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已发表论文
一种用于预测接受 PD-1 抑制剂治疗的肝细胞癌患者生存预后的新型营养免疫炎症评分模型的建立与验证
Authors Liu K , Lv Y, Fu S, Mao Y, Xu Y , Huang S, Wu J
Received 11 June 2025
Accepted for publication 11 September 2025
Published 27 September 2025 Volume 2025:18 Pages 13397—13412
DOI https://doi.org/10.2147/JIR.S546164
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Junhao Wang
Kan Liu,1,* Yaqin Lv,2,* Shumin Fu,1,* Ye Mao,1 Yongkang Xu,1 Shenglan Huang,1 Jianbing Wu1
1Department of Oncology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, People’s Republic of China; 2The Wuxi Branch of the 904th Hospital of the Joint Logistic Support Force, Wuxi, Jiangsu Province, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Jianbing Wu, Department of Oncology, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Donghu District, Nanchang City, Jiangxi Province, 330006, People’s Republic of China, Email hhgwjb@163.com Shenglan Huang, Department of Oncology, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Donghu District, Nanchang City, Jiangxi Province, 330006, People’s Republic of China, Email 0796643011@163.com
Purpose: Immune checkpoint inhibitors, particularly PD-1 inhibitors, are widely used in hepatocellular carcinoma therapy, many received PD-1 inhibitors beyond first-line, but heterogeneous treatment responses require reliable biomarkers. The interaction of immune function, nutritional status, and inflammatory responses affects tumor progression and survival, yet their prognostic value in PD-1 inhibitor-treated HCC patients remains unclear. This study developed a novel nutritional-immune-inflammatory score (NIIS) to evaluate its prognostic value in HCC patients receiving PD-1 inhibitors.
Patients and Methods: We analyzed 355 HCC patients treated with PD-1 inhibitors (training: n=249; validation: n=106), the cohort included 18.6% Child-Pugh B patients. Fourteen nutritional, immune, and inflammatory biomarkers were evaluated. Prognostic indicators were selected via univariate and LASSO Cox regression. The NIIS was constructed and validated for OS prediction. A nomogram integrating the NIIS with clinical variables was developed and validated based on calibration curves, AUC, and DCA, and compared with the BCLC staging system. The primary outcome assessed was OS from the initiation of PD-1 inhibitor therapy in HCC patients.
Results: The NIIS (ALRI, APRI, PALBI, AAPR) showed strong prognostic stratification. High-risk patients had shorter OS (training: P =1.764× 10^− 8; verification: P=2.775× 10^− 6). Higher NIIS were significantly associated with advanced tumor stage, poor liver function grade, multiple and larger tumors, tumor thrombus, vascular invasion, and elevated AFP levels (P< 0.05). Multivariate Cox analysis confirmed the NIIS as an independent prognostic factor for OS (training: HR=1.565, 95% CI: 1.273– 1.925; verification: HR=1.341, 95% CI: 1.065– 1.687). A nomogram integrating the NIIS with clinical variables was constructed for individualized prognosis prediction, demonstrating superior predictive performance compared to the conventional BCLC staging system.
Conclusion: The NIIS and nomogram provide a clinically useful tool for risk stratification in HCC immunotherapy, this model outperforming conventional staging systems and may optimize patient selection for PD-1 inhibitor therapy. Prospective multicenter studies are warranted to validate its generalizability.
Keywords: nutritional-immuno-inflammatory indicators, PD-1 inhibitors, hepatocellular carcinoma, survival prediction, prognostic model
1Department of Oncology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, People’s Republic of China; 2The Wuxi Branch of the 904th Hospital of the Joint Logistic Support Force, Wuxi, Jiangsu Province, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Jianbing Wu, Department of Oncology, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Donghu District, Nanchang City, Jiangxi Province, 330006, People’s Republic of China, Email hhgwjb@163.com Shenglan Huang, Department of Oncology, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Donghu District, Nanchang City, Jiangxi Province, 330006, People’s Republic of China, Email 0796643011@163.com
Purpose: Immune checkpoint inhibitors, particularly PD-1 inhibitors, are widely used in hepatocellular carcinoma therapy, many received PD-1 inhibitors beyond first-line, but heterogeneous treatment responses require reliable biomarkers. The interaction of immune function, nutritional status, and inflammatory responses affects tumor progression and survival, yet their prognostic value in PD-1 inhibitor-treated HCC patients remains unclear. This study developed a novel nutritional-immune-inflammatory score (NIIS) to evaluate its prognostic value in HCC patients receiving PD-1 inhibitors.
Patients and Methods: We analyzed 355 HCC patients treated with PD-1 inhibitors (training: n=249; validation: n=106), the cohort included 18.6% Child-Pugh B patients. Fourteen nutritional, immune, and inflammatory biomarkers were evaluated. Prognostic indicators were selected via univariate and LASSO Cox regression. The NIIS was constructed and validated for OS prediction. A nomogram integrating the NIIS with clinical variables was developed and validated based on calibration curves, AUC, and DCA, and compared with the BCLC staging system. The primary outcome assessed was OS from the initiation of PD-1 inhibitor therapy in HCC patients.
Results: The NIIS (ALRI, APRI, PALBI, AAPR) showed strong prognostic stratification. High-risk patients had shorter OS (training: P =1.764× 10^− 8; verification: P=2.775× 10^− 6). Higher NIIS were significantly associated with advanced tumor stage, poor liver function grade, multiple and larger tumors, tumor thrombus, vascular invasion, and elevated AFP levels (P< 0.05). Multivariate Cox analysis confirmed the NIIS as an independent prognostic factor for OS (training: HR=1.565, 95% CI: 1.273– 1.925; verification: HR=1.341, 95% CI: 1.065– 1.687). A nomogram integrating the NIIS with clinical variables was constructed for individualized prognosis prediction, demonstrating superior predictive performance compared to the conventional BCLC staging system.
Conclusion: The NIIS and nomogram provide a clinically useful tool for risk stratification in HCC immunotherapy, this model outperforming conventional staging systems and may optimize patient selection for PD-1 inhibitor therapy. Prospective multicenter studies are warranted to validate its generalizability.
Keywords: nutritional-immuno-inflammatory indicators, PD-1 inhibitors, hepatocellular carcinoma, survival prediction, prognostic model