Frontiers in immunology · 2026
Baseline systemic immune-inflammation index and a novel FLIPI-SII model predict POD24 and long-term survival in grade 1-3a follicular lymphoma.
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Yu Jingwei, Sun Cong, Liu Qian, Wang Ganggang, Wang Jiesong, Li Lanfang, Qiu Lihua, Qian Zhengzi, Zhou Shiyong, Wang Xianhuo, Zhang Huilai
Аннотация
Follicular lymphoma (FL) exhibits substantial clinical heterogeneity, and progression of disease within 24 months (POD24) represents a critical adverse clinical endpoint. Traditional prognostic models rely predominantly on tumor-related parameters and overlook systemic immune-inflammatory status. The newly established FLIPI24 index emphasizes peripheral blood markers but lacks immune-related indicators. Here, we investigated the prognostic value of the baseline systemic immune-inflammation index (SII) and developed a novel FLIPI-SII model to improve risk stratification in patients with grade 1-3a FL. A total of 628 patients were used for model training/internal validation, and 187 R-CHOP-treated patients for external validation. High SII (>580) was significantly correlated with inferior overall survival (OS) and progression-free survival (PFS), and was identified as an independent prognostic risk factor in multivariate regression analysis. The predictive efficacy of SII remained stable in patients receiving rituximab-based immunochemotherapy. We further constructed a 6-item FLIPI-SII scoring system, which categorized patients into four distinct risk subgroups and exerted powerful predictive performance for POD24. The model effectively predicted both PFS and OS in our cohort and was validated in two external centers. The FLIPI-SII model presented higher C-index values than conventional FLIPI, FLIPI2, and PRIMPI for both OS and PFS prediction. In conclusion, baseline SII acts as a stable, non-invasive, and independent prognostic biomarker for grade 1-3a FL. The newly developed FLIPI-SII model greatly improves the prediction of POD24 and long-term survival, providing a reliable immune-associated tool for individualized clinical risk assessment.