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 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
BACKGROUND There are currently no relevant studies at home or abroad that combine inflammatory indicators and nomograms to predict the prognosis of gastrointestinal stromal tumor(GIST)patients after surgery.The purpos...BACKGROUND There are currently no relevant studies at home or abroad that combine inflammatory indicators and nomograms to predict the prognosis of gastrointestinal stromal tumor(GIST)patients after surgery.The purpose of this study was to investigate the predictive value of related inflammatory indicators[systemic immune-inflammation index(SII),neutrophil/lymphocyte ratio(NLR),platelet/lymphocyte ratio(PLR)and monocyte/Lymphocyte ratio(MLR)]in patients undergoing GIST surgery,incorporating relevant risk factors to establish a nomogram prediction model,with the aim of better predicting the prognosis of GIST patients.AIM To explore the relationships between the SII,NLR,PLR,and MLR and postoperative recurrence in patients with GIST.METHODS This study retrospectively included patients who underwent GIST surgery from January 2014 to January 2017 and analyzed the potential relationships between the preoperative SII,NLR,PLR,and MLR and clinicopathological features.The independent risk factors influencing the prognosis of GIST patients were obtained via multivariate regression analysis,and a nomogram model based on the independent risk factors was established.RESULTS Among the 124 GIST patients included in the present study,31(25%)experienced recurrence within 5 years.Kaplan-Meier survival analysis revealed a correlation between the MLR and PLR and tumor size(P=0.016 and P=0.002,respectively).The preoperative SII,MLR,NLR,and PLR were significantly associated with recurrence-free survival(RFS)(P<0.05).The multivariate analysis results identified the PLR,MLR,and targeted therapy as independent prognostic factors for patient outcomes.CONCLUSION Preoperative MLR and PLR,which are independent risk factors for GIST recurrence,were correlated with RFS.Nomograms based on the PLR,MLR and targeted therapy can be used for clinical treatment.展开更多
BACKGROUND Post-hepatectomy liver failure(PHLF)after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma(HCC).It is crucial to help clinicians identif...BACKGROUND Post-hepatectomy liver failure(PHLF)after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma(HCC).It is crucial to help clinicians identify potential high-risk PHLF patients as early as possible through preoperative evaluation.AIM To identify risk factors for PHLF and develop a prediction model.METHODS This study included 248 patients with HCC at The Second Affiliated Hospital of Air Force Medical University between January 2014 and December 2023;these patients were divided into a training group(n=164)and a validation group(n=84)via random sampling.The independent variables for the occurrence of PHLF were identified by univariate and multivariate analyses and visualized as nomograms.Ultimately,comparisons were made with traditional models via receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).RESULTS In this study,portal vein width[odds ratio(OR)=1.603,95%CI:1.288-1.994,P≤0.001],the preoperative neutrophil-to-lymphocyte ratio(NLR)(OR=1.495,95%CI:1.126-1.984,P=0.005),and the albumin-bilirubin(ALBI)score(OR=8.868,95%CI:2.144-36.678,P=0.003)were independent risk factors for PHLF.A nomogram prediction model was developed using these factors.ROC and DCA analyses revealed that the predictive efficacy and clinical value of this model were better than those of traditional models.CONCLUSION A new Nomogram model for predicting PHLF in HCC patients was successfully established based on portal vein width,the NLR,and the ALBI score,which outperforms the traditional model.展开更多
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.
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.
基金Supported by The Chengdu Municipal Science and Technology Program,No.2023097.
文摘BACKGROUND There are currently no relevant studies at home or abroad that combine inflammatory indicators and nomograms to predict the prognosis of gastrointestinal stromal tumor(GIST)patients after surgery.The purpose of this study was to investigate the predictive value of related inflammatory indicators[systemic immune-inflammation index(SII),neutrophil/lymphocyte ratio(NLR),platelet/lymphocyte ratio(PLR)and monocyte/Lymphocyte ratio(MLR)]in patients undergoing GIST surgery,incorporating relevant risk factors to establish a nomogram prediction model,with the aim of better predicting the prognosis of GIST patients.AIM To explore the relationships between the SII,NLR,PLR,and MLR and postoperative recurrence in patients with GIST.METHODS This study retrospectively included patients who underwent GIST surgery from January 2014 to January 2017 and analyzed the potential relationships between the preoperative SII,NLR,PLR,and MLR and clinicopathological features.The independent risk factors influencing the prognosis of GIST patients were obtained via multivariate regression analysis,and a nomogram model based on the independent risk factors was established.RESULTS Among the 124 GIST patients included in the present study,31(25%)experienced recurrence within 5 years.Kaplan-Meier survival analysis revealed a correlation between the MLR and PLR and tumor size(P=0.016 and P=0.002,respectively).The preoperative SII,MLR,NLR,and PLR were significantly associated with recurrence-free survival(RFS)(P<0.05).The multivariate analysis results identified the PLR,MLR,and targeted therapy as independent prognostic factors for patient outcomes.CONCLUSION Preoperative MLR and PLR,which are independent risk factors for GIST recurrence,were correlated with RFS.Nomograms based on the PLR,MLR and targeted therapy can be used for clinical treatment.
基金Supported by Shaanxi Provincial Social Development Fund,No.2024SF-YBXM-140.
文摘BACKGROUND Post-hepatectomy liver failure(PHLF)after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma(HCC).It is crucial to help clinicians identify potential high-risk PHLF patients as early as possible through preoperative evaluation.AIM To identify risk factors for PHLF and develop a prediction model.METHODS This study included 248 patients with HCC at The Second Affiliated Hospital of Air Force Medical University between January 2014 and December 2023;these patients were divided into a training group(n=164)and a validation group(n=84)via random sampling.The independent variables for the occurrence of PHLF were identified by univariate and multivariate analyses and visualized as nomograms.Ultimately,comparisons were made with traditional models via receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).RESULTS In this study,portal vein width[odds ratio(OR)=1.603,95%CI:1.288-1.994,P≤0.001],the preoperative neutrophil-to-lymphocyte ratio(NLR)(OR=1.495,95%CI:1.126-1.984,P=0.005),and the albumin-bilirubin(ALBI)score(OR=8.868,95%CI:2.144-36.678,P=0.003)were independent risk factors for PHLF.A nomogram prediction model was developed using these factors.ROC and DCA analyses revealed that the predictive efficacy and clinical value of this model were better than those of traditional models.CONCLUSION A new Nomogram model for predicting PHLF in HCC patients was successfully established based on portal vein width,the NLR,and the ALBI score,which outperforms the traditional model.
