scholarly journals Multifactorial Landscape Parses to Reveal a Predictive Model for Knee Osteoarthritis

2021 ◽  
Vol 18 (11) ◽  
pp. 5933
Author(s):  
Monica Singh ◽  
Srishti Valecha ◽  
Rubanpal Khinda ◽  
Nitin Kumar ◽  
Surinderpal Singh ◽  
...  
Keyword(s):  
Knee Osteoarthritis ◽  
Roc Curve ◽  
Inflammatory Markers ◽  
Significant Risk ◽  
Predictive Ability ◽  
Predictive Marker ◽  
Risk Scores ◽  
Multivariable Logistic Regression Analysis ◽  
Poor Sleep ◽  
Roc Curve Analysis

The present study attempted to investigate whether concerted contributions of significant risk variables, pro-inflammatory markers, and candidate genes translate into a predictive marker for knee osteoarthritis (KOA). The present study comprised 279 confirmed osteoarthritis patients (Kellgren and Lawrence scale >2) and 287 controls. Twenty SNPs within five genes (CRP, COL1A1, IL-6, VDR, and eNOS), four pro-inflammatory markers (interleukin-6 (IL-6), interleuin-1 beta (IL-1β), tumor necrosis factor alpha (TNF-α), and high sensitivity C-reactive protein (hsCRP)), along with significant risk variables were investigated. A receiver operating characteristic (ROC) curve was used to observe the predictive ability of the model for distinguishing patients with KOA. Multivariable logistic regression analysis revealed that higher body mass index (BMI), triglycerides (TG), poor sleep, IL-6, IL-1β, and hsCRP were independent predictors for KOA after adjusting for the confounding from other risk variables. Four susceptibility haplotypes for the risk of KOA, AGT, GGGGCT, AGC, and CTAAAT, were observed within CRP, IL-6, VDR, and eNOS genes, which showed their impact in recessive β(SE): 2.11 (0.76), recessive β(SE): 2.75 (0.59), dominant β(SE): 1.89 (0.52), and multiplicative modes β(SE): 1.89 (0.52), respectively. ROC curve analysis revealed the model comprising higher values of BMI, poor sleep, IL-6, and IL-1β was predictive of KOA (AUC: 0.80, 95%CI: 0.74–0.86, p< 0.001), and the strength of the predictive ability increased when susceptibility haplotypes AGC and GGGGCT were involved (AUC: 0.90, 95%CI: 0.87–0.95, p< 0.001).This study offers a predictive marker for KOA based on the risk scores of some pertinent genes and their genetic variants along with some pro-inflammatory markers and traditional risk variables.

scholarly journals Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score

2019 ◽  
Vol 11 ◽  
pp. 1759720X1988555 ◽  
Author(s):  
Wanlong Wu ◽  
Jun Ma ◽  
Yuhong Zhou ◽  
Chao Tang ◽  
Feng Zhao ◽  
...  
Keyword(s):  
Emergency Department ◽  
Prediction Model ◽  
Risk Score ◽  
Roc Curve ◽  
Curve Analysis ◽  
Multivariable Logistic Regression Analysis ◽  
Invasive Infection ◽  
Roc Curve Analysis ◽  
All Cause Mortality ◽  
Qsofa Score

Background: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. Methods: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. Results: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections ( n = 108). Conclusions: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice.

scholarly journals What are the optimal cut-off points of anthropometric indices for prediction of overweight and obesity? Predictive validity of waist circumference, waist-to-hip and waist-to-height ratios

2020 ◽  
Vol 10 (2) ◽  
pp. 142-147 ◽  
Author(s):  
Helda Tutunchi ◽  
Mehrangiz Ebrahimi-Mameghani ◽  
Alireza Ostadrahimi ◽  
Mohammad Asghari-Jafarabadi
Keyword(s):  
Waist Circumference ◽  
Roc Curve ◽  
Predictive Ability ◽  
Diagnostic Value ◽  
Cross Sectional Study ◽  
Overweight And Obesity ◽  
Roc Curve Analysis ◽  
Anthropometric Indices ◽  
Cross Sectional ◽  
Anthropometric Indicators

