Systemic immune-inflammation index as a prognostic marker in pancreatic ductal adenocarcinoma: a metaanalysis

Pachinger-Molnár, Bence and Menyhárt, Otília (2026) Systemic immune-inflammation index as a prognostic marker in pancreatic ductal adenocarcinoma: a metaanalysis. CANCER TREATMENT AND RESEARCH COMMUNICATIONS, 48. No. 101326. ISSN 2468-2942

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Abstract

Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with limited durable treatment options despite evolving multimodal and systemic strategies. Systemic inflammation has emerged as a clinically relevant determinant of outcomes in several cancers. The systemic immune-inflammation index (SII; platelet count x neutrophil count / lymphocyte count) integrates key circulating immune cell populations and may serve as an accessible prognostic biomarker in PDAC. Methods A systematic search of PubMed was performed for studies published up to 11 April 2025. Eligible full-text English studies reported hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) according to SII (typically high versus low SII, defined by a study-specific cutoff). Pooled HRs were calculated using an inverse-variance random-effects model. Heterogeneity was assessed using Cochran's Q and the I-2 statistic. Small-study effects were evaluated by funnel plot inspection and Egger's regression test. Results Seventeen studies (18 datasets) comprising 4218 patients were included. Elevated SII was associated with worse OS (pooled HR 1.58, 95% CI 1.19 - 2.08; p < 0.01). Between-study heterogeneity was substantial (I-2 = 89.9%). Funnel plot inspection did not suggest major asymmetry, and Egger's test did not provide statistical evidence of small-study effects (p = 0.072). Conclusions Elevated SII is associated with poorer overall survival and represents a practical prognostic biomarker derived from routine laboratory testing. Considerable heterogeneity across studies-likely driven by differences in case mix, treatment context, and SII cutoff definitions-underscores the need for standardized thresholds and prospective, harmonized validation studies.

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