Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predi...Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predict NDMM patient outcomes. The Durie-Salmon (D-S) staging system reflects tumor burden and clinical progression staging with prognostic value.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
The reliable,rapid,and accurate Remaining Useful Life(RUL)prognostics of aircraft power supply and distribution system are essential for enhancing the reliability and stability of system and reducing the life-cycle co...The reliable,rapid,and accurate Remaining Useful Life(RUL)prognostics of aircraft power supply and distribution system are essential for enhancing the reliability and stability of system and reducing the life-cycle costs.To achieve the reliable,rapid,and accurate RUL prognostics,the balance between accuracy and computational burden deserves more attention.In addition,the uncertainty is intrinsically present in RUL prognostic process.Due to the limitation of the uncertainty quantification,the point-wise prognostics strategy is not trustworthy.A Dual Adaptive Sliding-window Hybrid(DASH)RUL probabilistic prognostics strategy is proposed to tackle these deficiencies.The DASH strategy contains two adaptive mechanisms,the adaptive Long Short-Term Memory-Polynomial Regression(LSTM-PR)hybrid prognostics mechanism and the adaptive sliding-window Kernel Density Estimation(KDE)probabilistic prognostics mechanism.Owing to the dual adaptive mechanisms,the DASH strategy can achieve the balance between accuracy and computational burden and obtain the trustworthy probabilistic prognostics.Based on the degradation dataset of aircraft electromagnetic contactors,the superiority of DASH strategy is validated.In terms of probabilistic,point-wise and integrated prognostics performance,the proposed strategy increases by 66.89%,81.73% and 25.84%on average compared with the baseline methods and their variants.展开更多
BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized p...BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized prognostic models that can effectively predict esophagogastric variceal rebleeding in patients with liver cirrhosis are lacking.AIM To construct and externally validate a reliable prognostic model for predicting the occurrence of esophagogastric variceal rebleeding.METHODS This study included 477 EGVB patients across 2 cohorts:The derivation cohort(n=322)and the validation cohort(n=155).The primary outcome was rebleeding events within 1 year.The least absolute shrinkage and selection operator was applied for predictor selection,and multivariate Cox regression analysis was used to construct the prognostic model.Internal validation was performed with bootstrap resampling.We assessed the discrimination,calibration and accuracy of the model,and performed patient risk stratification.RESULTS Six predictors,including albumin and aspartate aminotransferase concentrations,white blood cell count,and the presence of ascites,portal vein thrombosis,and bleeding signs,were selected for the rebleeding event prediction following endoscopic treatment(REPET)model.In predicting rebleeding within 1 year,the REPET model ex-hibited a concordance index of 0.775 and a Brier score of 0.143 in the derivation cohort,alongside 0.862 and 0.127 in the validation cohort.Furthermore,the REPET model revealed a significant difference in rebleeding rates(P<0.01)between low-risk patients and intermediate-to high-risk patients in both cohorts.CONCLUSION We constructed and validated a new prognostic model for variceal rebleeding with excellent predictive per-formance,which will improve the clinical management of rebleeding in EGVB patients.展开更多
BACKGROUND Emerging evidence implicates Candida albicans(C.albicans)in human oncogenesis.Notably,studies have supported its involvement in regulating outcomes in colorectal cancer(CRC).This study investigated the para...BACKGROUND Emerging evidence implicates Candida albicans(C.albicans)in human oncogenesis.Notably,studies have supported its involvement in regulating outcomes in colorectal cancer(CRC).This study investigated the paradoxical role of C.albicans in CRC,aiming to determine whether it promotes or suppresses tumor development,with a focus on the mechanistic basis linked to its metabolic profile.AIM To investigate the dual role of C.albicans in the development and progression of CRC through metabolite profiling and to establish a prognostic model that integrates the microbial and metabolic interactions in CRC,providing insights into potential therapeutic strategies and clinical outcomes.METHODSA prognostic model integrating C. albicans with CRC was developed, incorporating enrichment analysis, immuneinfiltration profiling, survival analysis, Mendelian randomization, single-cell sequencing, and spatial transcriptomics.The effects of the C. albicans metabolite mixture on CRC cells were subsequently validated in vitro. Theprimary metabolite composition was characterized using liquid chromatography-mass spectrometry.RESULTSA prognostic model based on five specific mRNA markers, EHD4, LIME1, GADD45B, TIMP1, and FDFT1, wasestablished. The C. albicans metabolite mixture significantly reduced CRC cell viability. Post-treatment analysisrevealed a significant decrease in gene expression in HT29 cells, while the expression levels of TIMP1, EHD4, andGADD45B were significantly elevated in HCT116 cells. Conversely, LIME1 expression and that of other CRC celllines showed reductions. In normal colonic epithelial cells (NCM460), GADD45B, TIMP1, and FDFT1 expressionlevels were significantly increased, while LIME1 and EHD4 levels were markedly reduced. Following metabolitetreatment, the invasive and migratory capabilities of NCM460, HT29, and HCT116 cells were reduced. Quantitativeanalysis of extracellular ATP post-treatment showed a significant elevation (P < 0.01). The C. albicans metabolitemixture had no effect on reactive oxygen species accumulation in CRC cells but led to a reduction in mitochondrialmembrane potential, increased intracellular lipid peroxidation, and induced apoptosis. Metabolomic profilingrevealed significant alterations, with 516 metabolites upregulated and 531 downregulated.CONCLUSIONThis study introduced a novel prognostic model for CRC risk assessment. The findings suggested that the C.albicans metabolite mixture exerted an inhibitory effect on CRC initiation.展开更多
BACKGROUND Anastomotic leakage(AL)is a serious complication following rectal cancer surgery and is associated with increased recurrence,mortality,extended hospital stays,and delayed chemotherapy.The Onodera prognostic...BACKGROUND Anastomotic leakage(AL)is a serious complication following rectal cancer surgery and is associated with increased recurrence,mortality,extended hospital stays,and delayed chemotherapy.The Onodera prognostic nutritional index(OPNI)and inflammation-related biomarkers,such as the neutrophil-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR),have been studied in the context of cancer prognosis,but their combined efficacy in predicting AL remains unclear.AIM To investigate the relationships between AL and these markers and developed a predictive model for AL.METHODS A retrospective cohort study analyzed the outcomes of 434 patients who had undergone surgery for rectal cancer at a tertiary cancer center from 2016 to 2023.The patients were divided into two groups on the basis of the occurrence of AL:One group consisted of patients who experienced AL(n=49),and the other group did not(n=385).The investigation applied logistic regression to develop a risk prediction model utilizing clinical,pathological,and laboratory data.The efficacy of this model was then evaluated through receiver operating characteristic curve analysis.RESULTS In the present study,11.28%of the participants(49 out of 434 participants)suffered from AL.Multivariate analysis revealed that preoperative levels of the OPNI,NLR,and PLR emerged as independent risk factors for AL,with odds ratios of 0.705(95%CI:0.641-0.775,P=0.012),1.628(95%CI:1.221-2.172,P=0.024),and 0.994(95%CI:0.989-0.999,P=0.031),respectively.These findings suggest that these biomarkers could effectively predict AL risk.Furthermore,the proposed predictive model has superior discriminative ability,as demonstrated by an area under the curve of 0.910,a sensitivity of 0.898,and a specificity of 0.826,reflecting its high level of accuracy.CONCLUSION The risk of AL in rectal cancer surgery patients can be effectively predicted by assessing the preoperative levels of serum nutritional biomarkers and inflammatory indicators,emphasizing their importance in the preoperative evaluation process.展开更多
