Survival Curves Research Articles

UBE2T is a diagnostic and prognostic biomarker for endometrial cancer.

Endometrial cancer (UCEC) is one of the most common malignant tumors in gynecology, and early diagnosis is crucial for its treatment. Currently, there is a lack of early screening tests specific to UCEC, and treatment advances are limited. It is crucial to identify more sensitive biomarkers for screening, diagnosis, and predicting UCEC. Previous studies have shown that UBE2T is involved in the development of various tumors such as breast cancer and liver cancer, but research on the role of UBE2T in UCEC is limited. Using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and UALCAN databases, we analyzed the differential expression of UBE2T mRNA and protein in endometrial cancer (UCEC), along with its clinical relevance. A total of 113 clinical samples were collected, and immunohistochemistry and Western blot analysis were employed to validate bioinformatics analysis results. Volcano plots were generated using UBE2T and its differentially expressed genes, and a protein-protein interaction (PPI) network was constructed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), and immune infiltration analysis were used to predict the functional role of UBE2T in UCEC progression. Correlation between UBE2T expression and patient survival was analyzed using TCGA data, and Kaplan-Meier survival curves were plotted. UBE2T is significantly overexpressed in UCEC and correlates with poor prognosis. Its overexpression is closely associated with mitosis, cell cycle regulation, and histological grade in UCEC patients. UBE2T is highly expressed in UCEC and suppresses anti-tumor immune responses in UCEC patients. It serves as a key participant in UCEC progression, associated with a range of adverse outcomes, and holds potential as a clinical diagnostic and prognostic biomarker.

Association of urinary and blood lead concentrations with all-cause mortality in US adults with chronic kidney disease: a prospective cohort study.

Epidemiological evidence on the relationship between lead exposure and mortality in specific chronic kidney disease (CKD) populations is limited. We aimed to examine the relationship between urinary lead and blood lead concentrations and all-cause mortality in US patients with CKD. This cohort study included 2320 participants with CKD from the National Health and Nutrition Examination Survey (2005-2018), with follow-up until December 31, 2019. All-cause mortality was ascertained by matching US National Death Index records. Hazard ratios (HRs) and 95% confidence intervals (CI) for urinary lead and blood lead concentrations in relation to all-cause mortality were estimated using a weighted Cox regression model. During a median follow-up period of 79months, a total of 625 participants with CKD succumbed to mortality. Compared to the lowest quartile, the highest quartile of urine and blood lead concentrations was associated with an increased risk of all-cause mortality, with HRs and corresponding 95% CIs of 1.77 (1.05-2.99) and 2.65 (1.38-5.10), respectively. Furthermore, each additional unit increase in urinary and blood lead concentrations was associated with HRs for all-cause mortality of 1.21 (95% CI 1.06-1.38) and 1.09 (95% CI 1.01-1.19), respectively. Kaplan-Meier survival curve analysis and restricted cubic regression spline curve analysis demonstrated significant positive associations between elevated blood lead levels, elevated urinary lead levels, and all-cause mortality risk (P < 0.05). A nonlinear concentration-response relationship was observed between blood lead level and all-cause mortality risk (PNonlinear < 0.05), with an inflection point at a concentration of 1.613µg/dL. Subgroup analysis as well as sensitivity analysis yielded consistent findings. Our findings demonstrate that elevated levels of lead in urine and blood are associated with a significantly increased mortality risk among patients with CKD, underscoring the importance of reducing lead exposure to mitigate mortality risk in individuals at high risk for CKD.

Relative biological effectiveness of clinically relevant photon energies for the survival of human colorectal, cervical, and prostate cancer cell lines

Objective.Relative biological effectiveness (RBE) differs between radiation qualities. However, an RBE of 1.0 has been established for photons regardless of the wide range of photon energies used clinically, the lack of reproducibility in radiobiological studies, and outdated reference energies used in the experimental literature. Moreover, due to intrinsic radiosensitivity, different cancer types have different responses to radiation. This study aimed to characterize the RBE of clinically relevant high and low photon energiesin vitrofor three human cancer cell lines: HCT116 (colon), HeLa (cervix), and PC3 (prostate).Approach.Experiments were conducted following dosimetry protocols provided by the American Association of Physicists in Medicine. Cells were irradiated with 6 MV x-rays, an192Ir brachytherapy source, 225 kVp and 50 kVp x-rays. Cell survival post-irradiation was assessed using the clonogenic assay. Survival fractions were fitted using the linear quadratic model, and survival curves were generated for RBE calculations.Main results.Cell killing was more efficient with decreasing photon energy. Using 225 kVp x-rays as the reference, the HCT116 RBESF0.1for 6 MV x-rays,192Ir, and 50 kVp x-rays were 0.89 ± 0.03, 0.95 ± 0.03, and 1.24 ± 0.04; the HeLa RBESF0.1were 0.95 ± 0.04, 0.97 ± 0.05, and 1.09 ± 0.03, and the PC3 RBESF0.1were 0.84 ± 0.01, 0.84 ± 0.01, and 1.13 ± 0.02, respectively. HeLa and PC3 cells had varying radiosensitivity when irradiated with 225 and 50 kVp x-rays.Significance.This difference supports the notion that RBE may not be 1.0 for all photons through experimental investigations that employed precise dosimetry. It highlights that different cancer types may not have identical responses to the same irradiation quality. Additionally, the RBE of clinically relevant photons was updated to the reference energy of 225 kVp x-rays.

