scholarly journals Development and validation of a prognostic nomogram for lower-grade glioma based on an autophagy-related lncRNA signature

2022 ◽  
Author(s):  
Jiazhe Lin ◽  
Nuan Lin ◽  
Wei-jiang Zhao
Keyword(s):  
Proportional Hazards ◽  
Cox Regression ◽  
Cox Proportional Hazards ◽  
Differentially Expressed ◽  
Survival Prediction ◽  
Lower Grade ◽  
Lasso Regression ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Kaplan Meier

IntroductionGliomas account for 75% of the primary malignant brain tumors. The prognosis and treatment planning vary in lower-grade gliomas (LGG) due to their heterogeneous clinical behaviors. The dysregulation of autophagy-related (ATG) lncRNAs plays a crucial role in LGG. We aimed to develop and validate an ATG lncRNA risk signature, and a survival nomogram with integration of novel prognostic for LGG patients.Material and methodsDifferentially expressed ATG lncRNAs were screened out based on TCGA and GTEx RNA-seq databases. ATG lncRNA prognostic signature was then established by Kaplan–Meier, univariate Cox proportional hazards regression, Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox proportional hazards regression, with its predictive value validated by time-dependent receiver operating characteristic (ROC) curves. Kaplan–Meier, univariate Cox regression and multivariate Cox proportional hazards regression were used to screen out clinical and molecular variables. A nomogram was developed and internally validated by ROC and calibration plots.ResultsAn ATG lncRNA risk signature was constructed with six differentially expressed lncRNAs (LINC00599, LINC02609, AC021739.2, AL118505.1, AL354892.2, and AL590666.2). Based on the risk signature, a nomogram was developed by addition of the significant prognostic clinical variables (age and grade) and molecular variables (IDH status and MGMT status).ConclusionsWe identified an ATG lncRNA risk signature and develop a nomogram for individualized survival prediction in LGG patients. A user-friendly free online calculator to facilitate the use of this nomogram among clinicians is also provided: https://linstu2009.shinyapps.io/LGGPRODICTORapp/?_ga=2.3154800.1506830296.1588641469-159983587.1588641469.

Serum FGF21 Is Associated with Future Cardiovascular Events in Patients with Coronary Artery Disease

Cardiology ◽  
2018 ◽  
Vol 139 (4) ◽  
pp. 212-218 ◽  
Author(s):  
Yun Shen ◽  
Xueli Zhang ◽  
Yiting Xu ◽  
Qin Xiong ◽  
Zhigang Lu ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Regression Analysis ◽  
Coronary Artery ◽  
Cardiovascular Events ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Kaplan Meier ◽  
Artery Disease

Objectives: To investigate whether serum fibroblast growth factor 21 (FGF21) levels can be used to predict the future development of major adverse cardiovascular events (MACEs). Methods: This study included 253 patients who received subsequent follow-up, and complete data were collected for 234 patients. Independent predictors of MACEs were identified by using the Cox proportional-hazards regression analysis. The prognostic value of FGF21 levels for MACEs was evaluated by Kaplan-Meier survival analysis. Results: Of 229 patients finally enrolled in the analysis, 27/60 without coronary artery disease (CAD) at baseline experienced a MACE, and 132/169 patients with CAD at baseline experienced a MACE. Among patients with CAD at baseline, serum FGF21 levels were significantly higher in patients with MACEs (p < 0.05) than in patients without MACEs. Kaplan-Meier survival analysis showed patients with a higher serum FGF21 had a significantly lower event-free survival (p = 0.001) than those with a lower level. Further Cox proportional-hazards regression analysis, including the traditional risk factors for cardiovascular disease, showed that serum FGF21 was an independent predictor of MACE occurrence. Conclusions: In patients with CAD at baseline, an elevated serum FGF21 level was associated with the development of a MACE in the future.

