{"title":"全身免疫炎症指数对不可切除肝癌患者免疫治疗的预后价值。","authors":"Tian He, Bin Xu, Lu-Na Wang, Zi-Yi Wang, Huan-Chen Shi, Cheng-Jie Zhong, Xiao-Dong Zhu, Ying-Hao Shen, Jian Zhou, Jia Fan, Hui-Chuan Sun, Bo Hu, Cheng Huang","doi":"10.1186/s40364-024-00722-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Predicting the efficacy of immune-based therapy in patients with unresectable hepatocellular carcinoma (HCC) remains a clinical challenge. This study aims to evaluate the prognostic value of the systemic immune-inflammation index (SII) in forecasting treatment response and survival outcomes for HCC patients undergoing immune-based therapy.</p><p><strong>Methods: </strong>We analyzed a cohort of 268 HCC patients treated with immune-based therapy from January 2019 to March 2023. A training cohort of 93 patients received atezolizumab plus bevacizumab (T + A), while a validation cohort of 175 patients underwent treatment with tyrosine kinase inhibitors (TKIs) combined with anti-PD-(L)1 therapy. The SII cutoff value, determined using X-tile analysis based on overall survival (OS) in the training cohort, divided patients into high (> 752*10<sup>9</sup>) and low (≤ 752*10<sup>9</sup>) SII groups. Prognostic factors were identified through univariate and multivariate logistic and Cox regression analyses, and survival outcomes were assessed using Kaplan-Meier methods. The predictive accuracy of SII was evaluated using receiver operating characteristic (ROC) curves.</p><p><strong>Results: </strong>An optimal SII cutoff of 752*10<sup>9</sup> stratified patients into high and low SII groups. Univariate and multivariate logistic regression indicated that SII was a significant predictor of the objective response rate (ORR), which was markedly different between the low and high SII subgroups (34.72% vs. 9.52%, P = 0.019). This finding was consistent in the validation cohort (34.09% vs. 16.28%, P = 0.026). SII also demonstrated prognostic value in Cox regression and Kaplan-Meier analyses. ROC curves confirmed that SII had superior predictive accuracy compared to common clinical indicators, with predictive relevance even in AFP-negative patients. Furthermore, a lower SII was associated with a higher T cell ratio and an increased number of CD8<sup>+</sup> T cells and Granzyme B<sup>+</sup> CD8<sup>+</sup> T cells in peripheral blood.</p><p><strong>Conclusion: </strong>SII is a promising predictor of both therapeutic efficacy and prognosis in HCC patients undergoing immune-based treatments. Its application may enhance clinical decision-making, thereby improving patient outcomes from immune-based therapy.</p>","PeriodicalId":54225,"journal":{"name":"Biomarker Research","volume":"13 1","pages":"10"},"PeriodicalIF":9.5000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11730499/pdf/","citationCount":"0","resultStr":"{\"title\":\"The prognostic value of systemic immune-inflammation index in patients with unresectable hepatocellular carcinoma treated with immune-based therapy.\",\"authors\":\"Tian He, Bin Xu, Lu-Na Wang, Zi-Yi Wang, Huan-Chen Shi, Cheng-Jie Zhong, Xiao-Dong Zhu, Ying-Hao Shen, Jian Zhou, Jia Fan, Hui-Chuan Sun, Bo Hu, Cheng Huang\",\"doi\":\"10.1186/s40364-024-00722-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Predicting the efficacy of immune-based therapy in patients with unresectable hepatocellular carcinoma (HCC) remains a clinical challenge. This study aims to evaluate the prognostic value of the systemic immune-inflammation index (SII) in forecasting treatment response and survival outcomes for HCC patients undergoing immune-based therapy.</p><p><strong>Methods: </strong>We analyzed a cohort of 268 HCC patients treated with immune-based therapy from January 2019 to March 2023. A training cohort of 93 patients received atezolizumab plus bevacizumab (T + A), while a validation cohort of 175 patients underwent treatment with tyrosine kinase inhibitors (TKIs) combined with anti-PD-(L)1 therapy. The SII cutoff value, determined using X-tile analysis based on overall survival (OS) in the training cohort, divided patients into high (> 752*10<sup>9</sup>) and low (≤ 752*10<sup>9</sup>) SII groups. Prognostic factors were identified through univariate and multivariate logistic and Cox regression analyses, and survival outcomes were assessed using Kaplan-Meier methods. The predictive accuracy of SII was evaluated using receiver operating characteristic (ROC) curves.</p><p><strong>Results: </strong>An optimal SII cutoff of 752*10<sup>9</sup> stratified patients into high and low SII groups. Univariate and multivariate logistic regression indicated that SII was a significant predictor of the objective response rate (ORR), which was markedly different between the low and high SII subgroups (34.72% vs. 9.52%, P = 0.019). This finding was consistent in the validation cohort (34.09% vs. 16.28%, P = 0.026). SII also demonstrated prognostic value in Cox regression and Kaplan-Meier analyses. ROC curves confirmed that SII had superior predictive accuracy compared to common clinical indicators, with predictive relevance even in AFP-negative patients. Furthermore, a lower SII was associated with a higher T cell ratio and an increased number of CD8<sup>+</sup> T cells and Granzyme B<sup>+</sup> CD8<sup>+</sup> T cells in peripheral blood.