Eniluracil blocks AREG signalling-induced pro-inflammatory fibroblasts of melanoma in heart failure.

Heart failure (HF) is characterized by a heightened risk of melanoma, which often metastasizes to the heart. The overlap pathology between HF and melanoma includes chronic low-grade inflammation and dysregulation of inflammatory cancer-associated fibroblasts (iCAFs). The impact of HF on iCAF-driven tumour inflammation remains obscure. To identify critical genes for HF development, transcriptomic data (GSE57338) containing 313 clinical HF samples [136 healthy controls, 95 ischaemia (ISCH) and 82 dilated cardiomyopathy (DCM)] were analysed to screen differentially expressed genes (DEGs) and perform enrichment analysis. Fifty-one DEGs in ISCH and 62 DEGs in DCM were identified with log2|fold change (FC)|≥1 and P value ≤0.05. All these genes are involved in extracellular matrix organization, immune/inflammatory responses and Wnt signalling pathways. Then, the overall survival curves and prognostic models of DEGs in melanoma were evaluated. The correlation of gene expression with lymphocyte infiltration levels was assessed. Only aldehyde oxidase 1 (AOX1) and amphiregulin (AREG) maintained the same trend in melanoma as in HF, negatively affecting prognosis by regulating lymphocyte infiltration (log-rank P value=0.0017 and 0.0019). The potential drug molecules were screened, and the binding energies were calculated via molecular docking. Eniluracil, a known AOX1 targeting drug, was found to stably bind with AREG (hydrogen bond binding energies: -65.633, -63.592 and -62.813kcal/mol). The increased prevalence of melanoma in HF patients and its propensity for cardiac metastasis may be due to AREG-mediated systemic low-grade inflammation. Eniluracil holds promise as a therapeutic agent that may block AREG signalling, inhibiting the activation of iCAF mediated by regulatory T cell (Treg) and neutrophil.

Semaglutide exposure and its association with adverse outcomes in diabetic patients undergoing transforaminal lumbar interbody fusion for lumbar degenerative disc disease.

Semaglutide, a novel glucagon-like peptide-1 receptor agonist, has transformed the therapeutic landscape for type 2 diabetes mellitus. However, its effect on osteoclast activity and its potential to induce weight-related muscle loss raises concerns about its impact on spine surgery outcomes. As such, evaluating semaglutide's influence on transforaminal lumbar interbody fusion (TLIF) is imperative, given the procedure's reliance on successful bony fusion to prevent postoperative instability and further interventions. Using an all-payer database (MARINER), the authors analyzed data from patients with type 2 diabetes mellitus who were 18-74 years of age and who underwent short-segment fusion (≤ 3-level) TLIFs between January 2018 and October 2022. Patients were either exposed to semaglutide or not. A comprehensive 1:3 (exposure vs no exposure) matching was performed based on age, sex, obesity, hypertension, coronary artery disease, chronic kidney disease, smoking status, osteoporosis, levels of surgery, and basal-bolus insulin dependence. Kaplan-Meier survival curves and log-rank testing were performed to study the probability of additional lumbar fusion surgery within 1 year. After the 1:3 matching, 1781 patients were identified, with 447 in the semaglutide-exposed cohort and 1334 in the nonexposed cohort. Most patients in both groups were 55-69 years old, and 59.3% were female. Analysis showed that the likelihood of undergoing additional lumbar fusion surgery within 1 year post-TLIF was significantly higher in the semaglutide-exposed group than in the nonexposed group (OR 11.79, 95% CI 8.17-17.33). Kaplan-Meier plots and log-rank testing further confirmed a statistically significant divergent probability in the need for additional surgery within 1 year between the cohorts (log-rank, p < 0.001). Semaglutide exposure appears to be associated with a higher likelihood of additional lumbar fusion surgeries within 1 year post-TLIF, especially in patients receiving the medication for longer durations. Although the mechanisms remain speculative, potential impacts on bone turnover and the onset of muscle loss may be contributory factors. Further research is needed to elucidate the exact mechanisms and to develop strategies for optimizing surgical outcomes in these patients.

