Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in medicine.About 17.9 million people die from CVDs annually,ac...Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in medicine.About 17.9 million people die from CVDs annually,accounting for 31%of all deaths worldwide.With a timely prognosis and thorough consideration of the patient’s medical history and lifestyle,it is possible to predict CVDs and take preventive measures to eliminate or control this life-threatening disease.In this study,we used various patient datasets from a major hospital in the United States as prognostic factors for CVD.The data was obtained by monitoring a total of 918 patients whose criteria for adults were 28-77 years old.In this study,we present a data mining modeling approach to analyze the performance,classification accuracy and number of clusters on Cardiovascular Disease Prognostic datasets in unsupervised machine learning(ML)using the Orange data mining software.Various techniques are then used to classify the model parameters,such as k-nearest neighbors,support vector machine,random forest,artificial neural network(ANN),naïve bayes,logistic regression,stochastic gradient descent(SGD),and AdaBoost.To determine the number of clusters,various unsupervised ML clustering methods were used,such as k-means,hierarchical,and density-based spatial clustering of applications with noise clustering.The results showed that the best model performance analysis and classification accuracy were SGD and ANN,both of which had a high score of 0.900 on Cardiovascular Disease Prognostic datasets.Based on the results of most clustering methods,such as k-means and hierarchical clustering,Cardiovascular Disease Prognostic datasets can be divided into two clusters.The prognostic accuracy of CVD depends on the accuracy of the proposed model in determining the diagnostic model.The more accurate the model,the better it can predict which patients are at risk for CVD.展开更多
BACKGROUND Hepatocellular carcinoma(HCC),the sixth most common cancer and fourthleading cause of cancer-related mortality globally,imposes a significant burden in Vietnam due to endemic hepatitis B virus(HBV)and hepat...BACKGROUND Hepatocellular carcinoma(HCC),the sixth most common cancer and fourthleading cause of cancer-related mortality globally,imposes a significant burden in Vietnam due to endemic hepatitis B virus(HBV)and hepatitis C virus(HCV)infections.Accurate prognostication is crucial for optimizing treatment and outcomes.Numerous staging systems exist,including the Barcelona Clinic Liver Cancer(BCLC),Hong Kong Liver Cancer(HKLC),cancer of the liver Italian Program(CLIP),Italian Liver Cancer(ITA.LI.CA),Japan Integrated Staging(JIS),Tokyo Score,and model to estimate survival in ambulatory HCC patients(MESIAH).However,their comparative performance in Vietnamese patients remains underexplored.AIM To compare the prognostic accuracy of seven HCC staging systems in predicting survival and identify the optimal model.METHODS This retrospective cohort study included 987 patients with HCC diagnosed at Nhan dan Gia Dinh Hospital,Vietnam,from January 2016 to December 2023.Patients were staged using BCLC,HKLC,CLIP,ITA.LI.CA,JIS,Tokyo score,and MESIAH.Overall survival was analyzed using Kaplan-Meier methods,and prognostic performance was evaluated via the area under the receiver operating characteristic(ROC)curve,Harrell’s concordance index,and calibration plots.RESULTS The HKLC and BCLC systems demonstrated the highest discriminatory ability,with area under the ROC curves of 0.834 and 0.830,respectively,at 12 months and 0.859 for both systems at 36 months.CLIP and ITA.LI.CA exhibited superior calibration,particularly at 36 months.The JIS system consistently showed the poorest discriminatory performance.Subgroup analyses revealed that HKLC maintained strong performance across different viral etiologies(HBV,HCV,non-B-non-C)and treatment modalities(transarterial chemoembolization,surgery,ablation).CONCLUSION The HKLC and BCLC systems showed superior prognostic performance for Vietnamese patients with HCC,supporting HKLC adoption in clinical practice.展开更多
BACKGROUND Clinical predictors of dengue fever are crucial for guiding timely management and avoiding life-threatening complications.While prognostic scores are available,a systematic evaluation of these tools is lack...BACKGROUND Clinical predictors of dengue fever are crucial for guiding timely management and avoiding life-threatening complications.While prognostic scores are available,a systematic evaluation of these tools is lacking.AIM To evaluate the performance and accuracy of various proposed dengue clinical prognostic scores.METHODS Three databases,PubMed,EMBASE and Cochrane,were searched for peer-reviewed studies published from inception to 4 September 2023.Studies either developing or validating a prognostic model relevant to dengue fever were included.A total of 29 studies(n=17910)were included.RESULTS Most commonly studied outcomes were severe dengue(15 models)and mortality(8 models).For the paediatric population,Bedside Dengue Severity Score by Gayathri et al(specificity=0.98)and the nomogram model by Nguyen et al(sensitivity=0.87)performed better.For the adult population,the most specific model was reported by Leo et al(specificity=0.98).The most sensitive score is shared between Warning Signs for Severe Dengue as reported by Leo et al and Model 2 by Lee et al(sensitivity=1.00).CONCLUSION While several models demonstrated precision and reliability in predicting severe dengue and mortality,broader application across diverse geographic settings is needed to assess their external validity.展开更多
In this article,we discuss the recently published article by Yang et al.This retrospective analysis,which was conducted at a large urban tertiary care center,focused on comparing Lille model scores at days 3 and 7 wit...In this article,we discuss the recently published article by Yang et al.This retrospective analysis,which was conducted at a large urban tertiary care center,focused on comparing Lille model scores at days 3 and 7 with established scoring systems and identifying critical clinical predictors,such as renal dysfunction,nutritional status,and underlying cirrhosis.Alcoholic hepatitis(AH),a severe manifestation of alcohol-related liver disease,is associated with high morbidity and mortality,necessitating accurate prognostic tools and comprehensive clinical assessments.Prognostic tools are invaluable for early risk stratification,but they must be contextualized within the multifactorial nature of AH.Acute renal dysfunction and poor nutritional status,for example,are not just complications but pivotal markers of disease severity and systemic impact.Addressing these factors requires a holistic approach that extends beyond scoring systems to include targeted interventions and comprehensive patient care.This editorial emphasizes the need for a paradigm shift in AH management,where prognostic models are complemented by a deeper understanding of patient-specific factors.Such an approach can guide clinicians in tailoring therapies and improving outcomes for this high-risk population.展开更多
BACKGROUND Partial hepatectomy continues to be the primary treatment approach for liver tumors,and post-hepatectomy liver failure(PHLF)remains the most critical lifethreatening complication following surgery.AIM To co...BACKGROUND Partial hepatectomy continues to be the primary treatment approach for liver tumors,and post-hepatectomy liver failure(PHLF)remains the most critical lifethreatening complication following surgery.AIM To comprehensively review the PHLF prognostic models developed in recent years and objectively assess the risk of bias in these models.METHODS This review followed the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline.Three databases were searched from November 2019 to December 2022,and references as well as cited literature in all included studies were manually screened in March 2023.Based on the defined inclusion criteria,articles on PHLF prognostic models were selected,and data from all included articles were extracted by two independent reviewers.The PROBAST was used to evaluate the quality of each included article.RESULTS A total of thirty-four studies met the eligibility criteria and were included in the analysis.Nearly all of the models(32/34,94.1%)were developed and validated exclusively using private data sources.Predictive variables were categorized into five distinct types,with the majority of studies(32/34,94.1%)utilizing multiple types of data.The area under the curve for the training models included ranged from 0.697 to 0.956.Analytical issues resulted in a high risk of bias across all studies included.CONCLUSION The validation performance of the existing models was substantially lower compared to the development models.All included studies were evaluated as having a high risk of bias,primarily due to issues within the analytical domain.The progression of modeling technology,particularly in artificial intelligence modeling,necessitates the use of suitable quality assessment tools.展开更多