BACKGROUND Non-ST segment elevation myocardial infarction(NSTEMI)poses significant challenges in clinical management due to its diverse outcomes.Understanding the prognostic role of hematological parameters and derive...BACKGROUND Non-ST segment elevation myocardial infarction(NSTEMI)poses significant challenges in clinical management due to its diverse outcomes.Understanding the prognostic role of hematological parameters and derived ratios in NSTEMI patients could aid in risk stratification and improve patient care.AIM To evaluate the predictive value of hemogram-derived ratios for major adverse cardiovascular events(MACE)in NSTEMI patients,potentially improving clinical outcomes.METHODS A prospective,observational cohort study was conducted in 2021 at the Internal Medicine Clinic of the University Hospital in Tuzla,Bosnia and Herzegovina.The study included 170 patients with NSTEMI,who were divided into a group with MACE and a control group without MACE.Furthermore,the MACE group was subdivided into lethal and non-lethal groups for prognostic analysis.Alongside hematological parameters,an additional 13 hematological-derived ratios(HDRs)were monitored,and their prognostic role was investigated.RESULTS Hematological parameters did not significantly differ between non-ST segment elevation myocardial infarction(NSTEMI)patients with MACE and a control group at T1 and T2.However,significant disparities emerged in HDRs among NSTEMI patients with lethal and non-lethal outcomes post-MACE.Notably,neutrophil-to-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR)were elevated in lethal outcomes.Furthermore,C-reactive protein-to-lymphocyte ratio(CRP/Ly)at T1(>4.737)demonstrated predictive value[odds ratio(OR):3.690,P=0.024].Both NLR at T1(>4.076)and T2(>4.667)emerged as significant predictors,with NLR at T2 exhibiting the highest diagnostic performance,as indicated by an area under the curve of 0.811(95%CI:0.727-0.859)and OR of 4.915(95%CI:1.917-12.602,P=0.001),emphasizing its important role as a prognostic marker.CONCLUSION This study highlights the significant prognostic value of hemogram-derived indexes in predicting MACE among NSTEMI patients.During follow-up,NLR,PLR,and CRP/Ly offer important insights into the inflammatory processes underlying cardiovascular events.展开更多
Gastric cancer(GC)has remained one of the leading causes of cancer-related deaths globally.The development of noninvasive biomarkers in cancer diagnosis and treatment has gained substantial traction in recent years.Re...Gastric cancer(GC)has remained one of the leading causes of cancer-related deaths globally.The development of noninvasive biomarkers in cancer diagnosis and treatment has gained substantial traction in recent years.Recent evidence highlights hypercoagulation as a promising prognostic biomarker,particularly in locally advanced GC(LAGC)who underwent radical resection after neoadjuvant immunochemotherapy(NICT).A recent study by Li et al showed that hypercoagulation is a valuable prognostic indicator for patients with LAGC who have undergone radical resection following NICT.While the study addresses an important clinical issue and provides insightful findings,the present study offered valuable insights;the applicability of these findings was constrained by the retrospective design,the focus on a single center,and the small sample size of the existing studies.Additionally,vital confounders,such as preoperative comorbidities and systemic inflammation,are inadequately addressed.Future studies should focus on prospective multicenter trials,incorporating advanced predictive models such as machine learning algorithms to integrate coagulation markers with other clinical variables for personalized risk stratification.In addition,we are required to validate findings to examine the biological mechanisms correlating hypercoagulation to tumor progression.Integrating machine learning,comprehensive biomarker panels,and real-world data would allow the researchers to have personalized risk stratification,improve predictive accuracy,and optimize clinical decision-making.Finally,A multidisciplinary approach,including lifestyle interventions and imaging modalities,is essential to improve outcomes among patients with GC.展开更多
Background:Acute cholangitis is an infection due to the bile duct obstruction.Despite progress in treat-ment,acute cholangitis remains potentially fatal.Early diagnosis and treatment improve the patient out-comes.The ...Background:Acute cholangitis is an infection due to the bile duct obstruction.Despite progress in treat-ment,acute cholangitis remains potentially fatal.Early diagnosis and treatment improve the patient out-comes.The present study aimed to identify clinical and biological factors at admission associated with 30-day mortality in acute cholangitis,to build an efficient prognostic score based on these parameters and to study the performances of this new score.Methods:We enrolled all adult patients consecutively hospitalized for acute cholangitis between January 2017 and December 2021.We developed a score system named ProChol using variables significantly asso-ciated with 30-day mortality in multivariate logistic analysis and simplified this system(named sProChol)based on a simple points-based approach.Results:In total,528 patients were included,with an average age of 77±13 years,a male predominance(54.2%)and a majority of lithiasis etiology(66.5%).Mortality in 30 days was 11.9%.In multivariate logis-tic analysis,tumor etiology[adjusted odds ratio(aOR)=15.43,95%confidence interval(CI):5.90-40.40],stent obstruction(aOR=5.12,95%CI:2.02-12.99),hypoalbuminemia(aOR=3.50,95%CI:1.25-9.81),renal failure(aOR=6.51,95%CI:2.62-16.18),oxygen therapy(aOR=4.63,95%CI:1.02-20.92)and cu-rative anticoagulation(aOR=2.60,95%CI:1.23-5.52)were independently associated with the 30-day mortality while fever was a protective factor(aOR=0.37,95%CI:0.16-0.84).ProChol score using these 7 parameters and sProChol using the 3 robust factors(etiology,renal failure and anticoagulation)presented respectively an area under receiver operating characteristic(ROC)curves(AUC)of 0.81 and 0.77,higher than Tokyo(AUC=0.72)and Gravito-Soares et al.score(AUC=0.71).Patients with sProChol≥4 had a significantly higher risk of transfer to intensive care unit(13.3%vs.5.1%;P<0.001)and longer length of stay(P=0.0006).Conclusions:ProChol and sProChol constructed from simple clinico-biological parameters at admission,present interesting performances in predicting the 30-day mortality in acute cholangitis.展开更多
Objective:To explore the application value of a machine learning-based prediction model in assessing the prognosis of septic children in the pediatric intensive care unit(PICU)and provide data support for clinical dec...Objective:To explore the application value of a machine learning-based prediction model in assessing the prognosis of septic children in the pediatric intensive care unit(PICU)and provide data support for clinical decision-making.Methods:A total of 180 septic children admitted to the PICU of a tertiary hospital from January 2020 to December 2024 were selected.They were divided into a control group(90 cases,using traditional scoring methods to predict prognosis)and an observation group(90 cases,using a multivariable model based on machine learning algorithms to predict prognosis)according to the random number table method.General information,laboratory indicators,and clinical interventions were collected.Various models such as Random Forest(RF),Support Vector Machine(SVM),and Logistic Regression(LR)were established.The model performance was evaluated using ROC curve,AUC value,accuracy,sensitivity,and specificity.Results:The machine learning models performed better than traditional scoring methods in predicting the 28-day mortality rate of septic children.Among them,the RF model achieved an AUC value of 0.921,a sensitivity of 85.6%,and a specificity of 88.1%,which were significantly higher than the PIM3 score(AUC 0.762).The prediction accuracy and timeliness of clinical intervention in the observation group were significantly improved,leading to a shortened hospital stay and reduced mortality rate(p<0.05).Conclusion:The prediction model based on machine learning can more accurately assess the prognostic risk of septic children in PICU,showing good clinical application prospects and providing references for individualized treatment and optimal resource allocation.展开更多
Gastric cancer(GC)remains a leading cause of cancer-related mortality worldwide,necessitating the identification of reliable prognostic indicators to enhance treatment outcomes.Recent research has highlighted the trig...Gastric cancer(GC)remains a leading cause of cancer-related mortality worldwide,necessitating the identification of reliable prognostic indicators to enhance treatment outcomes.Recent research has highlighted the triglyceride-glucose(TyG)index as a potential surrogate marker for insulin resistance,which may significantly influence the prognosis of patients undergoing immunotherapy combined with chemotherapy.In this context,the study by Yao et al demonstrates that a high TyG index correlates with improved overall survival and progressionfree survival in advanced GC patients receiving sintilimab and chemotherapy.Specifically,patients in the high TyG group had a significantly longer median progression-free survival of 9.8 months[95%confidence interval(CI):9.2-10.9]compared to 8.0 months(95%CI:7.5-8.5)in the low TyG group(hazard ratio=0.58,95%CI:0.43-0.79,P<0.001).Similarly,the median overall survival was significantly longer in the high TyG group at 23.1 months(95%CI:21.2-NA)vs 16.5 months(95%CI:13.9-18.3)in the low TyG group(hazard ratio=0.30,95%CI:0.21-0.42,P<0.001).These findings underscore the strong prognostic potential of the TyG index in guiding treatment strategies for advanced GC.These findings underscore the need for further investigation into the TyG index’s role as a prognostic tool and its underlying mechanisms in influencing treatment efficacy.We advocate for additional multicenter studies to validate these results and explore the TyG index’s applicability across diverse patient populations,ultimately aiming to refine treatment strategies and improve patient outcomes in advanced GC.展开更多