Background: Planning for obesity prevention is an important global health priority. Our aim in this study was to find the optimal cut-off points of waist circumference (WC), waist- to- hipratio (WHR) and waist- to- height ratio (WHtR), as three anthropometric indices, for prediction of overweight and obesity. We also aimed to compare the predictive ability of these indices to introduce the best choice. Methods: In this cross-sectional study, a total of 500 subjects were investigated. Anthropometric indicators were measured using a standard protocol. We considered body mass index (BMI) as the simple and most commonly used index for measuring general obesity as the comparison indicator in the present study to assess the diagnostic value for other reported obesity indices.We also performed receiver operating characteristic (ROC) curve analysis to define the optimal cut-off points of the anthropometric indicators and the best indices for overweight and obesity. Results: The proposed optimal cut-offs for WC, WHtR, and WHR were 84 cm, 0.48 and 0.78for women and 98 cm, 0.56 and 0.87 for men, respectively. The area under the ROC curve ofWHtR (women: AUC=0.97, 95% CI: 0.96-0.99 vs. men: AUC=0.97, 95%CI: 0.96-0.99) and WC(women: AUC=0.97, 95% CI, 0.95-0.99 vs. men: AUC=0.98, 95% CI: 0.97-0.99) were greater than WHR (women: AUC=0.79, 95% CI =0.74-0.85 vs. men: AUC=0.84, 95% CI=0.79-0.88). Conclusion: This study demonstrated that the WC and WHtR indicators are stronger indicators compared to the others. However, further studies using desirable and also local cutoffs against more accurate techniques for body fat measurement such as computerized tumor (CT) scans and dual-energy x-ray absorptiometry (DEXA) are required.

scholarly journals The Association between ESR and CRP and Systemic Hypertension in Sarcoidosis

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Mehdi Mirsaeidi ◽  
Hesham R. Omar ◽  
Golnaz Ebrahimi ◽  
Micheal Campos
Keyword(s):  
Multivariate Analysis ◽  
Systemic Inflammation ◽  
Roc Curve ◽  
Inflammatory Markers ◽  
Curve Analysis ◽  
Systemic Hypertension ◽  
Roc Curve Analysis ◽  
Mean Values ◽  
Auc Value ◽  
Serum Inflammatory Markers

Introduction.The association between the level of systemic inflammation and systemic hypertension (sHTN) among subjects with sarcoidosis has not been previously explored.Methods.A retrospective study was conducted to investigate the relation between the level of systemic inflammation in sarcoidosis, measured by various serum inflammatory markers, and sHTN.Results.Among a total of 108 cases with sarcoidosis (mean age: 53.4 years, 76.9% females), 55 (50.9%) had sHTN and 53 (49.1%) were normotensive. ESR was highly associated with sHTN. The patients with sHTN had higher mean ESR levels compared with normotensives (48.8 ± 35 versus 23.2 ± 27 mm/hr, resp.;P=0.001). ROC curve analysis for ESR revealed an AUC value of 0.795 (95% CI: 0.692–0.897;P=0.0001). With regard to CRP, there was a trend towards higher mean values in sHTN group (3.4 versus 1.7 mg/L;P=0.067) and significantly higher prevalence of sHTN in the highest CRP quartile compared to the lowest one (69.6% versus 30%; OR 4.95;P=0.017). ROC curve analysis for CRP revealed an AUC value of 0.644 (95% CI: 0.518–0.769;P=0.03). On multivariate analysis, ESR and the CRP remained independent predictors for sHTN among subjects with sarcoidosis.Conclusion.Systemic inflammation is associated with the presence of sHTN in sarcoidosis.

scholarly journals Impact of comorbidity burden on mortality in patients with COVID-19 using the Korean health insurance database