BACKGROUND Gastric cancer(GC)is the fifth most common cancer and the third leading cause of cancer-related deaths in China.Many patients with GC frequently experience symptoms related to the disease,including anorexia...BACKGROUND Gastric cancer(GC)is the fifth most common cancer and the third leading cause of cancer-related deaths in China.Many patients with GC frequently experience symptoms related to the disease,including anorexia,nausea,vomiting,and other discomforts,and often suffer from malnutrition,which in turn negatively affects perioperative safety,prognosis,and the effectiveness of adjuvant therapeutic measures.Consequently,some nutritional indicators such as nutritional risk index(NRI),prognostic nutritional index(PNI),and systemic immune-inflammatorynutritional index(SIINI)can be used as predictors of the prognosis of GC patients.AIM To examine the prognostic significance of PNI,NRI,and SIINI in postoperative patients with GC.METHODS A retrospective analysis was conducted on the clinical data of patients with GC who underwent surgical treatment at the Guangxi Medical University Cancer Hospital between January 2010 and December 2018.The area under the receiver operating characteristic(ROC)curve was assessed using ROC curve analysis,and the optimal cutoff values for NRI,PNI,and SIINI were identified using the You-Review-HTMLden index.Survival analysis was performed using the Kaplan-Meier method.In addition,univariate and multivariate analyses were conducted using the Cox proportional hazards regression model.RESULTS This study included a total of 803 patients.ROC curves were used to evaluate the prognostic ability of NRI,PNI,and SIINI.The results revealed that SIINI had superior predictive accuracy.Survival analysis indicated that patients with GC in the low SIINI group had a significantly better survival rate than those in the high SIINI group(P<0.05).Univariate analysis identified NRI[hazard ratio(HR)=0.68,95%confidence interval(CI):0.52-0.89,P=0.05],PNI(HR=0.60,95%CI:0.46-0.79,P<0.001),and SIINI(HR=2.10,95%CI:1.64-2.69,P<0.001)as prognostic risk factors for patients with GC.However,multifactorial analysis indicated that SIINI was an independent risk factor for the prognosis of patients with GC(HR=1.65,95%CI:1.26-2.16,P<0.001).CONCLUSION Analysis of clinical retrospective data revealed that SIINI is a valuable indicator for predicting the prognosis of patients with GC.Compared with NRI and PNI,SIINI may offer greater application for prognostic assessment.展开更多
Background:Lung cancer is the leading cause of cancer-related mortality,and while low-dose computed tomography screening may reduce mortality,emerging prognostic models show superior discriminative efficacy compared t...Background:Lung cancer is the leading cause of cancer-related mortality,and while low-dose computed tomography screening may reduce mortality,emerging prognostic models show superior discriminative efficacy compared to age-and smoking history-based screening.However,further research is needed to assess their reliability in predicting lung cancer risk in high-risk patients.Methods:This study evaluated the predictive performance and quality of existing lung cancer prognostic models through a systematic review and meta-analysis.A comprehensive search was conducted in PubMed,Cochrane,Web of Science,CNKI,and Wanfang for articles published between January 1,2000,and February 13,2025,identifying population-basedmodels incorporating all available modeling data.Results:Among 72 analyzed studies,models were developed from Asian(28 studies,including 23 Chinese cohorts)and European/American(48 studies)populations,with only 6 focusing on nonsmokers.Twenty-one models included genetic markers,15 used clinical factors,and 40 integrated epidemiological predictors.Although 37 models underwent external validation,only 4 demonstrated minimal bias and clinical applicability.A meta-analysis of 11 repeatedly validated models revealed calibration and discrimination,though some lacked calibration data.Conclusions:Few lung cancer prognostic models exist for nonsmokers.Most models exhibit poor predictive performance in external validations,with significant bias and limited application scope.Widespread external validation,standardized model development,and reporting techniques are needed to accurately identify high-risk individuals and ensure applicability across diverse populations.展开更多
Objective The systemic immune-inflammation index(SII)has recently attracted significant interest as a new biomarker for predicting the prognosis of patients with glioblastoma(GBM).However,the predictive significance o...Objective The systemic immune-inflammation index(SII)has recently attracted significant interest as a new biomarker for predicting the prognosis of patients with glioblastoma(GBM).However,the predictive significance of it is still a subject of debate.This study intended to assess the clinical effectiveness of the SII in GBM and establish a nomogram.Methods Receiver operating characteristic(ROC)curves were utilized to determine the optimal cut-off values of the SII.Kaplan–Meier(KM)survival curves were used to analyze the median overall survival(OS).Cox regression analysis was carried out to evaluate the associations between OS and different clinical factors.Based on the SII and clinical characteristics,a nomogram was constructed,and its value in clinical application was evaluated by means of decision curve analysis.Results The optimal SII cut-off value was 610.13.KM analysis revealed that GBM patients with higher SII values had shorter OS(15.0 vs.34.0 months,P=0.044).Multivariate analysis demonstrated that a high SII was an independent predictor of poor outcome in GBM(HR=1.79,P=0.029).The nomogram incorporating the preoperative SII showed good predictive accuracy for GBM patient prognosis(C-index=0.691).Conclusions The SII is an independent predictive indicator for GBM.Patients with elevated SII levels tend to have a poorer prognosis.A nomogram combining the SII with clinical and molecular pathological features can assist clinicians in assessing the risk of death in GBM patients,providing a basis for individualized treatment decisions.展开更多
BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive ...BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive lymph node ratio(LNR)and log odds of positive lymph nodes(LODDS)were introduced.AIM To assess the prognostic accuracy and stratification efficacy of three nodal staging systems in GC.METHODS A systematic review identified 12 studies,from which hazard ratios(HRs)for overall survival(OS)were summarized.Sensitivity analyses,subgroup analyses,publication bias assessments,and quality evaluations were conducted.To enhance comparability,data from studies with identical cutoff values for pN,LNR,and LODDS were pooled.Homogeneous stratification was then applied to generate Kaplan-Meier(KM)survival curves,assessing the stratification efficacy of three staging systems.RESULTS The HRs and 95%confidence intervals for pN,LNR,and LODDS were 2.16(1.72-2.73),2.05(1.65-2.55),and 3.15(2.15-4.37),respectively,confirming all three as independent prognostic risk factors for OS.Comparative analysis of HRs demonstrated that LODDS had superior prognostic predictive power over LNR and pN.KM curves for pN(N0,N1,N2,N3a,N3b),LNR(0.1/0.2/0.5),and LODDS(-1.5/-1.0/-0.5/0)revealed significant differences(P<0.001)among all prognostic stratifications.Mean differences and standard deviations in 60-month relative survival were 27.93%±0.29%,41.70%±0.30%,and 26.60%±0.28%for pN,LNR,and LODDS,respectively.CONCLUSION All three staging systems are independent prognostic factors for OS.LODDS demonstrated the highest specificity,making it especially useful for predicting outcomes,while pN was the most effective in homogeneous stratification,offering better patient differentiation.These findings highlight the complementary roles of LODDS and pN in enhancing prognostic accuracy and stratification.展开更多
This commentary critically appraises the study by Li et al which pioneered the exploration of the triglyceride-glucose(TyG)index as a prognostic marker in hepatitis B virus-related advanced hepatocellular carcinoma pa...This commentary critically appraises the study by Li et al which pioneered the exploration of the triglyceride-glucose(TyG)index as a prognostic marker in hepatitis B virus-related advanced hepatocellular carcinoma patients undergoing combined camrelizumab and lenvatinib therapy.While we acknowledge the study’s clinical relevance in proposing an easily accessible metabolic biomarker,we delve into the mechanistic plausibility linking insulin resistance to immunotherapy response and angiogenic inhibition.We further critically examine the methodological limitations,including the retrospective design,the populationspecific TyG cut-off value,and unaddressed metabolic confounders.We highlight the imperative for future research to validate its utility across diverse etiologies and treatment settings,and to unravel the underlying immunometabolic pathways.展开更多
