Short-term prognostic factors for hepatitis B virus-related acute-onchronic liver failure

BACKGROUND Acute-on-chronic liver failure(ACLF)is the abrupt exacerbation of declined hepatic function in patients with chronic liver disease.AIM To explore the independent predictors of short-term prognosis in patients with hepatitis B virus(HBV)-related ACLF and to establish a predictive short-term prognosis model for HBV-related ACLF.METHODS From January 2016 to December 2019,207 patients with HBV-related ACLF attending the 910^(th) Hospital of Chinese People's Liberation Army were continuously included in this retrospective study.Patients were stratified based on their survival status 3 mo after diagnosis.Information was collected regarding gender and age;coagulation function in terms of prothrombin time and international normalized ratio(INR);hematological profile in terms of neutrophil-tolymphocyte ratio(NLR)and platelet count(PLT);blood biochemistry in terms of alanine aminotransferase,aspartate aminotransferase,total bilirubin(Tbil),albumin,cholinesterase,blood urea nitrogen(BUN),creatinine,blood glucose,and sodium(Na);tumor markers including alpha-fetoprotein(AFP)and Golgi protein 73(GP73);virological indicators including HBV-DNA,HBsAg,HBeAg,Anti-HBe,and Anti-HBc;and complications including hepatic encephalopathy,hepatorenal syndrome,spontaneous peritonitis,gastrointestinal bleeding,and pulmonary infection.RESULTS There were 157 and 50 patients in the survival and death categories,respectively.Univariate analysis revealed significant differences in age,PLT,Tbil,BUN,NLR,HBsAg,AFP,GP73,INR,stage of liver failure,classification of liver failure,and incidence of complications(pulmonary infection,hepatic encephalopathy,spontaneous bacterial peritonitis,and upper gastrointestinal bleeding)between the two groups(P<0.05).GP73[hazard ratio(HR):1.009,95%confidence interval(CI):1.005-1.013,P=0.000],middle stage of liver failure(HR:5.056,95%CI:1.792-14.269,P=0.002),late stage of liver failure(HR:22.335,95%CI:8.544-58.388,P=0.000),pulmonary infection(HR:2.056,95%CI:1.145-3.690,P=0.016),hepatorenal syndrome(HR:6.847,95%CI:1.930-24.291,P=0.003),and HBsAg(HR:0.690,95%CI:0.524-0.908,P=0.008)were independent risk factors for short-term prognosis in patients with HBV-related ACLF.Following binary logistics regression analysis,we arrived at the following formula for predicting short-term prognosis:Logit(P)=Ln(P/1-P)=0.013×(GP73 ng/mL)+1.907×(middle stage of liver failure)+4.146×(late stage of liver failure)+0.734×(pulmonary infection)+22.320×(hepatorenal syndrome)-0.529×(HBsAg)-5.224.The predictive efficacy of the GP73-ACLF score was significantly better than that of the Model for End-Stage Liver Disease(MELD)and MELD-Na score models(P<0.05).CONCLUSION The stage of liver failure,presence of GP73,pulmonary infection,hepatorenal syndrome,and HBsAg are independent predictors of short-term prognosis in patients with HBV-related ACLF,and the GP73-ACLF model has good predictive value among these patients.

Prognostic model for esophagogastric variceal rebleeding after endoscopic treatment in liver cirrhosis: A Chinese multicenter study

BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized prognostic models that can effectively predict esophagogastric variceal rebleeding in patients with liver cirrhosis are lacking.AIM To construct and externally validate a reliable prognostic model for predicting the occurrence of esophagogastric variceal rebleeding.METHODS This study included 477 EGVB patients across 2 cohorts:The derivation cohort(n=322)and the validation cohort(n=155).The primary outcome was rebleeding events within 1 year.The least absolute shrinkage and selection operator was applied for predictor selection,and multivariate Cox regression analysis was used to construct the prognostic model.Internal validation was performed with bootstrap resampling.We assessed the discrimination,calibration and accuracy of the model,and performed patient risk stratification.RESULTS Six predictors,including albumin and aspartate aminotransferase concentrations,white blood cell count,and the presence of ascites,portal vein thrombosis,and bleeding signs,were selected for the rebleeding event prediction following endoscopic treatment(REPET)model.In predicting rebleeding within 1 year,the REPET model ex-hibited a concordance index of 0.775 and a Brier score of 0.143 in the derivation cohort,alongside 0.862 and 0.127 in the validation cohort.Furthermore,the REPET model revealed a significant difference in rebleeding rates(P<0.01)between low-risk patients and intermediate-to high-risk patients in both cohorts.CONCLUSION We constructed and validated a new prognostic model for variceal rebleeding with excellent predictive per-formance,which will improve the clinical management of rebleeding in EGVB patients.

