Objective:To develop a survival prediction model for primary conjunctival malignant tumors.Methods:Detailed information on cases diagnosed with primary conjunctival malignant tumors from 2000 to 2019 was collected fro...Objective:To develop a survival prediction model for primary conjunctival malignant tumors.Methods:Detailed information on cases diagnosed with primary conjunctival malignant tumors from 2000 to 2019 was collected from SEER database.Subsequently,cases meeting the inclusion criteria were randomly assigned to either the development group(1,216 cases)or validation group(608 cases).Relevant risk factors affecting overall survival(OS)were identified using Cox proportional hazards regression analysis.A nomogram was constructed to predict the 1-year,3-year,and 5-year survival rates.The concordance index(C index)was calculated to assess the predictive power of the model.Receiver operating characteristic curves(ROC curves)and calibration curves were plotted.The area under the curve(AUC)was measured.Decision curve analysis(DCA)was also applied.Results:The overall survival rate was 77.8%.Statistically significant differences in the survival time distribution were observed among groups based on age(P<0.001),histology(P<0.001),and stage(P=0.01).According to the multivariate analysis,patients with lymphoma,younger age,and localized lesions exhibited better survival outcomes.The C-index of the constructed model was 0.79.In the training group,the AUC values for predicting 1-year,3-year,and 5-year mortality were 0.824,0.796,and 0.815,respectively.In the validation group,age corresponding AU values were 0.750,0.820,and 0.838.The DCA results demonstrated a significant advantage of the model,while the calibration plots indicated that the predicted OS was in good agreement with the actual OS in both groups.Conclusions:This study presents a satisfying survival prediction model for malignant conjunctival tumors.展开更多
BACKGROUND Colon adenocarcinoma(COAD)ranks second in terms of cancer-related deaths.We found that fatty acid-binding protein 4(FABP4),which is related to cell adhesion and immunity,affects the occurrence and developme...BACKGROUND Colon adenocarcinoma(COAD)ranks second in terms of cancer-related deaths.We found that fatty acid-binding protein 4(FABP4),which is related to cell adhesion and immunity,affects the occurrence and development of COAD.This study focused on the possibility of using FABP4 as a biomarker for COAD and constructed a nomogram for predicting the survival of COAD patients.AIM To verify the possibility of using FABP4 as a biomarker for COAD.METHODS A total of 453 COAD tissue samples,along with 41 normal tissue samples,were obtained from The Cancer Genome Atlas database.The difference in FABP4 expression between COAD tissues and normal tissues was analyzed,and the results were verified by immunohistochemistry.The WGCNA algorithm links FABP4 expression with an enrichment analysis and with immune cell infiltration pathways.The biological functions of FABP4 and its coexpressed genes were explored through enrichment analyses.The ESTIMATE,CIBERSORT and ssGSEA methods were used for the immune infiltration analysis.Finally,risk scores were calculated by a Cox analysis.A nomogram was constructed by combining risk scores with routine clinicopathological factors.We assessed the accuracy of survival predictions based on the C-index.The C-index ranges from 0.5 to 1.0,and in general,a C-index value greater than 0.65 indicates a reasonable estimate.The results were validated using the Gene Expression Omnibus(GEO)database.RESULTS FABP4 was significantly differentially expressed in COAD.It is a promising auxiliary biomarker for screening and diagnosis.Enrichment analyses suggested that FABP4 may influence the invasion and progression of COAD through cell adhesion.The immunological analysis revealed that FABP4 expression in COAD was significantly positively correlated with immune cell infiltration.Moreover,a nomogram to predict the survival of COAD patients was successfully constructed by integrating the calculated risk scores of 15 candidate genes and routine clinicopathological factors.This nomogram could effectively predict 1-year,3-year,and 5-year survival(C-index=0.786)and was verified(C-index=0.73).CONCLUSION This study established FABP4 as an effective biomarker for screening,assisting in the diagnosis and determining the prognosis.展开更多
Background:Few studies have shown nomograms that may predict disease-specific survival(DSS)probability after curative D2 gastrectomy for advanced gastric cancer(AGC),particularly among Chinese patients.This study soug...Background:Few studies have shown nomograms that may predict disease-specific survival(DSS)probability after curative D2 gastrectomy for advanced gastric cancer(AGC),particularly among Chinese patients.This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese patients.Methods:A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1,2000 and December 31,2012 from three large medical hospitals in China.We assigned patients from Sun Yat-sen University Cancer Center to the training set,and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets.A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set,and a nomogram was constructed.Harrell’s C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation sets.Results:The multivariate Cox regression model identified age,tumor size,location,Lauren classification,lymphatic/venous invasion,depth of invasion,and metastatic lymph node ratio as covariates associated with survival.In the training set,the nomogram exhibited superior discrimination power compared with the 8th American Joint Com-mittee on Cancer TNM classification(Harrell’s C-index,0.82 vs.0.74;P<0.001).In two validation sets,the nomogram’s discrimination power was also excellent relative to TNM classification(C-index,0.83 vs.0.75 and 0.81 vs.0.74,respec-tively;P<0.001 for both).After calibration,the nomogram produced survival predictions that corresponded closely with actual survival rate.Conclusions:The established nomogram was able to predict 3-,5-,and 10-year DSS probabilities for AGC patients.Validation revealed that this nomogram exhibited excellent discrimination and calibration capacity,suggesting its clinical utility.展开更多
文摘Objective:To develop a survival prediction model for primary conjunctival malignant tumors.Methods:Detailed information on cases diagnosed with primary conjunctival malignant tumors from 2000 to 2019 was collected from SEER database.Subsequently,cases meeting the inclusion criteria were randomly assigned to either the development group(1,216 cases)or validation group(608 cases).Relevant risk factors affecting overall survival(OS)were identified using Cox proportional hazards regression analysis.A nomogram was constructed to predict the 1-year,3-year,and 5-year survival rates.The concordance index(C index)was calculated to assess the predictive power of the model.Receiver operating characteristic curves(ROC curves)and calibration curves were plotted.The area under the curve(AUC)was measured.Decision curve analysis(DCA)was also applied.Results:The overall survival rate was 77.8%.Statistically significant differences in the survival time distribution were observed among groups based on age(P<0.001),histology(P<0.001),and stage(P=0.01).According to the multivariate analysis,patients with lymphoma,younger age,and localized lesions exhibited better survival outcomes.The C-index of the constructed model was 0.79.In the training group,the AUC values for predicting 1-year,3-year,and 5-year mortality were 0.824,0.796,and 0.815,respectively.In the validation group,age corresponding AU values were 0.750,0.820,and 0.838.The DCA results demonstrated a significant advantage of the model,while the calibration plots indicated that the predicted OS was in good agreement with the actual OS in both groups.Conclusions:This study presents a satisfying survival prediction model for malignant conjunctival tumors.
