Chao Chen, Xiaoyuan Chu, Hong Liu, Mingzhen Zhou, Zhan Shi, Anfeng Si, Ying Zhao, Xiufeng Liu, Jie Shen, Baorui Liu
{"title":"预测免疫检查点抑制剂治疗后肝细胞癌患者预后的新提名图:一项基于中国人群的单中心研究。","authors":"Chao Chen, Xiaoyuan Chu, Hong Liu, Mingzhen Zhou, Zhan Shi, Anfeng Si, Ying Zhao, Xiufeng Liu, Jie Shen, Baorui Liu","doi":"10.21037/hbsn-23-646","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) persists as a dominant cause of cancer-related mortality globally, with a notably rapid escalation in mortality rates. The advent of immunotherapy, particularly immune checkpoint inhibitors (ICIs), has ushered in a new era in the management of liver cancer, albeit with unresolved challenges in the context of treatment beyond progression (TBP) and stratified prognosis in diverse populations. This study aimed to develop and validate a novel nomogram model to identify factors that predict the benefit of continued immunotherapy for hepatocellular carcinoma patients following disease progression in clinical practice.</p><p><strong>Methods: </strong>This study retrospectively analyzed the efficacy of ICIs in TBP, focusing on the Chinese population with advanced liver cancer. A nomogram was constructed based on four independent risk factors identified through Cox multivariate analysis, aiming to predict patient prognosis post-ICI treatment. The model was validated through receiver operating characteristic (ROC) curve analysis and categorized patients into high-, intermediate-, and low-risk groups, with further validation using calibration plots and decision curve analysis (DCA).</p><p><strong>Results: </strong>The low-risk group demonstrated significantly enhanced overall survival (OS) compared to the high-risk group, with the nomogram predictions aligning closely with actual outcomes for 6- and 9-month OS. The model exhibited commendable predictive accuracy, achieving a C-index exceeding 0.7 in both training and validation datasets. The DCA underscored the clinical utility of the nomogram-based prognostic model, further substantiated by the area under the ROC curve (AUC).</p><p><strong>Conclusions: </strong>The developed nomogram presents a potentially valuable tool for predicting the prognosis of HCC patients undergoing ICI therapy beyond progression, particularly within the Chinese demographic. However, the study is constrained by its retrospective, single-center nature and necessitates further validation through large-scale, multicenter clinical studies across varied populations.</p>","PeriodicalId":12878,"journal":{"name":"Hepatobiliary surgery and nutrition","volume":"13 5","pages":"771-787"},"PeriodicalIF":6.1000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534779/pdf/","citationCount":"0","resultStr":"{\"title\":\"A novel nomogram for predicting the prognosis of hepatocellular carcinoma patients following immune checkpoint inhibitors treatment beyond progression: a single center study based on Chinese population.\",\"authors\":\"Chao Chen, Xiaoyuan Chu, Hong Liu, Mingzhen Zhou, Zhan Shi, Anfeng Si, Ying Zhao, Xiufeng Liu, Jie Shen, Baorui Liu\",\"doi\":\"10.21037/hbsn-23-646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) persists as a dominant cause of cancer-related mortality globally, with a notably rapid escalation in mortality rates. The advent of immunotherapy, particularly immune checkpoint inhibitors (ICIs), has ushered in a new era in the management of liver cancer, albeit with unresolved challenges in the context of treatment beyond progression (TBP) and stratified prognosis in diverse populations. This study aimed to develop and validate a novel nomogram model to identify factors that predict the benefit of continued immunotherapy for hepatocellular carcinoma patients following disease progression in clinical practice.</p><p><strong>Methods: </strong>This study retrospectively analyzed the efficacy of ICIs in TBP, focusing on the Chinese population with advanced liver cancer. A nomogram was constructed based on four independent risk factors identified through Cox multivariate analysis, aiming to predict patient prognosis post-ICI treatment. The model was validated through receiver operating characteristic (ROC) curve analysis and categorized patients into high-, intermediate-, and low-risk groups, with further validation using calibration plots and decision curve analysis (DCA).