Hemogram-derived ratios as prognostic markers for major adverse cardiovascular events in patients with non-ST-segment elevation myocardial infarction

BACKGROUND Non-ST segment elevation myocardial infarction(NSTEMI)poses significant challenges in clinical management due to its diverse outcomes.Understanding the prognostic role of hematological parameters and derived ratios in NSTEMI patients could aid in risk stratification and improve patient care.AIM To evaluate the predictive value of hemogram-derived ratios for major adverse cardiovascular events(MACE)in NSTEMI patients,potentially improving clinical outcomes.METHODS A prospective,observational cohort study was conducted in 2021 at the Internal Medicine Clinic of the University Hospital in Tuzla,Bosnia and Herzegovina.The study included 170 patients with NSTEMI,who were divided into a group with MACE and a control group without MACE.Furthermore,the MACE group was subdivided into lethal and non-lethal groups for prognostic analysis.Alongside hematological parameters,an additional 13 hematological-derived ratios(HDRs)were monitored,and their prognostic role was investigated.RESULTS Hematological parameters did not significantly differ between non-ST segment elevation myocardial infarction(NSTEMI)patients with MACE and a control group at T1 and T2.However,significant disparities emerged in HDRs among NSTEMI patients with lethal and non-lethal outcomes post-MACE.Notably,neutrophil-to-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR)were elevated in lethal outcomes.Furthermore,C-reactive protein-to-lymphocyte ratio(CRP/Ly)at T1(>4.737)demonstrated predictive value[odds ratio(OR):3.690,P=0.024].Both NLR at T1(>4.076)and T2(>4.667)emerged as significant predictors,with NLR at T2 exhibiting the highest diagnostic performance,as indicated by an area under the curve of 0.811(95%CI:0.727-0.859)and OR of 4.915(95%CI:1.917-12.602,P=0.001),emphasizing its important role as a prognostic marker.CONCLUSION This study highlights the significant prognostic value of hemogram-derived indexes in predicting MACE among NSTEMI patients.During follow-up,NLR,PLR,and CRP/Ly offer important insights into the inflammatory processes underlying cardiovascular events.

A Meta-Analysis of the Prognostic and Clinicopathological Significance of circZFR in Human Gastrointestinal Cancers

Background: Studies of gastrointestinal (GIT) cancers have shown that circZFR could be involved in the development and progression of various GIT cancers. However, small sample sizes limit the clinical significance of these studies. Here, a meta-analysis was conducted to ascertain the actual involvement of circZFR in the development and prognosis of GIT cancers. Methods: PubMed, Embase, Web of Science, and the Cochrane Library were searched up to December 31, 2023. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were pooled to evaluate the association between circZFR expression and overall survival (OS). Publication bias was measured using the funnel plot and Egger’s test. Results: 10 studies having 659 participants were enrolled for meta-analysis. High circZFR expression was associated with poor OS (HR = 1.4, 95% CI: 1.20, 1.70). High circZFR expression also predicted larger tumor size (OR = 4.38, 95% CI 2.65, 7.25), advanced clinical stage (OR = 5.33, 95% CI 3.10, 9.16), and tendency for distant metastasis (OR = 2.89, 95% CI: 1.62, 5.11), but was not related to age, gender, and histological grade. Conclusions: In summary, high circZFR expression was associated with poor OS, larger tumor size, advanced stage cancer and tendency for distant metastasis. These findings suggested that circZFR could be a prognostic marker for GIT cancers.

Construction and validation of a pancreatic cancer prognostic model based on genes related to the hypoxic tumor microenvironment

