Objective： In our previous work, we incorporated complete blood count （CBC） into TNM stage to develop a new prognostic score model, which was validated to improve prediction efficiency of TNM stage for nasopharynge...Objective： In our previous work, we incorporated complete blood count （CBC） into TNM stage to develop a new prognostic score model, which was validated to improve prediction efficiency of TNM stage for nasopharyngeal carcinoma （NPC）. The purpose of this study was to revalidate the accuracy of the model, and its superiority to TNM stage, through data from a prospective study.Methods： CBC of 249 eligible patients from the 863 Program No. 2006AA02Z4B4 was evaluated. Prognostic index （PI） of each patient was calculated according to the score model. Then they were divided by the PI into three categories： the low-, intermediate-and high-risk patients. The 5-year disease-specific survival （DSS） of the three categories was compared by a log-rank test. The model and TNM stage （Tth edition） were compared on efficiency for predicting the 5-year DSS, through comparison of the area under curve （AUC） of their receiver-operating characteristic curves.Results： The 5-year DSS of the low-, intermediate- and high-risk patients were 96.0%, 79.1% and 62.2%, respectively. The low- and intermediate-risk patients had better DSS than the high-risk patients （P〈0.001 and P〈0.005, respectively）. And there was a trend of better DSS in the low-risk patients, compared with the intermediate-risk patients （P=0.049）. The AUC of the model was larger than that of TNM stage （0.726 vs. 0.661, P：0.023）. Conclusions： A CBC-based prognostic score model was revalidated to be accurate and superior to TNM stage on predicting 5-year DSS of NPC.展开更多
Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulf...Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. Methods From the hos- pital electronic medical database, we idemified 3550 patients who received PCI （78.0% males, mean age 60 years） in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic 01OC） analysis were performed. Results The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation （all P 〈 0.001）. The rate of VVRS [95% confidence interval （CI）] in patients receiving PCI was 4.5% （4.1%-5.6%）. Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stems im- plantation in the left anterior descending （LAD）, and the femoral puncture site. The multivariate analysis suggested that they were independ- ent risk factors for predicting the incidence of VVRS （all P 〈 0.001）. We developed a risk prediction score model for VVRS. ROC analysis showed that the risk prediction score model was effectively predictive of the incidence of VVRS in patients receiving PCI （c-statistic 0.76, 95% CI： 0.72-0.79, P 〈 0.001）. There were decreased evems of VVRS in the patients receiving PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute （AUC： 0.84, 95% CI： 0.81-0.87, P 〈 0.001）. Conclusion The risk prediction score is quite efficient in predicting the incidence of VVRS in patients receiving PCI. In which, the following factors may be in- volved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.展开更多
BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for...BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for clinical stage II/III rectal cancer.However,few patients achieve a complete pathological response,and most patients require surgical resection and adjuvant therapy.Therefore,identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival(OS)and disease-free survival(DFS)for LARC treated with NT.METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017.The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors,which were validated by the Cox regression method.Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves,and that of the two nomograms was conducted by calculating the concordance index(C-index)and calibration curves.The results were validated in a cohort of 65 patients from 2015 to 2017.RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model:Vascular_tumors_bolt,cancer nodules,yN,body mass index,matchmouth distance from the edge,nerve aggression and postoperative carcinoembryonic antigen.The nomogram showed good predictive value for OS,with a C-index of 0.91(95%CI:0.85,0.97)and good calibration.In the validation cohort,the C-index was 0.69(95%CI:0.53,0.84).The risk factor prediction model showed good predictive value.The areas under the curve for 3-and 5-year survival were 0.811 and 0.782.The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77(95%CI:0.69,0.85).In the validation cohort,the C-index was 0.71(95%CI:0.61,0.81).The prediction model for DFS also had good predictive value,with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.展开更多