BACKGROUND Older patients are more likely to have a poor performance status and comor-bidities.There is a reluctance to extensively investigate and treat older patients.As elderly individuals and patients with neoplas...BACKGROUND Older patients are more likely to have a poor performance status and comor-bidities.There is a reluctance to extensively investigate and treat older patients.As elderly individuals and patients with neoplasms each increase in number,palliative treatment of older patients is expected to grow as an issue.AIM To investigated the role of palliative radiotherapy in older patients and patients who were expected to demonstrate a therapeutic effect.METHODS From February 2019 to February 2022,33 patients aged≥80 years underwent palliative radiotherapy.The prognosis in palliative care study predictor(PiPS),palliative prognostic index(PPI),and delirium-palliative prognostic score(D-PaP)models were used for prognosis prediction.D-PaP scores calculated according to the doctor's prediction of clinical prediction of survival(CPS)were excluded and then analyzed for comparison.Radiation was prescribed at a dose of 2.5-7 Gy per fraction,up to a median of 39 Gy10(range,28-75 Gy10).RESULTS The median follow-up was 2.4 months(range,0.2-27.5 months),and 28 patients(84.8%)showed subjective symptom improvements following treatment.The 2-and 6-month survival rates of all patients were 91.5%and 91.5%,respectively.According to regression analysis,the performance status index,symptom type,and radiation dose all showed no significant correlation with the treatment re-sponse.When survival was expected for>55 days in the PiPS model,the 2-month survival rate was 94.4%.For patients with PPI and D-PaP-CPS values of 0-3.9 points,the 2-month survival rates were 90.0%and 100%,respectively.For patients with a score of≥4 points,the 2-month survival rates were 37.5%and 0%,res-pectively.Core Tip:This is a retrospective study to investigate the role of palliative radiotherapy in older patients and patients who were expected to demonstrate a great therapeutic effect.The prognosis in palliative care study predictor,palliative prognostic index,and delirium-palliative prognostic score models were used for prognosis prediction.Most of patients showed subjective symptom improvements following treatment.The prognosis prediction model showed good correlation with survival.In order to increase the therapeutic effectiveness in palliative radiotherapy,it is necessary to assess a patient's exact prognosis and select appropriate patients accordingly.INTRODUCTION The incidence of cancer is high among individuals 60-69 years old and is 11 times greater among those≥65-years-old compared to those<65-years-old.For this reason,about half of all cancer cases are diagnosed in individuals aged≥70 years,and older patients account for a large portion of the total population regarding the prevalence of cancer[1].Cancer is one of the most significant diseases in older patients.About 60%of all cancer-related deaths occur in older patients aged 70 years[1,2].Moreover,cancer accounts for about one-third of the causes of death in the elderly population[1,2].When choosing a cancer treatment,both the characteristics of the cancer and the overall health status of the patient,such as their general condition and any underlying diseases,should be considered[2].Older patients have a shorter life expectancy than younger patients;moreover,they typically have many accompanying underlying diseases and have a poorer general condition.For this reason,older patients are often rejected from receiving active testing and treatment services.Therefore,even if other factors,such as the underlying disease,are the same in young and old patients,older patients typically receive less treatment due to the simple fact that they are older[3].Palliative treatment is a treatment approach that improves the pain and symptoms of a patient and their quality of life.Although palliative treatment is applicable regardless of patient age and the type and severity of their disease,most patients requiring palliative treatment are cancer patients.Palliative radiotherapy is relatively effective for cancer patients and tends to be a well-tolerated treatment.Although some studies have reported the usefulness of palliative radiotherapy in elderly patients,a large number of patients and caregivers are not receiving treatment due to fears of treatment,the risks of side effects,and doubts about treatment effectiveness[1].Since actual age is not always associated with physical ability,the determination of treatment based solely on age can be an obstacle preventing appropriate treatment opportunities.The importance of palliative care is increasing due to the recent growth of the elderly population,as well as,the increase in cancer incidence,and the changes in traditional views or perceptions,such as a growing acceptance of the pursuit of a dignified death[4].Therefore,in this study,we investigated the role of palliative radiotherapy in older patients and in patients who are expected to show a great therapeutic effect.展开更多
Hepatocellular carcinoma(HCC),a leading cause of cancer mortality,faces diagnostic and therapeutic challenges due to its histopathological complexity and clinical heterogeneity.Pathomics,an emerging discipline that in...Hepatocellular carcinoma(HCC),a leading cause of cancer mortality,faces diagnostic and therapeutic challenges due to its histopathological complexity and clinical heterogeneity.Pathomics,an emerging discipline that integrates artificial intelligence(AI)with quantitative pathology image analysis,aims to decode disease heterogeneity by extracting high-dimensional features from histopathological specimens.This review highlights how AI-driven pathomics has revolutionized liver cancer management through automated analysis of whole-slide images.Pathomics integrates deep learning with histopathological features to enable precise tumour classification(e.g.,HCC vs cholangiocarcinoma),microvascular invasion(MVI)detection,recurrence risk stratification,and survival prediction.Advanced frameworks such as MVI-AI diagnostic model and CHOWDER demonstrate high accuracy in identifying prognostic biomarkers,whereas multiomics integration links morphometric patterns to molecular signatures(e.g.,EZH2 expression and immune infiltration).Despite these breakthroughs,critical bottlenecks persist,including limited multicentre validation studies,"black box"model interpretability,and clinical workflow integration.Future studies should emphasize AI-enhanced multimodal fusion(radiogenomics and liquid biopsy)and standardized platforms to bridge computational pathology and precision oncology,ultimately improving personalized therapeutic strategies for liver malignancies.This synthesis aims to guide research translation and advance personalized therapeutic strategies for liver malignancies.展开更多
BACKGROUND Gastric signet-ring cell carcinoma(GSRCC)is a more aggressive subtype of gastric cancer compared to gastric adenocarcinoma(GA),with an increasing incidence.However,the prognostic differences between these s...BACKGROUND Gastric signet-ring cell carcinoma(GSRCC)is a more aggressive subtype of gastric cancer compared to gastric adenocarcinoma(GA),with an increasing incidence.However,the prognostic differences between these subtypes,particularly in re-sectable cases,remain unclear.AIM To evaluate prognostic factors and develop a predictive model for GA and GSRCC patients undergoing curative resection.METHODS This retrospective cohort study included patients with GA and GSRCC who underwent curative surgery at the National Cancer Center/Cancer Hospital,Chinese Academy of Medical Sciences,from 2011 to 2018.Propensity score ma-tching(PSM)(1:1)balanced the baseline characteristics.Prognostic factors were identified using univariate and multivariate Cox and least absolute shrinkage and selection operator(LASSO)regression analyses.Model performance was eva-luated through calibration curves,decision curve analysis(DCA),and time-dependent receiver operating characteristic curves.Subgroup analysis and Ka-plan-Meier survival curves were generated.RESULTS In a cohort of 3027 patients,the GSRCC group was characterized by a significantly higher prevalence of individuals under 60 years of age,females,cases with poor differentiation,and early-stage(stage I)disease(all P<0.001).After PSM,the baseline was balanced and 761 patients were retained in each group.Variables identified through univariate Cox regression were included in the LASSO regression analysis.Mul-tivariate Cox regression analysis identified age,tumor differentiation,tumor size,vascular invasion,and post-treatment nodal margin staging as independent prognostic factors.Subgroup analysis indicated a notably poorer prognosis for GSRCC in patients aged 60 and above(hazard ratio=1.36,P=0.025).The nomogram(C-index=0.755)exhibited greater predictive accuracy than tumor node metastasis(TNM)staging for 1-,3-,and 5-year overall survival(all P<0.001),and provided a higher clinical net benefit according to DCA.CONCLUSION This study systematically compared resectable GA and GSRCC,revealing no overall survival difference.However,GSRCC demonstrated a significantly elevated mortality risk in subgroups stratified by age and tumor size.Multivariate analysis identified age,differentiation,tumor size,vascular invasion,and TNM stage as independent prognostic factors.The nomogram integrates clinicopathological features for precise risk stratification,surpassing traditional TNM staging.展开更多
