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Meta-Analysis
. 2025 May 23:16:1576845.
doi: 10.3389/fimmu.2025.1576845. eCollection 2025.

Prognostic value of systemic inflammation response index in patients with glioma: a meta-analysis

Yizhen Jiang  1 , Lin Zhou  2
Affiliations
Meta-Analysis

Prognostic value of systemic inflammation response index in patients with glioma: a meta-analysis

Yizhen Jiang et al. Front Immunol. .

Abstract

Background: The systemic inflammation response index (SIRI) has been investigated for its prognostic relevance in patients with glioma; however, findings remain inconsistent. Therefore, this meta-analysis aimed to clarify the prognostic value of SIRI in glioma.

Methods: PubMed, Web of Science, Embase, Cochrane Library, and CNKI were systematically searched through December 28, 2024. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to assess the association between SIRI and glioma prognosis.

Results: A total of 10 studies including 1,942 participants were analyzed. Elevated SIRI was significantly associated with poorer overall survival (OS) (HR=1.67, 95% CI=1.46-1.91, p<0.001) and shorter progression-free survival (PFS) (HR=1.80, 95% CI=1.29-2.52, p=0.001). Subgroup analyses indicated that the prognostic value of SIRI for OS and PFS was consistent regardless of sample size, pathological subtype, cutoff value, or type of survival analysis (p<0.05). Sensitivity and publication bias analyses confirmed the robustness of the results.

Conclusion: This meta-analysis demonstrates that high SIRI is a significant predictor of OS and PFS in patients with glioma. SIRI may serve as a promising prognostic biomarker in glioma-related clinical practice.

Keywords: biomarker; glioma; meta-analysis; prognosis; systemic inflammation response index.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
PRISMA flow diagram of study selection.
Figure 2
Figure 2
Forest plots of HR with 95% CI for correlation between SIRI and OS in patients with glioma.
Figure 3
Figure 3
Forest plots of HR with 95% CI for correlation between SIRI and PFS in patients with glioma.
Figure 4
Figure 4
Sensitivity analysis. (A) OS and (B) PFS.
Figure 5
Figure 5
Publication bias by Begg’s test and Egger’s test. (A) Begg’s test for OS, p=0.371; (B) Egger’s test for OS, p=0.408; (C) Begg’s test for PFS, p=0.127; and (D) Egger’s test for PFS, p=0.225.
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