AIM: To establish a clinical scoring model to predict risk of acute-on-chronic liver failure(ACLF) in chronic hepatitis B(CHB) patients.METHODS: This was a retrospective study of 1457 patients hospitalized for CHB bet...AIM: To establish a clinical scoring model to predict risk of acute-on-chronic liver failure(ACLF) in chronic hepatitis B(CHB) patients.METHODS: This was a retrospective study of 1457 patients hospitalized for CHB between October 2008 and October 2013 at the Beijing Ditan Hospital, Capital Medical University, China. The patients were divided into two groups: severe acute exacerbation(SAE) group(n = 382) and non-SAE group(n = 1075). The SAE group was classified as the high-risk group based on the higher incidence of ACLF in this group than in the non-SAE group(13.6% vs 0.4%). Two-thirds of SAE patients were randomly assigned to risk-model derivation and the other one-third to model validation. Univariate risk factors associated with the outcome were entered into a multivariate logistic regression model for screening independent risk factors. Each variable was assigned an integer value based on the regression coefficients, and the final score was the sum of these values in the derivation set. Model discrimination and calibration were assessed using area under the receiver operating characteristic curve and the Hosmer-Lemeshow test. RESULTS: The risk prediction scoring model includedthe following four factors: age ≥ 40 years, total bilirubin ≥ 171 μmol/L, prothrombin activity 40%-60%, and hepatitis B virus DNA > 107 copies/m L. The sum risk score ranged from 0 to 7; 0-3 identified patients with lower risk of ACLF, whereas 4-7 identified patients with higher risk. The Kaplan-Meier analysis showed the cumulative risk for ACLF and ACLF-related death in the two risk groups(0-3 and 4-7 scores) of the primary cohort over 56 d, and log-rank test revealed a significant difference(2.0% vs 33.8% and 0.8% vs 9.4%, respectively; both P < 0.0001). In the derivation and validation data sets, the model had good discrimination(C index = 0.857, 95% confidence interval: 0.800-0.913 and C index = 0.889, 95% confidence interval: 0.820-0.957, respectively) and calibration demonstrated by the Hosmer-Lemeshow test(χ2 = 4.516, P = 0.808 and χ2 = 1.959, P = 0.923, respectively).CONCLUSION: Using the scoring model, clinicians can easily identify patients(total score ≥ 4) at high risk of ACLF and ACLF-related death early during SAE.展开更多
Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8^(+)T cell immune infiltration and immune suppression.We constructed a CD8^(+)T cells related risk score model to predic...Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8^(+)T cell immune infiltration and immune suppression.We constructed a CD8^(+)T cells related risk score model to predict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8^(+)T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS 2,and TNFRSF1B was constructed.The risk score model was well validated through an independent external validation cohort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P<0.0001)and lower CD8^(+)T cells infiltration(P<0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P<0.01).Drug sensitivity analysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene model was verified by immunohistochemistry.In summary,the establishment and validation of a CD8^(+)T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.展开更多
The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT...The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.展开更多
BACKGROUND Designing a feasible risk prediction model for advanced colorectal neoplasia(ACN)can enhance colonoscopy screening efficiency.Abdominal obesity is associated with colorectal cancer development.AIM To propos...BACKGROUND Designing a feasible risk prediction model for advanced colorectal neoplasia(ACN)can enhance colonoscopy screening efficiency.Abdominal obesity is associated with colorectal cancer development.AIM To propose and evaluate a modified scoring model incorporating waist-hip ratio for the prediction of ACN.METHODS A total of 6483 patients who underwent their first screening or diagnostic colonoscopy in our center between 2020 and 2023 were recruited,in which 4592 were in the derivation cohort and 1891 formed a validation cohort.Multivariate logistic regression was used to investigate the risk factors of ACN in the derivation cohort based on endoscopic findings,and a new scoring model for ACN prediction was developed.The discriminatory capability of the scoring model was validated by the validation cohort.RESULTS Age,male gender,smoking,and wait-to-hip ratio were identified as independent risk factors for ACN,and a 7-point scoring model was developed.The prevalence of ACN was 3.3%,9.3%and 18.5%in participants with scores of 0-2[low risk(LR)],3–4[moderate risk(MR)],and 5–7[high risk(HR)],respectively,in the derivation cohort.With the scoring model,49.9%,38.4%,and 11.7%of patients in the validation cohort were categorized as LR,MR,and HR,respectively.The corresponding prevalence rates of ACN were 5.0%,10.3%,and 17.6%,respectively.The C-statistic of the new scoring model was 0.66,which was higher than that of the Asia-Pacific Colorectal Screening model(0.63).CONCLUSION A modified scoring model incorporating waist-hip ratio has an improved predictive performance in the prediction of ACN.展开更多
This editorial discusses an article by Liu et al,which focuses on the development and evaluation of a modified scoring model incorporating the waist-to-hip ratio for predicting advanced colorectal neoplasia(ACN).This ...This editorial discusses an article by Liu et al,which focuses on the development and evaluation of a modified scoring model incorporating the waist-to-hip ratio for predicting advanced colorectal neoplasia(ACN).This editorial provides an overview of the study,including the background of ACN risk prediction,the study design,key findings,and the significance and limitations of the new model.The study identified independent risk factors for ACN and developed a 7-point scoring model with better predictive performance than existing models.However,challenges,such as generalizability across ethnic groups and selection bias,exist.Further research involving multi-ethnic cohorts and the integration of novel biomarkers is needed to improve the model and its clinical application.展开更多
