scholarly journals Plasma Interleukin-6 Level: A Potential Prognostic Indicator of Emergent HBV-Associated ACLF

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Zhe-Bin Wu ◽  
Yu-Bao Zheng ◽  
Ke Wang ◽  
Zhi-Shuo Mo ◽  
Xu Zhen ◽  
...  
Keyword(s):  
Hepatitis B ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Total Bilirubin Level ◽  
Prognostic Indicator ◽  
High Plasma ◽  
T Helper 17 ◽  
Time Model ◽  
Cox Regression Analysis ◽  
Auc Value

Objective. To identify markers that predict the progression to hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF). Methods. We recruited 125 patients with chronic hepatitis B (CHB) between September 2013 and March 2017. During hospitalization, 25 patients progressed to LF and were classified as the LF group, while the remaining 100 patients were classified as the non-LF (NLF) group. We compared the kinetic changes in clinical and immune indicators including age, total bilirubin level, prothrombin time, model for end-stage liver disease score, interleukin (IL)-6, IL-8, and IL-10 cytokine levels, and number of T helper 17 and regulatory T cells between groups to determine their association with progression to HBV-ACLF. The prognostic value of clinical and immune indicators was determined using the area under the receiver operating characteristic curve (AUC) value. Results. Cox regression analysis suggested that the plasma IL-6 level could predict CHB progression to HBV-ACLF (relative risk = 1.082, 95% confidence interval: 1.006–1.164; P = 0.034 ). The AUC value, sensitivity, and specificity of baseline IL-6 level for predicting HBV-ACLF were 82.63%, 83.3%, and 82.9%, respectively ( P = 0.001 ). Conclusion. A high plasma IL-6 level in CHB patients could be an early biomarker for HBV-ACLF.

scholarly journals Identification and Validation of a Prognostic 5-Protein Signature for Biochemical Recurrence Following Radical Prostatectomy for Prostate Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Daojun Lv ◽  
Zanfeng Cao ◽  
Wenjie Li ◽  
Haige Zheng ◽  
Xiangkun Wu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Analysis ◽  
Biochemical Recurrence ◽  
Cox Regression ◽  
Characteristic Curve ◽  
The Cancer Genome Atlas ◽  
Medical Decision ◽  
Regression Analyses ◽  
Cox Regression Analysis ◽  
Protein Signature

Background: Biochemical recurrence (BCR) is an indicator of prostate cancer (PCa)-specific recurrence and mortality. However, there is a lack of an effective prediction model that can be used to predict prognosis and to determine the optimal method of treatment for patients with BCR. Hence, the aim of this study was to construct a protein-based nomogram that could predict BCR in PCa.Methods: Protein expression data of PCa patients was obtained from The Cancer Proteome Atlas (TCPA) database. Clinical data on the patients was downloaded from The Cancer Genome Atlas (TCGA) database. Lasso and Cox regression analyses were conducted to select the most significant prognostic proteins and formulate a protein signature that could predict BCR. Subsequently, Kaplan–Meier survival analysis and Cox regression analyses were conducted to evaluate the performance of the prognostic protein-based signature. Additionally, a nomogram was constructed using multivariate Cox regression analysis.Results: We constructed a 5-protein-based prognostic prediction signature that could be used to identify high-risk and low-risk groups of PCa patients. The survival analysis demonstrated that patients with a higher BCR showed significantly worse survival than those with a lower BCR (p < 0.0001). The time-dependent receiver operating characteristic curve showed that the signature had an excellent prognostic efficiency for 1, 3, and 5-year BCR (area under curve in training set: 0.691, 0.797, 0.808 and 0.74, 0.739, 0.82 in the test set). Univariate and multivariate analyses indicated that this 5-protein signature could be used as independent prognosis marker for PCa patients. Moreover, the concordance index (C-index) confirmed the predictive value of this 5-protein signature in 3, 5, and 10-year BCR overall survival (C-index: 0.764, 95% confidence interval: 0.701–0.827). Finally, we constructed a nomogram to predict BCR of PCa.Conclusions: Our study identified a 5-protein-based signature and constructed a nomogram that could reliably predict BCR. The findings might be of paramount importance for the prediction of PCa prognosis and medical decision-making.Subjects: Bioinformatics, oncology, urology.