Gastric cancer(GC)is a leading cause of cancer-related deaths,highlighting the need for reliable prognostic biomarkers to guide treatment.Wei et al’s systematic review and meta-analysis evaluates the neutrophil-to-ly...Gastric cancer(GC)is a leading cause of cancer-related deaths,highlighting the need for reliable prognostic biomarkers to guide treatment.Wei et al’s systematic review and meta-analysis evaluates the neutrophil-to-lymphocyte ratio(NLR)as a potential biomarker for GC patients undergoing neoadjuvant chemotherapy.NLR is a simple and cost-effective measure of systemic inflammation that shows promise in predicting treatment response and survival outcomes,including overall survival and progression-free survival.However,variations in NLR thresholds and timing of measurements affect its accuracy and clinical utility.Moreover,the studies reviewed primarily involved Asian populations,which may limit the generalizability of the findings.To improve NLR’s clinical relevance,future research should focus on standardizing NLR thresholds,refining measurement timing,and incorporating additional inflammatory markers like platelet-to-lymphocyte ratio and Glasgow prognostic score.Addressing con-founders and including diverse patient populations will help improve NLR’s reliability as a prognostic marker for GC.展开更多
Background:The centrosome,a crucial cellular structure involved in the mitotic process of eukaryotic cells,plays a significant role in tumor progression by regulating the growth and differentiation of neoplastic cells...Background:The centrosome,a crucial cellular structure involved in the mitotic process of eukaryotic cells,plays a significant role in tumor progression by regulating the growth and differentiation of neoplastic cells.This makes the centrosome a promising target for therapeutic strategies in cancer treatment.Methods:Utilizing data from the TCGA database,we identified centrosome-related genes and constructed a prognostic model for 518 lung adenocarcinoma patients.Prognosis-associated genes were initially screened using univariate Cox regression,with overfitting minimized by applying LASSO regression to remove collinearity.Finally,a set of 12 genes was selected through multivariable Cox regression for inclusion in the prognostic model.Results:The model’s performance was assessed using ROC curve analysis,demonstrating a robust predictive ability with an AUC of 0.728 in the training group and 0.695 in the validation group.Differential expression analysis between high-risk(HRLAs)and low-risk(LRLAs)individuals was performed,followed by enrichment analyses using KEGG,GO,Progeny,GSVA,and GSEA.These analyses revealed significant differences in immune-related pathways between the two groups.Immune microenvironment assessment through ssGSEA and ESTIMATE indicated that individuals with poor prognosis exhibited lower immune,stromal,and ESTIMATE scores,along with higher tumor purity,suggesting an impaired immune microenvironment in HRLAs patients.Drug susceptibility analysis and molecular docking showed that HRLAs individuals were more responsive to docetaxel,emphasizing the therapeutic relevance of paclitaxel in this cohort.Conclusion:We successfully developed and validated a centrosome-associated gene-based prognostic model,offering clinicians valuable insights for improved decision-making and personalized treatment strategies.This model may facilitate the identification of high-risk patients and guide therapeutic interventions in lung adenocarcinoma.展开更多
Pancreatic ductal adenocarcinoma(PDAC)is the most prevalent type of pan-creatic neoplasm.It is a highly aggressive lethal malignancy related to its delayed in diagnosis and limited response to treatments.The incidence...Pancreatic ductal adenocarcinoma(PDAC)is the most prevalent type of pan-creatic neoplasm.It is a highly aggressive lethal malignancy related to its delayed in diagnosis and limited response to treatments.The incidence and mortality of pancreatic cancer have been increasing over the years.Tumor budding is a proven independent,adverse prognostic factor in PDAC.It is helpful for improvement of prognosis in PDAC in early and precise diagnostic modalities.Tumor budding should be conveyed in pathology reports and taken into account by future onco-logic staging systems.展开更多
BACKGROUND Acute-on-chronic liver failure(ACLF)is a liver disease based on chronic liver disease,which is significantly influenced by clinical treatment regimen and disease status,and despite the existence of multiple...BACKGROUND Acute-on-chronic liver failure(ACLF)is a liver disease based on chronic liver disease,which is significantly influenced by clinical treatment regimen and disease status,and despite the existence of multiple prognostic assessment indicators for ACLF,the overall sensitivity and accuracy are relatively low.AIM To investigate the prognostic value of the combined detection of alpha-fetoprotein(AFP),plasma prothrombin activity(PTA),and serum prealbumin(PA)in ACLF.METHODS This retrospective study included 87 patients with ACLF admitted from February 2021 to February 2023 and categorized them into the survival(n=47)and death(n=40)groups according to their clinical outcomes 3 months posttreatment.All the participants underwent AFP,PTA,and PA level measurements upon admission.Baseline data,as well as AFP,PTA,and PA levels,were comparatively analyzed.Pearson correlation coefficients were utilized to analyze the correlations of AFP,PTA,and PA with different survival outcomes in patients with ACLF.Receiver operating characteristic(ROC)curves and areas under the curves were used to evaluate the predictive value of AFP,PTA,and PA for ACLF prognosis.RESULTS AFP,PTA,and PA levels were markedly decreased in the death group than in the survival group(P<0.05).Pearson analysis indicated a positive association of the AFP,PTA,and PA levels with the survival of patients with ACLF(P<0.05).ROC curve analysis determined the sensitivity and specificity of the combined diagnosis at 91.24%and 100.00%,respectively,both of which were notably increased compared to the single-index diagnosis.The ROC of their combined diagnosis was 0.989,significantly surpassing 0.907,0.849,and 0.853 of AFP,PTA,and PA,respectively.No statistically significant variance was determined in the sensitivity and specificity of the combined diagnosis vs the single detection(P>0.05).CONCLUSION The combined detection of AFP,PTA,and PA levels demonstrates favorable diagnostic value for the short-term prognosis of patients with ACLF,featuring high sensitivity and specificity.展开更多
BACKGROUND Esophageal cancer patients had the highest intensive care unit(ICU)admitted rate in cancer patients.But their prognosis and evaluation methods were rarely studied.AIM To depict the short-term mortality outc...BACKGROUND Esophageal cancer patients had the highest intensive care unit(ICU)admitted rate in cancer patients.But their prognosis and evaluation methods were rarely studied.AIM To depict the short-term mortality outcome and identify the potential prognostic factors of esophageal cancer patients admitted into ICU.METHODS A multicenter cross-sectional study was performed from May 10,2021 to July 10,2021 at ICU departments of 37 cancer specialized hospitals in China.Patients aged≥14 years with ICU duration≥24 hours were included.Clinical records of patients with primary esophageal cancer diagnosis were reviewed.Patients were separated into groups according to the 90 days survival.Characteristics between groups were compared.Single and multi-variate regression tests were applied to analyze the correlated factors of ICU outcomes.Predictive values of disease severity scores were assessed using receiver operating characteristic curve analysis.RESULTS Total 180 esophageal cancer patients were included.The 90 days mortality was 22.2%.Patients with mortality outcome showed differences from those survived mostly in disease severity and unplanned transfer from clinical ward.The current evaluation tools,including Sequential Organ Failure Assessment and Acute Physiology and Chronic Health Evaluation II scores had low accuracy in prediction of short-term death.ICU admitted esophageal cancer patients have poor prognosis,especially those with acute illness.CONCLUSION The prognostic tools for these patients need to be further optimized.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
基金supported by the National Natural Science Foundation of China (Grant nos. 82470209 and 82170141)the Jiaxing Key Discipiline of Medcine-Nephrology (Grant no. 2023-ZC-011)。
文摘Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predict NDMM patient outcomes. The Durie-Salmon (D-S) staging system reflects tumor burden and clinical progression staging with prognostic value.