The Timing of Subsequent Treatment for Teeth Restored with Large Amalgams and Crowns: Factors Related to the Need for Subsequent Treatment

2004 ◽  
Vol 83 (11) ◽  
pp. 854-858 ◽  
Author(s):  
J.L. Kolker ◽  
P.C. Damiano ◽  
M.P. Jones ◽  
D.V. Dawson ◽  
D.J. Caplan ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Subsequent Treatment ◽  
Cox Proportional Hazards ◽  
Regression Modeling ◽  
Survival Curves ◽  
Rank Tests ◽  
Factors Associated ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Kaplan Meier

Crowns and large amalgams protect structurally compromised teeth to various degrees in different situations. The aim of this investigation was to evaluate the survival of teeth with these two types of restorations and the factors associated with better outcomes. Retrospective administrative and chart data were used. Survival was defined and modeled as: (1) receipt of no treatment and (2) receipt of no catastrophic treatment over five- and 10-year periods. Analyses included: Kaplan-Meier survival curves, Log-Rank tests, and Cox proportional hazards regression modeling. Crowns survived longer with no treatment and with no catastrophic treatment; however, mandibular large amalgams were least likely to have survived with no treatment, and maxillary large amalgams were least likely to have survived with no catastrophic treatment. Having no adjacent teeth also decreased survival. Crowns survived longer than large amalgams, but factors such as arch type and the presence of adjacent teeth contributed to the survival of large amalgams.

scholarly journals Integrated Analysis of Cell Cycle–Related and Immunity-Related Biomarker Signatures to Improve the Prognosis Prediction of Lung Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Fangyu Chen ◽  
Jiahang Song ◽  
Ziqi Ye ◽  
Bing Xu ◽  
Hongyan Cheng ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Lung Adenocarcinoma ◽  
Risk Model ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Survival Prediction ◽  
Lasso Regression ◽  
Kaplan Meier ◽  
Geo Database

BackgroundLung adenocarcinoma (LUAD) is a leading malignancy and has a poor prognosis over the decades. LUAD is characterized by dysregulation of cell cycle. Immunotherapy has emerged as an ideal option for treating LUAD. Nevertheless, optimal biomarkers to predict outcomes of immunotherapy is still ill-defined and little is known about the interaction of cell cycle-related genes (CCRGs) and immunity-related genes (IRGs).MethodsWe downloaded gene expression and clinical data from TCGA and GEO database. LASSO regression and Cox regression were used to construct a differentially expressed CCRGs and IRGs signature. We used Kaplan-Meier analysis to compare survival of LUAD patients. We constructed a nomogram to predict the survival and calibration curves were used to evaluate the accuracy.ResultsA total of 61 differentially expressed CCRGs and IRGs were screened out. We constructed a new risk model based on 8 genes, including ACVR1B, BIRC5, NR2E1, INSR, TGFA, BMP7, CD28, NUDT6. Subgroup analysis revealed the risk model accurately predicted the overall survival in LUAD patients with different clinical features and was correlated with immune cells infiltration. A nomogram based on the risk model exhibited excellent performance in survival prediction of LUAD.ConclusionsThe 8 gene survival signature and nomogram in our study are effective and have potential clinical application to predict prognosis of LUAD.

scholarly journals T83. SUBSTANCE-INDUCED PSYCHOSIS LINKED TO BOTH INFECTIONS AND SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S263-S263
Author(s):  
Carsten Hjorthøj ◽  
Marie Starzer ◽  
Michael Benros ◽  
Merete Nordentoft
Keyword(s):  
Bipolar Disorder ◽  
Proportional Hazards ◽  
Strong Support ◽  
Cox Proportional Hazards ◽  
Schizophrenia Spectrum Disorders ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Kaplan Meier ◽  
Long Term Prognosis ◽  
Time Varying Covariates