Neutrophil-to-lymphocyte ratio and its association with latent tuberculosis infection and all-cause mortality in the US adult population: a cohort study from NHANES 2011–2012

BackgroundThere has been little study done on the possible connection between all-cause mortality and the neutrophil-to-lymphocyte ratio (NLR), particularly in individuals with latent tuberculosis infection (LTBI). The objective of this research was to examine the correlation between the NLR and LTBI, along with their effects on all-cause mortality in a cohort of individuals who had either LTBI or not.MethodsThis research incorporated data from the National Health and Nutrition Examination Survey (NHANES) 2011–2012, with a total of 4938 subjects involved. To investigate the connection between LTBI and variables, multivariable logistic regression models were used. Multivariable Cox proportional hazards models and Kaplan-Meier (KM) survival curves were employed to examine the association between NLR and all-cause death in individuals with and without LTBI.ResultsWhen analyzed as a continuous variable, The calculated odds ratios (ORs) for the different models-Model 1, Model 2, and Model 3 were 0.86, 0.83, and 0.84 (P &amp;lt; 0.005). NLR was evaluated as a categorical parameter, revealing that individuals in the tertile T3 had a notably lower rate of LTBI in comparison to those in the T1 group. After adjusting for different confounders, the odds ratio for T3 varied in the various models, being 0.75 (0.60∼0.95), 0.69 (0.54∼0.89), and 0.71 (0.56∼0.92), respectively. Additionally, higher NLR was significantly link to a greater risk of all-cause mortality in individuals with or without LTBI. Following multivariate adjustment, an 8% (Model 3, HR 1.08, 95% CI 1.05–1.12, P &amp;lt; 0.001) greater risk of mortality from all-cause was linked to every unit rise in NLR.ConclusionResults from the study revealed a negative correlation between NLR and the likelihood of LTBI as well as a higher risk of death from all causes. Therefore, NLR may be a helpful technique for risk categorization in the adult LTBI in the United States. To clarify the underlying mechanisms and any therapeutic implications of these findings, more investigation is necessary.

Machine Learning Model to Predict Early Recurrence in Patients with Perihilar Cholangiocarcinoma Planned Treatment with Curative Resection: A Multicenter Study

Background & AimsEarly recurrence is the leading cause of death for patients with perihilar cholangiocarcinoma (pCCA) after surgery. Identifying high-risk patients preoperatively is important. This study aimed to construct a preoperative prediction model for the early recurrence of pCCA patients planned treatment with curative resection. MethodsThis study ultimately enrolled 400 pCCA patients after curative resection in five hospitals between 2013 and 2019. They were randomly divided into training (n=300) and testing groups (n=100) at a ratio of 3:1. Associated variables were identified via LASSO regression. Four machine learning models were constructed: support vector machine (SVM), random forest (RF), logistic regression, and K-nearest neighbors (KNN). The predictive ability of the models was evaluated via receiver operating characteristic (ROC) curves, precision–recall curve (PRC) curves, and decision curve analysis (DCA). KaplanMeier survival curves were drawn for the high/low-risk population. ResultsFive factors, CA19-9, tumor size, total bilirubin, hepatic artery invasion, and portal vein invasion, were selected by LASSO regression. In both the training and testing groups, the ROC curve (AUC: 0.983 vs 0.952) and the PRC (0.981 vs 0.939) showed that RF was the best. The cutoff value for distinguishing high- and low-risk patients was 0.51. KM survival curves revealed that in both groups, there was a significant difference in RFS between high- and low-risk patients (P<0.001). ConclusionThis study used preoperative variables from a large, multicenter database to construct a machine learning model that could effectively predict the early recurrence of pCCA patients planned treatment with curative resection and help clinicians make better treatment decisions.

Association between risk of Alzheimer’s disease and related dementias and angiotensin receptor Ⅱ blockers treatment for individuals with hypertension in high-volume claims data

Findings regarding the protective effect of Angiotensin II receptor blockers (ARBs) against Alzheimer's disease and related dementias (AD/ADRD) and cognitive decline have been inconclusive. Individuals with hypertension who do not have any prior ADRD diagnosis were included in this retrospective cohort study from Optum's de-identified Clinformatics® Data Mart. We identified antihypertensive medication (AHM) drug classes and subclassified ARBs by blood-brain barrier (BBB) permeability. We compared baseline characteristics and used the Kaplan-Meier (KM) survival curve and adjusted Cox proportional hazards (PH) model for survival analyses. From 6,390,826 individuals with hypertension, there were 1,839,176 ARB users, 3,366,841 non-ARB AHM users, and 1,184,809 AHM non-users. The unadjusted KM curve showed that ARB users had lower cumulative hazard than other AHM users or AHM non-users (P<0.0001). In Cox PH analysis, ARB users showed a 20% lower adjusted hazard of developing ADRD compared to angiotensin-converting enzyme inhibitor (ACEI) users and a 29% and 18% reduced hazard when compared to non-ARB/ACEI AHM users and AHM non-users (all P<0.0001). Consumption of BBB-crossing ARBs was linked to a lower hazard of ADRD development than non-BBB-crossing ARBs, undetermined ARBs, and non-consumption of AHMs by 11%, 25%, and 31% (all P<0.0001). This study suggests that ARBs are superior to ACEIs, non-ARB/ACEI AHMs, or non-use of AHMs in reducing the hazard of ADRD among patients with hypertension. Also, BBB-permeability in ARBs was associated with lower ADRD incidence. There is no cure for AD, ADRD, or vascular dementia; hence, these findings are significant in preventing those disorders in an inexpensive, convenient, and safe way. Limitations in claims data should be considered when interpreting our findings. This research was supported by the National Institute on Aging grants (R01AG084236, R01AG083039, RF1AG072799, R56AG074604).