</p><p><strong>Conclusion: </strong>SII is a promising predictor of both therapeutic efficacy and prognosis in HCC patients undergoing immune-based treatments. Its application may enhance clinical decision-making, thereby improving patient outcomes from immune-based therapy.</p>\",\"PeriodicalId\":54225,\"journal\":{\"name\":\"Biomarker Research\",\"volume\":\"13 1\",\"pages\":\"10\"},\"PeriodicalIF\":9.5000,\"publicationDate\":\"2025-01-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11730499/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomarker Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40364-024-00722-6\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomarker Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40364-024-00722-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
摘要
背景:预测免疫治疗对不可切除肝细胞癌(HCC)患者的疗效仍然是一个临床挑战。本研究旨在评估系统性免疫炎症指数(SII)在预测HCC患者接受免疫治疗的治疗反应和生存结果方面的预后价值。方法:我们分析了2019年1月至2023年3月期间接受免疫治疗的268例HCC患者的队列。93名患者接受了atezolizumab + bevacizumab (T + A)的训练队列,而175名患者接受了酪氨酸激酶抑制剂(TKIs)联合抗pd -(L)1治疗。SII截止值采用基于训练队列总生存期(OS)的X-tile分析确定,将患者分为高SII组(bbb752 *109)和低SII组(≤752*109)。通过单因素和多因素logistic和Cox回归分析确定预后因素,并使用Kaplan-Meier方法评估生存结果。采用受试者工作特征(ROC)曲线评价SII的预测准确性。结果:752*109例患者分为高SII组和低SII组,获得最佳SII截止值。单因素和多因素logistic回归结果显示,SII是客观缓解率(ORR)的显著预测因子,低SII亚组和高SII亚组的客观缓解率(ORR)差异有统计学意义(34.72% vs. 9.52%, P = 0.019)。这一发现在验证队列中也是一致的(34.09% vs. 16.28%, P = 0.026)。SII在Cox回归和Kaplan-Meier分析中也显示了预后价值。ROC曲线证实SII与常见临床指标相比具有更高的预测准确性,即使在afp阴性患者中也具有预测相关性。此外,较低的SII与外周血中较高的T细胞比例以及CD8+ T细胞和颗粒酶B+ CD8+ T细胞数量的增加有关。结论:SII是肝癌患者免疫治疗疗效和预后的一个有希望的预测指标。它的应用可以增强临床决策,从而改善基于免疫治疗的患者预后。
The prognostic value of systemic immune-inflammation index in patients with unresectable hepatocellular carcinoma treated with immune-based therapy.
Background: Predicting the efficacy of immune-based therapy in patients with unresectable hepatocellular carcinoma (HCC) remains a clinical challenge. This study aims to evaluate the prognostic value of the systemic immune-inflammation index (SII) in forecasting treatment response and survival outcomes for HCC patients undergoing immune-based therapy.
Methods: We analyzed a cohort of 268 HCC patients treated with immune-based therapy from January 2019 to March 2023. A training cohort of 93 patients received atezolizumab plus bevacizumab (T + A), while a validation cohort of 175 patients underwent treatment with tyrosine kinase inhibitors (TKIs) combined with anti-PD-(L)1 therapy. The SII cutoff value, determined using X-tile analysis based on overall survival (OS) in the training cohort, divided patients into high (> 752*109) and low (≤ 752*109) SII groups. Prognostic factors were identified through univariate and multivariate logistic and Cox regression analyses, and survival outcomes were assessed using Kaplan-Meier methods. The predictive accuracy of SII was evaluated using receiver operating characteristic (ROC) curves.
Results: An optimal SII cutoff of 752*109 stratified patients into high and low SII groups. Univariate and multivariate logistic regression indicated that SII was a significant predictor of the objective response rate (ORR), which was markedly different between the low and high SII subgroups (34.72% vs. 9.52%, P = 0.019). This finding was consistent in the validation cohort (34.09% vs. 16.28%, P = 0.026). SII also demonstrated prognostic value in Cox regression and Kaplan-Meier analyses. ROC curves confirmed that SII had superior predictive accuracy compared to common clinical indicators, with predictive relevance even in AFP-negative patients. Furthermore, a lower SII was associated with a higher T cell ratio and an increased number of CD8+ T cells and Granzyme B+ CD8+ T cells in peripheral blood.
Conclusion: SII is a promising predictor of both therapeutic efficacy and prognosis in HCC patients undergoing immune-based treatments. Its application may enhance clinical decision-making, thereby improving patient outcomes from immune-based therapy.
Biomarker ResearchBiochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
15.80
自引率
1.80%
发文量
80
审稿时长
10 weeks
期刊介绍:
Biomarker Research, an open-access, peer-reviewed journal, covers all aspects of biomarker investigation. It seeks to publish original discoveries, novel concepts, commentaries, and reviews across various biomedical disciplines. The field of biomarker research has progressed significantly with the rise of personalized medicine and individual health. Biomarkers play a crucial role in drug discovery and development, as well as in disease diagnosis, treatment, prognosis, and prevention, particularly in the genome era.