculate the risk score and patients were classified into high- and low-risk groups based on cutoff. Kaplan-Meier survival analysis was used to compare the survival between two groups. Cox regression analysis was used to determine whether risk score was an independent prognostic factor. A nomogram was then constructed based on independent prognostic factors and assessed by C-index and calibration plot. Gene set enrichment analysis and immune cell infiltration analysis were performed to uncover further mechanisms of this lncRNA signature. Results LGG patients with high risk had poorer prognosis than those with low risk in both training and validation sets. Recipient operating characteristic curves showed good performance of the prognostic signature. Univariate and multivariate Cox regression confirmed that the established lncRNA signature was an independent prognostic factor. C-index and calibration plots showed good predictive performance of nomogram. Gene set enrichment analysis showed that genes in the high-risk group were enriched in apoptosis, cell adhesion, pathways in cancer, hypoxia etc. Immune cells were higher in high-risk group. Conclusion The present study showed the value of the 14-lncRNA signature in predicting survival of LGGs and these 14 lncRNAs could be further investigated to reveal more mechanisms involved in gliomas.

scholarly journals A TP53 mutation model for the prediction of prognosis and therapeutic responses in head and neck squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Congyu Shi ◽  
Shan Liu ◽  
Xudong Tian ◽  
Xiaoyi Wang ◽  
Pan Gao
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Mutation Model ◽  
Therapeutic Responses

Abstract Background Tumor protein p53 (TP53) is the most frequently mutated gene in head and neck squamous cell carcinoma (HNSC), and TP53 mutations are associated with inhibited immune signatures and poor prognosis. We established a TP53 mutation associated risk score model to evaluate the prognosis and therapeutic responses of patients with HNSC. Methods Differentially expressed genes between patients with and without TP53 mutations were determined by using data from the HNSC cohort in The Cancer Genome Atlas database. Patients with HNSC were divided into high- and low-risk groups based on a prognostic risk score that was generated from ten TP53 mutation associated genes via the multivariate Cox regression model. Results TP53 was the most common mutant gene in HNSC, and TP53 mutations were associated with immunogenic signatures, including the infiltration of immune cells and expression of immune-associated genes. Patients in the high-risk group had significantly poorer overall survival than those in the low-risk group. The high-risk group showed less response to anti-programmed cell death protein 1 (PD-1) therapy but high sensitivity to some chemotherapies. Conclusion The risk score based on our TP53 mutation model was associated with poorer survival and could act as a specific predictor for assessing prognosis and therapeutic response in patients with HNSC.

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 Retrospective Comparative Analysis of POPF Using Fistula Risk Score According to Pancreaticoenterostomy Method

2021 ◽  
Vol 105 (1-3) ◽  
pp. 559-563
Author(s):  
Seungmin Lee ◽  
Kwang Yeol Paik
Keyword(s):  
High Risk ◽  
Pancreatic Fistula ◽  
Risk Score ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Postoperative Pancreatic Fistula ◽  
Clinical Risk Score ◽  
Reconstructive Methods ◽  
Fistula Risk Score

Background The aim of this study is to examine whether pancreaticogastrostomy (PG) or pancreaticojejunostomy (PJ) is the better reconstructive method to reduce postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy (PD) according to the fistula risk. Methods An institutional database was reviewed for patients undergoing PD between January 2008 and August 2019. A total of 159 patients were stratified into 4 groups according to the Clinical Risk Score-Pancreatic Fistula. POPF according to 4 risk groups was compared between PJ and PG. Results Of the 159 patients, 82 underwent PG (51.6%) and 77 underwent PJ (48.4%) reconstruction. POPF rate was 17.1% (n = 14) in the PG group and 12.9% (n = 10) in the PJ group (P = 0.51). POPF rates were not different in intermediate, low, and negligible risks between 2 reconstructive methods. In the high-risk group (n = 47), there were 4 POPFs (22.2%) in PJ group and 9 (31.0%) in the PG group, respectively (P = 0.74). Conclusion In PD, there was no superior method of reconstruction with regard to POPF, even in high-risk glands.