With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily meas...With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.展开更多
BACKGROUND Chronic liver disease is a growing global health problem,leading to hepatic decompensation characterized by an array of clinical and biochemical complic-ations.Several scoring systems have been introduced i...BACKGROUND Chronic liver disease is a growing global health problem,leading to hepatic decompensation characterized by an array of clinical and biochemical complic-ations.Several scoring systems have been introduced in assessing the severity of hepatic decompensation with the most frequent ones are Child-Pugh score,model of end-stage liver disease(MELD)score,and MELD-Na score.Anemia is frequently observed in cirrhotic patients and is linked to worsened clinical outcomes.Although studies have explored anemia in liver disease,few have investigated the correlation of hemoglobin level with the severity of hepatic decompensation.AIM To determine the relationship between hemoglobin levels and the severity of decompensated liver disease and comparing the strength of this correlation using the Child-Pugh,MELD,and MELD-Na scores.METHODS This cross-sectional study was conducted at a tertiary care hospital with 652 decompensated liver disease patients enrolled in the study.Data was collected on demographics,clinical history,and laboratory findings,including hemoglobin levels,bilirubin,albumin,prothrombin time(international normalized ratio),sodium,and creatinine.The Child-Pugh,MELD,and MELD-Na scores were calculated.Statistical analysis was performed using Statistical Package for the Social Sciences version 26,and correlations between hemoglobin levels and severity scores were assessed using Spearman's correlation coefficient.RESULTS The study included 405 males(62.1%)and 247 females(37.9%)with an average age of 58.8 years.Significant inverse correlations were found between hemoglobin levels and Child-Pugh,MELD,and MELD-Na scores(P<0.01),with the MELD scoring system being the strongest correlator among all.One-way analysis of variance revealed significant differences in hemoglobin levels across the severity groups of each scoring system(P=0.001).Tukey's post hoc analysis confirmed significant internal differences among each severity group.CONCLUSION Understanding the correlation between hemoglobin and liver disease severity can improve patient management by offering insights into prognosis and guiding treatment decisions.展开更多
Background:Cardiac rupture (CR) is a major lethal complication of acute myocardial infarction (AMI).However,no valid risk score model was found to predict CR after AMI in previous researches.This study aimed to establ...Background:Cardiac rupture (CR) is a major lethal complication of acute myocardial infarction (AMI).However,no valid risk score model was found to predict CR after AMI in previous researches.This study aimed to establish a simple model to assess risk of CR after AMI,which could be easily used in a clinical environment.Methods:This was a retrospective case-control study that included 53 consecutive patients with CR after AMI during a period from January 1,2010 to December 31,2017.The controls included 524 patients who were selected randomly from 7932 AMI patients without CR at a 1:10 ratio.Risk factors for CR were identified using univariate analysis and multivariate logistic regression.Risk score model was developed based on multiple regression coefficients.Performance of risk model was evaluated using receiveroperating characteristic (ROC) curves and internal validity was explored using bootstrap analysis.Results:Among all 7985 AMI patients,53 (0.67%) had CR (free wall rupture,n=39;ventricular septal rupture,n=14).Hospital mortalities were 92.5% and 4.01% in patients with and without CR (P<0.001).Independent variables associated with CR included:older age,female gender,higher heart rate at admission,body mass index (BMI)<25 kg/m^2,lower left ventricular ejection fraction (LVEF) and no primary percutaneous coronary intervention (pPCI) treatment.In ROC analysis,our CR risk assess model demonstrated a very good discriminate power (area under the curve [AUC]= 0.895,95% confidence interval:0.845–0.944,optimism-corrected AUC= 0.821,P<0.001).Conclusion:This study developed a novel risk score model to help predict CR after AMI,which had high accuracy and was very simple to use.展开更多
BACKGROUND:Decreased cardiac contractility has been observed in cirrhosis,suggesting a latent cardiomyopathy in these patients.This study was designed to evaluate left ventricular structure and function in patients wi...BACKGROUND:Decreased cardiac contractility has been observed in cirrhosis,suggesting a latent cardiomyopathy in these patients.This study was designed to evaluate left ventricular structure and function in patients with end-stage liver disease by the model for end-stage liver disease(MELD) scoring system. METHODS:We recruited 82 patients(72 male,10 female; mean age 50.3±8.9 years)with end-stage liver disease who underwent orthotopic liver transplantation between January 2002 and May 2008.Seventy-eight patients had cirrhosis and 4 had primary liver cancer.Patients were categorized into three groups on the basis of MELD score:≤9(27 patients, 33%);10-19(40,49%);and≥20(15,18%).The relationship between MELD score and cardiac structure and function was determined.Preoperative assessments of blood biochemistry, blood coagulation,serum virology,echocardiography and electrocardiography