Prognostic significance of preoperative systemic inflammation response index in newly diagnosed glioblastoma patients underwent gross total resection: a propensity score matching analysis.
Glioblastoma (GBM)
Gross total resection (GTR)
Neutrophil to lymphocyte ratio (NLR)
Prognosis
Systemic inflammation response index (SIRI)
Journal
World journal of surgical oncology
ISSN: 1477-7819
Titre abrégé: World J Surg Oncol
Pays: England
ID NLM: 101170544
Informations de publication
Date de publication:
29 Apr 2022
29 Apr 2022
Historique:
received:
06
12
2021
accepted:
02
04
2022
entrez:
30
4
2022
pubmed:
1
5
2022
medline:
4
5
2022
Statut:
epublish
Résumé
Glioblastoma (GBM) is the most frequent and lethal brain tumor, which possesses highly malignant characteristics and predominates in elder patients. Systemic inflammatory response index (SIRI) is a novel prognostic marker from peripheral blood, which is defined as neutrophil count × monocyte count/lymphocyte count. In the current research, we aim to explore the relationship between SIRI and newly diagnosed GBM underwent gross total resection (GTR). A retrospective analysis was conducted on consecutive newly diagnosed GBM patients underwent operation at West China Hospital from March 2015 to January 2019. X-tile software was used to determine the optimal cut-off values of SIRI, and neutrophil to lymphocyte ratio (NLR). All statistical analyses were performed using SPSS software and R software. Propensity score matching (PSM) was conducted to adjust for imbalance of all potential confounding covariates. The current research included a total of 291 consecutive newly diagnosed GBM patients underwent gross total resection. Among them, 186 were male patients and 105 were female patients. In original cohort, only gender was evidently related to SIRI level. SIRI and NLR were independent prognostic indicators both in original cohort and PSM cohort. Prognostic models based on the independent prognostic factors were established, and prognostic capacity of Model SIRI was superior to Model NLR. In the current research, SIRI was determined to be an independent prognostic indicator for GBM. And the prognostic predictive ability of SIRI was stronger than NLR.
Sections du résumé
BACKGROUND
BACKGROUND
Glioblastoma (GBM) is the most frequent and lethal brain tumor, which possesses highly malignant characteristics and predominates in elder patients. Systemic inflammatory response index (SIRI) is a novel prognostic marker from peripheral blood, which is defined as neutrophil count × monocyte count/lymphocyte count. In the current research, we aim to explore the relationship between SIRI and newly diagnosed GBM underwent gross total resection (GTR).
METHODS
METHODS
A retrospective analysis was conducted on consecutive newly diagnosed GBM patients underwent operation at West China Hospital from March 2015 to January 2019. X-tile software was used to determine the optimal cut-off values of SIRI, and neutrophil to lymphocyte ratio (NLR). All statistical analyses were performed using SPSS software and R software. Propensity score matching (PSM) was conducted to adjust for imbalance of all potential confounding covariates.
RESULTS
RESULTS
The current research included a total of 291 consecutive newly diagnosed GBM patients underwent gross total resection. Among them, 186 were male patients and 105 were female patients. In original cohort, only gender was evidently related to SIRI level. SIRI and NLR were independent prognostic indicators both in original cohort and PSM cohort. Prognostic models based on the independent prognostic factors were established, and prognostic capacity of Model SIRI was superior to Model NLR.
CONCLUSION
CONCLUSIONS
In the current research, SIRI was determined to be an independent prognostic indicator for GBM. And the prognostic predictive ability of SIRI was stronger than NLR.
Identifiants
pubmed: 35488347
doi: 10.1186/s12957-022-02588-0
pii: 10.1186/s12957-022-02588-0
pmc: PMC9052476
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
137Informations de copyright
© 2022. The Author(s).
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