Effect of deep testosterone reduction on the prognosis of metastatic prostate cancer with high-volume disease.

This study aims to investigate the correlation between serum testosterone levels after one month of treatment and prognosis in patients with high-volume disease metastatic prostate cancer (mPCa) who are undergoing combined androgen blockade therapy (CAB). The clinical data of 199 patients with high-volume disease mPCa, diagnosed through biopsy pathology and imaging, were retrospectively analyzed from January 2010 to October 2022 in the Department of Urology at the First Affiliated Hospital of Xinjiang Medical University. Among these patients, 111 cases had a deep reduction in serum testosterone (< 0.7nmol/l) after one month of treatment, while 88 cases did not achieve a deep reduction (≥ 0.7nmol/l). The study utilized the Kaplan-Meier method to plot survival curves and employed the multifactor COX regression model to analyze independent risk factors. The risk factors with a significance level of P < 0.05 in the multivariate analysis were included in the nomogram prediction model. The accuracy of the model was assessed using the ROC curve and the calibration curve, while the net benefit for patients was evaluated through the decision curve analysis (DCA). The group that achieved deep testosterone reduction(DTR) had a higher proportion of PSA < 0.2ng/ml and a greater PSA decline rate after six months of treatment (P < 0.05). The group that achieved DTR and the group that did not achieve DTR had a progression to castration resistant prostate cancer(CRPC) time of 17.93 ± 6.68months and 13.43 ± 6.12months, respectively (P < 0.001). The median progression-free survival time for the 2 groups were 18months and 12months, respectively (P < 0.001). The median overall survival times were 57months and 32months, respectively (P < 0.001). The median progression-free survival times were 18, 15, and 10months for the group that achieved DTR within 1month, the group that achieved DTR beyond 1month but within 1year, and the group that did not achieve DTR within 1year, respectively (P < 0.001), and the median survival times were 57, 45, and 26months, respectively (P < 0.001). COX multivariate analysis revealed that a testosterone level of ≥ 0.7nmol/l at 1month of treatment is an independent risk factor for the progression to CRPC and prognosis in patients with high-volume disease mPCa (P < 0.05). The risk of death in patients with a testosterone level of ≥ 0.7nmol/l at 1month of treatment was 2.087 times higher than that of patients with a level of < 0.7nmol/l (P < 0.05). A nomogram prediction model was developed using independent risk factors, with the area under the ROC curve (AUC) for progression-free survival (PFS) at 12, 15, 18, and 21months being 0.788, 0.772, 0.760, and 0.739, respectively. For 3 and 5years, the AUCs for overall survival (OS) were 0.691 and 0.624. The calibration curve demonstrated good consistency between the model's predicted values and the actual outcomes. Patients with high-volume disease mPCa who receive CAB treatment may experience extended progression-free survival and overall survival if their serum testosterone levels are below 0.7nmol/l after one month of treatment. The longer it takes to achieve DTR, the worse the patient's prognosis may be. The nomogram prediction model developed in this study demonstrates good predictive ability in assessing the progression and prognosis of high-volume disease mPCa.

A Modified Model of PANoptosisto Identify Prognosis and Immunotherapy Response in Bladder Cancer

BackgroundCell death, including apoptosis and necrosis, collectively known as widespread apoptosis. The present study aims to investigate the mechanism of action in widespread apoptosis-related modification patterns in bladder cancer. MethodsUsing a clinical genomics database, we obtained transcriptomic data and related clinical information of bladder cancer patients. By employing the least absolute shrinkage analysis, we were able to construct a risk model and single-cell sequencing analysis of differential genes in bladder cancer. ResultsFive differentially expressed genes (TMPRSS4, TPST1, FOXD1, ELOVL4, EMP1) associated with widespread apoptosis were identified as features for predicting the prognosis of bladder cancer patients. Survival curve analysis revealed significant differences in prognosis (P<0.05). Additionally, multivariate Cox regression analysis determined the independent risk factor for bladder cancer prognosis as the risk score (P<0.001), with high confidence in the scoring model validated internally (P<0.001). Single-cell sequencing reveals high expression of CDKN2A, ERBB2, and TMPRSS4 in B cells, while HRAS is significantly expressed in fibroblasts. ConclusionPANscore, as a potential prognostic and immunotherapeutic biomarker, will provide more precise and rational basis for personalized treatment strategies

Validation of an Artificial Intelligence-Based Prediction Model Using 5 External PET/CT Datasets of Diffuse Large B-Cell Lymphoma.