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Soo Ick Cho ◽  
Susie Yoon ◽  
Ho-Jin Lee
Keyword(s):  
Risk Factors ◽  
Health Insurance ◽  
Roc Curve ◽  
Significant Risk ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Comorbidity Burden ◽  
Comorbidity Index ◽  
The Impact ◽  
Age And Sex

AbstractWe aimed to investigate the impact of comorbidity burden on mortality in patients with coronavirus disease (COVID-19). We analyzed the COVID-19 data from the nationwide health insurance claims of South Korea. Data on demographic characteristics, comorbidities, and mortality records of patients with COVID-19 were extracted from the database. The odds ratios of mortality according to comorbidities in these patients with and without adjustment for age and sex were calculated. The predictive value of the original Charlson comorbidity index (CCI) and the age-adjusted CCI (ACCI) for mortality in these patients were investigated using the receiver operating characteristic (ROC) curve analysis. Among 7590 patients, 227 (3.0%) had died. After age and sex adjustment, hypertension, diabetes mellitus, congestive heart failure, dementia, chronic pulmonary disease, liver disease, renal disease, and cancer were significant risk factors for mortality. The ROC curve analysis showed that an ACCI threshold > 3.5 yielded the best cut-off point for predicting mortality (area under the ROC 0.92; 95% confidence interval 0.91–0.94). Our study revealed multiple risk factors for mortality in patients with COVID-19. The high predictive power of the ACCI for mortality in our results can support the importance of old age and comorbidities in the severity of COVID-19.

CHA2DS2-VASc score for prediction of ischemic stroke in patients with systemic lupus erythematosus without atrial fibrillation

Lupus ◽  
2018 ◽  
Vol 27 (8) ◽  
pp. 1240-1246 ◽  
Author(s):  
W-S Hu ◽  
C-L Lin
Keyword(s):  
Atrial Fibrillation ◽  
Systemic Lupus Erythematosus ◽  
Ischemic Stroke ◽  
Roc Curve ◽  
Lupus Erythematosus ◽  
Predictive Ability ◽  
Systemic Lupus ◽  
Roc Curve Analysis ◽  
Discrimination Power ◽  
Cox Models

Objective We conducted this study to assess the role of CHA2DS2-VASc score in predicting ischemic stroke among systemic lupus erythematosus (SLE) patients without atrial fibrillation (AF). Methods We selected the SLE patients from the Registry of Catastrophic Illnesses Patient Database in Taiwan. We excluded the SLE patients with AF or atrial flutter. The patients were followed up until the occurrence of ischemic stroke, censored for death or withdrawal from the dataset, or the end of follow-up. Cox models were performed to obtain the hazard ratios (HRs) and the 95% confidence intervals (CIs) of ischemic stroke associated with the CHA2DS2-VASc score. A receiver operating characteristic (ROC) curve was generated to evaluate the predictive ability of CHA2DS2-VASc score for ischemic stroke in SLE patients without AF. Results A total of 11,962 study participants were included in this study. The incidence of ischemic stroke increased from 4.00 per 1000 person-years (PYs) for patients with a CHA2DS2-VASc score of 0 to 87.4 per 1000 PYs for those with a CHA2DS2-VASc score of ≧6. Moreover, patients with a CHA2DS2-VASc score of ≧2 were 3.98-fold (95% CI 3.15–5.04) more likely to develop ischemic stroke than those with a CHA2DS2-VASc score of <2 (14.0 vs. 2.99 per 1000 PYs). ROC curve analysis of the CHA2DS2-VASc score demonstrated a moderate discrimination power for ischemic stroke development with a c-statistic of 0.65(95% CI 0.62–0.69). Conclusions We found that a CHA2DS2-VASc score greater than or equal to 2 in SLE patients without AF is associated with a significantly higher rate of ischemic stroke.