scholarly journals Prediction Model of HBsAg Seroclearance in Patients with Chronic HBV Infection

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Jing Cao ◽  
Jiao Gong ◽  
Christ-Jonathan Tsia Hin Fong ◽  
Cuicui Xiao ◽  
Guoli Lin ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Hepatitis B ◽  
Cox Regression ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Hbsag Loss ◽  
Actual Observation ◽  
Hbsag Seroclearance ◽  
Low Incidence ◽  
Validation Set

Background. Prediction of HBsAg seroclearance, defined as the loss of circulating HBsAg with or without development of antibodies for HBsAg in patients with chronic hepatitis B (CHB), is highly difficult and challenging due to its low incidence. This study is aimed at developing and validating a nomogram for prediction of HBsAg loss in CHB patients. Methods. We analyzed a total of 1398 patients with CHB. Two-thirds of the patients were randomly assigned to the training set (n=918), and one-third were assigned to the validation set (n=480). Univariate and multivariate analysis by Cox regression analysis was performed using the training set, and the nomogram was constructed. Discrimination and calibration were performed using the training set and validation set. Results. On multivariate analysis of the training set, independent factors for HBsAg loss including BMI, HBeAg status, HBsAg titer (quantitative HBsAg), and baseline hepatitis B virus (HBV) DNA level were incorporated into the nomogram. The HBsAg seroclearance calibration curve showed an optimal agreement between predictions by the nomogram and actual observation. The concordance index (C-index) of nomogram was 0.913, with confirmation in the validation set where the C-index was 0.886. Conclusions. We established and validated a novel nomogram that can individually predict HBsAg seroclearance and non-seroclearance for CHB patients, which is clinically unprecedented. This practical prognostic model may help clinicians in decision-making and design of clinical studies.

Inflammatory markers in cerebrospinal fluid: independent prognostic biomarkers in amyotrophic lateral sclerosis?

2019 ◽  
pp. jnnp-2018-319586 ◽  
Author(s):  
Benjamin Gille ◽  
Maxim De Schaepdryver ◽  
Lieselot Dedeene ◽  
Janne Goossens ◽  
Kristl G Claeys ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Cerebrospinal Fluid ◽  
Disease Progression ◽  
Inflammatory Markers ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Progression Rate ◽  
Cox Regression Analysis ◽  
Lateral Sclerosis ◽  
Discriminatory Performance

ObjectiveInflammation is a key pathological hallmark in amyotrophic lateral sclerosis (ALS), which seems to be linked to the disease progression. It is not clear what the added diagnostic and prognostic value are of inflammatory markers in the cerebrospinal fluid (CSF) of patients with ALS.MethodsChitotriosidase-1 (CHIT1), chitinase-3-like protein 1 (YKL-40) and monocyte chemoattractant protein-1 (MCP-1) were measured in CSF and serum of patients with ALS (n=105), disease controls (n=102) and patients with a disease mimicking ALS (n=16). The discriminatory performance was evaluated by means of a receiver operating characteristic curve analysis. CSF and serum levels were correlated with several clinical parameters. A multivariate Cox regression analysis, including eight other established prognostic markers, was used to evaluate survival in ALS.ResultsIn CSF, CHIT1, YKL-40 and MCP-1 showed a weak discriminatory performance between ALS and ALS mimics (area under the curve: 0.79, p<0.0001; 0.72, p=0.001; 0.75, p=0.001, respectively). CHIT1 and YKL-40 correlated with the disease progression rate (ρ=0.28, p=0.009; ρ=0.34, p=0.002, respectively). CHIT1 levels were elevated in patients with a higher number of regions displaying motor neuron degeneration (one vs three regions: 4248 vs 13 518 pg/mL, p = 0.0075). In CSF, YKL-40 and MCP-1 were independently associated with survival (HR: 29.7, p=0.0003; 6.14, p=0.001, respectively).ConclusionsOur findings show that inflammation in patients with ALS reflects the disease progression as an independent predictor of survival. Our data encourage the use of inflammatory markers in patient stratification and as surrogate markers of therapy response in clinical trials.