The aim of this study was to validate a previously developed deep learning model in 5 independent clinical trials. The predictive performance of this model was compared with the international prognostic index (IPI) and 2 models incorporating radiomic PET/CT features (clinical PET and PET models). Methods: In total, 1,132 diffuse large B-cell lymphoma patients were included: 296 for training and 836 for external validation. The primary outcome was 2-y time to progression. The deep learning model was trained on maximum-intensity projections from PET/CT scans. The clinical PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, SUVpeak, age, and performance status. The PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, and SUVpeak Model performance was assessed using the area under the curve (AUC) and Kaplan-Meier curves. Results: The IPI yielded an AUC of 0.60 on all external data. The deep learning model yielded a significantly higher AUC of 0.66 (P < 0.01). For each individual clinical trial, the model was consistently better than IPI. Radiomic model AUCs remained higher for all clinical trials. The deep learning and clinical PET models showed equivalent performance (AUC, 0.69; P > 0.05). The PET model yielded the highest AUC of all models (AUC, 0.71; P < 0.05). Conclusion: The deep learning model predicted outcome in all trials with a higher performance than IPI and better survival curve separation. This model can predict treatment outcome in diffuse large B-cell lymphoma without tumor delineation but at the cost of a lower prognostic performance than with radiomics.

Association between neutrophil-to-lymphocyte ratio and short-term all-cause mortality in patients with cerebrovascular disease admitted to the intensive care unit-a study based on the MIMIC-IV database

BackgroundInflammation plays a crucial role in cerebrovascular disease (CVD) progression. Neutrophil-to-lymphocyte ratio (NLR) is an important inflammatory marker, though its diagnostic role in CVD is still under investigation. This study evaluates the relationship between NLR and short-term all-cause mortality in patients with CVD admitted to the intensive care unit (ICU).MethodsWe conducted a retrospective study using data from the Medical Information Mart for Intensive Care (MIMIC-IV) (v2.2) database, including 4,327 adult ICU-admitted CVD patients. NLR values at admission were analyzed alongside various mortality variables. Multivariate Cox proportional hazards regression models and Kaplan–Meier (K-M) survival curves assessed the relationship between NLR and short-term all-cause mortality. Predictive power, sensitivity, specificity, and area under the curve (AUC) of NLR for short-term mortality were investigated using Receiver Operating Characteristic (ROC) analysis. Additionally, restricted cubic spline (RCS) curves and subgroup analyses were conducted.ResultsAmong the 4,327 patients, 3,600 survived (survival group) and 727 died (non-survival group) within 28 days of admission (mortality rate: 16.8%). A multivariate Cox regression analysis identified NLR as an independent predictor of 28-day all-cause mortality (hazard ratio: 1.013; 95% confidence interval: 1.0086–1.0188; p &amp;lt; 0.001). The predictive model, incorporating NLR, age, gender, BMI, Charlson comorbidity index (CCI), WBC counts, Platelet, INR, and CRP, achieved an AUC of 0.686 (95% confidence interval: 0.665–0.70). While platelet-to-lymphocyte ratio was also analyzed, its predictive efficiency was less pronounced compared to NLR. A best NLR threshold of 6.19 was determined, distinguishing survivors from non-survivors. Kaplan–Meier survival curves showed that patients with NLR ≥ 6.19 had significantly lower survival rates at 7-, 14-, 21-, and 28-days. Subgroup analyses indicated that NLR did not significantly interact with most subgroups.ConclusionNLR may serve as an independent predictor for short-term all-cause mortality in ICU-admitted CVD patients, enhancing our understanding of the association between inflammatory biomarkers and CVD prognosis.

Advanced lung cancer inflammation index is associated with mortality in critically ill patients with heart failure.

Nutrition and inflammation status play a vital role in the prognosis of patients with heart failure (HF). This study aimed to investigate the association between the advanced lung cancer inflammation index (ALI), a novel composite indicator of inflammation and nutrition, and short-term mortality among critically ill patients with HF. This retrospective study included 548 critically ill patients with HF from the MIMIC-IV database. ALI was computed using body mass index, serum albumin and neutrophil-lymphocyte ratio. The primary endpoint was all-cause in-hospital mortality, and the secondary endpoint was 90day mortality. Kaplan-Meier survival curve analysis with long-rank test and Cox proportional hazards regression models were employed to assess the relationship between baseline ALI and short-term mortality risk. The incremental predictive ability of ALI was evaluated by C-statistic, continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI). The average age of 548 patients was 72.2 (61.9, 82.1) years, with 60% being male. Sixty-three patients (11.5%) died in the hospital, and 114 patients (20.8%)died within 90days of intensive care unit admission. The Kaplan-Meier analysis revealed that the cumulative incidences of both in-hospital and 90day mortality were significantly higher in patients with lower ALI (log-rank test, in-hospital mortality: P<0.001; 90day mortality: P<0.001). The adjusted Cox proportional hazard model revealed that ALI was inversely associated with both in-hospital and 90day mortality after adjusting for confounders [hazard ratio (HR) (95% confidence interval) (CI): 0.97 (0.94, 0.99), P=0.035; HR (95% CI): 0.62 (0.39, 0.99), P=0.046]. A linear relationship was observed between ALI and in-hospital mortality (P for non-linearity=0.211). The addition of ALI significantly improved the prognostic ability of GWTG-HF score in the in-hospital mortality [C-statistic improved from 0.62 to 0.68, P=0.001; continuous NRI (95% CI): 0.44 (0.20, 0.67), P<0.001; IDI (95% CI): 0.03 (0.01, 0.04), P<0.001] and 90day mortality [C-statistic improved from 0.63 to 0.70, P<0.001; continuous NRI (95% CI): 0.31 (0.11, 0.50), P=0.002; IDI (95% CI): 0.01 (0.00, 0.02), P=0.034]. Subgroup analysis revealed stronger correlations between ALI and in-hospital mortality in males and patients aged over 65years (interaction P=0.031 and 0.010, respectively). The C-statistic of in-hospital mortality in patients over 65years was 0.66 (95% CI: 0.58, 0.74). ALI at baseline can independently predict the risk of short-term mortality in critically ill patients with HF, with lower ALI significantly associated with higher mortality. Further large prospective research with extended follow-up periods is necessary to validate the findings of this study.