Systemic inflammation is a marker of poor prognosis preoperatively present in around 20%-40%of colorectal cancer patients.The hallmarks of systemic inflammation include an increased production of proinflammatory cytok...Systemic inflammation is a marker of poor prognosis preoperatively present in around 20%-40%of colorectal cancer patients.The hallmarks of systemic inflammation include an increased production of proinflammatory cytokines and acute phase proteins that enter the circulation.While the low-level systemic inflammation is often clinically silent,its consequences are many and may ultimately lead to chronic cancer-associated wasting,cachexia.In this review,we discuss the pathogenesis of cancer-related systemic inflammation,explore the role of systemic inflammation in promoting cancer growth,escaping antitumor defense,and shifting metabolic pathways,and how these changes are related to less favorable outcome.展开更多
Background: The prognostic nutritional index(PNI) has been widely applied for predicting survival outcomes of patients with various malignant tumors. Although a low PNI predicts poor prognosis in patients with colorec...Background: The prognostic nutritional index(PNI) has been widely applied for predicting survival outcomes of patients with various malignant tumors. Although a low PNI predicts poor prognosis in patients with colorectal cancer after tumor resection, the prognostic value remains unknown in patients with stage Ⅲ colon cancer undergoing curative tumor resection followed by adjuvant chemotherapy. This study aimed to investigate the prognostic value of PNI in patients with stage III colon cancer.Methods: Medical records of 274 consecutive patients with stage Ⅲ colon cancer undergoing curative tumor resection followed by adjuvant chemotherapy with oxaliplatin and capecitabine between December 2007 and December2013 were reviewed. The optimal PNI cutoff value was determined using receiver operating characteristic(ROC) curve analysis. The associations of PNI with systemic inflammatory response markers, including lymphocyte-to-monocyte ratio(LMR), neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), and C-reactive protein(CRP)level, and clinicopathologic characteristics were assessed using the Chi square or Fisher's exact test. Correlation analysis was performed using Spearman's correlation coefficient. Disease-free survival(DFS) and overall survival(OS)stratified by PNI were analyzed using Kaplan-Meier method and log-rank test, and prognostic factors were identified by Cox regression analyses.Results: The preoperative PNI was positively correlated with LMR(r= 0.483, P < 0.001) and negatively correlated with NLR(r =-0.441, P < 0.001), PLR(r =-0.607, P < 0.001), and CRP level(r =-0.333, P < 0.001). A low PNI(≤49.22)was significantly associated with short OS and DFS in patients with stage ⅢC colon cancer but not in patients with stage ⅢA/ⅢB colon cancer.In addition, patients with a low PNI achieved a longer OS and DFS after being treated with6-8 cycles of adjuvant chemotherapy than did those with < 6 cycles. Multivariate analyses revealed that PNI was independently associated with DFS(hazard ratios 2.001; 95% confidence interval 1.157-3.462; P = 0.013).Conclusion: The present study identified preoperative PNI as a valuable predictor for survival outcomes in patients with stage Ⅲ colon cancer receiving curative tumor resection followed by adjuvant chemotherapy.展开更多
AIM To clarify the previous discrepant conclusions, we performed a meta-analysis to evaluate the prognostic value of red cell distribution width(RDW) in esophageal cancer(EC). METHODS We searched the PubM ed, EMBASE, ...AIM To clarify the previous discrepant conclusions, we performed a meta-analysis to evaluate the prognostic value of red cell distribution width(RDW) in esophageal cancer(EC). METHODS We searched the PubM ed, EMBASE, Web of Science and Cochrane Library databases to identify clinical studies, followed by using STATA version 12.0 for statistical analysis. Studies that met the following criteria were considered eligible:(1) Studies including EC patients who underwent radical esophagectomy;(2) studies including patients with localized disease without distant metastasis;(3) studies including patients without preoperative neoadjuvant therapy;(4) studies including patients without previous antiinflammatory therapies and with available preoperative laboratory outcomes;(5) studies reporting association between the preoperative RDW and overall survival(OS)/disease-free survival(DFS)/cancer-specific survival(CSS); and(6) studies published in English.RESULTS A total of six articles, published between 2015 and 2017, fulfilled the selection criteria in the end. Statistical analysis showed that RDW was not associated with the prognosis of EC patients, irrespective of OS/CSS [hazard ratio(HR) = 1.27, 95% confidence interval(CI): 0.97-1.57, P = 0.000] or DFS(HR = 1.42, 95%CI: 0.96-1.88, P = 0.000). Subgroup analysis indicated that elevated RDW was significantly associated with worse OS/CSS of EC patients when RDW > 13%(HR = 1.45, 95%CI: 1.13-1.76, P = 0.000), when the patient number ≤ 400(HR = 1.45, 95%CI: 1.13-1.76, P = 0.000) and when the study type was retrospective(HR = 1.42, 95%CI : 1.16-1.69, P = 0.000).CONCLUSION Contrary to our general understanding, this meta-analysis revealed that RDW cannot serve as an indicator of poor prognosis in patients with EC. However, it may still be a useful predictor of unfavorable prognosis using an appropriate cut-off value.展开更多
Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life（RUL） prognostics of electroni...Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life（RUL） prognostics of electronics-rich system including avionics.Prognostics and health management（PHM） have become highly desirable to provide avionics with system level health management.This paper presents a health management and fusion prognostic model for avionics system,combining three baseline prognostic approaches that are model-based,data-driven and knowledge-based approaches,and integrates merits as well as eliminates some limitations of each single approach to achieve fusion prognostics and improved prognostic performance of RUL estimation.A fusion model built upon an optimal linear combination forecast model is then utilized to fuse single prognostic algorithm representing the three baseline approaches correspondingly,and the presented case study shows that the fusion prognostics can provide RUL estimation more accurate and more robust than either algorithm alone.展开更多
BACKGROUND The prognosis of intrahepatic cholangiocarcinoma(ICC)patients following surgical resection remains poor.It is necessary to investigate effective biomarkers or prognostic models for ICC patients.AIM To inves...BACKGROUND The prognosis of intrahepatic cholangiocarcinoma(ICC)patients following surgical resection remains poor.It is necessary to investigate effective biomarkers or prognostic models for ICC patients.AIM To investigate the prognostic effect of systemic immune-inflammation index(SII)to predict long-term outcomes in ICC patients with undergoing hepatic resection.METHODS Consecutive ICC patients who underwent initial hepatectomy with curative intent from January 2009 to September 2017 were retrospectively reviewed.Receiver-operating characteristic(ROC)curves were used to determine the optimal cut-off values of SII.Kaplan-Meier curves and Cox proportional hazards regression were performed to evaluate the discriminative ability of preoperative SII in predicting overall survival(OS)and recurrence-free survival(RFS).RESULTS A total of 530 patients were included and randomly divided into derivation(n=265)and validation cohort(n=265).The optimal cut-off value for SII was 450.Ata median follow-up of 18 mo(range,1-115.4 mo),317(59.8%)patients died and381(71.9%)patients experienced tumor relapse.Low SII level was associated with better OS and RFS(both P<0.05).Multivariate analyses identified multiple tumors,node invasion and high SII level as independent risk factors for OS,while multiple tumors,node invasion and high SII level were identified as independent risk factors for RFS.Validation cohort confirmed the findings of derivation cohort.CONCLUSION The present study demonstrated the feasibility of preoperative SII as a prognostic indicator for ICC.Patients with increased SII level were associated with worse OS and earlier tumor recurrence.Elevated SII level was an independent risk factor for OS and RFS in patients with ICC after hepatectomy.In the future,the SII could help stratifying patients with ICC,thus guiding therapeutic choices,especially in immunotherapy.展开更多
Objective:Spontaneous hepatocellular carcinoma(HCC)rupture can be fatal,and hepatic resection could achieve a favorable long-term survival among all strategies of tumor rupture.However,there is no available prognostic...Objective:Spontaneous hepatocellular carcinoma(HCC)rupture can be fatal,and hepatic resection could achieve a favorable long-term survival among all strategies of tumor rupture.However,there is no available prognostic scoring system for patients with ruptured HCC who underwent partial hepatectomy.Methods:From January 2005 to May 2015,129 patients with spontaneous HCC rupture underwent partial hepatectomy.Preoperative clinical data were collected and analyzed.Independent risk factors affecting overall survival(OS)were used to develop the new scoring system.Harrell’s C statistics,Akaike information criterion(AIC),the relative likelihood,and the log likelihood ratio were calculated to measure the homogeneity and discriminatory ability of a prognostic system.Results:In the multivariable Cox regression analysis,three factors,including tumor size,preoperativeα-fetoprotein level,and alkaline phosphatase level,were chosen for the new tumor-associated antigen(TAA)prognostic scoring system.The 1-year OS rates were 88.1%,43.2%,and 30.2%for TAA scores of 0–5 points(low-risk group),6–9 points(moderate-risk group),and 10–13points(high-risk group),respectively.The TAA scoring system had superior homogeneity and discriminatory ability(Harrell’s C statistics,0.693 vs.0.627 and 0.634;AIC,794.79 vs.817.23 and 820.16;relative likelihood,both<0.001;and log likelihood ratio,45.21 vs.22.77 and 21.84)than the Barcelona Clinic Liver Cancer staging system and the Cancer of the Liver Italian Program in predicting OS.Similar results were found while predicting disease-free survival(DFS).Conclusions:The new prognostic scoring system is simple and effective in predicting both OS and DFS of patients with spontaneous ruptured HCC.展开更多
