BACKGROUND Ampullary adenocarcinoma is a rare malignant tumor of the gastrointestinal tract.Currently,only a few cases have been reported,resulting in limited information on survival.AIM To develop a dynamic nomogram ...BACKGROUND Ampullary adenocarcinoma is a rare malignant tumor of the gastrointestinal tract.Currently,only a few cases have been reported,resulting in limited information on survival.AIM To develop a dynamic nomogram using internal and external validation to predict survival in patients with ampullary adenocarcinoma.METHODS Data were sourced from the surveillance,epidemiology,and end results stat database.The patients in the database were randomized in a 7:3 ratio into training and validation groups.Using Cox regression univariate and multivariate analyses in the training group,we identified independent risk factors for overall survival and cancer-specific survival to develop the nomogram.The nomogram was validated with a cohort of patients from the First Affiliated Hospital of the Army Medical University.RESULTS For overall and cancer-specific survival,12(sex,age,race,lymph node ratio,tumor size,chemotherapy,surgical modality,T stage,tumor differentiation,brain metastasis,lung metastasis,and extension)and 6(age;surveillance,epidemiology,and end results stage;lymph node ratio;chemotherapy;surgical modality;and tumor differentiation)independent risk factors,respectively,were incorporated into the nomogram.The area under the curve values at 1,3,and 5 years,respectively,were 0.807,0.842,and 0.826 for overall survival and 0.816,0.835,and 0.841 for cancer-specific survival.The internal and external validation cohorts indicated good consistency of the nomogram.CONCLUSION The dynamic nomogram offers robust predictive efficacy for the overall and cancer-specific survival of ampullary adenocarcinoma.展开更多
BACKGROUND Postoperative enterostomy is increasing in patients with colorectal cancer,but there is a lack of a model that can predict the probability of early complications.AIM To explore the factors influencing early...BACKGROUND Postoperative enterostomy is increasing in patients with colorectal cancer,but there is a lack of a model that can predict the probability of early complications.AIM To explore the factors influencing early postoperative stoma complications in colorectal cancer patients and to construct a nomogram prediction model for predicting the probability of these complications.METHODS A retrospective study of 462 patients who underwent postoperative ostomy for colorectal cancer in the Gastrointestinal Department of the Anhui Provincial Cancer Hospital.The patients’basic information,surgical details,pathological results,and preoperative inflammatory and nutritional indicators were reviewed.We used univariate and multivariate logistic regression to analyze the risk factors for early postoperative stoma complications in colorectal cancer patients and constructed a nomogram prediction model to predict the probability of these complications.RESULTS Binary logistic regression analysis revealed that diabetes[odds ratio(OR)=3.088,95%confidence interval(CI):1.419-6.719],preoperative radiotherapy and chemotherapy(OR=6.822,95%CI:2.171-21.433),stoma type(OR=2.118,95%CI:1.151-3.898),Nutritional risk screening 2002 score(OR=2.034,95%CI:1.082-3.822)and prognostic nutritional index(OR=0.486,95%CI:0.254-0.927)were risk factors for early stoma complications after colorectal cancer surgery(P<0.05).On the basis of these results,a prediction model was constructed and the area under the re-ceiver operating characteristic curve was 0.740(95%CI:0.669-0.811).After internal validation,the area under the receiver operating characteristic curve of the validation group was 0.725(95%CI:0.631-0.820).The calibration curves for the modeling group and validation group are displayed.The predicted results have a good degree of overlap with the actual results.CONCLUSION A previous history of diabetes,preoperative radiotherapy and chemotherapy,stoma type,Nutritional risk screening 2002 score and prognostic nutritional index are risk factors for early stoma complications after colorectal cancer surgery.The nomogram prediction model constructed on the basis of the results of logistic regression analysis in this study can effectively predict the probability of early stomal complications after colorectal cancer surgery.展开更多
BACKGROUND The prevalence and mortality rates of gastric carcinoma are disproportionately elevated in China,with the disease's intricate and varied characteristics further amplifying its health impact.Precise fore...BACKGROUND The prevalence and mortality rates of gastric carcinoma are disproportionately elevated in China,with the disease's intricate and varied characteristics further amplifying its health impact.Precise forecasting of overall survival(OS)is of paramount importance for the clinical management of individuals afflicted with this malignancy.AIM To develop and validate a nomogram model that provides precise gastric cancer prevention and treatment guidance and more accurate survival outcome prediction for patients with gastric carcinoma.METHODS Data analysis was conducted on samples collected from hospitalized gastric cancer patients between 2018 and 2020.Least absolute shrinkage and selection operator,univariate,and multivariate Cox regression analyses were employed to identify independent prognostic factors.A nomogram model was developed to predict gastric cancer patient outcomes.The