A-235 Systemic Inflammation is associated with worse outcomes from SARS-CoV-2 infection but not neutralizing antibody

Abstract Background Numerous studies have demonstrated an association between systemic inflammation and mortality in patients with COVID-19. However, it is unclear how neutralizing antibody to severe acute respiratory syndrome related coronavirus 2 (SARS-CoV-2) associates with outcomes. Further, how systemic inflammation impacts neutralizing antibody production is relatively poorly understood. The aim of this study was to determine the association between the neutralizing antibody response to SARS-CoV-2, inflammatory markers, and clinical outcomes in a cohort of hospitalized patients without prior exposure/vaccination. Methods This prospective observational study approved by the Washington University IRB included adults admitted through the ED at Barnes Jewish Hospital between 10/2020 and 10/2021 with symptomatic RT-PCR confirmed SARS-CoV-2 infection. A total of 395 serial samples were assessed from 208 patients without previous vaccination or documented exposure to SARS-CoV-2. Neutralization of SARS-CoV-2 was assessed using the Architect ACE2 binding inhibition assay (Abbott, Research Use only) which measures the % inhibition of interactions between antibodies and the SARS-COV-2 viral Spike Receptor Binding Domain. While 12.5% inhibition of ACE2 was considered positive &amp;gt;80% neutralization is the expected standard. CRP was assessed using the Architect Multigent CRP assay with 9.6mg/dL as the categorical cutoff for risk and interleukin 6 (IL-6) was assessed using the Alinity IL-6 assay (Abbott, Research Use Only) using 30 pg/mL as the threshold for risk in categorical analyses. The electronic medical record (EPIC) was interrogated for comorbidities, age, gender, 30-day mortality, 10-day intubation, and pharmacological interventions. Correlation between biomarkers was assessed using Spearman r. Kaplan-Meier curves and Cox proportional hazards models were constructed for 30-day mortality and 10-day intubation. Results 37 of 208 (18%) of patients died within thirty days of ED presentation and 59 (28%) required intubation within 10-days. There was a significant correlation between IL-6 and CRP (r=0.34) but not with ACE-2 binding (Spearman r &amp;lt;0.06 for both IL-6 and CRP). There was significantly higher CRP in those that died (median = 14 mg/dL, IQR = 8-21) than those that survived (5 mg/dL, 2-11). IL-6 was higher in patients that died (344 pg/mL, 0-870) than those that survived (65 pg/mL, 28-140). Median ACE-2 inhibition trended higher in those that survived (18%, 0-65%) than those that died (3%, 0-48%). Survival curves demonstrated that patients with IL-6 &amp;gt; 30 pg/mL, CRP &amp;gt; 9.6 mg/dL, and ACE2 binding &amp;lt;12.5% at baseline were more likely to die within 30-days. Multivariate modeling found that only IL-6 (Hazard Ratio, 1.28, 95%CI 1.08-1.52 for each doubling) and age (1.04, 1.01-1.08) were significantly associated with 30-day mortality. Conclusions Systemic inflammation measured by IL-6 and CRP upon admission is highly associated with 30-day mortality from SARS-CoV-2 infection. While ACE-2 inhibition was lower in those that died from COVID-19 at admission, it was not independently associated with mortality or correlated with inflammatory markers. This implies an importance of other aspects of the immune response for mediating inflammation and reducing risk of mortality from SARS-CoV-2.

A-228 Evaluation of an Equation for Low-Density Lipoproteins-Triglycerides in Predicting ASCVD Risk in the UK Biobank Population

