{"title":"胆囊癌根治性切除术患者预后的风险因素和生存预测模型的建立。","authors":"Xing-Fei Li, Tan-Tu Ma, Tao Li","doi":"10.4240/wjgs.v16.i10.3239","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Gallbladder cancer (GBC) is the most common malignant tumor of the biliary system, and is often undetected until advanced stages, making curative surgery unfeasible for many patients. Curative surgery remains the only option for long-term survival. Accurate postsurgical prognosis is crucial for effective treatment planning. tumor-node-metastasis staging, which focuses on tumor infiltration, lymph node metastasis, and distant metastasis, limits the accuracy of prognosis. Nomograms offer a more comprehensive and personalized approach by visually analyzing a broader range of prognostic factors, enhancing the precision of treatment planning for patients with GBC.</p><p><strong>Aim: </strong>To identify risk factors and develop a predictive model for GBC prognosis.</p><p><strong>Methods: </strong>A retrospective study analyzed the clinical and pathological data of 93 patients who underwent radical surgery for GBC at Peking University People's Hospital from January 2015 to December 2020. Kaplan-Meier analysis was used to calculate the 1-, 2- and 3-year survival rates. The log-rank test was used to evaluate factors impacting prognosis, with survival curves plotted for significant variables. Single-factor analysis revealed statistically significant differences, and multivariate Cox regression identified independent prognostic factors. A nomogram was developed and validated with receiver operating characteristic curves and calibration curves.</p><p><strong>Results: </strong>Among 93 patients who underwent radical surgery for GBC, 30 patients survived, accounting for 32.26% of the sample, with a median survival time of 38 months. The 1-year, 2-year, and 3-year survival rates were 83.87%, 68.82%, and 53.57%, respectively. Univariate analysis revealed that carbohydrate antigen 19-9 expression, T stage, lymph node metastasis, histological differentiation, surgical margins, and invasion of the liver, extrahepatic bile duct, nerves, and vessels (<i>P</i> ≤ 0.001) significantly impacted patient prognosis after curative surgery. Multivariate Cox regression identified lymph node metastasis (<i>P</i> = 0.03), histological differentiation (<i>P</i> < 0.05), nerve invasion (<i>P</i> = 0.036), and extrahepatic bile duct invasion (<i>P</i> = 0.014) as independent risk factors. A nomogram model with a concordance index of 0.838 was developed. Internal validation confirmed the model's consistency in predicting the 1-year, 2-year, and 3-year survival rates.</p><p><strong>Conclusion: </strong>Lymph node metastasis, tumor differentiation, extrahepatic bile duct invasion, and perineural invasion are independent risk factors. A nomogram based on these factors can be used to personalize and improve treatment strategies.</p>","PeriodicalId":23759,"journal":{"name":"World Journal of Gastrointestinal Surgery","volume":"16 10","pages":"3239-3252"},"PeriodicalIF":1.8000,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11577418/pdf/","citationCount":"0","resultStr":"{\"title\":\"Risk factors and survival prediction model establishment for prognosis in patients with radical resection of gallbladder cancer.\",\"authors\":\"Xing-Fei Li, Tan-Tu Ma, Tao Li\",\"doi\":\"10.4240/wjgs.v16.i10.3239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Gallbladder cancer (GBC) is the most common malignant tumor of the biliary system, and is often undetected until advanced stages, making curative surgery unfeasible for many patients. Curative surgery remains the only option for long-term survival. Accurate postsurgical prognosis is crucial for effective treatment planning. tumor-node-metastasis staging, which focuses on tumor infiltration, lymph node metastasis, and distant metastasis, limits the accuracy of prognosis. Nomograms offer a more comprehensive and personalized approach by visually analyzing a broader range of prognostic factors, enhancing the precision of treatment planning for patients with GBC.</p><p><strong>Aim: </strong>To identify risk factors and develop a predictive model for GBC prognosis.</p><p><strong>Methods: </strong>A retrospective study analyzed the clinical and pathological data of 93 patients who underwent radical surgery for GBC at Peking University People's Hospital from January 2015 to December 2020. Kaplan-Meier analysis was used to calculate the 1-, 2- and 3-year survival rates. The log-rank test was used to evaluate factors impacting prognosis, with survival curves plotted for significant variables. Single-factor analysis revealed statistically significant differences, and multivariate Cox regression identified independent prognostic factors. A nomogram was developed and validated with receiver operating characteristic curves and calibration curves.