Rongqiang Liu, Chenxuan Zhang, Yankun Shen, Jianguo Wang, Jing Ye, Jia Yu, Weixing Wang
{"title":"一种新的胆囊癌患者预后图的建立和验证。","authors":"Rongqiang Liu, Chenxuan Zhang, Yankun Shen, Jianguo Wang, Jing Ye, Jia Yu, Weixing Wang","doi":"10.1186/s40001-025-02513-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Gallbladder cancer (GBC) arises from the malignant transformation of epithelial cells that line the gallbladder mucosa. The likelihood of developing GBC escalates with advancing age, and the condition generally presents a dismal prognosis. Despite this, there is a limited amount of research focusing on the prognostic determinants linked to GBC. As a result, this study sought to create a nomogram for evaluating GBC prognostic factors.</p><p><strong>Methods: </strong>In this investigation, a total of 8,615 cases of GBC from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2000 to 2020 were collected. In a 7:3 ratio, these instances were randomly assigned to one of two groups: training or internal validation. To assess the impact of clinical variables on overall survival (OS) in patients with GBC, both univariate and multivariate Cox regression analyses were utilized. The clinical criteria established were used to develop a nomogram. The effectiveness of the nomogram was evaluated through several approaches, such as receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, and Kaplan-Meier (KM) analysis.</p><p><strong>Results: </strong>To predict the prognosis of GBC patients, a nomogram was created based on the following criteria: sex, rural-urban continuum, marital status, nodes, histology, radiation, chemotherapy, metastasis, age, surgery, and grade. The training set had an area under the curve for 1-year, 3-year, and 5-year OS of 0.79, 0.78, and 0.78, respectively. The DCA curves demonstrated that the model was clinically useful and well-corrected. Patients with GBC were categorized into high-risk and low-risk groups based on the median risk score. KM curves revealed a significantly lower survival rate for the high-risk group in comparison with the low-risk group (P < 0.001).</p><p><strong>Conclusions: </strong>Our model demonstrated strong predictive capabilities for the prognosis of GBC patients, thereby aiding in the refinement of treatment strategies for these individuals.</p>","PeriodicalId":11949,"journal":{"name":"European Journal of Medical Research","volume":"30 1","pages":"331"},"PeriodicalIF":2.8000,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12032734/pdf/","citationCount":"0","resultStr":"{\"title\":\"Establishment and validation of a novel prognostic nomogram for gallbladder cancer patients.\",\"authors\":\"Rongqiang Liu, Chenxuan Zhang, Yankun Shen, Jianguo Wang, Jing Ye, Jia Yu, Weixing Wang\",\"doi\":\"10.1186/s40001-025-02513-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Gallbladder cancer (GBC) arises from the malignant transformation of epithelial cells that line the gallbladder mucosa. The likelihood of developing GBC escalates with advancing age, and the condition generally presents a dismal prognosis. Despite this, there is a limited amount of research focusing on the prognostic determinants linked to GBC. As a result, this study sought to create a nomogram for evaluating GBC prognostic factors.</p><p><strong>Methods: </strong>In this investigation, a total of 8,615 cases of GBC from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2000 to 2020 were collected. In a 7:3 ratio, these instances were randomly assigned to one of two groups: training or internal validation. To assess the impact of clinical variables on overall survival (OS) in patients with GBC, both univariate and multivariate Cox regression analyses were utilized. The clinical criteria established were used to develop a nomogram. The effectiveness of the nomogram was evaluated through several approaches, such as receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, and Kaplan-Meier (KM) analysis.</p><p><strong>Results: </strong>To predict the prognosis of GBC patients, a nomogram was created based on the following criteria: sex, rural-urban continuum, marital status, nodes, histology, radiation, chemotherapy, metastasis, age, surgery, and grade. The training set had an area under the curve for 1-year, 3-year, and 5-year OS of 0.79, 0.78, and 0.78, respectively. The DCA curves demonstrated that the model was clinically useful and well-corrected. Patients with GBC were categorized into high-risk and low-risk groups based on the median risk score. KM curves revealed a significantly lower survival rate for the high-risk group in comparison with the low-risk group (P < 0.001).</p><p><strong>Conclusions: </strong>Our model demonstrated strong predictive capabilities for the prognosis of GBC patients, thereby aiding in the refinement of treatment strategies for these individuals.</p>\",\"PeriodicalId\":11949,\"journal\":{\"name\":\"European Journal of Medical Research\",\"volume\":\"30 1\",\"pages\":\"331\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12032734/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Medical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40001-025-02513-7\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Medical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40001-025-02513-7","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Establishment and validation of a novel prognostic nomogram for gallbladder cancer patients.
Background: Gallbladder cancer (GBC) arises from the malignant transformation of epithelial cells that line the gallbladder mucosa. The likelihood of developing GBC escalates with advancing age, and the condition generally presents a dismal prognosis. Despite this, there is a limited amount of research focusing on the prognostic determinants linked to GBC. As a result, this study sought to create a nomogram for evaluating GBC prognostic factors.
Methods: In this investigation, a total of 8,615 cases of GBC from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2000 to 2020 were collected. In a 7:3 ratio, these instances were randomly assigned to one of two groups: training or internal validation. To assess the impact of clinical variables on overall survival (OS) in patients with GBC, both univariate and multivariate Cox regression analyses were utilized. The clinical criteria established were used to develop a nomogram. The effectiveness of the nomogram was evaluated through several approaches, such as receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, and Kaplan-Meier (KM) analysis.
Results: To predict the prognosis of GBC patients, a nomogram was created based on the following criteria: sex, rural-urban continuum, marital status, nodes, histology, radiation, chemotherapy, metastasis, age, surgery, and grade. The training set had an area under the curve for 1-year, 3-year, and 5-year OS of 0.79, 0.78, and 0.78, respectively. The DCA curves demonstrated that the model was clinically useful and well-corrected. Patients with GBC were categorized into high-risk and low-risk groups based on the median risk score. KM curves revealed a significantly lower survival rate for the high-risk group in comparison with the low-risk group (P < 0.001).
Conclusions: Our model demonstrated strong predictive capabilities for the prognosis of GBC patients, thereby aiding in the refinement of treatment strategies for these individuals.
期刊介绍:
European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.