Abstract Background Low-density lipoprotein-cholesterol (LDL-C) is the main univariate risk marker recommended for initial atherosclerotic cardiovascular disease (ASCVD) risk stratification. LDL, however, transports other constituents that can serve as pro-atherogenic risk markers. Like LDL-C, the triglyceride content of LDL (LDL-TG) can also be estimated from the lipid panel. Using data from UK Biobank (UKB), we compared LDL-C to LDL-TG for predicting future ASCVD events. Methods A UKB dataset (N=270,436) of primary prevention individuals not on lipid lowering therapy was used for analysis. LDL-C was calculated by the following equations: Friedewald, Extended Martin-Hopkins, Sampson-NIH, and Enhanced Sampson-NIH. LDL-TG was calculated by our newly devised equation (eLDL-TG = TG/38.46 + nonHDL-C/5.75 + (TG/nonHDL-C)/0.103 + (1/HDL-C)/0.0041 - 2.95)), which was derived from a dyslipidemic cohort (N=40,202) analyzed by the beta-quantification reference method. Results Although there was only a modest comparison between eLDL-TG and measured LDL-TG (R2=0.601, slope=0.611), eLDL-TG appeared to be a better risk marker than LDL-C in UKB. When the population was divided into quintiles and analyzed by survival curve analysis, eLDL-TG was better than LDL-C in segregating patients into low- and high-risk groups (Figure). Similar findings on the relative value of LDL-TG over other risk markers were also found when analyzed by ROC analysis (AUC: eLDL-TG&amp;gt;HDL-C&amp;gt;remnant-cholesterol&amp;gt;NonHDL-C&amp;gt;TG&amp;gt;apoB&amp;gt;Sampson-NIH-LDL-C). By Cox-proportional hazard analysis eLDL-TG showed alongside apoB and NonHDL-C the strongest association with future ASCVD events. Discordance analysis showed that when stratified as LDL-TG/LDL-C as High/Low there was an 26% increased risk for ASCVD, and when as High/High showed an 40% increased risk for ASCVD. Conclusions Like LDL-C, LDL-TG levels can also be estimated from the standard lipid panel. If our findings hold in other populations, the superiority of LDL-TG over LDL-C as a risk marker suggest that the reporting of calculated LDL-TG along with LDL-C could be a new strategy for improving ASCVD risk stratification.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways “BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation” and “AMAN pathway”. In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

Comparison of laparoscopic hepatectomy and radiofrequency ablation for small hepatocellular carcinoma patients: a SEER population-based propensity score matching study.

This study was designed to compare the efficacy of laparoscopic hepatectomy (LH) and radiofrequency ablation (RFA) in terms of their therapeutic effect on small hepatocellular carcinoma (SHCC). The SEER database was employed to integrate SHCC patients who had received treatment with either LH (n = 1132) or RFA (n = 797). The LH group (n = 623) and the RFA group (n = 623) were matched with 1:1 propensity score matching (PSM) in order to reduce the possibility of selection bias. The Kaplan-Meier method and Cox proportional hazards regression method were employed to ascertain the prognostic factors associated with overall survival (OS) and disease-specific survival (DSS). Both before and after PSM, the 1, 3 and 5-years OS and DSS were significantly higher in the LH groups compared to the RFA group. Besides, for SHCC with tumor size ≤ 2cm (n = 418), even P values not reaching statistical significance, the survival curves were compatible with a superiority of LH over RFA for OS and DSS in overall (P = 0.054 and P = 0.077), primary SHCC (P = 0.110 and P = 0.058) and recurrent SHCC (P = 0.068 and P = 1.000) cohorts. In contrast, for SHCC with tumor size between 2 and 3 cm (n = 828), LH group always had a better OS and DSS in the all cohorts (all P < 0.05). In addition, higher AFP level, poor differentiation grade, recurrent tumor and treatment type were independent prognostic factors for OS, while poor differentiation grade, larger tumor size and treatment type were the independent prognostic factors for DSS (all P < 0.05). LH was associated with better OS and DSS than RFA in SHCC patients. Even in tumor size ≤ 2cm, LH still should be the first choice as its long-term survival benefits.

The potential of EZH2 expression to facilitate treatment choice in stage II colorectal adenocarcinoma.

The current selection criteria of patients with stage II colorectal carcinoma (CRC) suitable for adjuvant therapy are not satisfactory. Enhancer of zeste homolog 2 (EZH2) has been demonstrated to be over-expressed in CRC. However, data regarding the role of EZH2 in CRC survival remains controversial, and little is known about it in stage II CRC. Thus, we conducted this study to investigate the clinical significance of EZH2 expression in stage II CRC. Cases with stage II CRC resected between 2015 and 2018 were retrospectively reviewed. EZH2 expression was analyzed by immunohistochemistry using tissue microarrays. The relationship between EZH2 expression and clinicopathological variables was analyzed. Survival curves were estimated by the Kaplan-Meier approach. We found high EZH2 expression in 134 of 221 analyzable stage II tumors (60.63%). No significant associations were observed between EZH2 expression and common clinicopathological factors. Survival analyses showed that cases receiving surgery alone had inferior overall survival (OS) than those receiving surgery and chemotherapy (P=0.0075) in stage II CRC with high EZH2 expression, however, metastasis-free survival (MFS) was similar between these two subgroups. Treatment choice had no impact on the survival of stage II CRC with low EZH2 expression. The OS of stage II CRC with high EZH2 expression improved more strikingly with surgery and adjuvant chemotherapy than with surgery alone, which suggests the potential of EZH2 expression as a biomarker to help identify a subgroup of early-stage CRC benefiting from surgery and adjuvant chemotherapy. More large-scale studies are warranted to corroborate this finding and to further evaluate the predictive nature of EZH2.