The prognostic value of T category for locoregional control in patients with nasopharyngeal carcinoma(NPC)has decreased with the extensive use of intensity-modulated radiotherapy(IMRT).We aimed to develop a prognostic...The prognostic value of T category for locoregional control in patients with nasopharyngeal carcinoma(NPC)has decreased with the extensive use of intensity-modulated radiotherapy(IMRT).We aimed to develop a prognostic scoring system(PSS)that incorporated tumor extension and clinical characteristics for locoregional control in NPC patients treated with IMRT.The magnetic resonance imaging scans and medical records of 717 patients with nonmetastatic NPC treated with IMRT at Sun Yat-sen University Cancer Center between January 2003 and January 2008 were reviewed.Age,pathologic classification,primary tumor extension,primary gross tumor volume(GTV-p),T and N categories,and baseline lactate dehydrogenase(LDH)level were analyzed.Hierarchical cluster analysis as well as univariate and multivariate analyses were used to develop the PSS.Independent prognostic factors for locoregional relapse included N2–3 stage,GTV-p≥26.8 mL,and involvement of one or more structures within cluster3.We calculated a risk score derived from the regression coefficient of each factor and classified patients into four groups:low risk(score 0),intermediate risk(score>0 and≤1),high risk(score>1 and≤2),and extremely high risk(score>2).The 5-year locoregional control rates for these groups were 97.4%,93.6%,85.2%,and 78.6%,respectively(P<0.001).We have developed a PSS that can help identify NPC patients who are at high risk for locoregional relapse and can guide individualized treatments for NPC patients.展开更多
Oil and gas facilities used in the petroleum industry can be considered as complex dynamic systems in that they require different types of equipment with various causal relationships among components and process varia...Oil and gas facilities used in the petroleum industry can be considered as complex dynamic systems in that they require different types of equipment with various causal relationships among components and process variables under monitoring.As the systems grow increasingly large,high speed,automated and intelligent,the nonlinear relations among these process variables and their effects on accidents are to be fully understood for both system reliability and safety assurance.Failures that occur during the process can both cause tremendous loss to the petroleum industry and compromise product quality and affect the environment.Therefore,failures should be detected as soon as possible,and the root causes need to be identified so that corrections can be made in time to avoid further loss,which relate to the safety prognostic technology.By investigation of the relationship of accident causing factors in complex systems,new progress into diagnosis and prognostic technology from international research institutions is reviewed,and research highlights from China University of Petroleum（Beijing） in this area are also presented.By analyzing the present domestic and overseas research situations,the current problems and future directions in the fundamental research and engineering applications are proposed.展开更多
Objective:To develop and validate a radiomics prognostic scoring system(RPSS)for prediction of progressionfree survival(PFS)in patients with stageⅣnon-small cell lung cancer(NSCLC)treated with platinum-based chemothe...Objective:To develop and validate a radiomics prognostic scoring system(RPSS)for prediction of progressionfree survival(PFS)in patients with stageⅣnon-small cell lung cancer(NSCLC)treated with platinum-based chemotherapy.Methods:In this retrospective study,four independent cohorts of stageⅣNSCLC patients treated with platinum-based chemotherapy were included for model construction and validation(Discovery:n=159;Internal validation:n=156;External validation:n=81,Mutation validation:n=64).First,a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography(CT)images of each patient.Then,a radiomics signature was constructed using the least absolute shrinkage and selection operator method(LASSO)penalized Cox regression analysis.Finally,an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction.Results:The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts(All P<0.05).On the multivariable analysis,independent factors for PFS were radiomics signature,performance status(PS),and N stage,which were all selected into construction of RPSS.The RPSS showed significant prognostic performance for predicting PFS in discovery[C-index:0.772,95%confidence interval(95%CI):0.765-0.779],internal validation(C-index:0.738,95%CI:0.730-0.746),external validation(C-index:0.750,95%CI:0.734-0.765),and mutation validation(Cindex:0.739,95%CI:0.720-0.758).Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness(All P<0.05).Conclusions:This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stageⅣNSCLC patients treated with platinumbased chemotherapy,which holds promise for guiding personalized pre-therapy of stageⅣNSCLC.展开更多
AIM: To study the significance of scoring systems assessing severity and prognostic factors in patients with colonic perforation. METHODS: A total of 26 patients (9 men, 17 women; mean age 72.7 ± 11.6 years) unde...AIM: To study the significance of scoring systems assessing severity and prognostic factors in patients with colonic perforation. METHODS: A total of 26 patients (9 men, 17 women; mean age 72.7 ± 11.6 years) underwent emergency operation for colorectal perforation in our institution between 1993 and 2005. Several clinical factors were measured preoperatively and 24 h postoperatively. Acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ), Mannheim peritonitis index (MPI) and peritonitis index of Altona (PIA Ⅱ) scores were calculated preoperatively. RESULTS: Overall postoperative mortality rate was 23.1% (6 patients). Compared with survivors, non- survivors displayed low blood pressure, low serum protein and high serum creatinine preoperatively, and low blood pressure, low white blood cell count, low pH, low PaO2/FiO2, and high serum creatinine postoperatively. APACHE Ⅱ score was significantly lower in survivors than in non-survivors (10.4 ± 3.84 vs 19.3 ± 2.87, P = 0.00003). Non-survivors tended to display high MPI score and low PIA Ⅱ score, but no signif icant difference was identif ied. CONCLUSION: Pre- and postoperative blood pressure and serum creatinine level appear related to prognosis of colonic perforation. APACHE Ⅱ score is most associated with prognosis and scores ≥ 20 are associated with signif icantly increased mortality rate.展开更多
文摘Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in medicine.About 17.9 million people die from CVDs annually,accounting for 31%of all deaths worldwide.With a timely prognosis and thorough consideration of the patient’s medical history and lifestyle,it is possible to predict CVDs and take preventive measures to eliminate or control this life-threatening disease.In this study,we used various patient datasets from a major hospital in the United States as prognostic factors for CVD.The data was obtained by monitoring a total of 918 patients whose criteria for adults were 28-77 years old.In this study,we present a data mining modeling approach to analyze the performance,classification accuracy and number of clusters on Cardiovascular Disease Prognostic datasets in unsupervised machine learning(ML)using the Orange data mining software.Various techniques are then used to classify the model parameters,such as k-nearest neighbors,support vector machine,random forest,artificial neural network(ANN),naïve bayes,logistic regression,stochastic gradient descent(SGD),and AdaBoost.To determine the number of clusters,various unsupervised ML clustering methods were used,such as k-means,hierarchical,and density-based spatial clustering of applications with noise clustering.The results showed that the best model performance analysis and classification accuracy were SGD and ANN,both of which had a high score of 0.900 on Cardiovascular Disease Prognostic datasets.Based on the results of most clustering methods,such as k-means and hierarchical clustering,Cardiovascular Disease Prognostic datasets can be divided into two clusters.The prognostic accuracy of CVD depends on the accuracy of the proposed model in determining the diagnostic model.The more accurate the model,the better it can predict which patients are at risk for CVD.