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.
基金co-supported by the National Natural Science Foundation of China(Nos.52272403,52402506)Natural Science Basic Research Program of Shaanxi,China(Nos.2022JC-27,2023-JC-QN-0599)。
文摘The reliable,rapid,and accurate Remaining Useful Life(RUL)prognostics of aircraft power supply and distribution system are essential for enhancing the reliability and stability of system and reducing the life-cycle costs.To achieve the reliable,rapid,and accurate RUL prognostics,the balance between accuracy and computational burden deserves more attention.In addition,the uncertainty is intrinsically present in RUL prognostic process.Due to the limitation of the uncertainty quantification,the point-wise prognostics strategy is not trustworthy.A Dual Adaptive Sliding-window Hybrid(DASH)RUL probabilistic prognostics strategy is proposed to tackle these deficiencies.The DASH strategy contains two adaptive mechanisms,the adaptive Long Short-Term Memory-Polynomial Regression(LSTM-PR)hybrid prognostics mechanism and the adaptive sliding-window Kernel Density Estimation(KDE)probabilistic prognostics mechanism.Owing to the dual adaptive mechanisms,the DASH strategy can achieve the balance between accuracy and computational burden and obtain the trustworthy probabilistic prognostics.Based on the degradation dataset of aircraft electromagnetic contactors,the superiority of DASH strategy is validated.In terms of probabilistic,point-wise and integrated prognostics performance,the proposed strategy increases by 66.89%,81.73% and 25.84%on average compared with the baseline methods and their variants.
基金Supported by National Natural Science Foundation of China,No.81874390 and No.81573948Shanghai Natural Science Foundation,No.21ZR1464100+1 种基金Science and Technology Innovation Action Plan of Shanghai Science and Technology Commission,No.22S11901700the Shanghai Key Specialty of Traditional Chinese Clinical Medicine,No.shslczdzk01201.
文摘BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized prognostic models that can effectively predict esophagogastric variceal rebleeding in patients with liver cirrhosis are lacking.AIM To construct and externally validate a reliable prognostic model for predicting the occurrence of esophagogastric variceal rebleeding.METHODS This study included 477 EGVB patients across 2 cohorts:The derivation cohort(n=322)and the validation cohort(n=155).The primary outcome was rebleeding events within 1 year.The least absolute shrinkage and selection operator was applied for predictor selection,and multivariate Cox regression analysis was used to construct the prognostic model.Internal validation was performed with bootstrap resampling.We assessed the discrimination,calibration and accuracy of the model,and performed patient risk stratification.RESULTS Six predictors,including albumin and aspartate aminotransferase concentrations,white blood cell count,and the presence of ascites,portal vein thrombosis,and bleeding signs,were selected for the rebleeding event prediction following endoscopic treatment(REPET)model.In predicting rebleeding within 1 year,the REPET model ex-hibited a concordance index of 0.775 and a Brier score of 0.143 in the derivation cohort,alongside 0.862 and 0.127 in the validation cohort.Furthermore,the REPET model revealed a significant difference in rebleeding rates(P<0.01)between low-risk patients and intermediate-to high-risk patients in both cohorts.CONCLUSION We constructed and validated a new prognostic model for variceal rebleeding with excellent predictive per-formance,which will improve the clinical management of rebleeding in EGVB patients.
基金Supported by Gansu Province Joint Fund General Program,No.24JRRA878Gansu Provincial Science and Technology Program Project,No.24JRRA1020+2 种基金Gansu Province Key Talent Program,No.2025RCXM006Teaching Research and Reform Program for Postgraduate Education at Gansu University of Traditional Chinese Medicine(GUSTCM),No.YBXM-202406Special Fund for Mentors of“Qihuang Talents”in the First-Level Discipline of Chinese Medicine,No.ZYXKBD-202415。
文摘BACKGROUND Emerging evidence implicates Candida albicans(C.albicans)in human oncogenesis.Notably,studies have supported its involvement in regulating outcomes in colorectal cancer(CRC).This study investigated the paradoxical role of C.albicans in CRC,aiming to determine whether it promotes or suppresses tumor development,with a focus on the mechanistic basis linked to its metabolic profile.AIM To investigate the dual role of C.albicans in the development and progression of CRC through metabolite profiling and to establish a prognostic model that integrates the microbial and metabolic interactions in CRC,providing insights into potential therapeutic strategies and clinical outcomes.METHODSA prognostic model integrating C. albicans with CRC was developed, incorporating enrichment analysis, immuneinfiltration profiling, survival analysis, Mendelian randomization, single-cell sequencing, and spatial transcriptomics.The effects of the C. albicans metabolite mixture on CRC cells were subsequently validated in vitro. Theprimary metabolite composition was characterized using liquid chromatography-mass spectrometry.RESULTSA prognostic model based on five specific mRNA markers, EHD4, LIME1, GADD45B, TIMP1, and FDFT1, wasestablished. The C. albicans metabolite mixture significantly reduced CRC cell viability. Post-treatment analysisrevealed a significant decrease in gene expression in HT29 cells, while the expression levels of TIMP1, EHD4, andGADD45B were significantly elevated in HCT116 cells. Conversely, LIME1 expression and that of other CRC celllines showed reductions. In normal colonic epithelial cells (NCM460), GADD45B, TIMP1, and FDFT1 expressionlevels were significantly increased, while LIME1 and EHD4 levels were markedly reduced. Following metabolitetreatment, the invasive and migratory capabilities of NCM460, HT29, and HCT116 cells were reduced. Quantitativeanalysis of extracellular ATP post-treatment showed a significant elevation (P < 0.01). The C. albicans metabolitemixture had no effect on reactive oxygen species accumulation in CRC cells but led to a reduction in mitochondrialmembrane potential, increased intracellular lipid peroxidation, and induced apoptosis. Metabolomic profilingrevealed significant alterations, with 516 metabolites upregulated and 531 downregulated.CONCLUSIONThis study introduced a novel prognostic model for CRC risk assessment. The findings suggested that the C.albicans metabolite mixture exerted an inhibitory effect on CRC initiation.
基金Supported by Natural Science Foundation of Xinjiang Uygur Autonomous Region,No.2022D01C297.
文摘BACKGROUND Anastomotic leakage(AL)is a serious complication following rectal cancer surgery and is associated with increased recurrence,mortality,extended hospital stays,and delayed chemotherapy.The Onodera prognostic nutritional index(OPNI)and inflammation-related biomarkers,such as the neutrophil-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR),have been studied in the context of cancer prognosis,but their combined efficacy in predicting AL remains unclear.AIM To investigate the relationships between AL and these markers and developed a predictive model for AL.METHODS A retrospective cohort study analyzed the outcomes of 434 patients who had undergone surgery for rectal cancer at a tertiary cancer center from 2016 to 2023.The patients were divided into two groups on the basis of the occurrence of AL:One group consisted of patients who experienced AL(n=49),and the other group did not(n=385).The investigation applied logistic regression to develop a risk prediction model utilizing clinical,pathological,and laboratory data.The efficacy of this model was then evaluated through receiver operating characteristic curve analysis.RESULTS In the present study,11.28%of the participants(49 out of 434 participants)suffered from AL.Multivariate analysis revealed that preoperative levels of the OPNI,NLR,and PLR emerged as independent risk factors for AL,with odds ratios of 0.705(95%CI:0.641-0.775,P=0.012),1.628(95%CI:1.221-2.172,P=0.024),and 0.994(95%CI:0.989-0.999,P=0.031),respectively.These findings suggest that these biomarkers could effectively predict AL risk.Furthermore,the proposed predictive model has superior discriminative ability,as demonstrated by an area under the curve of 0.910,a sensitivity of 0.898,and a specificity of 0.826,reflecting its high level of accuracy.CONCLUSION The risk of AL in rectal cancer surgery patients can be effectively predicted by assessing the preoperative levels of serum nutritional biomarkers and inflammatory indicators,emphasizing their importance in the preoperative evaluation process.