Abstract Background Substance-induced psychosis is an under-researched phenomenon, and little is known about its etiology (other than exposure to substances) and long-term prognosis. In this presentation, we aim to present results from two recent studies, one of which was recently published and the other is currently in the process of being analyzed. The first study investigates rates and predictors of conversion from substance-induced psychosis; the second study investigates the association between severe infections and substance-induced psychosis, including the contribution of infections on conversion to schizophrenia. Methods Both studies utilized the nationwide Danish registers. In study 1, we included all people diagnosed with substance-induced psychosis from 1994 to 2014 (n=6,788). These were followed using the Kaplan-Meier method and Cox proportional hazards regression to estimate rates and predictors of conversion to schizophrenia or bipolar disorder. In study 2, we included the entire Danish population born since 1981 (n=2,256,779). These were followed in Cox proportional hazards regression models, linking hospital-requiring infections as time-varying covariates to development of substance-induced psychosis. In further analyses, we followed those who had developed substance-induced psychosis to determine whether infections would influence the risk of converting to schizophrenia. Results Study 1: Overall, 32.2% (95% CI 29.7–34.9) of patients with a substance-induced psychosis converted to either bipolar or schizophrenia-spectrum disorders. The highest conversion rate was found for cannabis-induced psychosis, with 47.4% (95% CI 42.7–52.3) converting to either schizophrenia or bipolar disorder. Young age was associated with a higher risk of converting to schizophrenia. Self-harm was significantly linked to a higher risk of converting to both schizophrenia and bipolar disorder. Study 2: Infections increased the risk of substance-induced psychosis (HR=1.30, 95% CI 1.22–1.39) in the fully adjusted model. Hepatitis was the infection most strongly associated with substance-induced psychosis, at HR=3.42 (95% CI 2.47–4.74). Different sites of infections showed associations with different types of substance-induced psychosis. Finally, hepatitis increased the risk of conversion to schizophrenia with HR=1.87 (95% CI 1.07–3.26). Discussion Substance-induced psychosis is strongly associated with the development of severe mental illness, and a long follow-up period is needed to identify the majority of cases. Infections appear to play a role in the etiology of substance-induced psychosis which is very similar to the role infections play in the etiology of schizophrenia. This lends strong support to the existence of an immune-related component to psychosis in general, and not just to schizophrenia.

Effectiveness of Adjuvant Chemotherapy After Radical Nephroureterectomy for Locally Advanced and/or Positive Regional Lymph Node Upper Tract Urothelial Carcinoma

2017 ◽  
Vol 35 (8) ◽  
pp. 852-860 ◽  
Author(s):  
Thomas Seisen ◽  
Ross E. Krasnow ◽  
Joaquim Bellmunt ◽  
Morgan Rouprêt ◽  
Jeffrey J. Leow ◽  
...  
Keyword(s):  
Lymph Node ◽  
Adjuvant Chemotherapy ◽  
Proportional Hazards ◽  
Regional Lymph Node ◽  
Locally Advanced ◽  
Cox Proportional Hazards ◽  
Radical Nephroureterectomy ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Kaplan Meier

Purpose There is limited evidence to support the use of adjuvant chemotherapy (AC) after radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC). Against this backdrop, we hypothesized that such treatment is associated with overall survival (OS) benefit in patients with locally advanced and/or positive regional lymph node disease. Patients and Methods Within the National Cancer Database (2004 to 2012), we identified 3,253 individuals who received AC or observation after RNU for pT3/T4 and/or pN+ UTUC. Inverse probability of treatment weighting (IPTW) –adjusted Kaplan-Meier curves and Cox proportional hazards regression analyses were used to compare OS of patients in the two treatment groups. In addition, we performed exploratory analyses of treatment effect according to age, gender, Charlson comorbidity index, pathologic stage (pT3/T4N0, pT3/T4Nx and pTanyN+), and surgical margin status. Results Overall, 762 (23.42%) and 2,491 (76.58%) patients with pT3/T4 and/or pN+ UTUC received AC and observation, respectively, after RNU. IPTW-adjusted Kaplan-Meier curves showed that median OS was significantly longer for AC versus observation (47.41 [interquartile range,19.88 to 112.39] v 35.78 [interquartile range, 14.09 to 99.22] months; P < .001). The 5-year IPTW-adjusted rates of OS for AC versus observation were 43.90% and 35.85%, respectively. In IPTW-adjusted Cox proportional hazards regression analysis, AC was associated with a significant OS benefit (hazard ratio, 0.77 [95% CI, 0.68 to 0.88]; P < .001). This benefit was consistent across all subgroups examined (all P < .05), and no significant heterogeneity of treatment effect was observed (all Pinteraction > .05). Conclusion We report an OS benefit in patients who received AC versus observation after RNU for pT3/T4 and/or pN+ UTUC. Although our results are limited by the usual biases related to the observational study design, we believe that the present findings should be considered when advising post-RNU management of advanced UTUC, pending level I evidence.

