Evidence map›Paper›PMID 40240723›Full record

ArticleCurrent medical science2025

The Prognostic Value of the Systemic Immune-Inflammation Index in Glioblastoma Patients and the Establishment of a Nomogram.

Hao Xu, Li-Hao Jiang, Sheng-Nan Yu, Qing-Lan Ren

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Article in Current medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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2citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hao XuDepartment of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Li-Hao JiangDepartment of Oncology, The People's Hospital of Dazu District, Chongqing, 402360, China.
Sheng-Nan YuDepartment of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Qing-Lan RenDepartment of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China. renqlwu@163.com.

Funding

National Natural Science Foundation of China 82203007
6 · The paper itself

Abstract

objectiveThe systemic immune-inflammation index (SII) has recently attracted significant interest as a new biomarker for predicting the prognosis of patients with glioblastoma (GBM). However, the predictive significance of it is still a subject of debate. This study intended to assess the clinical effectiveness of the SII in GBM and establish a nomogram.

methodsReceiver operating characteristic (ROC) curves were utilized to determine the optimal cut-off values of the SII. Kaplan-Meier (KM) survival curves were used to analyze the median overall survival (OS). Cox regression analysis was carried out to evaluate the associations between OS and different clinical factors. Based on the SII and clinical characteristics, a nomogram was constructed, and its value in clinical application was evaluated by means of decision curve analysis.

resultsThe optimal SII cut-off value was 610.13. KM analysis revealed that GBM patients with higher SII values had shorter OS (15.0 vs. 34.0 months, P = 0.044). Multivariate analysis demonstrated that a high SII was an independent predictor of poor outcome in GBM (HR = 1.79, P = 0.029). The nomogram incorporating the preoperative SII showed good predictive accuracy for GBM patient prognosis (C-index = 0.691).

conclusionsThe SII is an independent predictive indicator for GBM. Patients with elevated SII levels tend to have a poorer prognosis. A nomogram combining the SII with clinical and molecular pathological features can assist clinicians in assessing the risk of death in GBM patients, providing a basis for individualized treatment decisions.

Indexed as

Brain NeoplasmsGlioblastomaInflammationNomogramsAdultAgedBiomarkers, TumorFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisROC CurveBiomarkers, TumorGlioblastomaOverall survivalPrognostic predictionSystemic immune-inflammation index

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.