文摘BACKGROUND Hepatocellular carcinoma(HCC),the sixth most common cancer and fourthleading cause of cancer-related mortality globally,imposes a significant burden in Vietnam due to endemic hepatitis B virus(HBV)and hepatitis C virus(HCV)infections.Accurate prognostication is crucial for optimizing treatment and outcomes.Numerous staging systems exist,including the Barcelona Clinic Liver Cancer(BCLC),Hong Kong Liver Cancer(HKLC),cancer of the liver Italian Program(CLIP),Italian Liver Cancer(ITA.LI.CA),Japan Integrated Staging(JIS),Tokyo Score,and model to estimate survival in ambulatory HCC patients(MESIAH).However,their comparative performance in Vietnamese patients remains underexplored.AIM To compare the prognostic accuracy of seven HCC staging systems in predicting survival and identify the optimal model.METHODS This retrospective cohort study included 987 patients with HCC diagnosed at Nhan dan Gia Dinh Hospital,Vietnam,from January 2016 to December 2023.Patients were staged using BCLC,HKLC,CLIP,ITA.LI.CA,JIS,Tokyo score,and MESIAH.Overall survival was analyzed using Kaplan-Meier methods,and prognostic performance was evaluated via the area under the receiver operating characteristic(ROC)curve,Harrell’s concordance index,and calibration plots.RESULTS The HKLC and BCLC systems demonstrated the highest discriminatory ability,with area under the ROC curves of 0.834 and 0.830,respectively,at 12 months and 0.859 for both systems at 36 months.CLIP and ITA.LI.CA exhibited superior calibration,particularly at 36 months.The JIS system consistently showed the poorest discriminatory performance.Subgroup analyses revealed that HKLC maintained strong performance across different viral etiologies(HBV,HCV,non-B-non-C)and treatment modalities(transarterial chemoembolization,surgery,ablation).CONCLUSION The HKLC and BCLC systems showed superior prognostic performance for Vietnamese patients with HCC,supporting HKLC adoption in clinical practice.
文摘BACKGROUND Clinical predictors of dengue fever are crucial for guiding timely management and avoiding life-threatening complications.While prognostic scores are available,a systematic evaluation of these tools is lacking.AIM To evaluate the performance and accuracy of various proposed dengue clinical prognostic scores.METHODS Three databases,PubMed,EMBASE and Cochrane,were searched for peer-reviewed studies published from inception to 4 September 2023.Studies either developing or validating a prognostic model relevant to dengue fever were included.A total of 29 studies(n=17910)were included.RESULTS Most commonly studied outcomes were severe dengue(15 models)and mortality(8 models).For the paediatric population,Bedside Dengue Severity Score by Gayathri et al(specificity=0.98)and the nomogram model by Nguyen et al(sensitivity=0.87)performed better.For the adult population,the most specific model was reported by Leo et al(specificity=0.98).The most sensitive score is shared between Warning Signs for Severe Dengue as reported by Leo et al and Model 2 by Lee et al(sensitivity=1.00).CONCLUSION While several models demonstrated precision and reliability in predicting severe dengue and mortality,broader application across diverse geographic settings is needed to assess their external validity.
文摘In this article,we discuss the recently published article by Yang et al.This retrospective analysis,which was conducted at a large urban tertiary care center,focused on comparing Lille model scores at days 3 and 7 with established scoring systems and identifying critical clinical predictors,such as renal dysfunction,nutritional status,and underlying cirrhosis.Alcoholic hepatitis(AH),a severe manifestation of alcohol-related liver disease,is associated with high morbidity and mortality,necessitating accurate prognostic tools and comprehensive clinical assessments.Prognostic tools are invaluable for early risk stratification,but they must be contextualized within the multifactorial nature of AH.Acute renal dysfunction and poor nutritional status,for example,are not just complications but pivotal markers of disease severity and systemic impact.Addressing these factors requires a holistic approach that extends beyond scoring systems to include targeted interventions and comprehensive patient care.This editorial emphasizes the need for a paradigm shift in AH management,where prognostic models are complemented by a deeper understanding of patient-specific factors.Such an approach can guide clinicians in tailoring therapies and improving outcomes for this high-risk population.
基金Supported by The Science and Technology Innovation 2030-Major Project,No.2021ZD0140406.
文摘BACKGROUND Partial hepatectomy continues to be the primary treatment approach for liver tumors,and post-hepatectomy liver failure(PHLF)remains the most critical lifethreatening complication following surgery.AIM To comprehensively review the PHLF prognostic models developed in recent years and objectively assess the risk of bias in these models.METHODS This review followed the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline.Three databases were searched from November 2019 to December 2022,and references as well as cited literature in all included studies were manually screened in March 2023.Based on the defined inclusion criteria,articles on PHLF prognostic models were selected,and data from all included articles were extracted by two independent reviewers.The PROBAST was used to evaluate the quality of each included article.RESULTS A total of thirty-four studies met the eligibility criteria and were included in the analysis.Nearly all of the models(32/34,94.1%)were developed and validated exclusively using private data sources.Predictive variables were categorized into five distinct types,with the majority of studies(32/34,94.1%)utilizing multiple types of data.The area under the curve for the training models included ranged from 0.697 to 0.956.Analytical issues resulted in a high risk of bias across all studies included.CONCLUSION The validation performance of the existing models was substantially lower compared to the development models.All included studies were evaluated as having a high risk of bias,primarily due to issues within the analytical domain.The progression of modeling technology,particularly in artificial intelligence modeling,necessitates the use of suitable quality assessment tools.