BACKGROUND Pancreatic cancer is one of the most lethal malignancies,characterized by poor prognosis and low survival rates.Traditional prognostic factors for pancreatic cancer offer inadequate predictive accuracy,often failing to capture the complexity of the disease.The hypoxic tumor microenvironment has been recognized as a significant factor influencing cancer progression and resistance to treatment.This study aims to develop a prognostic model based on key hypoxia-related molecules to enhance prediction accuracy for patient outcomes and to guide more effective treatment strategies in pancreatic cancer.AIM To develop and validate a prognostic model for predicting outcomes in patients with pancreatic cancer using key hypoxia-related molecules.METHODS This pancreatic cancer prognostic model was developed based on the expression levels of the hypoxia-associated genes CAPN2,PLAU,and CCNA2.The results were validated in an independent dataset.This study also examined the correlations between the model risk score and various clinical features,components of the immune microenvironment,chemotherapeutic drug sensitivity,and metabolism-related pathways.Real-time quantitative PCR verification was conducted to confirm the differential expression of the target genes in hypoxic and normal pancreatic cancer cell lines.RESULTS The prognostic model demonstrated significant predictive value,with the risk score showing a strong correlation with clinical features:It was significantly associated with tumor grade(G)(bP<0.01),moderately associated with tumor stage(T)(aP<0.05),and significantly correlated with residual tumor(R)status(bP<0.01).There was also a significant negative correlation between the risk score and the half-maximal inhibitory concentration of some chemotherapeutic drugs.Furthermore,the risk score was linked to the enrichment of metabolism-related pathways in pancreatic cancer.CONCLUSION The prognostic model based on hypoxia-related genes effectively predicts pancreatic cancer outcomes with improved accuracy over traditional factors and can guide treatment selection based on risk assessment.

Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data

BACKGROUND Pyroptosis impacts the development of malignant tumors,yet its role in colorectal cancer(CRC)prognosis remains uncertain.AIM To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration.METHODS Gene expression data were obtained from The Cancer Genome Atlas(TCGA)and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus(GEO).Pyroptosis-related gene expression in cell clusters was analyzed,and enrichment analysis was conducted.A pyroptosis-related risk model was developed using the LASSO regression algorithm,with prediction accuracy assessed through K-M and receiver operating characteristic analyses.A nomo-gram predicting survival was created,and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations.Finally,the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database.RESULTS An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B,SDHB,BST2,UBE2D2,GJA1,AIM2,PDCD6IP,and SEZ6L2(P<0.05).Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis(P<0.05).Patients with higher risk scores demonstrated increased death risk and reduced overall survival(P<0.05).Significant differences in immune infiltration were observed between low-and high-risk groups,correlating with pyroptosis-related gene expression.CONCLUSION We developed a pyroptosis-related prognostic model for CRC,affirming its correlation with immune infiltration.This model may prove useful for CRC prognostic evaluation.

Prognostic analysis of related factors of adverse reactions to immunotherapy in advanced gastric cancer and establishment of a nomogram model

BACKGROUND Immunotherapy for advanced gastric cancer has attracted widespread attention in recent years.However,the adverse reactions of immunotherapy and its relationship with patient prognosis still need further study.In order to determine the association between adverse reaction factors and prognosis,the aim of this study was to conduct a systematic prognostic analysis.By comprehensively evaluating the clinical data of patients with advanced gastric cancer treated by immunotherapy,a nomogram model will be established to predict the survival status of patients more accurately.AIM To explore the characteristics and predictors of immune-related adverse reactions(irAEs)in advanced gastric cancer patients receiving immunotherapy with programmed death protein-1(PD-1)inhibitors and to analyze the correlation between irAEs and patient prognosis.METHODS A total of 140 patients with advanced gastric cancer who were treated with PD-1 inhibitors in our hospital from June 2021 to October 2023 were selected.Patients were divided into the irAEs group and the non-irAEs group according to whether or not irAEs occurred.Clinical features,manifestations,and prognosis of irAEs in the two groups were collected and analyzed.A multivariate logistic regression model was used to analyze the related factors affecting the occurrence of irAEs,and the prediction model of irAEs was established.The receiver operating characteristic(ROC)curve was used to evaluate the ability of different indicators to predict irAEs.A Kaplan-Meier survival curve was used to analyze the correlation between irAEs and prognosis.The Cox proportional risk model was used to analyze the related factors affecting the prognosis of patients.RESULTS A total of 132 patients were followed up,of whom 63(47.7%)developed irAEs.We looked at the two groups’clinical features and found that the two groups were statistically different in age≥65 years,Ki-67 index,white blood cell count,neutrophil count,and regulatory T cell(Treg)count(all P<0.05).Multivariate logistic regression analysis showed that Treg count was a protective factor affecting irAEs occurrence(P=0.030).The ROC curve indicated that Treg+Ki-67+age(≥65 years)combined could predict irAEs well(area under the curve=0.753,95%confidence interval:0.623-0.848,P=0.001).Results of the Kaplan-Meier survival curve showed that progressionfree survival(PFS)was longer in the irAEs group than in the non-irAEs group(P=0.001).Cox proportional hazard regression analysis suggested that the occurrence of irAEs was an independent factor for PFS(P=0.006).CONCLUSION The number of Treg cells is a separate factor that affects irAEs in advanced gastric cancer patients receiving PD-1 inhibitor immunotherapy.irAEs can affect the patients’PFS and result in longer PFS.Treg+Ki-67+age(≥65 years old)combined can better predict the occurrence of adverse reactions.