model's predictability and discriminative ability were evaluated via receiver operating characteristic curves.To evaluate the clinical utility of the model,Kaplan-Meier and decision curve analyses were performed.RESULTS A total of ten independent prognostic factors were identified,including body mass index,tumor-node-metastasis(TNM)stage,radiation,chemotherapy,surgery,albumin,globulin,neutrophil count,lactate dehydrogenase,and platelet-to-lymphocyte ratio.The area under the curve(AUC)values for the 1-,3-,and 5-year survival prediction in the training set were 0.843,0.850,and 0.821,respectively.The AUC values were 0.864,0.820,and 0.786 for the 1-,3-,and 5-year survival prediction in the validation set,respectively.The model exhibited strong discriminative ability,with both the time AUC and time C-index exceeding 0.75.Compared with TNM staging,the model demonstrated superior clinical utility.Ultimately,a nomogram was developed via a web-based interface.CONCLUSION This study established and validated a novel nomogram model for predicting the OS of gastric cancer patients,which demonstrated strong predictive ability.Based on these findings,this model can aid clinicians in implementing personalized interventions for patients with gastric cancer.展开更多
BACKGROUND Myocardial injury is common during liver transplantation and is associated with poor outcomes.The development of a reliable prediction system for this type of injury is crucial for reducing the incidence of...BACKGROUND Myocardial injury is common during liver transplantation and is associated with poor outcomes.The development of a reliable prediction system for this type of injury is crucial for reducing the incidence of cardiac complications in children receiving living donor liver transplantation(LDLT).However,establishing a practical myocardial injury prediction system for children with biliary atresia remains a considerable challenge.AIM To create and validate a nomogram model for predicting myocardial injury in children with biliary atresia who received LDLT.METHODS Clinical data from pediatric patients who received LDLT for biliary atresia between November,2019 and January,2022 were retrospectively analyzed.The complete dataset was randomly partitioned into a training set and a validation set at a ratio of 7:3.Least absolute shrinkage and selection operator regression was used to preliminarily screen out the predictors of myocardial injury.The prediction model was established via multivariable logistic regression and presented in the form of a nomogram.RESULTS This study included 321 patients,150(46.7%)of whom had myocardial injury.The participants were randomly allocated into two groups:A training group consisting of 225 patients and a validation group comprising 96 patients.The predictors in this nomogram included the preoperative neutrophil-to-lymphocyte ratio,high sensitivity C-reactive protein level,pediatric end-stage liver disease score and postreperfusion syndrome.The area under the curve for predicting myocardial injury was 0.865 in the training set and 0.856 in the validation set.The calibration curve revealed that the predicted values were very close to the actual values in the two sets.Decision curve analysis revealed that the prediction model offered a favorable net benefit.CONCLUSION The nomogram developed in this study effectively predicts myocardial injury in pediatric LDLT patients,showing good accuracy and potential for clinical application.展开更多
BACKGROUND Rectal cancer is prevalent and associated with substantial morbidity and mortality.AIM To develop a nomogram prediction model for overall survival(OS)in patients with rectal cancer by leveraging a comprehen...BACKGROUND Rectal cancer is prevalent and associated with substantial morbidity and mortality.AIM To develop a nomogram prediction model for overall survival(OS)in patients with rectal cancer by leveraging a comprehensive analysis of demographic,clinicopathological,haematological,and follow-up data to identify independent prognostic factors.METHODS We conducted a prospective cohort study in China involving rectal cancer patients and applied Cox regression and least absolute shrinkage and selection operator regression to assess the significance of various variables as independent prognostic factors for OS.The identified factors were integrated into a nomogram model,which was evaluated for predictive accuracy via the C-index,area under the curve(AUC),calibration curve,and decision curve analysis(DCA).RESULTS Multivariate analysis revealed independent predictors of OS,including the Karnofsky performance status,age,sex,TNM stage,chemotherapy,surgery,targeted therapy,β2-microglobulin,lactate dehydrogenase,and the neutrophil-to-lymphocyte ratio.The nomogram demonstrated a C-index of 0.80 for the training and validation cohorts,with AUC values indicating high predictive accuracy for 1-year,3-year,and 5-year OS.The calibration curves confirmed the model's excellent agreement with the observed survival rates,and DCA revealed the superior clinical utility of the nomogram over the TNM staging system.CONCLUSION In this study,a novel prognostic model that accurately predicts the OS of rectal cancer patients was developed.The model exhibited excellent discriminatory and calibration capabilities,thus offering a reliable tool for health care professionals to estimate patient survival.展开更多
基金Supported by the Appropriate Technology Promotion Program in Chongqing,No.2023jstg005.