Value of serum neuroendocrine markers in evaluation of neuroendocrine prostate cancer: A validation study using metastatic biopsies.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 278-278 ◽  
Author(s):  
Panagiotis J. Vlachostergios ◽  
Nicolas Peruzzo ◽  
Jones Nauseef ◽  
Clara Oromendia ◽  
Jyothi Manohar ◽  
...  
Keyword(s):  
Roc Curve ◽  
De Novo ◽  
Predictive Ability ◽  
Curve Analysis ◽  
Continuous Variables ◽  
Roc Curve Analysis ◽  
Non Invasive ◽  
Neuroendocrine Prostate Cancer ◽  
Median Serum ◽  
Genomic Characterization

278 Background: NEPC, de novo or treatment-related in late stage CRPC, is a distinct entity with poor prognosis. Developing non-invasive methods for detection of NEPC is important for clinical practice and trial enrollment. We previously reported on the clinical and genomic characterization of NEPC (Conteduca et al ESMO 2018). A separate study (Aggarwal et al JCO 2018) suggested that low levels of NSE and CgA were associated with a strong NPV for NEPC on biopsy (bx). This study aimed to validate the utility of NSE and CgA in evaluation of NEPC by comparison with met bx. Methods: Our IRB-approved NEPC database was screened for pts who underwent met bx and had concurrent serum NSE, CgA. Clinical data, serum PSA, LDH, ALP, Hb were recorded at time of bx. Comparison of continuous variables between CRPC adeno and NEPC was assessed by nonparametric Kruskal-Wallis test. ROC curve analysis was performed for evaluation of predictive models with serum NE markers. Results: 152 men were identified, median age 71 yrs (49-97). 35 pts had pure/mixed NEPC, while the rest (N=117) had typical adenoca on bx. Half of pts (80/152, 52.6%) received abiraterone or/and enzalutamide. Liver mets were more common in NEPC pts (P=0.001). Median serum NSE (11.2 vs 8.6 ng/mL, P=0.008) and CgA (211 vs 135 ng/mL, P=0.035) were higher in pts with NEPC vs CRPC adeno (Table). Using ROC curve analysis for NSE (normal 3.7-8.9 ng/mL) and CgA (normal 0-95 ng/mL) as independent diagnostic tests, the following cut-offs were identified: NSE 30.1 (Sn: 37%, Sp: 94%, PPV: 34%, NPV: 82%), CgA 170 (Sn: 63%, Sp: 59%, PPV: 23%, NPV: 83%). Conclusions: Our study confirms the potential utility of serum NSE and CgA in excluding a morphological dx of NEPC when below certain thresholds. However, our findings cannot support deferring a met bx in such cases. Larger studies are needed to evaluate for a more robust predictive ability of serum NE markers. [Table: see text]

scholarly journals Maximal kidney length predicts need for native nephrectomy in ADPCKD patients undergoing renal transplantation

2014 ◽  
Vol 8 (7-8) ◽  
pp. 278 ◽  
Author(s):  
Octav Cristea ◽  
Daniel Yanko ◽  
Sarah Felbel ◽  
Andrew House ◽  
Alp Sener ◽  
...  
Keyword(s):  
Renal Transplantation ◽  
Roc Curve ◽  
Test Performance ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Roc Curves ◽  
Clinical Tool ◽  
Roc Curve Analysis ◽  
Kidney Length ◽  
Autosomal Dominant Polycystic Kidney

Introduction: Native nephrectomy in patients with autosomal dominant polycystic kidney disease (ADPKD) is performed on a case-by-case basis. We determine if pre-transplant maximal kidney length (MKL) can be used to predict ultimate nephrectomy status.Methods: We performed a retrospective review of ADPKD patients who underwent renal transplantation at our centre between January2000 and December 2012. Pre-transplant measurements of MKL alone, MKL adjusted for height (HtMKL), weight (WtMKL) and body mass index (BMI-MKL) were each assessed for their predictive ability via a receiver operating characteristic (ROC) curve analysis.Results: In total, 84 patients met our inclusion criteria, of which17 (20.2%) underwent native nephrectomy. An MKL ROC curve analysis revealed an area under the curve (AUC) of 0.867 (95% confidence interval [CI] 0.775–0.931; p < 0.001). An optimal cut-off criterion of >21.5 cm revealed a sensitivity of 94.1% (95% CI 71.3–99.9) and specificity of 70.1% (95% CI 57.7–80.7) for eventual nephrectomy. The AUC of HtMKL, WtMKL and BMI-MKL ROC curves did not differ significantly from MKL alone. HtMKL improved specificity, but not overall test performance. The determination of the cut-off MKL may be influenced by the single-centre retrospective nature of this analysis, as well as the fact that renal size was determined by ultrasound and not computerized tomography or magnetic resonance imaging.Conclusion: MKL in patients with ADPKD is associated with the eventual need for nephrectomy and may be a useful clinical tool to risk stratify these patients and therefore guide patient conversations to a decision to leave the native kidneys in situ.