Use of machine learning models for the prognostication of liver transplantation: A systematic review

BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.

Establishment and evaluation of a prognostic model for patients with unresectable gastric cancer liver metastases

BACKGROUND Liver metastases(LM)is the primary factor contributing to unfavorable outcomes in patients diagnosed with gastric cancer(GC).The objective of this study is to analyze significant prognostic risk factors for patients with GCLM and develop a reliable nomogram model that can accurately predict individualized prognosis,thereby enhancing the ability to evaluate patient outcomes.AIM To analyze prognostic risk factors for GCLM and develop a reliable nomogram model to accurately predict individualized prognosis,thereby enhancing patient outcome assessment.METHODS Retrospective analysis was conducted on clinical data pertaining to GCLM(type III),admitted to the Department of General Surgery across multiple centers of the Chinese PLA General Hospital from January 2010 to January 2018.The dataset was divided into a development cohort and validation cohort in a ratio of 2:1.In the development cohort,we utilized univariate and multivariate Cox regression analyses to identify independent risk factors associated with overall survival in GCLM patients.Subsequently,we established a prediction model based on these findings and evaluated its performance using receiver operator characteristic curve analysis,calibration curves,and clinical decision curves.A nomogram was created to visually represent the prediction model,which was then externally validated using the validation cohort.RESULTS A total of 372 patients were included in this study,comprising 248 individuals in the development cohort and 124 individuals in the validation cohort.Based on Cox analysis results,our final prediction model incorporated five independent risk factors including albumin levels,primary tumor size,presence of extrahepatic metastases,surgical treatment status,and chemotherapy administration.The 1-,3-,and 5-years Area Under the Curve values in the development cohort are 0.753,0.859,and 0.909,respectively;whereas in the validation cohort,they are observed to be 0.772,0.848,and 0.923.Furthermore,the calibration curves demonstrated excellent consistency between observed values and actual values.Finally,the decision curve analysis curve indicated substantial net clinical benefit.CONCLUSION Our study identified significant prognostic risk factors for GCLM and developed a reliable nomogram model,demonstrating promising predictive accuracy and potential clinical benefit in evaluating patient outcomes.

Preoperative controlling nutritional status as an optimal prognostic nutritional index to predict the outcome for colorectal cancer

BACKGROUND The controlling nutritional status(CONUT)score effectively reflects a patient’s nutritional status,which is closely related to cancer prognosis.This study invest-igated the relationship between the CONUT score and prognosis after radical surgery for colorectal cancer,and compared the predictive ability of the CONUT score with other indexes.AIM To analyze the predictive performance of the CONUT score for the survival rate of colorectal cancer patients who underwent potentially curative resection.METHODS This retrospective analysis included 217 patients with newly diagnosed colorectal.The CONUT score was calculated based on the serum albumin level,total lymphocyte count,and total cholesterol level.The cutoff value of the CONUT score for predicting prognosis was 4 according to the Youden Index by the receiver operating characteristic curve.The associations between the CONUT score and the prognosis were performed using Kaplan-Meier curves and Cox regression analysis.RESULTS Using the cutoff value of the CONUT score,patients were stratified into CONUT low(n=189)and CONUT high groups(n=28).The CONUT high group had worse overall survival(OS)(P=0.013)and relapse-free survival(RFS)(P=0.015).The predictive performance of CONUT was superior to the modified Glasgow prognostic score,the prognostic nutritional index,and the neutrophil-to-lymphocyte ratio.Meanwhile,the predictive performances of CONUT+tumor node metastasis(TNM)stage for 3-year OS[area under the receiver operating characteristics curve(AUC)=0.803]and 3-year RFS(AUC=0.752)were no less than skeletal muscle mass index(SMI)+TNM stage.The CONUT score was negatively correlated with SMI(P<0.01).CONCLUSION As a nutritional indicator,the CONUT score could predict long-term outcomes after radical surgery for colorectal cancer,and its predictive ability was superior to other indexes.The correlation between the CONUT score and skeletal muscle may be one of the factors that play a predictive role.