were performed. RESULTS:MELD score was positively correlated with enlarged left atrial diameter,increased interventricular septum thickness(IVST),increased aortic flow,corrected QT interval (QTc)extension and cardiac output(P=0.033,0.002,0.000, 0.000 and 0.009,respectively).International normalized ratio also had a correlation with the above parameters and enlarged left ventricular end-diastolic diameter(P=0.043,0.010,0.000, 0.001,0.016 and 0.008,respectively).Serum creatinine was positively correlated with IVST(r=0.257,P=0.020),but negatively correlated with early maximal ventricular filling velocity/late diastolic or atrial velocity ratio(r=-0.300, P=0.006).A difference of QTc>440 ms among the three groups was statistically significant(χ2=9.791,P=0.007).CONCLUSIONS:Abnormalities in cardiac structure and function are common in patients with end-stage liver disease. MELD score is a practically useful approach for the assessment of cardiac function in such patients.展开更多
AIM: To assess the impact of model for end-stage liver disease(MELD) score on patient survival and morbidity post living donor liver transplantation(LDLT). METHODS: A retrospective study was performed on 80 adult pati...AIM: To assess the impact of model for end-stage liver disease(MELD) score on patient survival and morbidity post living donor liver transplantation(LDLT). METHODS: A retrospective study was performed on 80 adult patients who had LDLT from 2011-2013. Nine patients were excluded and 71 patients were divided into two groups; Group 1 included 38 patients with a MELD score < 20, and Group 2 included 33 patients with a MELD score > 20. Comparison between both groups was done regarding operative time, intra-operative blood requirement, intensive care unit(ICU) and hospital stay, infection, and patient survival.RESULTS: Eleven patients died(15.5%); 3/38(7.9%)patients in Group 1 and 8/33(24.2%) in Group 2 with significant difference(P = 0.02). Mean operative time, duration of hospital stay, and ICU stay were similar in both groups. Mean volume of blood transfusion and cell saver re-transfusion were 8 ± 4 units and 1668 ± 202 m L, respectively, in Group 1 in comparison to 10 ± 6 units and 1910 ± 679 m L, respectively, in Group 2 with no significant difference(P = 0.09 and 0.167, respectively). The rates of infection and systemic complications(renal, respiratory, cardiovascular and neurological complications) were similar in both groups. CONCLUSION: A MELD score > 20 may predict mortality after LDLT.展开更多
BACKGROUND Hepatic encephalopathy(HE)remains an enormous challenge in patients who undergo transjugular intrahepatic portosystemic shunt(TIPS)implantation.The preoperative indocyanine green retention rate at 15 min(IC...BACKGROUND Hepatic encephalopathy(HE)remains an enormous challenge in patients who undergo transjugular intrahepatic portosystemic shunt(TIPS)implantation.The preoperative indocyanine green retention rate at 15 min(ICG-R15),as one of the liver function assessment tools,has been developed as a prognostic indicator in patients undergoing surgery,but there are limited data on its role in TIPS.AIM To determine whether the ICG-R15 can be used for prediction of post-TIPS HE in decompensated cirrhosis patients with portal hypertension(PHT)and compare the clinical value of ICG-R15,Child-Pugh score(CPS),and model for end-stage liver disease(MELD)score in predicting post-TIPS HE with PHT.METHODS This retrospective study included 195 patients with PHT who underwent elective TIPS at Beijing Shijitan Hospital from January 2018 to June 2019.All patients underwent the ICG-R15 test,CPS evaluation,and MELD scoring 1 wk before TIPS.According to whether they developed HE or not,the patients were divided into two groups:HE group and non-HE group.The prediction of one-year post-TIPS HE by ICG-R15,CPS and MELD score was evaluated by the areas under the receiver operating characteristic curves(AUCs).RESULTS A total of 195 patients with portal hypertension were included and 23%(45/195)of the patients developed post-TIPS HE.The ICG-R15 was identified as an independent predictor of post-TIPS HE.The AUCs for the ICG-R15,CPS,and MELD score for predicting post-TIPS HE were 0.664(95%confidence interval[CI]:0.557-0.743,P=0.0046),0.596(95%CI:0.508-0.679,P=0.087),and 0.641(95%CI:0.554-0.721,P=0.021),respectively.The non-parametric approach(Delong-Delong&Clarke-Pearson)showed that there was statistical significance in pairwise comparison between AUCs of ICG-R15 and MELD score(P=0.0229).CONCLUSION The ICG-R15 has appreciated clinical value for predicting the occurrence of post-TIPS HE and is a choice for evaluating the prognosis of patients undergoing TIPS.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is a common cancer with a poor prognosis.Previous studies revealed that the tumor microenvironment(TME)plays an important role in HCC progression,recurrence,and metastasis,leadi...BACKGROUND Hepatocellular carcinoma(HCC)is a common cancer with a poor prognosis.Previous studies revealed that the tumor microenvironment(TME)plays an important role in HCC progression,recurrence,and metastasis,leading to poor prognosis.However,the effects of genes involved in TME on the prognosis of HCC patients remain unclear.Here,we investigated the HCC microenvironment to identify prognostic genes for HCC.AIM To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC.METHODS We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm.Additionally,a risk score model was established based on Differentially Expressed Genes(DEGs)between high and lowimmune/stromal score patients.RESULTS The risk score model consisting of eight genes was constructed and validated in the HCC patients.The patients were divided into high-or low-risk groups.The genes(Disabled homolog 2,Musculin,C-X-C motif chemokine ligand 8,Galectin 3,B-cell-activating transcription factor,Killer cell lectin like receptor B1,Endoglin and adenomatosis polyposis coli tumor suppressor)involved in our risk score model were considered to be potential immunotherapy targets,and they may provide better performance in combination.Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway,respectively,related to the immune-related genes in the DEGs between high-and low-risk groups.The receiver operating characteristic(ROC)curve analysis confirmed the good potency of the risk score prognostic model.Moreover,we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database.A nomogram was established to predict the overall survival of HCC patients.CONCLUSION The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.展开更多
基金supported by Hi-Tech Research and Development Program of China (863 Program) (No.2006AA02Z4B4)
文摘Objective： In our previous work, we incorporated complete blood count （CBC） into TNM stage to develop a new prognostic score model, which was validated to improve prediction efficiency of TNM stage for nasopharyngeal carcinoma （NPC）. The purpose of this study was to revalidate the accuracy of the model, and its superiority to TNM stage, through data from a prospective study.Methods： CBC of 249 eligible patients from the 863 Program No. 2006AA02Z4B4 was evaluated. Prognostic index （PI） of each patient was calculated according to the score model. Then they were divided by the PI into three categories： the low-, intermediate-and high-risk patients. The 5-year disease-specific survival （DSS） of the three categories was compared by a log-rank test. The model and TNM stage （Tth edition） were compared on efficiency for predicting the 5-year DSS, through comparison of the area under curve （AUC） of their receiver-operating characteristic curves.Results： The 5-year DSS of the low-, intermediate- and high-risk patients were 96.0%, 79.1% and 62.2%, respectively. The low- and intermediate-risk patients had better DSS than the high-risk patients （P〈0.001 and P〈0.005, respectively）. And there was a trend of better DSS in the low-risk patients, compared with the intermediate-risk patients （P=0.049）. The AUC of the model was larger than that of TNM stage （0.726 vs. 0.661, P：0.023）. Conclusions： A CBC-based prognostic score model was revalidated to be accurate and superior to TNM stage on predicting 5-year DSS of NPC.
文摘Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. Methods From the hos- pital electronic medical database, we idemified 3550 patients who received PCI （78.0% males, mean age 60 years） in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic 01OC） analysis were performed. Results The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation （all P 〈 0.001）. The rate of VVRS [95% confidence interval （CI）] in patients receiving PCI was 4.5% （4.1%-5.6%）. Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stems im- plantation in the left anterior descending （LAD）, and the femoral puncture site. The multivariate analysis suggested that they were independ- ent risk factors for predicting the incidence of VVRS （all P 〈 0.001）. We developed a risk prediction score model for VVRS. ROC analysis showed that the risk prediction score model was effectively predictive of the incidence of VVRS in patients receiving PCI （c-statistic 0.76, 95% CI： 0.72-0.79, P 〈 0.001）. There were decreased evems of VVRS in the patients receiving PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute （AUC： 0.84, 95% CI： 0.81-0.87, P 〈 0.001）. Conclusion The risk prediction score is quite efficient in predicting the incidence of VVRS in patients receiving PCI. In which, the following factors may be in- volved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.
文摘BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for clinical stage II/III rectal cancer.However,few patients achieve a complete pathological response,and most patients require surgical resection and adjuvant therapy.Therefore,identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival(OS)and disease-free survival(DFS)for LARC treated with NT.METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017.The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors,which were validated by the Cox regression method.Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves,and that of the two nomograms was conducted by calculating the concordance index(C-index)and calibration curves.The results were validated in a cohort of 65 patients from 2015 to 2017.RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model:Vascular_tumors_bolt,cancer nodules,yN,body mass index,matchmouth distance from the edge,nerve aggression and postoperative carcinoembryonic antigen.The nomogram showed good predictive value for OS,with a C-index of 0.91(95%CI:0.85,0.97)and good calibration.In the validation cohort,the C-index was 0.69(95%CI:0.53,0.84).The risk factor prediction model showed good predictive value.The areas under the curve for 3-and 5-year survival were 0.811 and 0.782.The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77(95%CI:0.69,0.85).In the validation cohort,the C-index was 0.71(95%CI:0.61,0.81).The prediction model for DFS also had good predictive value,with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.