文摘BACKGROUND Non-ST segment elevation myocardial infarction(NSTEMI)poses significant challenges in clinical management due to its diverse outcomes.Understanding the prognostic role of hematological parameters and derived ratios in NSTEMI patients could aid in risk stratification and improve patient care.AIM To evaluate the predictive value of hemogram-derived ratios for major adverse cardiovascular events(MACE)in NSTEMI patients,potentially improving clinical outcomes.METHODS A prospective,observational cohort study was conducted in 2021 at the Internal Medicine Clinic of the University Hospital in Tuzla,Bosnia and Herzegovina.The study included 170 patients with NSTEMI,who were divided into a group with MACE and a control group without MACE.Furthermore,the MACE group was subdivided into lethal and non-lethal groups for prognostic analysis.Alongside hematological parameters,an additional 13 hematological-derived ratios(HDRs)were monitored,and their prognostic role was investigated.RESULTS Hematological parameters did not significantly differ between non-ST segment elevation myocardial infarction(NSTEMI)patients with MACE and a control group at T1 and T2.However,significant disparities emerged in HDRs among NSTEMI patients with lethal and non-lethal outcomes post-MACE.Notably,neutrophil-to-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR)were elevated in lethal outcomes.Furthermore,C-reactive protein-to-lymphocyte ratio(CRP/Ly)at T1(>4.737)demonstrated predictive value[odds ratio(OR):3.690,P=0.024].Both NLR at T1(>4.076)and T2(>4.667)emerged as significant predictors,with NLR at T2 exhibiting the highest diagnostic performance,as indicated by an area under the curve of 0.811(95%CI:0.727-0.859)and OR of 4.915(95%CI:1.917-12.602,P=0.001),emphasizing its important role as a prognostic marker.CONCLUSION This study highlights the significant prognostic value of hemogram-derived indexes in predicting MACE among NSTEMI patients.During follow-up,NLR,PLR,and CRP/Ly offer important insights into the inflammatory processes underlying cardiovascular events.
文摘Gastric cancer(GC)has remained one of the leading causes of cancer-related deaths globally.The development of noninvasive biomarkers in cancer diagnosis and treatment has gained substantial traction in recent years.Recent evidence highlights hypercoagulation as a promising prognostic biomarker,particularly in locally advanced GC(LAGC)who underwent radical resection after neoadjuvant immunochemotherapy(NICT).A recent study by Li et al showed that hypercoagulation is a valuable prognostic indicator for patients with LAGC who have undergone radical resection following NICT.While the study addresses an important clinical issue and provides insightful findings,the present study offered valuable insights;the applicability of these findings was constrained by the retrospective design,the focus on a single center,and the small sample size of the existing studies.Additionally,vital confounders,such as preoperative comorbidities and systemic inflammation,are inadequately addressed.Future studies should focus on prospective multicenter trials,incorporating advanced predictive models such as machine learning algorithms to integrate coagulation markers with other clinical variables for personalized risk stratification.In addition,we are required to validate findings to examine the biological mechanisms correlating hypercoagulation to tumor progression.Integrating machine learning,comprehensive biomarker panels,and real-world data would allow the researchers to have personalized risk stratification,improve predictive accuracy,and optimize clinical decision-making.Finally,A multidisciplinary approach,including lifestyle interventions and imaging modalities,is essential to improve outcomes among patients with GC.
文摘Background:Acute cholangitis is an infection due to the bile duct obstruction.Despite progress in treat-ment,acute cholangitis remains potentially fatal.Early diagnosis and treatment improve the patient out-comes.The present study aimed to identify clinical and biological factors at admission associated with 30-day mortality in acute cholangitis,to build an efficient prognostic score based on these parameters and to study the performances of this new score.Methods:We enrolled all adult patients consecutively hospitalized for acute cholangitis between January 2017 and December 2021.We developed a score system named ProChol using variables significantly asso-ciated with 30-day mortality in multivariate logistic analysis and simplified this system(named sProChol)based on a simple points-based approach.Results:In total,528 patients were included,with an average age of 77±13 years,a male predominance(54.2%)and a majority of lithiasis etiology(66.5%).Mortality in 30 days was 11.9%.In multivariate logis-tic analysis,tumor etiology[adjusted odds ratio(aOR)=15.43,95%confidence interval(CI):5.90-40.40],stent obstruction(aOR=5.12,95%CI:2.02-12.99),hypoalbuminemia(aOR=3.50,95%CI:1.25-9.81),renal failure(aOR=6.51,95%CI:2.62-16.18),oxygen therapy(aOR=4.63,95%CI:1.02-20.92)and cu-rative anticoagulation(aOR=2.60,95%CI:1.23-5.52)were independently associated with the 30-day mortality while fever was a protective factor(aOR=0.37,95%CI:0.16-0.84).ProChol score using these 7 parameters and sProChol using the 3 robust factors(etiology,renal failure and anticoagulation)presented respectively an area under receiver operating characteristic(ROC)curves(AUC)of 0.81 and 0.77,higher than Tokyo(AUC=0.72)and Gravito-Soares et al.score(AUC=0.71).Patients with sProChol≥4 had a significantly higher risk of transfer to intensive care unit(13.3%vs.5.1%;P<0.001)and longer length of stay(P=0.0006).Conclusions:ProChol and sProChol constructed from simple clinico-biological parameters at admission,present interesting performances in predicting the 30-day mortality in acute cholangitis.
文摘Objective:To explore the application value of a machine learning-based prediction model in assessing the prognosis of septic children in the pediatric intensive care unit(PICU)and provide data support for clinical decision-making.Methods:A total of 180 septic children admitted to the PICU of a tertiary hospital from January 2020 to December 2024 were selected.They were divided into a control group(90 cases,using traditional scoring methods to predict prognosis)and an observation group(90 cases,using a multivariable model based on machine learning algorithms to predict prognosis)according to the random number table method.General information,laboratory indicators,and clinical interventions were collected.Various models such as Random Forest(RF),Support Vector Machine(SVM),and Logistic Regression(LR)were established.The model performance was evaluated using ROC curve,AUC value,accuracy,sensitivity,and specificity.Results:The machine learning models performed better than traditional scoring methods in predicting the 28-day mortality rate of septic children.Among them,the RF model achieved an AUC value of 0.921,a sensitivity of 85.6%,and a specificity of 88.1%,which were significantly higher than the PIM3 score(AUC 0.762).The prediction accuracy and timeliness of clinical intervention in the observation group were significantly improved,leading to a shortened hospital stay and reduced mortality rate(p<0.05).Conclusion:The prediction model based on machine learning can more accurately assess the prognostic risk of septic children in PICU,showing good clinical application prospects and providing references for individualized treatment and optimal resource allocation.