基金Supported by the Scientific Research Project of Hospital Pharmacy of Guangxi Pharmaceutical Association in 2022,No.GXYXH1-202202.
文摘BACKGROUND Gastric cancer(GC)is the fifth most common cancer and the third leading cause of cancer-related deaths in China.Many patients with GC frequently experience symptoms related to the disease,including anorexia,nausea,vomiting,and other discomforts,and often suffer from malnutrition,which in turn negatively affects perioperative safety,prognosis,and the effectiveness of adjuvant therapeutic measures.Consequently,some nutritional indicators such as nutritional risk index(NRI),prognostic nutritional index(PNI),and systemic immune-inflammatorynutritional index(SIINI)can be used as predictors of the prognosis of GC patients.AIM To examine the prognostic significance of PNI,NRI,and SIINI in postoperative patients with GC.METHODS A retrospective analysis was conducted on the clinical data of patients with GC who underwent surgical treatment at the Guangxi Medical University Cancer Hospital between January 2010 and December 2018.The area under the receiver operating characteristic(ROC)curve was assessed using ROC curve analysis,and the optimal cutoff values for NRI,PNI,and SIINI were identified using the You-Review-HTMLden index.Survival analysis was performed using the Kaplan-Meier method.In addition,univariate and multivariate analyses were conducted using the Cox proportional hazards regression model.RESULTS This study included a total of 803 patients.ROC curves were used to evaluate the prognostic ability of NRI,PNI,and SIINI.The results revealed that SIINI had superior predictive accuracy.Survival analysis indicated that patients with GC in the low SIINI group had a significantly better survival rate than those in the high SIINI group(P<0.05).Univariate analysis identified NRI[hazard ratio(HR)=0.68,95%confidence interval(CI):0.52-0.89,P=0.05],PNI(HR=0.60,95%CI:0.46-0.79,P<0.001),and SIINI(HR=2.10,95%CI:1.64-2.69,P<0.001)as prognostic risk factors for patients with GC.However,multifactorial analysis indicated that SIINI was an independent risk factor for the prognosis of patients with GC(HR=1.65,95%CI:1.26-2.16,P<0.001).CONCLUSION Analysis of clinical retrospective data revealed that SIINI is a valuable indicator for predicting the prognosis of patients with GC.Compared with NRI and PNI,SIINI may offer greater application for prognostic assessment.
基金funded by theGuangzhou Municipal Science and Tech-nology Bureau(No.2023A03J0507).
文摘Background:Lung cancer is the leading cause of cancer-related mortality,and while low-dose computed tomography screening may reduce mortality,emerging prognostic models show superior discriminative efficacy compared to age-and smoking history-based screening.However,further research is needed to assess their reliability in predicting lung cancer risk in high-risk patients.Methods:This study evaluated the predictive performance and quality of existing lung cancer prognostic models through a systematic review and meta-analysis.A comprehensive search was conducted in PubMed,Cochrane,Web of Science,CNKI,and Wanfang for articles published between January 1,2000,and February 13,2025,identifying population-basedmodels incorporating all available modeling data.Results:Among 72 analyzed studies,models were developed from Asian(28 studies,including 23 Chinese cohorts)and European/American(48 studies)populations,with only 6 focusing on nonsmokers.Twenty-one models included genetic markers,15 used clinical factors,and 40 integrated epidemiological predictors.Although 37 models underwent external validation,only 4 demonstrated minimal bias and clinical applicability.A meta-analysis of 11 repeatedly validated models revealed calibration and discrimination,though some lacked calibration data.Conclusions:Few lung cancer prognostic models exist for nonsmokers.Most models exhibit poor predictive performance in external validations,with significant bias and limited application scope.Widespread external validation,standardized model development,and reporting techniques are needed to accurately identify high-risk individuals and ensure applicability across diverse populations.
基金funded by National Natural Science Foundation of China,grant number 82203007.
文摘Objective The systemic immune-inflammation index(SII)has recently attracted significant interest as a new biomarker for predicting the prognosis of patients with glioblastoma(GBM).However,the predictive significance of it is still a subject of debate.This study intended to assess the clinical effectiveness of the SII in GBM and establish a nomogram.Methods Receiver operating characteristic(ROC)curves were utilized to determine the optimal cut-off values of the SII.Kaplan–Meier(KM)survival curves were used to analyze the median overall survival(OS).Cox regression analysis was carried out to evaluate the associations between OS and different clinical factors.Based on the SII and clinical characteristics,a nomogram was constructed,and its value in clinical application was evaluated by means of decision curve analysis.Results The optimal SII cut-off value was 610.13.KM analysis revealed that GBM patients with higher SII values had shorter OS(15.0 vs.34.0 months,P=0.044).Multivariate analysis demonstrated that a high SII was an independent predictor of poor outcome in GBM(HR=1.79,P=0.029).The nomogram incorporating the preoperative SII showed good predictive accuracy for GBM patient prognosis(C-index=0.691).Conclusions The SII is an independent predictive indicator for GBM.Patients with elevated SII levels tend to have a poorer prognosis.A nomogram combining the SII with clinical and molecular pathological features can assist clinicians in assessing the risk of death in GBM patients,providing a basis for individualized treatment decisions.
基金the Clinical Medical Team Introduction Program of Suzhou,No.SZYJTD201804.
文摘BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive lymph node ratio(LNR)and log odds of positive lymph nodes(LODDS)were introduced.AIM To assess the prognostic accuracy and stratification efficacy of three nodal staging systems in GC.METHODS A systematic review identified 12 studies,from which hazard ratios(HRs)for overall survival(OS)were summarized.Sensitivity analyses,subgroup analyses,publication bias assessments,and quality evaluations were conducted.To enhance comparability,data from studies with identical cutoff values for pN,LNR,and LODDS were pooled.Homogeneous stratification was then applied to generate Kaplan-Meier(KM)survival curves,assessing the stratification efficacy of three staging systems.RESULTS The HRs and 95%confidence intervals for pN,LNR,and LODDS were 2.16(1.72-2.73),2.05(1.65-2.55),and 3.15(2.15-4.37),respectively,confirming all three as independent prognostic risk factors for OS.Comparative analysis of HRs demonstrated that LODDS had superior prognostic predictive power over LNR and pN.KM curves for pN(N0,N1,N2,N3a,N3b),LNR(0.1/0.2/0.5),and LODDS(-1.5/-1.0/-0.5/0)revealed significant differences(P<0.001)among all prognostic stratifications.Mean differences and standard deviations in 60-month relative survival were 27.93%±0.29%,41.70%±0.30%,and 26.60%±0.28%for pN,LNR,and LODDS,respectively.CONCLUSION All three staging systems are independent prognostic factors for OS.LODDS demonstrated the highest specificity,making it especially useful for predicting outcomes,while pN was the most effective in homogeneous stratification,offering better patient differentiation.These findings highlight the complementary roles of LODDS and pN in enhancing prognostic accuracy and stratification.
文摘This commentary critically appraises the study by Li et al which pioneered the exploration of the triglyceride-glucose(TyG)index as a prognostic marker in hepatitis B virus-related advanced hepatocellular carcinoma patients undergoing combined camrelizumab and lenvatinib therapy.While we acknowledge the study’s clinical relevance in proposing an easily accessible metabolic biomarker,we delve into the mechanistic plausibility linking insulin resistance to immunotherapy response and angiogenic inhibition.We further critically examine the methodological limitations,including the retrospective design,the populationspecific TyG cut-off value,and unaddressed metabolic confounders.We highlight the imperative for future research to validate its utility across diverse etiologies and treatment settings,and to unravel the underlying immunometabolic pathways.