scholarly journals High AdiponectinHormone Modulation ofBlood Erythroid Parameters and its Relation with Erythropoietin in Patients with Diabetic Nephropathy

2020 ◽  
pp. 1593-1602
Author(s):  
Zhian Sherzad Hayder ◽  
Zrar Saleem Kareem
Keyword(s):  
Risk Factor ◽  
Diabetic Nephropathy ◽  
Roc Curve ◽  
Serum Insulin ◽  
Significant Risk ◽  
Curve Analysis ◽  
Serum Adiponectin ◽  
Dependent Diabetes Mellitus ◽  
Model Assessment ◽  
Roc Curve Analysis

Background: Serum adiponectin is a hormone of adipose tissue that activateslipid metabolism and exertsphysiological functions. Its level usually fluctuates in several metabolic diseases,including renal insufficiency and diabetes; it loses its protective role against diseases and becomes a potentially risk factor for erythroid abnormalities. Objectives: The study was designed to assess the association between adiponectin  hormone, blood erythroid and various parameters in groups of patients. Method:The study included 130 patientsand 42 healthy subjects. Parameters of serum adiponectin, erythropoietin (EPO), red blood cells (RBC), hemoglobin (Hb), hematocrit (Hct), renal function, serum insulin, fasting blood sugar (FBS), glycated hemoglobin % (HbA1c%) and homeostatic model assessment of insulin resistance (HOMA-IR) were estimated in all groups. Result: Statistical analysis showed that high level of adiponectin was significantly associated with erythroid-related variables (EPO, RBC, Hb and Hct) in patients groups when compared with the control. Receiver Operating Characteristic (ROC) curve analysis showed that adiponectin is a significant risk factor for anemia progression in non-insulin dependent diabetes mellitus (NIDDM), end stage renal disease (ESRD)and diabetic nephropathy patients. Conclusion: We suggest that high serum adiponectin level is dependently associated with EPO level and erythroid abnormalities in NIDDM, kidney failure and diabetic nephropathy patients. The present findings regarding ROC curve analysis of adiponectin suggested that this hormone could represent a risk factor for erythroid abnormality in diabetic nephropathy at ESRD.

scholarly journals Pulmonary Vein Index Is Associated With Early Prognosis of Surgical Treatment for Tetralogy of Fallot

2021 ◽  
Vol 9 ◽  
Author(s):  
Haoyong Yuan ◽  
Tao Qian ◽  
Ting Huang ◽  
Hui Yang ◽  
Can Huang ◽  
...  
Keyword(s):  
Surgical Treatment ◽  
Tetralogy Of Fallot ◽  
Pulmonary Vein ◽  
Roc Curve ◽  
Predictive Value ◽  
Significant Risk ◽  
Cox Proportional Hazards ◽  
Roc Curve Analysis ◽  
Crude Odds Ratio ◽  
Delayed Sternal Closure