文摘BACKGROUND Ampullary adenocarcinoma is a rare malignant tumor of the gastrointestinal tract.Currently,only a few cases have been reported,resulting in limited information on survival.AIM To develop a dynamic nomogram using internal and external validation to predict survival in patients with ampullary adenocarcinoma.METHODS Data were sourced from the surveillance,epidemiology,and end results stat database.The patients in the database were randomized in a 7:3 ratio into training and validation groups.Using Cox regression univariate and multivariate analyses in the training group,we identified independent risk factors for overall survival and cancer-specific survival to develop the nomogram.The nomogram was validated with a cohort of patients from the First Affiliated Hospital of the Army Medical University.RESULTS For overall and cancer-specific survival,12(sex,age,race,lymph node ratio,tumor size,chemotherapy,surgical modality,T stage,tumor differentiation,brain metastasis,lung metastasis,and extension)and 6(age;surveillance,epidemiology,and end results stage;lymph node ratio;chemotherapy;surgical modality;and tumor differentiation)independent risk factors,respectively,were incorporated into the nomogram.The area under the curve values at 1,3,and 5 years,respectively,were 0.807,0.842,and 0.826 for overall survival and 0.816,0.835,and 0.841 for cancer-specific survival.The internal and external validation cohorts indicated good consistency of the nomogram.CONCLUSION The dynamic nomogram offers robust predictive efficacy for the overall and cancer-specific survival of ampullary adenocarcinoma.
文摘BACKGROUND Postoperative enterostomy is increasing in patients with colorectal cancer,but there is a lack of a model that can predict the probability of early complications.AIM To explore the factors influencing early postoperative stoma complications in colorectal cancer patients and to construct a nomogram prediction model for predicting the probability of these complications.METHODS A retrospective study of 462 patients who underwent postoperative ostomy for colorectal cancer in the Gastrointestinal Department of the Anhui Provincial Cancer Hospital.The patients’basic information,surgical details,pathological results,and preoperative inflammatory and nutritional indicators were reviewed.We used univariate and multivariate logistic regression to analyze the risk factors for early postoperative stoma complications in colorectal cancer patients and constructed a nomogram prediction model to predict the probability of these complications.RESULTS Binary logistic regression analysis revealed that diabetes[odds ratio(OR)=3.088,95%confidence interval(CI):1.419-6.719],preoperative radiotherapy and chemotherapy(OR=6.822,95%CI:2.171-21.433),stoma type(OR=2.118,95%CI:1.151-3.898),Nutritional risk screening 2002 score(OR=2.034,95%CI:1.082-3.822)and prognostic nutritional index(OR=0.486,95%CI:0.254-0.927)were risk factors for early stoma complications after colorectal cancer surgery(P<0.05).On the basis of these results,a prediction model was constructed and the area under the re-ceiver operating characteristic curve was 0.740(95%CI:0.669-0.811).After internal validation,the area under the receiver operating characteristic curve of the validation group was 0.725(95%CI:0.631-0.820).The calibration curves for the modeling group and validation group are displayed.The predicted results have a good degree of overlap with the actual results.CONCLUSION A previous history of diabetes,preoperative radiotherapy and chemotherapy,stoma type,Nutritional risk screening 2002 score and prognostic nutritional index are risk factors for early stoma complications after colorectal cancer surgery.The nomogram prediction model constructed on the basis of the results of logistic regression analysis in this study can effectively predict the probability of early stomal complications after colorectal cancer surgery.