Impact of screening on mortality for patients diagnosed with hepatocellular carcinoma at a safety-net hospital: An opportunity for addressing disparities.

140 Background: Hepatocellular carcinoma (HCC) is a common and deadly cancer with a rising incidence in the US. HCC almost always develops on a background of chronic liver disease, which disproportionately affects individuals of lower socioeconomic status (SES), perpetuating existing disparities. Compounding these disparities, individuals of lower SES are less likely to participate in recommended cancer screening exams. Here, we describe the outcomes of patients diagnosed with HCC at a large urban safety-net hospital primarily serving the underserved. Methods: We identified patients diagnosed with HCC at John Peter Smith Hospital in Fort Worth, Texas from January 1, 2018, to March 31, 2021 to determine the impact of screening on survival. Patients were allocated to the screened cohort if they had undergone liver imaging within one year prior to HCC diagnosis. Kaplan-Meier methods and log-rank test were used to illustrate and compare 3-year survival curves from an index date of diagnosis until death. Cox proportional hazards model were used to calculate unadjusted and adjusted hazards ratios (HR) and 95% confidence intervals (CI). Lead time bias was adjusted in a sensitivity analysis using the Duffy adjustment and a sojourn time of 70 days and 140 days. Results: A total of 158 patients were included (n=53 screened, n=105 unscreened). The mean age was 62 years; 144 (91%) had cirrhosis, 78% were male, 34% were non-Hispanic white, and 8.2% had private insurance. Those in the unscreened cohort had more severe liver dysfunction (as measured by the ALBI grade) and produced higher levels of AFP, but were less likely to have cirrhosis than the screened cohort. The median overall survival (OS) for the screened cohort was 19.0 months (95% CI: 9.9-NA) and 5.4 months (95% CI: 3.7-8.5) in the unscreened cohort (HR death (unscreened v screened) = 2.4, 95% CI: 1.6-3.6; log rank P &lt;0.0001). After adjusting for ALBI grade, AFP, hepatitis C, insurance status and initial treatment, there was a statistical difference in hazard of death in the three years (HR: 2.3; 95% CI: 1.5-3.6), favoring the screened cohort. The benefit for screening remained after adjusting for lead-time bias. With a mean sojourn time of 70 days, the HR death was 2.19 (95% CI 1.4-3.3, P =0.0002) and was 2.09 (1.4-3.2, P =0.0005) with a 140-day sojourn time. Conclusions: In an urban safety-net population, screening for HCC was associated with improved outcomes compared to patients with incidentally-diagnosed HCC. Altogether, this implies that earlier diagnosis and institution of treatment can positively improve survival for patients with newly diagnosed HCC in a population of patients evaluated at a safety-net hospital. Development of screening programs in accordance with accepted guidelines with outreach to high-risk individuals represents an area of high value care for safety-net hospitals.

Construction and Validation of a Prognostic Model Based on Pyroptosis-related Genes in Bladder Cancer.

Bladder cancer (BCa) is a highly prevalent disease with a poor prognosis. There is no better forecasting method for it yet. Current studies demonstrate that pyroptosis is involved in the development and progression of various cancers. This study employed bioinformatics techniques to analyze the data of BCa patients obtained from the TCGA and GEO databases in order to construct a prognostic risk model. The TCGA dataset was used for the training set, and the multiple external datasets (including GSE13507, GSE31684, GSE48075, IMvigor210, and GSE32894) were applied as the validation sets. Prognostic-associated pyroptosis genes screened by univariate Cox regression analysis were utilized to construct the lasso Cox regression model. GO and KEGG analysis results identified the selected genes that are primarily involved in the inflammation and cell death processes. The related patients were grouped into low- and high-risk groups. Kaplan-Meier survival analysis was performed to compare survival differences between the risk groups. The accuracy of this risk prediction model was assessed by ROC. We also applied the Human Protein Atlas (HPA) to detect the protein expression of these genes. Subsequently, qRT-PCR was performed to verify the expression of these model genes. There are 29 pyroptosis-related genes with significant expression differences between BCa and corresponding adjacent tissues, and 11 genes (SH2D2A, CHMP4C, MRFAP1L1, GBP2, EHBP1, RAD9A, ANXA1, TMEM109, HEYL, APOL2, ORMDL1) were picked by univariate and LASSO Cox regression analysis. Immunological cell infiltration and ssGSEA results further indicated that the low and high-risk groups were substantially correlated with the immune status of BCa patients. According to TCGA and multiple external datasets, Kaplan-Meier survival curves showed the overall survival rate of the high-risk group to be decreased. ROC curves showed the model established to be accurate and reliable. Moreover, the HPA database also demonstrated the verification of the modeled genes' expression in BCa and normal bladder tissue using the HPA database. qRT-PCR results also suggested the up-regulated EHBP1 and down-regulated RAD9A mRNA expression levels to be confirmed in 15 pairs of BCa and corresponding adjacent tissues. This study presents the development and validation of a novel gene signature associated with pyroptosis, which holds the potential for predicting patient outcomes in BCa and providing insights into the immune microenvironment of BCa.