文摘Systemic inflammation is a marker of poor prognosis preoperatively present in around 20%-40%of colorectal cancer patients.The hallmarks of systemic inflammation include an increased production of proinflammatory cytokines and acute phase proteins that enter the circulation.While the low-level systemic inflammation is often clinically silent,its consequences are many and may ultimately lead to chronic cancer-associated wasting,cachexia.In this review,we discuss the pathogenesis of cancer-related systemic inflammation,explore the role of systemic inflammation in promoting cancer growth,escaping antitumor defense,and shifting metabolic pathways,and how these changes are related to less favorable outcome.
基金funded by the National Natural Science Foundation of China(No.81772595,81502459)Sun Yat-sen University Clinical Research 5010 Program(No.2015024,2013013)Science and Technology Planning Project of Guangdong Province(No.2013B021800146)
文摘Background: The prognostic nutritional index(PNI) has been widely applied for predicting survival outcomes of patients with various malignant tumors. Although a low PNI predicts poor prognosis in patients with colorectal cancer after tumor resection, the prognostic value remains unknown in patients with stage Ⅲ colon cancer undergoing curative tumor resection followed by adjuvant chemotherapy. This study aimed to investigate the prognostic value of PNI in patients with stage III colon cancer.Methods: Medical records of 274 consecutive patients with stage Ⅲ colon cancer undergoing curative tumor resection followed by adjuvant chemotherapy with oxaliplatin and capecitabine between December 2007 and December2013 were reviewed. The optimal PNI cutoff value was determined using receiver operating characteristic(ROC) curve analysis. The associations of PNI with systemic inflammatory response markers, including lymphocyte-to-monocyte ratio(LMR), neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), and C-reactive protein(CRP)level, and clinicopathologic characteristics were assessed using the Chi square or Fisher's exact test. Correlation analysis was performed using Spearman's correlation coefficient. Disease-free survival(DFS) and overall survival(OS)stratified by PNI were analyzed using Kaplan-Meier method and log-rank test, and prognostic factors were identified by Cox regression analyses.Results: The preoperative PNI was positively correlated with LMR(r= 0.483, P < 0.001) and negatively correlated with NLR(r =-0.441, P < 0.001), PLR(r =-0.607, P < 0.001), and CRP level(r =-0.333, P < 0.001). A low PNI(≤49.22)was significantly associated with short OS and DFS in patients with stage ⅢC colon cancer but not in patients with stage ⅢA/ⅢB colon cancer.In addition, patients with a low PNI achieved a longer OS and DFS after being treated with6-8 cycles of adjuvant chemotherapy than did those with < 6 cycles. Multivariate analyses revealed that PNI was independently associated with DFS(hazard ratios 2.001; 95% confidence interval 1.157-3.462; P = 0.013).Conclusion: The present study identified preoperative PNI as a valuable predictor for survival outcomes in patients with stage Ⅲ colon cancer receiving curative tumor resection followed by adjuvant chemotherapy.
基金Supported by CAMS Innovation Fund for Medical Science(CIFMS),No.2017-12M-4-003International Science and technology Cooperation Projects,No.2015DFA30650 and No.2016yFE0107100+1 种基金Capital Special Research Project for Health Development,No.2014-2-4012Beijing Natural Science Foundation,No.L172055
文摘AIM To clarify the previous discrepant conclusions, we performed a meta-analysis to evaluate the prognostic value of red cell distribution width(RDW) in esophageal cancer(EC). METHODS We searched the PubM ed, EMBASE, Web of Science and Cochrane Library databases to identify clinical studies, followed by using STATA version 12.0 for statistical analysis. Studies that met the following criteria were considered eligible:(1) Studies including EC patients who underwent radical esophagectomy;(2) studies including patients with localized disease without distant metastasis;(3) studies including patients without preoperative neoadjuvant therapy;(4) studies including patients without previous antiinflammatory therapies and with available preoperative laboratory outcomes;(5) studies reporting association between the preoperative RDW and overall survival(OS)/disease-free survival(DFS)/cancer-specific survival(CSS); and(6) studies published in English.RESULTS A total of six articles, published between 2015 and 2017, fulfilled the selection criteria in the end. Statistical analysis showed that RDW was not associated with the prognosis of EC patients, irrespective of OS/CSS [hazard ratio(HR) = 1.27, 95% confidence interval(CI): 0.97-1.57, P = 0.000] or DFS(HR = 1.42, 95%CI: 0.96-1.88, P = 0.000). Subgroup analysis indicated that elevated RDW was significantly associated with worse OS/CSS of EC patients when RDW > 13%(HR = 1.45, 95%CI: 1.13-1.76, P = 0.000), when the patient number ≤ 400(HR = 1.45, 95%CI: 1.13-1.76, P = 0.000) and when the study type was retrospective(HR = 1.42, 95%CI : 1.16-1.69, P = 0.000).CONCLUSION Contrary to our general understanding, this meta-analysis revealed that RDW cannot serve as an indicator of poor prognosis in patients with EC. However, it may still be a useful predictor of unfavorable prognosis using an appropriate cut-off value.
文摘Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life（RUL） prognostics of electronics-rich system including avionics.Prognostics and health management（PHM） have become highly desirable to provide avionics with system level health management.This paper presents a health management and fusion prognostic model for avionics system,combining three baseline prognostic approaches that are model-based,data-driven and knowledge-based approaches,and integrates merits as well as eliminates some limitations of each single approach to achieve fusion prognostics and improved prognostic performance of RUL estimation.A fusion model built upon an optimal linear combination forecast model is then utilized to fuse single prognostic algorithm representing the three baseline approaches correspondingly,and the presented case study shows that the fusion prognostics can provide RUL estimation more accurate and more robust than either algorithm alone.
基金Supported by the National Natural Science Foundation of China,No.81972747,No.81872004,No.81800564,No.81770615,No.81700555 and No.81672882the Science and Technology Support Program of Sichuan Province,No.2019YFQ0001,No.2018SZ0115 and No.2017SZ0003+1 种基金the Science and Technology Program of Tibet Autonomous Region,No.XZ201801-GB-02the 1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University,No.ZYJC18008.
文摘BACKGROUND The prognosis of intrahepatic cholangiocarcinoma(ICC)patients following surgical resection remains poor.It is necessary to investigate effective biomarkers or prognostic models for ICC patients.AIM To investigate the prognostic effect of systemic immune-inflammation index(SII)to predict long-term outcomes in ICC patients with undergoing hepatic resection.METHODS Consecutive ICC patients who underwent initial hepatectomy with curative intent from January 2009 to September 2017 were retrospectively reviewed.Receiver-operating characteristic(ROC)curves were used to determine the optimal cut-off values of SII.Kaplan-Meier curves and Cox proportional hazards regression were performed to evaluate the discriminative ability of preoperative SII in predicting overall survival(OS)and recurrence-free survival(RFS).RESULTS A total of 530 patients were included and randomly divided into derivation(n=265)and validation cohort(n=265).The optimal cut-off value for SII was 450.Ata median follow-up of 18 mo(range,1-115.4 mo),317(59.8%)patients died and381(71.9%)patients experienced tumor relapse.Low SII level was associated with better OS and RFS(both P<0.05).Multivariate analyses identified multiple tumors,node invasion and high SII level as independent risk factors for OS,while multiple tumors,node invasion and high SII level were identified as independent risk factors for RFS.Validation cohort confirmed the findings of derivation cohort.CONCLUSION The present study demonstrated the feasibility of preoperative SII as a prognostic indicator for ICC.Patients with increased SII level were associated with worse OS and earlier tumor recurrence.Elevated SII level was an independent risk factor for OS and RFS in patients with ICC after hepatectomy.In the future,the SII could help stratifying patients with ICC,thus guiding therapeutic choices,especially in immunotherapy.