基金Supported by Grants from National Natural Science Foundation of China,No.81273743,No.81473641and 215 Program,No.2013-2-11
文摘AIM: To establish a clinical scoring model to predict risk of acute-on-chronic liver failure(ACLF) in chronic hepatitis B(CHB) patients.METHODS: This was a retrospective study of 1457 patients hospitalized for CHB between October 2008 and October 2013 at the Beijing Ditan Hospital, Capital Medical University, China. The patients were divided into two groups: severe acute exacerbation(SAE) group(n = 382) and non-SAE group(n = 1075). The SAE group was classified as the high-risk group based on the higher incidence of ACLF in this group than in the non-SAE group(13.6% vs 0.4%). Two-thirds of SAE patients were randomly assigned to risk-model derivation and the other one-third to model validation. Univariate risk factors associated with the outcome were entered into a multivariate logistic regression model for screening independent risk factors. Each variable was assigned an integer value based on the regression coefficients, and the final score was the sum of these values in the derivation set. Model discrimination and calibration were assessed using area under the receiver operating characteristic curve and the Hosmer-Lemeshow test. RESULTS: The risk prediction scoring model includedthe following four factors: age ≥ 40 years, total bilirubin ≥ 171 μmol/L, prothrombin activity 40%-60%, and hepatitis B virus DNA > 107 copies/m L. The sum risk score ranged from 0 to 7; 0-3 identified patients with lower risk of ACLF, whereas 4-7 identified patients with higher risk. The Kaplan-Meier analysis showed the cumulative risk for ACLF and ACLF-related death in the two risk groups(0-3 and 4-7 scores) of the primary cohort over 56 d, and log-rank test revealed a significant difference(2.0% vs 33.8% and 0.8% vs 9.4%, respectively; both P < 0.0001). In the derivation and validation data sets, the model had good discrimination(C index = 0.857, 95% confidence interval: 0.800-0.913 and C index = 0.889, 95% confidence interval: 0.820-0.957, respectively) and calibration demonstrated by the Hosmer-Lemeshow test(χ2 = 4.516, P = 0.808 and χ2 = 1.959, P = 0.923, respectively).CONCLUSION: Using the scoring model, clinicians can easily identify patients(total score ≥ 4) at high risk of ACLF and ACLF-related death early during SAE.
基金国家自然科学基金项目(No.81902513)山西省应用基础研究计划项目(No.202303021211114 and 202103021224228)山西省高等教育百亿工程“科技引导”专项(No.BYJL047)资助。
文摘Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8^(+)T cell immune infiltration and immune suppression.We constructed a CD8^(+)T cells related risk score model to predict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8^(+)T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS 2,and TNFRSF1B was constructed.The risk score model was well validated through an independent external validation cohort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P<0.0001)and lower CD8^(+)T cells infiltration(P<0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P<0.01).Drug sensitivity analysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene model was verified by immunohistochemistry.In summary,the establishment and validation of a CD8^(+)T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.
基金supported by the“Regional Innovation System&Education(RISE)”through the Seoul RISE Center,funded by the Ministry of Education(MOE)and the Seoul Metropolitan Government(2025-RISE-01-018-05)supported by Quad Miners Corp。
文摘The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.
基金Supported by The Guangdong Medical Research Foundation of China,No.A2020603.
文摘BACKGROUND Designing a feasible risk prediction model for advanced colorectal neoplasia(ACN)can enhance colonoscopy screening efficiency.Abdominal obesity is associated with colorectal cancer development.AIM To propose and evaluate a modified scoring model incorporating waist-hip ratio for the prediction of ACN.METHODS A total of 6483 patients who underwent their first screening or diagnostic colonoscopy in our center between 2020 and 2023 were recruited,in which 4592 were in the derivation cohort and 1891 formed a validation cohort.Multivariate logistic regression was used to investigate the risk factors of ACN in the derivation cohort based on endoscopic findings,and a new scoring model for ACN prediction was developed.The discriminatory capability of the scoring model was validated by the validation cohort.RESULTS Age,male gender,smoking,and wait-to-hip ratio were identified as independent risk factors for ACN,and a 7-point scoring model was developed.The prevalence of ACN was 3.3%,9.3%and 18.5%in participants with scores of 0-2[low risk(LR)],3–4[moderate risk(MR)],and 5–7[high risk(HR)],respectively,in the derivation cohort.With the scoring model,49.9%,38.4%,and 11.7%of patients in the validation cohort were categorized as LR,MR,and HR,respectively.The corresponding prevalence rates of ACN were 5.0%,10.3%,and 17.6%,respectively.The C-statistic of the new scoring model was 0.66,which was higher than that of the Asia-Pacific Colorectal Screening model(0.63).CONCLUSION A modified scoring model incorporating waist-hip ratio has an improved predictive performance in the prediction of ACN.
文摘This editorial discusses an article by Liu et al,which focuses on the development and evaluation of a modified scoring model incorporating the waist-to-hip ratio for predicting advanced colorectal neoplasia(ACN).This editorial provides an overview of the study,including the background of ACN risk prediction,the study design,key findings,and the significance and limitations of the new model.The study identified independent risk factors for ACN and developed a 7-point scoring model with better predictive performance than existing models.However,challenges,such as generalizability across ethnic groups and selection bias,exist.Further research involving multi-ethnic cohorts and the integration of novel biomarkers is needed to improve the model and its clinical application.
文摘With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.