Prognostic value of PEA3 subfamily gene expression in cholangiocarcinoma

BACKGROUND Cholangiocarcinoma(CCA)is a lethal malignancy with limited treatment options and poor prognosis.The PEA3 subfamily of E26 transformation specific genes:ETV1,ETV4,and ETV5 are known to play significant roles in various cancers by influencing cell proliferation,invasion,and metastasis.AIM To analyze PEA3 subfamily gene expression levels in CCA and their correlation with clinical parameters to determine their prognostic value for CCA.METHODS The expression levels of PEA3 subfamily genes in pan-cancer and CCA data in the cancer genome atlas and genotype-tissue expression project databases were analyzed with R language software.Survival curve and receiver operating characteristic analyses were performed using the SurvMiner,Survival,and Procr language packages.The gene expression profiling interactive analysis 2.0 database was used to analyze the expression levels of PEA3 subfamily genes in different subtypes and stages of CCA.Web Gestalt was used to perform the gene ontology/Kyoto encyclopedia of genes and genomes(GO/KEGG)analysis,and STRING database analysis was used to determine the genes and proteins related to PEA3 subfamily genes.RESULTS ETV1,ETV4,and ETV5 expression levels were significantly increased in CCA.There were significant differences in ETV1,ETV4,and ETV5 expression levels among the different subtypes of CCA,and predictive analysis revealed that only high ETV1 and ETV4 expression levels were significantly associated with shorter overall survival in patients with CCA.GO/KEGG analysis revealed that PEA3 subfamily genes were closely related to transcriptional misregulation in cancer.In vitro and in vivo experiments revealed that PEA3 silencing inhibited the invasion and metastasis of CCA cells.CONCLUSION The expression level of ETV4 may be a predictive biomarker of survival in patients with CCA.

Elucidating the molecular basis of ATP-induced cell death in breast cancer: Construction of a robust prognostic model

BACKGROUND Breast cancer is a multifaceted and formidable disease with profound public health implications.Cell demise mechanisms play a pivotal role in breast cancer pathogenesis,with ATP-triggered cell death attracting mounting interest for its unique specificity and potential therapeutic pertinence.AIM To investigate the impact of ATP-induced cell death(AICD)on breast cancer,enhancing our understanding of its mechanism.METHODS The foundational genes orchestrating AICD mechanisms were extracted from the literature,underpinning the establishment of a prognostic model.Simultaneously,a microRNA(miRNA)prognostic model was constructed that mirrored the gene-based prognostic model.Distinctions between high-and low-risk cohorts within mRNA and miRNA characteristic models were scrutinized,with the aim of delineating common influence mechanisms,substantiated through enrichment analysis and immune infiltration assessment.RESULTS The mRNA prognostic model in this study encompassed four specific mRNAs:P2X purinoceptor 4,pannexin 1,caspase 7,and cyclin 2.The miRNA prognostic model integrated four pivotal miRNAs:hsa-miR-615-3p,hsa-miR-519b-3p,hsa-miR-342-3p,and hsa-miR-324-3p.B cells,CD4+T cells,CD8+T cells,endothelial cells,and macrophages exhibited inverse correlations with risk scores across all breast cancer subtypes.Furthermore,Kyoto Encyclopedia of Genes and Genomes analysis revealed that genes differentially expressed in response to mRNA risk scores significantly enriched 25 signaling pathways,while miRNA risk scores significantly enriched 29 signaling pathways,with 16 pathways being jointly enriched.CONCLUSION Of paramount significance,distinct mRNA and miRNA signature models were devised tailored to AICD,both potentially autonomous prognostic factors.This study's elucidation of the molecular underpinnings of AICD in breast cancer enhances the arsenal of potential therapeutic tools,offering an unparalleled window for innovative interventions.Essentially,this paper reveals the hitherto enigmatic link between AICD and breast cancer,potentially leading to revolutionary progress in personalized oncology.