文摘Gastric cancer(GC)remains a leading cause of cancer-related mortality worldwide,necessitating the identification of reliable prognostic indicators to enhance treatment outcomes.Recent research has highlighted the triglyceride-glucose(TyG)index as a potential surrogate marker for insulin resistance,which may significantly influence the prognosis of patients undergoing immunotherapy combined with chemotherapy.In this context,the study by Yao et al demonstrates that a high TyG index correlates with improved overall survival and progressionfree survival in advanced GC patients receiving sintilimab and chemotherapy.Specifically,patients in the high TyG group had a significantly longer median progression-free survival of 9.8 months[95%confidence interval(CI):9.2-10.9]compared to 8.0 months(95%CI:7.5-8.5)in the low TyG group(hazard ratio=0.58,95%CI:0.43-0.79,P<0.001).Similarly,the median overall survival was significantly longer in the high TyG group at 23.1 months(95%CI:21.2-NA)vs 16.5 months(95%CI:13.9-18.3)in the low TyG group(hazard ratio=0.30,95%CI:0.21-0.42,P<0.001).These findings underscore the strong prognostic potential of the TyG index in guiding treatment strategies for advanced GC.These findings underscore the need for further investigation into the TyG index’s role as a prognostic tool and its underlying mechanisms in influencing treatment efficacy.We advocate for additional multicenter studies to validate these results and explore the TyG index’s applicability across diverse patient populations,ultimately aiming to refine treatment strategies and improve patient outcomes in advanced GC.
文摘BACKGROUND Older patients are more likely to have a poor performance status and comor-bidities.There is a reluctance to extensively investigate and treat older patients.As elderly individuals and patients with neoplasms each increase in number,palliative treatment of older patients is expected to grow as an issue.AIM To investigated the role of palliative radiotherapy in older patients and patients who were expected to demonstrate a therapeutic effect.METHODS From February 2019 to February 2022,33 patients aged≥80 years underwent palliative radiotherapy.The prognosis in palliative care study predictor(PiPS),palliative prognostic index(PPI),and delirium-palliative prognostic score(D-PaP)models were used for prognosis prediction.D-PaP scores calculated according to the doctor's prediction of clinical prediction of survival(CPS)were excluded and then analyzed for comparison.Radiation was prescribed at a dose of 2.5-7 Gy per fraction,up to a median of 39 Gy10(range,28-75 Gy10).RESULTS The median follow-up was 2.4 months(range,0.2-27.5 months),and 28 patients(84.8%)showed subjective symptom improvements following treatment.The 2-and 6-month survival rates of all patients were 91.5%and 91.5%,respectively.According to regression analysis,the performance status index,symptom type,and radiation dose all showed no significant correlation with the treatment re-sponse.When survival was expected for>55 days in the PiPS model,the 2-month survival rate was 94.4%.For patients with PPI and D-PaP-CPS values of 0-3.9 points,the 2-month survival rates were 90.0%and 100%,respectively.For patients with a score of≥4 points,the 2-month survival rates were 37.5%and 0%,res-pectively.Core Tip:This is a retrospective study to investigate the role of palliative radiotherapy in older patients and patients who were expected to demonstrate a great therapeutic effect.The prognosis in palliative care study predictor,palliative prognostic index,and delirium-palliative prognostic score models were used for prognosis prediction.Most of patients showed subjective symptom improvements following treatment.The prognosis prediction model showed good correlation with survival.In order to increase the therapeutic effectiveness in palliative radiotherapy,it is necessary to assess a patient's exact prognosis and select appropriate patients accordingly.INTRODUCTION The incidence of cancer is high among individuals 60-69 years old and is 11 times greater among those≥65-years-old compared to those<65-years-old.For this reason,about half of all cancer cases are diagnosed in individuals aged≥70 years,and older patients account for a large portion of the total population regarding the prevalence of cancer[1].Cancer is one of the most significant diseases in older patients.About 60%of all cancer-related deaths occur in older patients aged 70 years[1,2].Moreover,cancer accounts for about one-third of the causes of death in the elderly population[1,2].When choosing a cancer treatment,both the characteristics of the cancer and the overall health status of the patient,such as their general condition and any underlying diseases,should be considered[2].Older patients have a shorter life expectancy than younger patients;moreover,they typically have many accompanying underlying diseases and have a poorer general condition.For this reason,older patients are often rejected from receiving active testing and treatment services.Therefore,even if other factors,such as the underlying disease,are the same in young and old patients,older patients typically receive less treatment due to the simple fact that they are older[3].Palliative treatment is a treatment approach that improves the pain and symptoms of a patient and their quality of life.Although palliative treatment is applicable regardless of patient age and the type and severity of their disease,most patients requiring palliative treatment are cancer patients.Palliative radiotherapy is relatively effective for cancer patients and tends to be a well-tolerated treatment.Although some studies have reported the usefulness of palliative radiotherapy in elderly patients,a large number of patients and caregivers are not receiving treatment due to fears of treatment,the risks of side effects,and doubts about treatment effectiveness[1].Since actual age is not always associated with physical ability,the determination of treatment based solely on age can be an obstacle preventing appropriate treatment opportunities.The importance of palliative care is increasing due to the recent growth of the elderly population,as well as,the increase in cancer incidence,and the changes in traditional views or perceptions,such as a growing acceptance of the pursuit of a dignified death[4].Therefore,in this study,we investigated the role of palliative radiotherapy in older patients and in patients who are expected to show a great therapeutic effect.
基金Supported by Wenzhou Municipal Science and Technology Bureau,No.Y20240109.
文摘Hepatocellular carcinoma(HCC),a leading cause of cancer mortality,faces diagnostic and therapeutic challenges due to its histopathological complexity and clinical heterogeneity.Pathomics,an emerging discipline that integrates artificial intelligence(AI)with quantitative pathology image analysis,aims to decode disease heterogeneity by extracting high-dimensional features from histopathological specimens.This review highlights how AI-driven pathomics has revolutionized liver cancer management through automated analysis of whole-slide images.Pathomics integrates deep learning with histopathological features to enable precise tumour classification(e.g.,HCC vs cholangiocarcinoma),microvascular invasion(MVI)detection,recurrence risk stratification,and survival prediction.Advanced frameworks such as MVI-AI diagnostic model and CHOWDER demonstrate high accuracy in identifying prognostic biomarkers,whereas multiomics integration links morphometric patterns to molecular signatures(e.g.,EZH2 expression and immune infiltration).Despite these breakthroughs,critical bottlenecks persist,including limited multicentre validation studies,"black box"model interpretability,and clinical workflow integration.Future studies should emphasize AI-enhanced multimodal fusion(radiogenomics and liquid biopsy)and standardized platforms to bridge computational pathology and precision oncology,ultimately improving personalized therapeutic strategies for liver malignancies.This synthesis aims to guide research translation and advance personalized therapeutic strategies for liver malignancies.
基金Supported by the National Natural Science Foundation of China,No.82473285Beijing Hope Run Special Fund of Cancer Foundation of China,No.LC2022B02.
文摘BACKGROUND Gastric signet-ring cell carcinoma(GSRCC)is a more aggressive subtype of gastric cancer compared to gastric adenocarcinoma(GA),with an increasing incidence.However,the prognostic differences between these subtypes,particularly in re-sectable cases,remain unclear.AIM To evaluate prognostic factors and develop a predictive model for GA and GSRCC patients undergoing curative resection.METHODS This retrospective cohort study included patients with GA and GSRCC who underwent curative surgery at the National Cancer Center/Cancer Hospital,Chinese Academy of Medical Sciences,from 2011 to 2018.Propensity score ma-tching(PSM)(1:1)balanced the baseline characteristics.Prognostic factors were identified using univariate and multivariate Cox and least absolute shrinkage and selection operator(LASSO)regression analyses.Model performance was eva-luated through calibration curves,decision curve analysis(DCA),and time-dependent receiver operating characteristic curves.Subgroup analysis and Ka-plan-Meier survival curves were generated.RESULTS In a cohort of 3027 patients,the GSRCC group was characterized by a significantly higher prevalence of individuals under 60 years of age,females,cases with poor differentiation,and early-stage(stage I)disease(all P<0.001).After PSM,the baseline was balanced and 761 patients were retained in each group.Variables identified through univariate Cox regression were included in the LASSO regression analysis.Mul-tivariate Cox regression analysis identified age,tumor differentiation,tumor size,vascular invasion,and post-treatment nodal margin staging as independent prognostic factors.Subgroup analysis indicated a notably poorer prognosis for GSRCC in patients aged 60 and above(hazard ratio=1.36,P=0.025).The nomogram(C-index=0.755)exhibited greater predictive accuracy than tumor node metastasis(TNM)staging for 1-,3-,and 5-year overall survival(all P<0.001),and provided a higher clinical net benefit according to DCA.CONCLUSION This study systematically compared resectable GA and GSRCC,revealing no overall survival difference.However,GSRCC demonstrated a significantly elevated mortality risk in subgroups stratified by age and tumor size.Multivariate analysis identified age,differentiation,tumor size,vascular invasion,and TNM stage as independent prognostic factors.The nomogram integrates clinicopathological features for precise risk stratification,surpassing traditional TNM staging.