scholarly journals Persistent SARS-CoV-2 RNA Shedding Without Evidence of Infectiousness: A Cohort Study of Individuals With COVID-19

2021 ◽  
Author(s):  
Daniel Owusu ◽  
Mary A Pomeroy ◽  
Nathaniel M Lewis ◽  
Ashutosh Wadhwa ◽  
Anna R Yousaf ◽  
...  
Keyword(s):  
Symptom Onset ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Viral Rna ◽  
Cox Proportional Hazards Regression ◽  
Viral Culture ◽  
Proportional Hazards Regression ◽  
Kaplan Meier ◽  
Participant Characteristics ◽  
Pcr Test

Abstract Background To better understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding and infectivity, we estimated SARS-CoV-2 RNA shedding duration, described participant characteristics associated with the first negative rRT-PCR test (resolution), and determined if replication-competent viruses was recoverable ≥10 days after symptom onset. Methods We collected serial nasopharyngeal specimens from 109 individuals with rRT-PCR–confirmed COVID-19 in Utah and Wisconsin. We calculated viral RNA shedding resolution probability using the Kaplan-Meier estimator and evaluated characteristics associated with shedding resolution using Cox proportional hazards regression. We attempted viral culture for 35 rRT-PCR–positive nasopharyngeal specimens collected ≥10 days after symptom onset. Results The likelihood of viral RNA shedding resolution at 10 days after symptom onset was approximately 3%. Time to shedding resolution was shorter among participants aged &lt;18 years (adjusted hazards ratio [aHR], 3.01; 95% confidence interval [CI], 1.6–5.6) and longer among those aged ≥50 years (aHR, 0.50; 95% CI, .3–.9) compared to participants aged 18–49 years. No replication-competent viruses were recovered. Conclusions Although most patients were positive for SARS-CoV-2 for ≥10 days after symptom onset, our findings suggest that individuals with mild to moderate COVID-19 are unlikely to be infectious ≥10 days after symptom onset.

scholarly journals Incorporating sampling weights into robust estimation of Cox proportional hazards regression model, with illustration in the Multi-Ethnic Study of Atherosclerosis

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Colleen M. Sitlani ◽  
Thomas Lumley ◽  
Barbara McKnight ◽  
Kenneth M. Rice ◽  
Nels C. Olson ◽  
...  
Keyword(s):  
Cohort Study ◽  
Regression Model ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Cox Proportional Hazards ◽  
Robust Methods ◽  
Time To Event ◽  
Sampling Weights ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

Abstract Background Cox proportional hazards regression models are used to evaluate associations between exposures of interest and time-to-event outcomes in observational data. When exposures are measured on only a sample of participants, as they are in a case-cohort design, the sampling weights must be incorporated into the regression model to obtain unbiased estimating equations. Methods Robust Cox methods have been developed to better estimate associations when there are influential outliers in the exposure of interest, but these robust methods do not incorporate sampling weights. In this paper, we extend these robust methods, which already incorporate influence weights, so that they also accommodate sampling weights. Results Simulations illustrate that in the presence of influential outliers, the association estimate from the weighted robust method is closer to the true value than the estimate from traditional weighted Cox regression. As expected, in the absence of outliers, the use of robust methods yields a small loss of efficiency. Using data from a case-cohort study that is nested within the Multi-Ethnic Study of Atherosclerosis (MESA) longitudinal cohort study, we illustrate differences between traditional and robust weighted Cox association estimates for the relationships between immune cell traits and risk of stroke. Conclusions Robust weighted Cox regression methods are a new tool to analyze time-to-event data with sampling, e.g. case-cohort data, when exposures of interest contain outliers.