</p><p><strong>Results: </strong>Among 93 patients who underwent radical surgery for GBC, 30 patients survived, accounting for 32.26% of the sample, with a median survival time of 38 months. The 1-year, 2-year, and 3-year survival rates were 83.87%, 68.82%, and 53.57%, respectively. Univariate analysis revealed that carbohydrate antigen 19-9 expression, T stage, lymph node metastasis, histological differentiation, surgical margins, and invasion of the liver, extrahepatic bile duct, nerves, and vessels (<i>P</i> ≤ 0.001) significantly impacted patient prognosis after curative surgery. Multivariate Cox regression identified lymph node metastasis (<i>P</i> = 0.03), histological differentiation (<i>P</i> < 0.05), nerve invasion (<i>P</i> = 0.036), and extrahepatic bile duct invasion (<i>P</i> = 0.014) as independent risk factors. A nomogram model with a concordance index of 0.838 was developed. Internal validation confirmed the model's consistency in predicting the 1-year, 2-year, and 3-year survival rates.</p><p><strong>Conclusion: </strong>Lymph node metastasis, tumor differentiation, extrahepatic bile duct invasion, and perineural invasion are independent risk factors. A nomogram based on these factors can be used to personalize and improve treatment strategies.</p>\",\"PeriodicalId\":23759,\"journal\":{\"name\":\"World Journal of Gastrointestinal Surgery\",\"volume\":\"16 10\",\"pages\":\"3239-3252\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11577418/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"World Journal of Gastrointestinal Surgery\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4240/wjgs.v16.i10.3239\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Journal of Gastrointestinal Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4240/wjgs.v16.i10.3239","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Risk factors and survival prediction model establishment for prognosis in patients with radical resection of gallbladder cancer.
Background: Gallbladder cancer (GBC) is the most common malignant tumor of the biliary system, and is often undetected until advanced stages, making curative surgery unfeasible for many patients. Curative surgery remains the only option for long-term survival. Accurate postsurgical prognosis is crucial for effective treatment planning. tumor-node-metastasis staging, which focuses on tumor infiltration, lymph node metastasis, and distant metastasis, limits the accuracy of prognosis. Nomograms offer a more comprehensive and personalized approach by visually analyzing a broader range of prognostic factors, enhancing the precision of treatment planning for patients with GBC.
Aim: To identify risk factors and develop a predictive model for GBC prognosis.
Methods: A retrospective study analyzed the clinical and pathological data of 93 patients who underwent radical surgery for GBC at Peking University People's Hospital from January 2015 to December 2020. Kaplan-Meier analysis was used to calculate the 1-, 2- and 3-year survival rates. The log-rank test was used to evaluate factors impacting prognosis, with survival curves plotted for significant variables. Single-factor analysis revealed statistically significant differences, and multivariate Cox regression identified independent prognostic factors. A nomogram was developed and validated with receiver operating characteristic curves and calibration curves.
Results: Among 93 patients who underwent radical surgery for GBC, 30 patients survived, accounting for 32.26% of the sample, with a median survival time of 38 months. The 1-year, 2-year, and 3-year survival rates were 83.87%, 68.82%, and 53.57%, respectively. Univariate analysis revealed that carbohydrate antigen 19-9 expression, T stage, lymph node metastasis, histological differentiation, surgical margins, and invasion of the liver, extrahepatic bile duct, nerves, and vessels (P ≤ 0.001) significantly impacted patient prognosis after curative surgery. Multivariate Cox regression identified lymph node metastasis (P = 0.03), histological differentiation (P < 0.05), nerve invasion (P = 0.036), and extrahepatic bile duct invasion (P = 0.014) as independent risk factors. A nomogram model with a concordance index of 0.838 was developed. Internal validation confirmed the model's consistency in predicting the 1-year, 2-year, and 3-year survival rates.
Conclusion: Lymph node metastasis, tumor differentiation, extrahepatic bile duct invasion, and perineural invasion are independent risk factors. A nomogram based on these factors can be used to personalize and improve treatment strategies.