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Record W4415493065 · doi:10.3389/fonc.2025.1707657

Prognostic value of the systemic immune-inflammation index in bladder cancer: an update evidence-based analysis

2025· article· en· W4415493065 on OpenAlexaboutno aff
Jingxing Bai, Yin Huang, Bo Chen, Biao Ran, Jinze Li, Jie Chen, Qian Wei, Dehong Cao, Liangren Liu

Bibliographic record

VenueFrontiers in Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsValue (mathematics)Index (typography)MEDLINEBladder cancer

Abstract

fetched live from OpenAlex

Background: Bladder cancer (BC) prognosis remains challenging to predict accurately with conventional tools. Systemic immune-inflammation index (SII) has emerged as a promising biomarker reflecting the tumor microenvironment. However, existing studies are limited by small sample sizes, heterogeneous designs, and inconsistent endpoints. This updated meta-analysis aims to comprehensively evaluate the association between high SII and key survival outcomes in BC patients. Methods: We systematically searched PubMed, Embase, Web of Science, and Cochrane up to August 2025. Cohort studies reporting hazard ratios (HRs) for overall survival (OS), recurrence-free survival (RFS), progression-free survival (PFS), or cancer-specific survival (CSS) comparing high vs. low SII groups in histologically confirmed BC were included. Study quality was assessed using the Newcastle-Ottawa Scale. Pooled HRs with 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup analyses by pathological type (NMIBC vs. MIBC) and sensitivity analyses were performed. Publication bias was evaluated via funnel plots and Egger's test. Results: Sixteen cohort studies involving 2,352 patients were analyzed. Meta-analysis revealed that elevated SII was significantly associated with worse OS (HR=1.66, 95% CI: 1.30-2.12, P < 0.0001) and RFS (HR=1.50, 95% CI: 1.28-1.76, P < 0.00001), with substantial heterogeneity (OS: I² = 81%; RFS: I² = 59%). Subgroup analysis showed significant predictive value of SII for RFS in both NMIBC (HR=1.55, 95% CI: 1.27-1.89, P < 0.0001; heterogeneity reduced to I² = 37%) and MIBC (HR=1.13, 95% CI: 1.01-1.26, P=0.03). However, OS subgroup associations for NMIBC (HR=1.15, P=0.50) and MIBC (HR=1.92, P=0.07) were non-significant. No significant associations were found for PFS (HR=1.55, 95% CI: 0.92-2.60, P=0.10, I² = 68%) or CSS (HR=1.50, 95% CI: 0.95-2.37, P=0.08, I² = 69%), likely due to limited study numbers (4 and 3, respectively). Significant publication bias was detected for OS and RFS. Conclusion: Elevated SII is significantly associated with poorer overall and recurrence-free survival in bladder cancer patients, particularly highlighting its potential predictive value for recurrence risk in NMIBC. However, significant heterogeneity, publication bias, and retrospective design limitations necessitate caution in interpretation. Future large-scale, prospective studies with standardized SII measurement and dynamic monitoring are crucial to validate its clinical utility and define optimal cut-offs for integration into risk-stratified management strategies. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251145769, Prospero identifier, CRD420251145769.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.036
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.020
Bibliometrics0.0070.008
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.314
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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