Objectives: To evaluate the predictive value of the pulmonary vein index (PVI) in the early prognosis of patients who received total tetralogy of Fallot (TOF) repair.Methods: We retrospectively reviewed 286 patients who underwent TOF repair in our institution between July 2013 and May 2020. The PVI, McGoon ratio, and Nakata index were measured and calculated. Logistic regression, linear stepwise regression, receiver operating characteristic (ROC) curve analysis, and Cox proportional hazards modeling were performed to evaluate the predictive value of PVI in the early prognosis after TOF repair surgery.Results: The median age and body weight were 1.23 (0.22–15.02) years and 9.00 (3.00–44.00) kg, respectively. There were five early deaths. The areas under the ROC curve for death were 0.89, 0.79, and 0.88 for the McGoon ratio, Nakata index, and PVI, respectively. A lower PVI better predicted prolonged postoperative hospital stay, cardiac intensive care unit stay, and ventilator time (Hazard Ratio, HR [95% Confidence intervals, CI]: 1.003 [1.002–1.004], p &lt; 0.001; 1.002 [1.001–1.004], p &lt; 0.001; 1.002 [1.001–1.003], p &lt; 0.001, respectively) and was a significant risk factor for high 24 h max Vasoactive inotropic score (Crude Odds Ratio [OR] [95% CI]: −0.015 [−0.022, −0.007], p &lt; 0.001), serous effusion (Crude OR [95% CI]: 0.996 [0.992–0.999], p = 0.020), delayed sternal closure (Crude OR [95% CI]: 0.983 [0.971–0.996], p = 0.010), and the need for peritoneal dialysis (Crude OR [95% CI]: 0.988 [0.980–0.996], p = 0.005). The area under the ROC curve of PVI for delayed postoperative recovery was 0.722 (p &lt; 0.001), and the estimated cutoff point was 300.3 mm2/m2.Conclusion: PVI is a good predictor of early prognosis for surgical treatment of TOF patients.

scholarly journals Identification of a Novel Glycolysis-Related LncRNA Signature for Predicting Overall Survival in Patients With Bladder Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhenming Zheng ◽  
Cong Lai ◽  
Wenshuang Li ◽  
Caixia Zhang ◽  
Kaiqun Ma ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Roc Curve ◽  
Prognostic Model ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Curve Analysis ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Roc Curve Analysis ◽  
Gene Set Enrichment

BackgroundBoth lncRNAs and glycolysis are considered to be key influencing factors in the progression of bladder cancer (BCa). Studies have shown that glycolysis-related lncRNAs are an important factor affecting the overall survival and prognosis of patients with bladder cancer. In this study, a prognostic model of BCa patients was constructed based on glycolysis-related lncRNAs to provide a point of reference for clinical diagnosis and treatment decisions.MethodsThe transcriptome, clinical data, and glycolysis-related pathway gene sets of BCa patients were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Set Enrichment Analysis (GSEA) official website. Next, differentially expressed glycolysis-related lncRNAs were screened out, glycolysis-related lncRNAs with prognostic significance were identified through LASSO regression analysis, and a risk scoring model was constructed through multivariate Cox regression analysis. Then, based on the median of the risk scores, all BCa patients were divided into either a high-risk or low-risk group. Kaplan-Meier (KM) survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive power of the model. A nomogram prognostic model was then constructed based on clinical indicators and risk scores. A calibration chart, clinical decision curve, and ROC curve analysis were used to evaluate the predictive performance of the model, and the risk score of the prognostic model was verified using the TCGA data set. Finally, Gene Set Enrichment Analysis (GSEA) was performed on glycolysis-related lncRNAs.ResultsA total of 59 differentially expressed glycolysis-related lncRNAs were obtained from 411 bladder tumor tissues and 19 pericarcinomatous tissues, and 9 of those glycolysis-related lncRNAs (AC099850.3, AL589843.1, MAFG-DT, AC011503.2, NR2F1-AS1, AC078778.1, ZNF667-AS1, MNX1-AS1, and AC105942.1) were found to have prognostic significance. A signature was then constructed for predicting survival in BCa based on those 9 glycolysis-related lncRNAs. ROC curve analysis and a nomogram verified the accuracy of the signature.ConclusionThrough this study, a novel prognostic prediction model for BCa was established based on 9 glycolysis-related lncRNAs that could effectively distinguish high-risk and low-risk BCa patients, and also provide a new point of reference for clinicians to make individualized treatment and review plans for patients with different levels of risk.

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