Prognostic value of D-dimer/fibrinogen ratio in the adverse outcomes of patients hospitalized for heart failure

2020 ◽  
Vol 14 (18) ◽  
pp. 1733-1745
Author(s):  
Tian-Jun Zhao ◽  
Qian-Kun Yang ◽  
Chun-Yu Tan ◽  
Li-Dan Bi ◽  
Jie Li ◽  
...  
Keyword(s):  
Heart Failure ◽  
Regression Analysis ◽  
Cox Regression ◽  
Prognostic Indicator ◽  
Adverse Outcomes ◽  
Rank Test ◽  
Clinical Value ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
D Dimer

Aim: To evaluate the clinical value of plasma D-dimer/fibrinogen ratio (DFR) in patients hospitalized for heart failure (HF). Methods: Clinical data of 235 patients were retrospectively analyzed. Kaplan–Meier method and Cox regression analysis were used to identify significant prognosticators. Results: The Kaplan–Meier analysis showed that a higher DFR level was significantly associated with an increase in the end point outcomes, including HF readmission, thrombotic events and death (log-rank test: p < 0.001). The multivariate Cox regression analysis showed that the high tertile of DFR was significantly associated with the study end points (HR: 2.18; 95% CI: 1.31–3.62; p = 0.003), compared with the low tertile. Conclusion: DFR is a reliable prognostic indicator for patients hospitalized for HF.

scholarly journals Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis

2020 ◽  
Vol 19 ◽  
pp. 153303382096357
Author(s):  
Xiaoyong Gong ◽  
Bobin Ning
Keyword(s):  
Prostate Cancer ◽  
Network Analysis ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Interaction Network ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Normal Prostate ◽  
Cox Regression Analysis ◽  
Incidence And Mortality

Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) between PCa and normal prostate tissues were screened from The Cancer Genome Atlas (TCGA) database. The DEPCGs were functionally annotated in terms of the enriched pathways. Weighted gene co-expression network analysis (WGCNA) of 104 PCa samples identified 15 co-expression modules, of which the Turquoise module was negatively correlated with cancer and included 5 key lncRNAs and 47 PCGs. KEGG pathway analyses of the core 47 PCGs showed significant enrichment in classic PCa-related pathways, and overlapped with the enriched pathways of the DEPCGs. LINC00857, LINC00900, LINC00908, LINC00900, SNHG3 and FENDRR were significantly associated with the survival of PCa and have not been reported previously. Finally, Multivariable Cox regression analysis was used to establish a prognostic risk formula, and the patients were accordingly stratified into the low- and high-risk groups. The latter had significantly worse OS compared to the low-risk group (P < 0.01), and the area under the receiver operating characteristic curve (ROC) of 14-year OS was 0.829. The accuracy of our prediction model was determined by calculating the corresponding concordance index (C-index) and risk curves. In conclusion, we established a 5-lncRNA prognostic signature that provides insights into the biological and clinical relevance of lncRNAs in PCa.

scholarly journals Predictive value of the serum RASSF10 promoter methylation status in gastric cancer

2019 ◽  
Vol 47 (7) ◽  
pp. 2890-2900 ◽  
Author(s):  
Yilin Hu ◽  
Peng Ma ◽  
Ying Feng ◽  
Peng Li ◽  
Hua Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Promoter Methylation ◽  
Cox Regression ◽  
Methylation Status ◽  
Disease Free Survival ◽  
Prognostic Indicator ◽  
Chronic Atrophic Gastritis ◽  
Survival Times ◽  
Cox Regression Analysis ◽  
Specific Pcr