文摘Gastric cancer(GC)is a leading cause of cancer-related deaths,highlighting the need for reliable prognostic biomarkers to guide treatment.Wei et al’s systematic review and meta-analysis evaluates the neutrophil-to-lymphocyte ratio(NLR)as a potential biomarker for GC patients undergoing neoadjuvant chemotherapy.NLR is a simple and cost-effective measure of systemic inflammation that shows promise in predicting treatment response and survival outcomes,including overall survival and progression-free survival.However,variations in NLR thresholds and timing of measurements affect its accuracy and clinical utility.Moreover,the studies reviewed primarily involved Asian populations,which may limit the generalizability of the findings.To improve NLR’s clinical relevance,future research should focus on standardizing NLR thresholds,refining measurement timing,and incorporating additional inflammatory markers like platelet-to-lymphocyte ratio and Glasgow prognostic score.Addressing con-founders and including diverse patient populations will help improve NLR’s reliability as a prognostic marker for GC.
基金Key Research and Development Foundation supported by Science and Technology Department of Sichuan Province.Project Number:2023YFS0243Project Name:Application of Multiple Nucleic Acid Detection of Respiratory Pathogens Based on Multiple Fusion Curve Technology in Rapid Pathogenic Analysis of Acute Respiratory Distress Syndrome Patients Caused By Atypical Pathogen Infections in Emergency Departments+1 种基金Fund Name:Applied Basic Research Foundation supported by Science and Technology Department of Sichuan Province.Project Number:2021YJ0135Project Name:Explorating the Antiinflammatory Mechanism of Extracellular Vesicles Secreted by Wharton’s Jelly Mesenchymal Stem Cells in Alleviating Pulmonary Vascular Endothelial Injury and Discussing the Effectiveness of VEGF Gene Modification in Sepsis-related ALI/ARDS.
文摘Background:The centrosome,a crucial cellular structure involved in the mitotic process of eukaryotic cells,plays a significant role in tumor progression by regulating the growth and differentiation of neoplastic cells.This makes the centrosome a promising target for therapeutic strategies in cancer treatment.Methods:Utilizing data from the TCGA database,we identified centrosome-related genes and constructed a prognostic model for 518 lung adenocarcinoma patients.Prognosis-associated genes were initially screened using univariate Cox regression,with overfitting minimized by applying LASSO regression to remove collinearity.Finally,a set of 12 genes was selected through multivariable Cox regression for inclusion in the prognostic model.Results:The model’s performance was assessed using ROC curve analysis,demonstrating a robust predictive ability with an AUC of 0.728 in the training group and 0.695 in the validation group.Differential expression analysis between high-risk(HRLAs)and low-risk(LRLAs)individuals was performed,followed by enrichment analyses using KEGG,GO,Progeny,GSVA,and GSEA.These analyses revealed significant differences in immune-related pathways between the two groups.Immune microenvironment assessment through ssGSEA and ESTIMATE indicated that individuals with poor prognosis exhibited lower immune,stromal,and ESTIMATE scores,along with higher tumor purity,suggesting an impaired immune microenvironment in HRLAs patients.Drug susceptibility analysis and molecular docking showed that HRLAs individuals were more responsive to docetaxel,emphasizing the therapeutic relevance of paclitaxel in this cohort.Conclusion:We successfully developed and validated a centrosome-associated gene-based prognostic model,offering clinicians valuable insights for improved decision-making and personalized treatment strategies.This model may facilitate the identification of high-risk patients and guide therapeutic interventions in lung adenocarcinoma.
文摘Pancreatic ductal adenocarcinoma(PDAC)is the most prevalent type of pan-creatic neoplasm.It is a highly aggressive lethal malignancy related to its delayed in diagnosis and limited response to treatments.The incidence and mortality of pancreatic cancer have been increasing over the years.Tumor budding is a proven independent,adverse prognostic factor in PDAC.It is helpful for improvement of prognosis in PDAC in early and precise diagnostic modalities.Tumor budding should be conveyed in pathology reports and taken into account by future onco-logic staging systems.
文摘BACKGROUND Acute-on-chronic liver failure(ACLF)is a liver disease based on chronic liver disease,which is significantly influenced by clinical treatment regimen and disease status,and despite the existence of multiple prognostic assessment indicators for ACLF,the overall sensitivity and accuracy are relatively low.AIM To investigate the prognostic value of the combined detection of alpha-fetoprotein(AFP),plasma prothrombin activity(PTA),and serum prealbumin(PA)in ACLF.METHODS This retrospective study included 87 patients with ACLF admitted from February 2021 to February 2023 and categorized them into the survival(n=47)and death(n=40)groups according to their clinical outcomes 3 months posttreatment.All the participants underwent AFP,PTA,and PA level measurements upon admission.Baseline data,as well as AFP,PTA,and PA levels,were comparatively analyzed.Pearson correlation coefficients were utilized to analyze the correlations of AFP,PTA,and PA with different survival outcomes in patients with ACLF.Receiver operating characteristic(ROC)curves and areas under the curves were used to evaluate the predictive value of AFP,PTA,and PA for ACLF prognosis.RESULTS AFP,PTA,and PA levels were markedly decreased in the death group than in the survival group(P<0.05).Pearson analysis indicated a positive association of the AFP,PTA,and PA levels with the survival of patients with ACLF(P<0.05).ROC curve analysis determined the sensitivity and specificity of the combined diagnosis at 91.24%and 100.00%,respectively,both of which were notably increased compared to the single-index diagnosis.The ROC of their combined diagnosis was 0.989,significantly surpassing 0.907,0.849,and 0.853 of AFP,PTA,and PA,respectively.No statistically significant variance was determined in the sensitivity and specificity of the combined diagnosis vs the single detection(P>0.05).CONCLUSION The combined detection of AFP,PTA,and PA levels demonstrates favorable diagnostic value for the short-term prognosis of patients with ACLF,featuring high sensitivity and specificity.
文摘BACKGROUND Esophageal cancer patients had the highest intensive care unit(ICU)admitted rate in cancer patients.But their prognosis and evaluation methods were rarely studied.AIM To depict the short-term mortality outcome and identify the potential prognostic factors of esophageal cancer patients admitted into ICU.METHODS A multicenter cross-sectional study was performed from May 10,2021 to July 10,2021 at ICU departments of 37 cancer specialized hospitals in China.Patients aged≥14 years with ICU duration≥24 hours were included.Clinical records of patients with primary esophageal cancer diagnosis were reviewed.Patients were separated into groups according to the 90 days survival.Characteristics between groups were compared.Single and multi-variate regression tests were applied to analyze the correlated factors of ICU outcomes.Predictive values of disease severity scores were assessed using receiver operating characteristic curve analysis.RESULTS Total 180 esophageal cancer patients were included.The 90 days mortality was 22.2%.Patients with mortality outcome showed differences from those survived mostly in disease severity and unplanned transfer from clinical ward.The current evaluation tools,including Sequential Organ Failure Assessment and Acute Physiology and Chronic Health Evaluation II scores had low accuracy in prediction of short-term death.ICU admitted esophageal cancer patients have poor prognosis,especially those with acute illness.CONCLUSION The prognostic tools for these patients need to be further optimized.
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.
