Ziqiang Li, Qingyong Hong, Zhizhan Ni, Zhidong Guo, Qimeng Shi, Xianqing Wang, Qi Huang, Kun Li, Bujun Ge
{"title":"一种预测小分离肝细胞癌患者生存的新Nomogram:一项基于人群的外部验证研究。","authors":"Ziqiang Li, Qingyong Hong, Zhizhan Ni, Zhidong Guo, Qimeng Shi, Xianqing Wang, Qi Huang, Kun Li, Bujun Ge","doi":"10.1080/08941939.2025.2536627","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Current prognostic tools lack precision for small hepatocellular carcinoma (HCC) (≤5 cm) and fail to capture tumor heterogeneity. This study aimed to construct a nomogram to predict survival in patients with isolated small HCC.</p><p><strong>Methods: </strong>A total of 5187 eligible patients from the SEER database were randomized into training and internal validation cohorts, while 180 patients from Zhongnan Hospital of Wuhan University served as an external validation cohort. Cox regression analysis identified factors affecting cancer-specific survival (CSS), which were used to construct the nomogram. Performance was evaluated using the consistency index (C-index), area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Finally, we used Kaplan-Meier curves for survival analysis.</p><p><strong>Results: </strong>We identified eleven independent risk factors influencing CSS in isolated small HCC patients. In the training, internal validation, and external validation cohort, the C-index of the nomogram was 0.702, 0.717, and 0.729, respectively. AUC, calibration curves, and DCA curves showed good predictive accuracy and clinical utility. Kaplan-Meier curves revealed significant CSS differences between high- and low-risk groups. Additionally, we developed an online prediction tool.</p><p><strong>Conclusions: </strong>The nomogram effectively predicts CSS in isolated small HCC patients and may aid in individualized clinical decision-making.</p>","PeriodicalId":16200,"journal":{"name":"Journal of Investigative Surgery","volume":"38 1","pages":"2536627"},"PeriodicalIF":3.5000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Nomogram for Prediction of Survival in Patients with Small Isolated Hepatocellular Carcinoma: A Population-Based and Externally Validated Study.\",\"authors\":\"Ziqiang Li, Qingyong Hong, Zhizhan Ni, Zhidong Guo, Qimeng Shi, Xianqing Wang, Qi Huang, Kun Li, Bujun Ge\",\"doi\":\"10.1080/08941939.2025.2536627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Current prognostic tools lack precision for small hepatocellular carcinoma (HCC) (≤5 cm) and fail to capture tumor heterogeneity. This study aimed to construct a nomogram to predict survival in patients with isolated small HCC.</p><p><strong>Methods: </strong>A total of 5187 eligible patients from the SEER database were randomized into training and internal validation cohorts, while 180 patients from Zhongnan Hospital of Wuhan University served as an external validation cohort. Cox regression analysis identified factors affecting cancer-specific survival (CSS), which were used to construct the nomogram. Performance was evaluated using the consistency index (C-index), area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Finally, we used Kaplan-Meier curves for survival analysis.</p><p><strong>Results: </strong>We identified eleven independent risk factors influencing CSS in isolated small HCC patients. In the training, internal validation, and external validation cohort, the C-index of the nomogram was 0.702, 0.717, and 0.729, respectively. AUC, calibration curves, and DCA curves showed good predictive accuracy and clinical utility. Kaplan-Meier curves revealed significant CSS differences between high- and low-risk groups. Additionally, we developed an online prediction tool.</p><p><strong>Conclusions: </strong>The nomogram effectively predicts CSS in isolated small HCC patients and may aid in individualized clinical decision-making.</p>\",\"PeriodicalId\":16200,\"journal\":{\"name\":\"Journal of Investigative Surgery\",\"volume\":\"38 1\",\"pages\":\"2536627\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Investigative Surgery\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/08941939.2025.2536627\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/29 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Investigative Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/08941939.2025.2536627","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/29 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
A Novel Nomogram for Prediction of Survival in Patients with Small Isolated Hepatocellular Carcinoma: A Population-Based and Externally Validated Study.
Background: Current prognostic tools lack precision for small hepatocellular carcinoma (HCC) (≤5 cm) and fail to capture tumor heterogeneity. This study aimed to construct a nomogram to predict survival in patients with isolated small HCC.
Methods: A total of 5187 eligible patients from the SEER database were randomized into training and internal validation cohorts, while 180 patients from Zhongnan Hospital of Wuhan University served as an external validation cohort. Cox regression analysis identified factors affecting cancer-specific survival (CSS), which were used to construct the nomogram. Performance was evaluated using the consistency index (C-index), area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Finally, we used Kaplan-Meier curves for survival analysis.
Results: We identified eleven independent risk factors influencing CSS in isolated small HCC patients. In the training, internal validation, and external validation cohort, the C-index of the nomogram was 0.702, 0.717, and 0.729, respectively. AUC, calibration curves, and DCA curves showed good predictive accuracy and clinical utility. Kaplan-Meier curves revealed significant CSS differences between high- and low-risk groups. Additionally, we developed an online prediction tool.
Conclusions: The nomogram effectively predicts CSS in isolated small HCC patients and may aid in individualized clinical decision-making.
期刊介绍:
Journal of Investigative Surgery publishes peer-reviewed scientific articles for the advancement of surgery, to the ultimate benefit of patient care and rehabilitation. It is the only journal that encompasses the individual and collaborative efforts of scientists in human and veterinary medicine, dentistry, basic and applied sciences, engineering, and law and ethics. The journal is dedicated to the publication of outstanding articles of interest to the surgical research community.