Development of a prognostic scoring system for hepatic vena cava Budd-Chiari syndrome with hepatocellular carcinoma

Background:Hepatocellular carcinoma(HCC)is a serious complication of hepatic vena cava Budd-Chiari syndrome(HVC-BCS)that significantly reduces the survival time of patients.Our study aimed to analyze the prognostic factors influencing the survival of HVC-BCS patients with HCC and to develop a prognostic scoring system.Methods:The clinical and follow-up data of 64 HVC-BCS patients with HCC who received invasive treatment at the First Affiliated Hospital of Zhengzhou University between January 2015 and December 2019 were retrospectively analyzed.Kaplan-Meier curves and log-rank tests were used to analyze the survival curve of patients and the difference in prognoses between the groups.Univariate and multivariate Cox regression analyses were performed to analyze the influence of biochemical,tumor,and etiological characteristics on the total survival time of patients,and a new prognostic scoring system was developed according to the regression coefficients of the independent predictors in the statistical model.The prediction efficiency was evaluated using the time-dependent receiver operating characteristics curve and concordance index.Results:Multivariate analysis showed that serum albumin level<34 g/L[hazard ratio(HR)=4.207,95%confidence interval(CI):1.816-8.932,P=0.001],maximum tumor diameter>7 cm(HR=8.623,95%CI:3.771-19.715,P<0.001),and inferior vena cava stenosis(HR=3.612,95%CI:1.646-7.928,P=0.001)were independent predictors of survival.A prognostic scoring system was developed according to the above-mentioned independent predictors,and patients were classified into grades A,B,C and D.Significant differences in survival were found among the four groups.Conclusions:This study successfully developed a prognostic scoring system for HVC-BCS patients with HCC,which is helpful for clinical evaluation of patient prognosis.

Advancing prognostic precision in gastric cancer with an immunoinflammatory index

Gastric cancer remains a major global health challenge with high morbidity and mortality rates.Recent advancements in immunology and inflammation research have highlighted the crucial roles that these biological processes play in tumor progression and patient outcomes.This has sparked new interest in developing prognostic biomarkers that integrate these two key biological processes.In this letter,we discuss the recent study by Ba et al,which proposed a novel prognostic immunoinflammatory index for patients with gastric cancer.We underscore the importance of this research,its potential impact on medical practice,and the prospective avenues for further investigation in this rapidly emerging area of study.

A pilot clinical study to evaluate feasibility of using single patient classifier as a prognostic test in stage Ⅱ-Ⅲ gastric cancer patients

Objective:Precision medicine approaches emphasize the importance of reliable prognostic tools for guiding individualized therapy decisions.In this study,we evaluated the clinical feasibility of the single patient classifier(SPC)test,a new clinical-grade prognostic assay,in stageⅡ-Ⅲgastric cancer patients.Methods:A prospective multicenter study was conducted,involving 237 patients who underwent gastrectomy between September 2019 and August 2020 across nine hospitals.The SPC test was employed to stratify patients into risk groups,and its feasibility and performance were evaluated.The primary endpoint was the proportion of the cases in which the test results were timely delivered before selecting postoperative treatment.Furthermore,3-year disease-free survivals of risk groups were analyzed.Results:The SPC test met the primary endpoint criteria.The 99.5%of SPC tests were timely delivered to hospitals before the postoperative treatment started.In a clinical setting,the median time from the specimen transfer to laboratory to the result delivery to hospital was 4 d.Furthermore,3-year disease-free survivals were significantly different between risk groups classified with SPC tests.Conclusions:This study highlights the SPC test's feasibility in offering crucial information timely delivered for making informed decisions regarding postoperative treatment strategies.It also provides evidence to support the implementation of a future prospective clinical trial aimed at evaluating the clinical utility of the SPC test in guiding personalized treatment decisions for gastric cancer patients.

A comprehensive and systematic analysis of Dihydrolipoamide S-acetyltransferase (DLAT) as a novel prognostic biomarker in pan-cancer and glioma

Background:Dihydrolipoamide S-acetyltransferase(DLAT)is a subunit of the pyruvate dehydrogenase complex(PDC),a rate-limiting enzyme complex,that can participate in either glycolysis or the tricarboxylic acid cycle(TCA).However,the pathogenesis is not fully understood.We aimed to perform a more systematic and comprehensive analysis of DLAT in the occurrence and progression of tumors,and to investigate its function in patients’prognosis and immunotherapy.Methods:The differential expression,diagnosis,prognosis,genetic and epigenetic alterations,tumor microenvironment,stemness,immune infiltration cells,function enrichment,single-cell analysis,and drug response across cancers were conducted based on multiple computational tools.Additionally,we validated its carcinogenic effect and possible mechanism in glioma cells.Results:We exhibited that DLAT expression was increased in most tumors,especially in glioma,and affected the survival of tumor patients.DLAT was related to RNA modification genes,DNA methylation,immune infiltration,and immune infiltration cells,including CD4+T cells,CD8+T cells,Tregs,and cancer-associatedfibroblasts.Single-cell analysis displayed that DLAT might regulate cancer by mediating angiogenesis,inflammation,and stemness.Enrichment analysis revealed that DLAT might take part in the cell cycle pathway.Increased expression of DLAT leads tumor cells to be more resistant to many kinds of compounds,including PI3Kβinhibitors,PKC inhibitors,HSP90 inhibitors,and MEK inhibitors.In addition,glioma cells with DLAT silence inhibited proliferation,migration,and invasion ability,and promoted cell apoptosis.Conclusion:We conducted a comprehensive analysis of DLAT in the occurrence and progression of tumors,and its possible functions and mechanisms.DLAT is a potential diagnostic,prognostic,and immunotherapeutic biomarker for cancer patients.