文摘BACKGROUND Chronic liver disease is a growing global health problem,leading to hepatic decompensation characterized by an array of clinical and biochemical complic-ations.Several scoring systems have been introduced in assessing the severity of hepatic decompensation with the most frequent ones are Child-Pugh score,model of end-stage liver disease(MELD)score,and MELD-Na score.Anemia is frequently observed in cirrhotic patients and is linked to worsened clinical outcomes.Although studies have explored anemia in liver disease,few have investigated the correlation of hemoglobin level with the severity of hepatic decompensation.AIM To determine the relationship between hemoglobin levels and the severity of decompensated liver disease and comparing the strength of this correlation using the Child-Pugh,MELD,and MELD-Na scores.METHODS This cross-sectional study was conducted at a tertiary care hospital with 652 decompensated liver disease patients enrolled in the study.Data was collected on demographics,clinical history,and laboratory findings,including hemoglobin levels,bilirubin,albumin,prothrombin time(international normalized ratio),sodium,and creatinine.The Child-Pugh,MELD,and MELD-Na scores were calculated.Statistical analysis was performed using Statistical Package for the Social Sciences version 26,and correlations between hemoglobin levels and severity scores were assessed using Spearman's correlation coefficient.RESULTS The study included 405 males(62.1%)and 247 females(37.9%)with an average age of 58.8 years.Significant inverse correlations were found between hemoglobin levels and Child-Pugh,MELD,and MELD-Na scores(P<0.01),with the MELD scoring system being the strongest correlator among all.One-way analysis of variance revealed significant differences in hemoglobin levels across the severity groups of each scoring system(P=0.001).Tukey's post hoc analysis confirmed significant internal differences among each severity group.CONCLUSION Understanding the correlation between hemoglobin and liver disease severity can improve patient management by offering insights into prognosis and guiding treatment decisions.
文摘Background:Cardiac rupture (CR) is a major lethal complication of acute myocardial infarction (AMI).However,no valid risk score model was found to predict CR after AMI in previous researches.This study aimed to establish a simple model to assess risk of CR after AMI,which could be easily used in a clinical environment.Methods:This was a retrospective case-control study that included 53 consecutive patients with CR after AMI during a period from January 1,2010 to December 31,2017.The controls included 524 patients who were selected randomly from 7932 AMI patients without CR at a 1:10 ratio.Risk factors for CR were identified using univariate analysis and multivariate logistic regression.Risk score model was developed based on multiple regression coefficients.Performance of risk model was evaluated using receiveroperating characteristic (ROC) curves and internal validity was explored using bootstrap analysis.Results:Among all 7985 AMI patients,53 (0.67%) had CR (free wall rupture,n=39;ventricular septal rupture,n=14).Hospital mortalities were 92.5% and 4.01% in patients with and without CR (P<0.001).Independent variables associated with CR included:older age,female gender,higher heart rate at admission,body mass index (BMI)<25 kg/m^2,lower left ventricular ejection fraction (LVEF) and no primary percutaneous coronary intervention (pPCI) treatment.In ROC analysis,our CR risk assess model demonstrated a very good discriminate power (area under the curve [AUC]= 0.895,95% confidence interval:0.845–0.944,optimism-corrected AUC= 0.821,P<0.001).Conclusion:This study developed a novel risk score model to help predict CR after AMI,which had high accuracy and was very simple to use.
基金supported by a grant from the Science and Technology Bureau of Liaoning Province,China(2007225011-1)
文摘BACKGROUND:Decreased cardiac contractility has been observed in cirrhosis,suggesting a latent cardiomyopathy in these patients.This study was designed to evaluate left ventricular structure and function in patients with end-stage liver disease by the model for end-stage liver disease(MELD) scoring system. METHODS:We recruited 82 patients(72 male,10 female; mean age 50.3±8.9 years)with end-stage liver disease who underwent orthotopic liver transplantation between January 2002 and May 2008.Seventy-eight patients had cirrhosis and 4 had primary liver cancer.Patients were categorized into three groups on the basis of MELD score:≤9(27 patients, 33%);10-19(40,49%);and≥20(15,18%).The relationship between MELD score and cardiac structure and function was determined.Preoperative assessments of blood biochemistry, blood coagulation,serum virology,echocardiography and electrocardiography were performed. RESULTS:MELD score was positively correlated with enlarged left atrial diameter,increased interventricular septum thickness(IVST),increased aortic flow,corrected QT interval (QTc)extension and cardiac output(P=0.033,0.002,0.000, 0.000 and 0.009,respectively).International normalized ratio also had a correlation with the above parameters and enlarged left ventricular end-diastolic diameter(P=0.043,0.010,0.000, 0.001,0.016 and 0.008,respectively).Serum creatinine was positively correlated with IVST(r=0.257,P=0.020),but negatively correlated with early maximal ventricular filling velocity/late diastolic or atrial velocity ratio(r=-0.300, P=0.006).A difference of QTc>440 ms among the three groups was statistically significant(χ2=9.791,P=0.007).CONCLUSIONS:Abnormalities in cardiac structure and function are common in patients with end-stage liver disease. MELD score is a practically useful approach for the assessment of cardiac function in such patients.