scholarly journals Gene selection in Cox regression model based on a new adaptive penalized method

2020 ◽  
Vol 8 (1) ◽  
pp. 16
Author(s):  
Oday Isam Alskal ◽  
Zakariya Yahya Algamal
Keyword(s):  
Regression Model ◽  
Survival Data ◽  
Proportional Hazards ◽  
Gene Selection ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Selection Operator

The common issues of high dimensional gene expression data for survival analysis are that many of genes may not be relevant to their diseases. Gene selection has been proved to be an effective way to improve the result of many methods. The Cox proportional hazards regression model is the most popular model in regression analysis for censored survival data. In this paper, an adaptive penalized Cox proportional hazards regression model is proposed, with the aim of identification relevant genes and provides high classification accuracy, by combining the Cox proportional hazards regression model with the weighted least absolute shrinkage and selection operator (LASSO) method. Experimental results show that the proposed method significantly outperforms two competitor methods in terms of the area under the curve and the number of the selected genes.  

scholarly journals A novel long non-coding RNA, AC012456.4, as a valuable and independent prognostic biomarker of survival in oral squamous cell carcinoma

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5307 ◽  
Author(s):  
Xuegang Hu ◽  
Zailing Qiu ◽  
Jianchai Zeng ◽  
Tingting Xiao ◽  
Zhihong Ke ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Survival Analysis ◽  
Oral Squamous Cell Carcinoma ◽  
Proportional Hazards ◽  
Prognostic Biomarker ◽  
Cox Proportional Hazards ◽  
Regression Analyses ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression ◽  
Kaplan Meier

Oral squamous cell carcinoma (OSCC) is a major malignant cancer of the head and neck. Long non-coding RNAs (lncRNAs) have emerged as critical regulators during the development and progression of cancers. This study aimed to identify a lncRNA-related signature with prognostic value for evaluating survival outcomes and to explore the underlying molecular mechanisms of OSCC. Associations between overall survival (OS), disease-free survival (DFS) and candidate lncRNAs were evaluated by Kaplan–Meier survival analysis and univariate and multivariate Cox proportional hazards regression analyses. The robustness of the prognostic significance was shown via the Gene Expression Omnibus (GEO) database. A total of 2,493 lncRNAs were differentially expressed between OSCC and control samples (fold change >2, p < 0.05). We used Kaplan–Meier survival analysis to identify 21 lncRNAs for which the expression levels were associated with OS and DFS of OSCC patients (p < 0.05) and found that down-expression of lncRNA AC012456.4 especially contributed to poor DFS (p = 0.00828) and OS (p = 0.00987). Furthermore, decreased expression of AC012456.4 was identified as an independent prognostic risk factor through multivariate Cox proportional hazards regression analyses (DFS: p = 0.004, hazard ratio (HR) = 0.600, 95% confidence interval(CI) [0.423–0.851]; OS: p = 0.002, HR = 0.672, 95% CI [0.523–0.863). Gene Set Enrichment Analysis (GSEA) indicated that lncRNA AC012456.4 were significantly enriched in critical biological functions and pathways and was correlated with tumorigenesis, such as regulation of cell activation, and the JAK-STAT and MAPK signal pathway. Overall, these findings were the first to evidence that AC012456.4 may be an important novel molecular target with great clinical value as a diagnostic, therapeutic and prognostic biomarker for OSCC patients.

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