文摘BACKGROUND The prevalence and mortality rates of gastric carcinoma are disproportionately elevated in China,with the disease's intricate and varied characteristics further amplifying its health impact.Precise forecasting of overall survival(OS)is of paramount importance for the clinical management of individuals afflicted with this malignancy.AIM To develop and validate a nomogram model that provides precise gastric cancer prevention and treatment guidance and more accurate survival outcome prediction for patients with gastric carcinoma.METHODS Data analysis was conducted on samples collected from hospitalized gastric cancer patients between 2018 and 2020.Least absolute shrinkage and selection operator,univariate,and multivariate Cox regression analyses were employed to identify independent prognostic factors.A nomogram model was developed to predict gastric cancer patient outcomes.The model's predictability and discriminative ability were evaluated via receiver operating characteristic curves.To evaluate the clinical utility of the model,Kaplan-Meier and decision curve analyses were performed.RESULTS A total of ten independent prognostic factors were identified,including body mass index,tumor-node-metastasis(TNM)stage,radiation,chemotherapy,surgery,albumin,globulin,neutrophil count,lactate dehydrogenase,and platelet-to-lymphocyte ratio.The area under the curve(AUC)values for the 1-,3-,and 5-year survival prediction in the training set were 0.843,0.850,and 0.821,respectively.The AUC values were 0.864,0.820,and 0.786 for the 1-,3-,and 5-year survival prediction in the validation set,respectively.The model exhibited strong discriminative ability,with both the time AUC and time C-index exceeding 0.75.Compared with TNM staging,the model demonstrated superior clinical utility.Ultimately,a nomogram was developed via a web-based interface.CONCLUSION This study established and validated a novel nomogram model for predicting the OS of gastric cancer patients,which demonstrated strong predictive ability.Based on these findings,this model can aid clinicians in implementing personalized interventions for patients with gastric cancer.
基金Supported by Tianjin Health Research Project,No.TJWJ2024QN037Research Empowerment-Medical Research and Application Fund Project,No.BHCF-KYFN-2024004the Young Talent Program of Tianjin First Central Hospital.
文摘BACKGROUND Myocardial injury is common during liver transplantation and is associated with poor outcomes.The development of a reliable prediction system for this type of injury is crucial for reducing the incidence of cardiac complications in children receiving living donor liver transplantation(LDLT).However,establishing a practical myocardial injury prediction system for children with biliary atresia remains a considerable challenge.AIM To create and validate a nomogram model for predicting myocardial injury in children with biliary atresia who received LDLT.METHODS Clinical data from pediatric patients who received LDLT for biliary atresia between November,2019 and January,2022 were retrospectively analyzed.The complete dataset was randomly partitioned into a training set and a validation set at a ratio of 7:3.Least absolute shrinkage and selection operator regression was used to preliminarily screen out the predictors of myocardial injury.The prediction model was established via multivariable logistic regression and presented in the form of a nomogram.RESULTS This study included 321 patients,150(46.7%)of whom had myocardial injury.The participants were randomly allocated into two groups:A training group consisting of 225 patients and a validation group comprising 96 patients.The predictors in this nomogram included the preoperative neutrophil-to-lymphocyte ratio,high sensitivity C-reactive protein level,pediatric end-stage liver disease score and postreperfusion syndrome.The area under the curve for predicting myocardial injury was 0.865 in the training set and 0.856 in the validation set.The calibration curve revealed that the predicted values were very close to the actual values in the two sets.Decision curve analysis revealed that the prediction model offered a favorable net benefit.CONCLUSION The nomogram developed in this study effectively predicts myocardial injury in pediatric LDLT patients,showing good accuracy and potential for clinical application.
文摘BACKGROUND Rectal cancer is prevalent and associated with substantial morbidity and mortality.AIM To develop a nomogram prediction model for overall survival(OS)in patients with rectal cancer by leveraging a comprehensive analysis of demographic,clinicopathological,haematological,and follow-up data to identify independent prognostic factors.METHODS We conducted a prospective cohort study in China involving rectal cancer patients and applied Cox regression and least absolute shrinkage and selection operator regression to assess the significance of various variables as independent prognostic factors for OS.The identified factors were integrated into a nomogram model,which was evaluated for predictive accuracy via the C-index,area under the curve(AUC),calibration curve,and decision curve analysis(DCA).RESULTS Multivariate analysis revealed independent predictors of OS,including the Karnofsky performance status,age,sex,TNM stage,chemotherapy,surgery,targeted therapy,β2-microglobulin,lactate dehydrogenase,and the neutrophil-to-lymphocyte ratio.The nomogram demonstrated a C-index of 0.80 for the training and validation cohorts,with AUC values indicating high predictive accuracy for 1-year,3-year,and 5-year OS.The calibration curves confirmed the model's excellent agreement with the observed survival rates,and DCA revealed the superior clinical utility of the nomogram over the TNM staging system.CONCLUSION In this study,a novel prognostic model that accurately predicts the OS of rectal cancer patients was developed.The model exhibited excellent discriminatory and calibration capabilities,thus offering a reliable tool for health care professionals to estimate patient survival.