A Four-gene Autophagy-related Prognostic Signature and Its Association With Immune Landscape in Lung Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Lumeng Luo ◽  
Minghe Lv ◽  
Xuan Li ◽  
Tiankui Qiao ◽  
Kuaile Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Immune Suppression ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk

Abstract Background: Recent advances in immune checkpoint inhibitors (ICIs) have dramatically changed the therapeutic strategy against lung squamous cell carcinoma (LUSC). In the era of immunotherapy, effective biomarkers to better predict outcomes and inform treatment decisions for patients diagnosed with LUSC are urgently needed. We hypothesized that immune contexture of LUSC is potentially dictated by tumor intrinsic events, such as autophagy. Thus, we attempted to construct an autophagy-related risk signature and examine its prediction value for immune phenotype in LUSC.Method: The expression profile of LUSC was obtained from the cancer genome atlas (TCGA) database and the profile of autophagy-related genes (ARGs) was extracted. The survival‑related ARGs (sARGs) was screened out through survival analyses. Random forest was performed to select the sARGs and construct a prognostic risk signature based on these sARGs. The signature was further validated by receiver operating characteristic (ROC) analysis and Cox regression. GEO dataset was used as an independent testing dataset. Patients were divided into high-risk and low-risk group based on the risk score. Then, gene set enrichment analysis (GSEA) was conducted between the two groups. The Single-Sample GSEA (ssGSEA) was introduced to quantify the relative infiltration of immune cells. The correlations between risk score and several main immune checkpoints were examined. And the ESTIMATE algorithm was used to calculate the estimate/immune/stromal scores of the LUSC. Results: Four ARGs (CFLAR, RGS19, PINK1 and CTSD) with the most significant prognostic values were enrolled to construct the risk signature. Patients in high-risk group had better prognosis than the low-risk group (P < 0.0001 in TCGA; P < 0.01 in GEO) and considered as an independent prognosis factor. We also found that high-risk group indicated an immune-suppression status and had higher levels of infiltrating regulatory T cells and macrophages, which are correlated with worse outcome. Besides, risk score showed a significantly positive correlation with the expression of PD-1 and CTLA4, as well as estimate score and immune score.Conclusion: This study established a novel autophagy-related four-gene prognostic risk signature, and the autophagy-related scores are associated with immune landscape of LUSC, with higher score indicating a stronger immune-suppression status.

Integrated Analysis of Immune-Related Genes in High-Risk Neuroblastoma

2020 ◽  
Author(s):  
FengLing Shao ◽  
Zhenni Wang ◽  
Shan Wang
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Clinical Characteristics ◽  
Roc Analysis ◽  
Risk Group ◽  
High Risk Group ◽  
Data Sets ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Immune Related Genes

Abstract BackgroundDue to the extremely high mortality rate of children with high-risk Neuroblastoma (NB), there is an urgent need for new indicators to further classify children in the high-risk group for more precise treatment. The purpose of our research is to explore the immune-related genes in NB in the high-risk group, and to further identify and develop a prognostic nomogram based on immune IRG signatures. MethodsThrough bioinformatics analysis to explore the abnormal expression of immune-related genes in the high-risk group. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related mRNA. The accuracy of the risk score is evaluated by Kaplan-Meier method and receiver operating characteristics (ROC) analysis, which is used to build a nomogram in combination with other clinical characteristics.. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to detect the accuracy of our results. ResultsA total of 127 common differentially expressed immune genes were found between the high-risk group and the non-high-risk group of the two data sets. Four immune-related genes (IRG) related to prognosis were identified and a risk score was established. Kaplan–Meier survival analysis and time-dependent ROC analysis showed that the 4-IRG risk score has satisfactory predictive potential and achieved consistency in the verification of external data sets. Subsequently, the risk score combined with clinical characteristics draws a nomogram. The reliability of the results was verified on 29 cases of NB tissues by qRT-PCR. ConclusionsOverall, we have developed a powerful multi-gene classifier that can effectively classify NB patients into low- and high-risk groups with poor prognosis, and draw a nomogram for children in the high-risk group. This feature can help select high-risk patients who need more aggressive adjuvant target therapy or immunotherapy.

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