Background This study aimed to investigate whether the detection of methylation in the promoter of the Ras association domain family 10 gene ( RASSF10) in the serum of patients with gastric cancer (GC) by methylation-specific PCR (MSP) can be used as a diagnostic and prognostic indicator of GC. Methods We used MSP to examine RASSF10 methylation levels in the serum and/or tumor samples from 100 GC patients, 50 patients with chronic atrophic gastritis (CAG), and 45 healthy controls (HC). We also analyzed clinicopathological and follow-up data. Results Our results showed that the rate of serum RASFF10 promoter methylation among patients with GC (49/100) was higher than in those with CAG (1/50) or HC (0/45). Moreover, the RASSF10 methylation status was consistent between serum and tumor tissues. GC patients with serum RASSF10 promoter methylation had significantly shorter overall survival and disease-free survival times than GC patients without serum RASSF10 promoter methylation. Multivariable Cox regression analysis showed that serum RASSF10 promoter methylation and lymph node metastasis both correlated with reduced survival in GC patients. Conclusions Detection of the serum RASSF10 methylation status by MSP is feasible as a diagnostic and prognostic indicator of GC.

scholarly journals Extramural Venous Invasion as Prognostic Factor of Recurrence in Stage 1 and 2 Colon Cancer

2017 ◽  
Vol 2017 ◽  
pp. 1-6
Author(s):  
E. E. van Eeghen ◽  
M. J. Flens ◽  
M. M. R. Mulder ◽  
R. J. L. F. Loffeld
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Cox Regression ◽  
Venous Invasion ◽  
Prognostic Indicator ◽  
Hazard Ratio ◽  
Cox Regression Analysis ◽  
Increased Risk ◽  
Additional Value ◽  
Stage 1

Aim. Extramural venous invasion (EMVI) is a prognostic indicator in patients with colorectal cancer. However, its additional value in patients with stage 1 and 2 colorectal cancer is uncertain. In the present study, the incidence of EMVI and the hazard ratio for recurrence in patients with stage 1 and 2 colon cancer were studied. Methods. 184 patients treated for stage 1 and 2 colon cancer were included with a follow-up of at least 5 years. Chart review was performed and EMVI was assessed by two separate pathologists. EMVI was scored with additional caldesmon staining on the resection specimen. Primary outcomes were recurrence-free survival (RFS) measured through the Cox regression analysis and prevalence of EMVI. Results. There were 10 cases of EMVI and 3 cases of intramural venous invasion (IMVI) all occurring in patients with stage 2 disease corresponding to a prevalence of 9%. Thirty-one percent of the patients with venous invasion experienced recurrence versus 14% in patients without, corresponding with a hazard ratio of 2.39 (p=0.11). Conclusion. The present study demonstrates a trend towards an increased risk of recurrence in patients with stage 2 colon cancer with venous invasion. This warrants consideration of adjuvant chemotherapy despite the lack of lymph node metastases.

scholarly journals Neutrophil to Lymphocyte Ratio as Prognostic Indicator for Patients with Esophageal Squamous Cell Cancer

2017 ◽  
Vol 32 (4) ◽  
pp. 409-414 ◽  
Author(s):  
Guo-Dong Gao ◽  
Bo Sun ◽  
Xian-Bin Wang ◽  
Shi-Meng Wang
Keyword(s):  
Overall Survival ◽  
Squamous Cell ◽  
Cox Regression ◽  
Cell Cancer ◽  
Prognostic Indicator ◽  
Neutrophil To Lymphocyte Ratio ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Leukocyte Counts ◽  
Clinical Records