文摘AIM: To assess the impact of model for end-stage liver disease(MELD) score on patient survival and morbidity post living donor liver transplantation(LDLT). METHODS: A retrospective study was performed on 80 adult patients who had LDLT from 2011-2013. Nine patients were excluded and 71 patients were divided into two groups; Group 1 included 38 patients with a MELD score < 20, and Group 2 included 33 patients with a MELD score > 20. Comparison between both groups was done regarding operative time, intra-operative blood requirement, intensive care unit(ICU) and hospital stay, infection, and patient survival.RESULTS: Eleven patients died(15.5%); 3/38(7.9%)patients in Group 1 and 8/33(24.2%) in Group 2 with significant difference(P = 0.02). Mean operative time, duration of hospital stay, and ICU stay were similar in both groups. Mean volume of blood transfusion and cell saver re-transfusion were 8 ± 4 units and 1668 ± 202 m L, respectively, in Group 1 in comparison to 10 ± 6 units and 1910 ± 679 m L, respectively, in Group 2 with no significant difference(P = 0.09 and 0.167, respectively). The rates of infection and systemic complications(renal, respiratory, cardiovascular and neurological complications) were similar in both groups. CONCLUSION: A MELD score > 20 may predict mortality after LDLT.
基金Beijing Municipal Science and Technology Commision,No.Z181100001718097.
文摘BACKGROUND Hepatic encephalopathy(HE)remains an enormous challenge in patients who undergo transjugular intrahepatic portosystemic shunt(TIPS)implantation.The preoperative indocyanine green retention rate at 15 min(ICG-R15),as one of the liver function assessment tools,has been developed as a prognostic indicator in patients undergoing surgery,but there are limited data on its role in TIPS.AIM To determine whether the ICG-R15 can be used for prediction of post-TIPS HE in decompensated cirrhosis patients with portal hypertension(PHT)and compare the clinical value of ICG-R15,Child-Pugh score(CPS),and model for end-stage liver disease(MELD)score in predicting post-TIPS HE with PHT.METHODS This retrospective study included 195 patients with PHT who underwent elective TIPS at Beijing Shijitan Hospital from January 2018 to June 2019.All patients underwent the ICG-R15 test,CPS evaluation,and MELD scoring 1 wk before TIPS.According to whether they developed HE or not,the patients were divided into two groups:HE group and non-HE group.The prediction of one-year post-TIPS HE by ICG-R15,CPS and MELD score was evaluated by the areas under the receiver operating characteristic curves(AUCs).RESULTS A total of 195 patients with portal hypertension were included and 23%(45/195)of the patients developed post-TIPS HE.The ICG-R15 was identified as an independent predictor of post-TIPS HE.The AUCs for the ICG-R15,CPS,and MELD score for predicting post-TIPS HE were 0.664(95%confidence interval[CI]:0.557-0.743,P=0.0046),0.596(95%CI:0.508-0.679,P=0.087),and 0.641(95%CI:0.554-0.721,P=0.021),respectively.The non-parametric approach(Delong-Delong&Clarke-Pearson)showed that there was statistical significance in pairwise comparison between AUCs of ICG-R15 and MELD score(P=0.0229).CONCLUSION The ICG-R15 has appreciated clinical value for predicting the occurrence of post-TIPS HE and is a choice for evaluating the prognosis of patients undergoing TIPS.
基金Supported by National Natural Science Foundation of China,No.81972255,No.81772597 and No.81672412Guangdong Natural Science Foundation,No.2017A030311002+4 种基金Guangdong Science and Technology Foundation,No.2017A020215196Fundamental Research Funds for the Central Universities of Sun YatSen University,No.17ykpy44Science Foundation of Jiangxi,No.20181BAB214002Education Department Science and Technology Foundation of Jiangxi,No.GJJ170936Grant from Guangdong Science and Technology Department,No.2017B030314026
文摘BACKGROUND Hepatocellular carcinoma(HCC)is a common cancer with a poor prognosis.Previous studies revealed that the tumor microenvironment(TME)plays an important role in HCC progression,recurrence,and metastasis,leading to poor prognosis.However,the effects of genes involved in TME on the prognosis of HCC patients remain unclear.Here,we investigated the HCC microenvironment to identify prognostic genes for HCC.AIM To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC.METHODS We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm.Additionally,a risk score model was established based on Differentially Expressed Genes(DEGs)between high and lowimmune/stromal score patients.RESULTS The risk score model consisting of eight genes was constructed and validated in the HCC patients.The patients were divided into high-or low-risk groups.The genes(Disabled homolog 2,Musculin,C-X-C motif chemokine ligand 8,Galectin 3,B-cell-activating transcription factor,Killer cell lectin like receptor B1,Endoglin and adenomatosis polyposis coli tumor suppressor)involved in our risk score model were considered to be potential immunotherapy targets,and they may provide better performance in combination.Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway,respectively,related to the immune-related genes in the DEGs between high-and low-risk groups.The receiver operating characteristic(ROC)curve analysis confirmed the good potency of the risk score prognostic model.Moreover,we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database.A nomogram was established to predict the overall survival of HCC patients.CONCLUSION The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.