</p><p><strong>Results: </strong>The low-risk group demonstrated significantly enhanced overall survival (OS) compared to the high-risk group, with the nomogram predictions aligning closely with actual outcomes for 6- and 9-month OS. The model exhibited commendable predictive accuracy, achieving a C-index exceeding 0.7 in both training and validation datasets. The DCA underscored the clinical utility of the nomogram-based prognostic model, further substantiated by the area under the ROC curve (AUC).</p><p><strong>Conclusions: </strong>The developed nomogram presents a potentially valuable tool for predicting the prognosis of HCC patients undergoing ICI therapy beyond progression, particularly within the Chinese demographic. However, the study is constrained by its retrospective, single-center nature and necessitates further validation through large-scale, multicenter clinical studies across varied populations.</p>\",\"PeriodicalId\":12878,\"journal\":{\"name\":\"Hepatobiliary surgery and nutrition\",\"volume\":\"13 5\",\"pages\":\"771-787\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534779/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hepatobiliary surgery and nutrition\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21037/hbsn-23-646\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/5/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hepatobiliary surgery and nutrition","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/hbsn-23-646","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/28 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
A novel nomogram for predicting the prognosis of hepatocellular carcinoma patients following immune checkpoint inhibitors treatment beyond progression: a single center study based on Chinese population.
Background: Hepatocellular carcinoma (HCC) persists as a dominant cause of cancer-related mortality globally, with a notably rapid escalation in mortality rates. The advent of immunotherapy, particularly immune checkpoint inhibitors (ICIs), has ushered in a new era in the management of liver cancer, albeit with unresolved challenges in the context of treatment beyond progression (TBP) and stratified prognosis in diverse populations. This study aimed to develop and validate a novel nomogram model to identify factors that predict the benefit of continued immunotherapy for hepatocellular carcinoma patients following disease progression in clinical practice.
Methods: This study retrospectively analyzed the efficacy of ICIs in TBP, focusing on the Chinese population with advanced liver cancer. A nomogram was constructed based on four independent risk factors identified through Cox multivariate analysis, aiming to predict patient prognosis post-ICI treatment. The model was validated through receiver operating characteristic (ROC) curve analysis and categorized patients into high-, intermediate-, and low-risk groups, with further validation using calibration plots and decision curve analysis (DCA).
Results: The low-risk group demonstrated significantly enhanced overall survival (OS) compared to the high-risk group, with the nomogram predictions aligning closely with actual outcomes for 6- and 9-month OS. The model exhibited commendable predictive accuracy, achieving a C-index exceeding 0.7 in both training and validation datasets. The DCA underscored the clinical utility of the nomogram-based prognostic model, further substantiated by the area under the ROC curve (AUC).
Conclusions: The developed nomogram presents a potentially valuable tool for predicting the prognosis of HCC patients undergoing ICI therapy beyond progression, particularly within the Chinese demographic. However, the study is constrained by its retrospective, single-center nature and necessitates further validation through large-scale, multicenter clinical studies across varied populations.
期刊介绍:
Hepatobiliary Surgery and Nutrition (HBSN) is a bi-monthly, open-access, peer-reviewed journal (Print ISSN: 2304-3881; Online ISSN: 2304-389X) since December 2012. The journal focuses on hepatopancreatobiliary disease and nutrition, aiming to present new findings and deliver up-to-date, practical information on diagnosis, prevention, and clinical investigations. Areas of interest cover surgical techniques, clinical and basic research, transplantation, therapies, NASH, NAFLD, targeted drugs, gut microbiota, metabolism, cancer immunity, genomics, and nutrition and dietetics. HBSN serves as a valuable resource for professionals seeking insights into diverse aspects of hepatobiliary surgery and nutrition.