基金Supported by the University Scientific Research Project of Anhui Province,No.2024AH051916the Quality Engineering Project of Anhui Province,No.2022sx159 and No.2022sdxx031the Key Research and Development Project of Anhui Province,No.2022e07020036.
文摘BACKGROUND Colon adenocarcinoma(COAD)ranks second in terms of cancer-related deaths.We found that fatty acid-binding protein 4(FABP4),which is related to cell adhesion and immunity,affects the occurrence and development of COAD.This study focused on the possibility of using FABP4 as a biomarker for COAD and constructed a nomogram for predicting the survival of COAD patients.AIM To verify the possibility of using FABP4 as a biomarker for COAD.METHODS A total of 453 COAD tissue samples,along with 41 normal tissue samples,were obtained from The Cancer Genome Atlas database.The difference in FABP4 expression between COAD tissues and normal tissues was analyzed,and the results were verified by immunohistochemistry.The WGCNA algorithm links FABP4 expression with an enrichment analysis and with immune cell infiltration pathways.The biological functions of FABP4 and its coexpressed genes were explored through enrichment analyses.The ESTIMATE,CIBERSORT and ssGSEA methods were used for the immune infiltration analysis.Finally,risk scores were calculated by a Cox analysis.A nomogram was constructed by combining risk scores with routine clinicopathological factors.We assessed the accuracy of survival predictions based on the C-index.The C-index ranges from 0.5 to 1.0,and in general,a C-index value greater than 0.65 indicates a reasonable estimate.The results were validated using the Gene Expression Omnibus(GEO)database.RESULTS FABP4 was significantly differentially expressed in COAD.It is a promising auxiliary biomarker for screening and diagnosis.Enrichment analyses suggested that FABP4 may influence the invasion and progression of COAD through cell adhesion.The immunological analysis revealed that FABP4 expression in COAD was significantly positively correlated with immune cell infiltration.Moreover,a nomogram to predict the survival of COAD patients was successfully constructed by integrating the calculated risk scores of 15 candidate genes and routine clinicopathological factors.This nomogram could effectively predict 1-year,3-year,and 5-year survival(C-index=0.786)and was verified(C-index=0.73).CONCLUSION This study established FABP4 as an effective biomarker for screening,assisting in the diagnosis and determining the prognosis.
基金supported by the Natural Science Foundation of Guangdong Province(No.2015A030313089)the Major Program of Collaborative Innovation of Guangzhou(No.201508030042).
文摘Background:Few studies have shown nomograms that may predict disease-specific survival(DSS)probability after curative D2 gastrectomy for advanced gastric cancer(AGC),particularly among Chinese patients.This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese patients.Methods:A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1,2000 and December 31,2012 from three large medical hospitals in China.We assigned patients from Sun Yat-sen University Cancer Center to the training set,and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets.A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set,and a nomogram was constructed.Harrell’s C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation sets.Results:The multivariate Cox regression model identified age,tumor size,location,Lauren classification,lymphatic/venous invasion,depth of invasion,and metastatic lymph node ratio as covariates associated with survival.In the training set,the nomogram exhibited superior discrimination power compared with the 8th American Joint Com-mittee on Cancer TNM classification(Harrell’s C-index,0.82 vs.0.74;P<0.001).In two validation sets,the nomogram’s discrimination power was also excellent relative to TNM classification(C-index,0.83 vs.0.75 and 0.81 vs.0.74,respec-tively;P<0.001 for both).After calibration,the nomogram produced survival predictions that corresponded closely with actual survival rate.Conclusions:The established nomogram was able to predict 3-,5-,and 10-year DSS probabilities for AGC patients.Validation revealed that this nomogram exhibited excellent discrimination and calibration capacity,suggesting its clinical utility.
