Cancer Center, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China.
Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China.
Int J Hyperthermia. 2024;41(1):2355279. doi: 10.1080/02656736.2024.2355279. Epub 2024 May 20.
This study aimed to explore the prognostic role of pan-immune-inflammation value (PIV) and develop a new risk model to guide individualized adjuvant systemic treatment following radiofrequency ablation (RFA) for early-stage hepatocellular carcinoma (HCC).
Patients with early-stage HCC treated by RFA were randomly divided into training cohort A ( = 65) and testing cohort B ( = 68). Another 265 counterparts were enrolled into external validating cohort C. Various immune-inflammatory biomarkers (IIBs) were screened in cohort A. Prognostic role of PIV was evaluated and validated in cohort B and C, respectively. A nomogram risk model was built in cohort C and validated in pooled cohort D. Clinical benefits of adjuvant anti-angiogenesis therapy plus immune checkpoint inhibitor (AA-ICI) following RFA was assessed in low- and high-risk groups.
The cutoff point of PIV was 120. High PIV was an independent predictor of unfavorable recurrence-free survival (RFS) and overall survival (OS). RFS and OS rates of patients with high PIV were significantly lower than those with low PIV both in cohort B (=0.016, =0.011) and C (<0.001, <0.001). The nomogram model based on PIV, tumor number and BCLC staging performed well in risk stratification in external validating cohort C. Adjuvant AA-ICI treatment showed an added benefit in OS ( = 0.011) for high-risk patients.
PIV is a feasible independent prognostic factor for RFS and OS in early-stage HCC patients who received curative RFA. The proposed PIV-based nomogram risk model could help clinicians identify high-risk patients and tailor adjuvant systemic treatment and disease follow-up scheme.
本研究旨在探讨泛免疫炎症值(PIV)的预后作用,并建立新的风险模型,以指导射频消融(RFA)治疗早期肝细胞癌(HCC)后的个体化辅助全身治疗。
接受 RFA 治疗的早期 HCC 患者被随机分为训练队列 A(n=65)和测试队列 B(n=68)。另外 265 名患者被纳入外部验证队列 C。在队列 A 中筛选了各种免疫炎症生物标志物(IIBs)。分别在队列 B 和 C 中评估和验证 PIV 的预后作用,并在队列 C 中构建列线图风险模型,并在汇总队列 D 中进行验证。评估 RFA 后辅助抗血管生成治疗加免疫检查点抑制剂(AA-ICI)在低危和高危组中的临床获益。
PIV 的截断值为 120。高 PIV 是不利无复发生存(RFS)和总生存(OS)的独立预测因子。在队列 B(=0.016,=0.011)和 C(<0.001,<0.001)中,PIV 较高的患者的 RFS 和 OS 率均显著低于 PIV 较低的患者。基于 PIV、肿瘤数量和 BCLC 分期的列线图模型在外验证队列 C 中具有良好的风险分层能力。高危患者的辅助 AA-ICI 治疗在 OS 方面具有显著获益(=0.011)。
PIV 是接受根治性 RFA 治疗的早期 HCC 患者 RFS 和 OS 的可行独立预后因素。所提出的基于 PIV 的列线图风险模型可以帮助临床医生识别高危患者,并制定辅助全身治疗和疾病随访方案。