文摘Objective:Spontaneous hepatocellular carcinoma(HCC)rupture can be fatal,and hepatic resection could achieve a favorable long-term survival among all strategies of tumor rupture.However,there is no available prognostic scoring system for patients with ruptured HCC who underwent partial hepatectomy.Methods:From January 2005 to May 2015,129 patients with spontaneous HCC rupture underwent partial hepatectomy.Preoperative clinical data were collected and analyzed.Independent risk factors affecting overall survival(OS)were used to develop the new scoring system.Harrell’s C statistics,Akaike information criterion(AIC),the relative likelihood,and the log likelihood ratio were calculated to measure the homogeneity and discriminatory ability of a prognostic system.Results:In the multivariable Cox regression analysis,three factors,including tumor size,preoperativeα-fetoprotein level,and alkaline phosphatase level,were chosen for the new tumor-associated antigen(TAA)prognostic scoring system.The 1-year OS rates were 88.1%,43.2%,and 30.2%for TAA scores of 0–5 points(low-risk group),6–9 points(moderate-risk group),and 10–13points(high-risk group),respectively.The TAA scoring system had superior homogeneity and discriminatory ability(Harrell’s C statistics,0.693 vs.0.627 and 0.634;AIC,794.79 vs.817.23 and 820.16;relative likelihood,both<0.001;and log likelihood ratio,45.21 vs.22.77 and 21.84)than the Barcelona Clinic Liver Cancer staging system and the Cancer of the Liver Italian Program in predicting OS.Similar results were found while predicting disease-free survival(DFS).Conclusions:The new prognostic scoring system is simple and effective in predicting both OS and DFS of patients with spontaneous ruptured HCC.
基金supported by grants from the Natural Science Foundation of China(No.81071836)Sun Yat-sen University 5010 projects(No.050243)
文摘The prognostic value of T category for locoregional control in patients with nasopharyngeal carcinoma(NPC)has decreased with the extensive use of intensity-modulated radiotherapy(IMRT).We aimed to develop a prognostic scoring system(PSS)that incorporated tumor extension and clinical characteristics for locoregional control in NPC patients treated with IMRT.The magnetic resonance imaging scans and medical records of 717 patients with nonmetastatic NPC treated with IMRT at Sun Yat-sen University Cancer Center between January 2003 and January 2008 were reviewed.Age,pathologic classification,primary tumor extension,primary gross tumor volume(GTV-p),T and N categories,and baseline lactate dehydrogenase(LDH)level were analyzed.Hierarchical cluster analysis as well as univariate and multivariate analyses were used to develop the PSS.Independent prognostic factors for locoregional relapse included N2–3 stage,GTV-p≥26.8 mL,and involvement of one or more structures within cluster3.We calculated a risk score derived from the regression coefficient of each factor and classified patients into four groups:low risk(score 0),intermediate risk(score>0 and≤1),high risk(score>1 and≤2),and extremely high risk(score>2).The 5-year locoregional control rates for these groups were 97.4%,93.6%,85.2%,and 78.6%,respectively(P<0.001).We have developed a PSS that can help identify NPC patients who are at high risk for locoregional relapse and can guide individualized treatments for NPC patients.
基金supported by the Natural Science Foundation of China (Grant No. 51104168)the Excellent Doctoral Dissertation Supervisor Project of Beijing (Grant YB20111141401)+3 种基金the Program for New Century Excellent Talents in University (NCET-12-0972)PetroChina Innovation Foundation (Grant No. 2011D-5006-0408)Beijing Natural Science Foundation (3132027)Supported by Science Foundation of China University of Petroleum (No. YJRC-2013-35)
文摘Oil and gas facilities used in the petroleum industry can be considered as complex dynamic systems in that they require different types of equipment with various causal relationships among components and process variables under monitoring.As the systems grow increasingly large,high speed,automated and intelligent,the nonlinear relations among these process variables and their effects on accidents are to be fully understood for both system reliability and safety assurance.Failures that occur during the process can both cause tremendous loss to the petroleum industry and compromise product quality and affect the environment.Therefore,failures should be detected as soon as possible,and the root causes need to be identified so that corrections can be made in time to avoid further loss,which relate to the safety prognostic technology.By investigation of the relationship of accident causing factors in complex systems,new progress into diagnosis and prognostic technology from international research institutions is reviewed,and research highlights from China University of Petroleum（Beijing） in this area are also presented.By analyzing the present domestic and overseas research situations,the current problems and future directions in the fundamental research and engineering applications are proposed.
基金supported by the National Key Research and Development Plan of China(No.2017YFC1309100)the National Science Fund for Distinguished Young Scholars(No.81925023)the National Natural Scientific Foundation of China(No.81771912,81901910,82072090,and 82001986)。
文摘Objective:To develop and validate a radiomics prognostic scoring system(RPSS)for prediction of progressionfree survival(PFS)in patients with stageⅣnon-small cell lung cancer(NSCLC)treated with platinum-based chemotherapy.Methods:In this retrospective study,four independent cohorts of stageⅣNSCLC patients treated with platinum-based chemotherapy were included for model construction and validation(Discovery:n=159;Internal validation:n=156;External validation:n=81,Mutation validation:n=64).First,a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography(CT)images of each patient.Then,a radiomics signature was constructed using the least absolute shrinkage and selection operator method(LASSO)penalized Cox regression analysis.Finally,an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction.Results:The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts(All P<0.05).On the multivariable analysis,independent factors for PFS were radiomics signature,performance status(PS),and N stage,which were all selected into construction of RPSS.The RPSS showed significant prognostic performance for predicting PFS in discovery[C-index:0.772,95%confidence interval(95%CI):0.765-0.779],internal validation(C-index:0.738,95%CI:0.730-0.746),external validation(C-index:0.750,95%CI:0.734-0.765),and mutation validation(Cindex:0.739,95%CI:0.720-0.758).Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness(All P<0.05).Conclusions:This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stageⅣNSCLC patients treated with platinumbased chemotherapy,which holds promise for guiding personalized pre-therapy of stageⅣNSCLC.
文摘AIM: To study the significance of scoring systems assessing severity and prognostic factors in patients with colonic perforation. METHODS: A total of 26 patients (9 men, 17 women; mean age 72.7 ± 11.6 years) underwent emergency operation for colorectal perforation in our institution between 1993 and 2005. Several clinical factors were measured preoperatively and 24 h postoperatively. Acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ), Mannheim peritonitis index (MPI) and peritonitis index of Altona (PIA Ⅱ) scores were calculated preoperatively. RESULTS: Overall postoperative mortality rate was 23.1% (6 patients). Compared with survivors, non- survivors displayed low blood pressure, low serum protein and high serum creatinine preoperatively, and low blood pressure, low white blood cell count, low pH, low PaO2/FiO2, and high serum creatinine postoperatively. APACHE Ⅱ score was significantly lower in survivors than in non-survivors (10.4 ± 3.84 vs 19.3 ± 2.87, P = 0.00003). Non-survivors tended to display high MPI score and low PIA Ⅱ score, but no signif icant difference was identif ied. CONCLUSION: Pre- and postoperative blood pressure and serum creatinine level appear related to prognosis of colonic perforation. APACHE Ⅱ score is most associated with prognosis and scores ≥ 20 are associated with signif icantly increased mortality rate.