Background This study aimed to evaluate the correlation between neutrophil to lymphocyte ratio (NLR) with overall survival (OS) of esophageal squamous cell carcinoma (ESCC) patients. Method Records of patients with diagnosed ESCC were reviewed. Leukocyte counts and patients' characteristics were extracted from their clinical records to calculate NLR. Correlation between NLR and baseline characteristics with overall survival (OS) was then analyzed using Cox regression. The patients were then separated into higher and lower NLR groups according to median NLR. OS was further compared between the 2 groups. Results A total of 1281 patients were included in the study. Cox regression analysis showed a significant correlation of NLR with OS of ESCC patients. The median pretreatment NLR was identified as 2.86. Higher NLR was associated with worse prognosis in terms of OS. Conclusions Pretreatment NLR is independently associated with OS of ESCC patients. Therefore, NLR may be used as a predictive indicator for pretreatment evaluation and adjustment of treatment regimen.

scholarly journals A Novel Prognostic Risk Score Based on Ferroptosis-related LncRNAs Predicting Ovarian Cancer Patient Survival

2021 ◽  
Author(s):  
Keyu Chen ◽  
Xiaohong Li ◽  
Caixia Qi
Keyword(s):  
Ovarian Cancer ◽  
Risk Score ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Therapeutic Targets ◽  
Cancer Prognosis ◽  
Cancer Tissue ◽  
Clinical Implementation ◽  
Tumour Immunity ◽  
Cox Regression Analysis

Abstract Background: Long non-coding RNAs (lncRNAs) are thought to be associated with several processes during cancer development and have been shown to be involved in the regulation of ferroptosis. Ovarian cancer is highly malignant tumour with a poor prognosis. The identification biomarkers with prognostic value in ovarian cancer may improve patient outcomes and can help to elucidate potential future therapeutic targets.Results: We report differential expression of 187 ferroptosis-related lncRNAs in normal and ovarian cancer tissue. Using univariate and multivariable Cox regression analysis, we identified four lncRNAs that were strongly associated with prognosis. We constructed a prognostic risk score based on these four lncRNAs which was effectively able to distinguish between low- and high-risk OC patients based on survival time. Univariate and multivariable Cox regression analyses and time-related receiver operating characteristic curve analyses revealed that this risk score represented an independent prognostic factor in patients with ovarian cancer. For clinical implementation, we developed a nomogram based on the prognostic feature and patient age. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the four ferroptosis-related lncRNAs were related to tumour immunity.Conclusions: we identify four novel ferroptosis-related lncRNAs as predictors of ovarian cancer prognosis and potential future therapeutic targets for ovarian cancer.

scholarly journals Association between lactate/albumin ratio and all-cause mortality in patients with acute respiratory failure: A retrospective analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255744
Author(s):  
Yan Lu ◽  
Haoyang Guo ◽  
Xuya Chen ◽  
Qiaohong Zhang
Keyword(s):  
Respiratory Failure ◽  
Acute Respiratory Failure ◽  
Medical Information ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Severe Heart Failure ◽  
Albumin Ratio ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
All Cause Mortality

Previous studies have shown that lactate/albumin ratio (LAR) can be used as a prognostic biomarker to independently predict the mortality of sepsis and severe heart failure. However, the role of LAR as an independent prognostic factor in all-cause mortality in patients with acute respiratory failure (ARF) remains to be clarified. Therefore, we retrospectively analyzed 2170 patients with ARF in Medical Information Mart for Intensive Care Database III from 2001 to 2012. By drawing the receiver operating characteristic curve, LAR shows a better predictive value in predicting the 30-day mortality of ARF patients (AUC: 0.646), which is higher than that of albumin (AUC: 0.631) or lactate (AUC: 0.616) alone, and even higher than SOFA score(AUC: 0.642). COX regression analysis and Kaplan-Meier curve objectively and intuitively show that high LAR is a risk factor for patients with ARF, which is positively correlated with all-cause mortality. As an easy-to-obtain and objective biomarker, LAR deserves further verification by multi-center prospective studies.

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