Clinical features and prognostic factors of duodenal neuroendocrine tumours:A comparative study of ampullary and nonampullary regions

BACKGROUND Duodenal neuroendocrine tumours(DNETs)are rare neoplasms.However,the incidence of DNETs has been increasing in recent years,especially as an incidental finding during endoscopic studies.Regrettably,there is no consensus regarding the ideal treatment of DNETs.Even there are few studies on the clinical features and survival analysis of DNETs.AIM To analyze the clinical characteristics and prognostic factors of patients with duodenal neuroendocrine tumours.METHODS The clinical data of DNETs diagnosed in the First Affiliated Hospital of Air Force Military Medical University from June 2011 to July 2022 were collected.Neuroen-docrine tumours located in the ampulla area of the duodenum were divided into the ampullary region group;neuroendocrine tumours in any part of the duo-denum outside the ampullary area were divided into the nonampullary region group.Using a retrospective study,the clinical characteristics of the two groups and risk factors affecting the survival of DNET patients were analysed.RESULTS Twenty-nine DNET patients were screened.The male to female ratio was 1:1.9,and females comprised the majority.The ampullary region group accounted for 24.1%(7/29),while the nonampullary region group accounted for 75.9%(22/29).When diagnosed,the clinical symptoms of the ampullary region group were mainly abdominal pain(85.7%),while those of the nonampullary region groups were mainly abdominal distension(59.1%).There were differences in the composition of staging of tumours between the two groups(Fisher's exact probability method,P=0.001),with nonampullary stage II tumours(68.2%)being the main stage(P<0.05).After the diagnosis of DNETs,the survival rate of the ampullary region group was 14.3%(1/7),which was lower than that of 72.7%(16/22)in the nonampullary region group(Fisher's exact probability method,P=0.011).The survival time of the ampullary region group was shorter than that of the nonampullary region group(P<0.000).The median survival time of the ampullary region group was 10.0 months and that of the nonampullary region group was 451.0 months.Multivariate analysis showed that tumours in the ampulla region and no surgical treatment after diagnosis were independent risk factors for the survival of DNET patients(HR=0.029,95%CI 0.004-0.199,P<0.000;HR=12.609,95%CI:2.889-55.037,P=0.001).Further analysis of nonampullary DNET patients showed that the survival time of patients with a tumour diameter<2 cm was longer than that of patients with a tumour diameter≥2 cm(t=7.243,P=0.048).As of follow-up,6 patients who died of nonampullary DNETs had a tumour diameter that was≥2 cm,and 3 patients in stage IV had liver metastasis.Patients with a tumour diameter<2 cm underwent surgical treatment,and all survived after surgery.CONCLUSION Surgical treatment is a protective factor for prolonging the survival of DNET patients.Compared to DNETs in the ampullary region,patients in the nonampullary region group had a longer survival period.The liver is the organ most susceptible to distant metastasis of nonampullary DNETs.

Prognostic value of neutrophil-to-lymphocyte ratio in gastric cancer patients undergoing neoadjuvant chemotherapy:A systematic review and meta-analysis

BACKGROUND In recent studies,accumulating evidence has revealed a strong association between the inflammatory response and the prognosis of many tumors.There is a certain correlation of neutrophil-to-lymphocyte ratio(NLR)with the prognosis in gastric cancer(GC)patients undergoing neoadjuvant chemotherapy(NAC).However,the existing research results have remained controversial.AIM To explore the relationship between NLR ratio and prognosis of GC patients receiving NAC.METHODS A thorough systematic search was performed in databases such as PubMed,Embase,Web of Science,and Cochrane Library,the search is available until February 29,2024,and studies exploring the interaction of NLR with clinical outcomes were collected.Relevant studies meeting pre-defined inclusion and exclusion criteria were carefully chosen.The outcomes included progression-free survival(PFS),relapse-free survival,disease-free survival(DFS),and overall survival(OS).The hazard ratio(HR)and its corresponding 95%confidence interval(CI)were utilized for estimation.RESULTS Our analysis encompassed 852 patients and incorporated data from 12 cohort studies.The comprehensive analysis revealed a significant association of high NLR with reduced OS(HR=1.76;95%CI:1.22-2.54,P=0.003),relapsefree survival(HR=3.73;95%CI:1.74-7.96,P=0.0007),and PFS(HR=2.32;95%CI:1.42-3.81,P=0.0008)in patients.However,this correlation in disease-free survival was not significant.NLR demonstrated its crucial role in effectively predicting the OS of GC patients undergoing NAC at different detection times,ages,regions,and NLR thresholds.CONCLUSION In GC patients receiving NAC,an elevated NLR is strongly associated with reduced OS and PFS.NLR has become an effective biomarker for patient prognosis evaluation,providing valuable insights for the treatment strategies of NAC in GC patients.

A Prognostic Model Based on Colony Stimulating Factors-related Genes in Triple-negative Breast Cancer

Objective Triple-negative breast cancer(TNBC)is the breast cancer subtype with the worst prognosis,and lacks effective therapeutic targets.Colony stimulating factors(CSFs)are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells,playing an important role in the malignant progression of TNBC.This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes(CRGs),and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy.Methods We downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database.Through LASSO Cox regression analysis,we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score(CRRS).We further analyzed the correlation between CRRS and patient prognosis,clinical features,tumor microenvironment(TME)in both high-risk and low-risk groups,and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy.Results We identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model.Kaplan-Meier survival curves,time-dependent receiver operating characteristic curves,and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival,and the predictive ability of CRRS prognostic model was further validated using the GEO dataset.Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients.Moreover,patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil,ipatasertib,and paclitaxel.Conclusion We have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs,which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment.Moreover,the key genes within this model may represent potential molecular targets for future therapies of TNBC.

Validation of prognostic scores for predicting acute liver failure and in-hospital death in patients with dengue-induced severe hepatitis

BACKGROUND Acute liver failure(ALF)in dengue is rare but fatal.Early identification of patients who are at risk of ALF is the key strategy to improve survival.AIM To validate prognostic scores for predicting ALF and in-hospital mortality in dengue-induced severe hepatitis(DISH).METHODS We retrospectively reviewed 2532 dengue patients over a period of 16 years(2007-2022).Patients with DISH,defined as transaminases>10 times the normal reference level and DISH with subsequent ALF,were included.Univariate regre-ssion analysis was used to identify factors associated with outcomes.Youden’s index in conjunction with receiver operating characteristic(ROC)analysis was used to determine optimal cut-off values for prognostic scores in predicting ALF and in-hospital death.Area under the ROC(AUROC)curve values were compared using paired data nonparametric ROC curve estimation.RESULTS Of 193 DISH patients,20 developed ALF(0.79%),with a mortality rate of 60.0%.International normalized ratio,bilirubin,albumin,and creatinine were indepen-dent predictors associated with ALF and death.Prognostic scores showed excel-lent performance:Model for end-stage liver disease(MELD)score≥15 predicted ALF(AUROC 0.917,sensitivity 90.0%,specificity 88.4%)and≥18 predicted death(AUROC 0.823,sensitivity 86.9%,specificity 89.1%);easy albumin-bilirubin(ALBI)score≥-30 predicted ALF and death(ALF:AUROC 0.835,sensitivity80.0%,specificity 72.2%;death:AUROC 0.808,sensitivity 76.9%,specificity 69.3%);ALBI score≥-2 predicted ALF and death(ALF:AUROC 0.806,sensitivity 80.0%,specificity 77.4%;death:AUROC 0.799,sensitivity 76.9%,specificity 74.3%).Platelet-ALBI score also showed good performance in predicting ALF and death(AUROC=0.786 and 0.699,respectively).MELD and EZ-ALBI scores had similar performance in predicting ALF(Z=1.688,P=0.091)and death(Z=0.322,P=0.747).CONCLUSION MELD score is the best predictor of ALF and death in DISH patients.EZ-ALBI score,a simpler yet effective score,shows promise as an alternative prognostic tool in dengue patients.