Prognostic value of preoperative inflammatory markers among different molecular subtypes of lower-grade glioma

Prognostic value of pretreatment lymphocyte-to-monocyte ratio in patients with glioma: a meta-analysis

BACKGROUND

Many studies have explored the prognostic role of the lymphocyte-to-monocyte ratio (LMR) in patients with glioma, but the results have been inconsistent. We therefore conducted the current meta-analysis to identify the accurate prognostic effect of LMR in glioma.

METHODS

The electronic databases of PubMed, Web of Science, Embase, and Cochrane Library were thoroughly searched from inception to July 25, 2023. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to estimate the prognostic role of LMR for glioma.

RESULTS

A total of 16 studies comprising 3,407 patients were included in this meta-analysis. A low LMR was significantly associated with worse overall survival (OS) (HR = 1.35, 95% CI = 1.13-1.61, p = 0.001) in glioma. However, there was no significant correlation between LMR and progression-free survival (PFS) (HR = 1.20, 95% CI = 0.75-1.91, p = 0.442) in glioma patients. Subgroup analysis indicated that a low LMR was significantly associated with inferior OS and PFS in glioma when using a cutoff value of ≤ 3.7 or when patients received mixed treatment.

CONCLUSIONS

This meta-analysis demonstrated that a low LMR was significantly associated with poor OS in glioma. There was no significant correlation between LMR and PFS in glioma patients. The LMR could be a promising and cost-effective prognostic biomarker in patients with glioma in clinical practice.

An alternative extension of telomeres related prognostic model to predict survival in lower grade glioma

OBJECTIVE

The alternative extension of the telomeres (ALT) mechanism is activated in lower grade glioma (LGG), but the role of the ALT mechanism has not been well discussed. The primary purpose was to demonstrate the significance of the ALT mechanism in prognosis estimation for LGG patients.

METHOD

Gene expression and clinical data of LGG patients were collected from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) cohort, respectively. ALT-related genes obtained from the TelNet database and potential prognostic genes related to ALT were selected by LASSO regression to calculate an ALT-related risk score. Multivariate Cox regression analysis was performed to construct a prognosis signature, and a nomogram was used to represent this signature. Possible pathways of the ALT-related risk score are explored by enrichment analysis.

RESULT

The ALT-related risk score was calculated based on the LASSO regression coefficients of 22 genes and then divided into high-risk and low-risk groups according to the median. The ALT-related risk score is an independent predictor of LGG (HR and 95% CI in CGGA cohort: 5.70 (3.79, 8.58); in TCGA cohort: 1.96 (1.09, 3.54)). ROC analysis indicated that the model contained ALT-related risk score was superior to conventional clinical features (AUC: 0.818 vs 0.729) in CGGA cohorts. The results in the TCGA cohort also shown a powerful ability of ALT-related risk score (AUC: 0.766 vs 0.691). The predicted probability and actual probability of the nomogram are consistent. Enrichment analysis demonstrated that the ALT mechanism was involved in the cell cycle, DNA repair, immune processes, and others.

CONCLUSION

ALT-related risk score based on the 22-gene is an important factor in predicting the prognosis of LGG patients.

Preoperative Systemic Immune-Inflammation Index is a Potential Biomarker in Adult Patients with High-Grade Gliomas Undergoing Radical Resection

Background

Increasing evidence has highlighted that systemic immune-inflammation index (SII), a recently developed prognostic biomarker that utilizes peripheral platelet, lymphocyte and neutrophil counts, is associated with unfavorable prognosis in various tumors. Nevertheless, the prognostic significance of SII in high-grade gliomas patients undergoing radical resection remains unclear. Therefore, the present study aimed to assess the potential of SII as a prognostic biomarker in this patient population.

Methods

A total of 111 adult patients with high-grade gliomas who underwent radical resection were consecutively enrolled in this investigation. The study involved the categorization of patients into high and low SII groups using predetermined cut-off values. Subsequently, forward stepwise logistic regression was employed to identify autonomous predictors for early gliomas recurrence. To mitigate the impact of confounding factors, a propensity score matching (PSM) analysis was performed between high and low SII patients. Finally, the Kaplan-Meier approach was utilized to compare the progression-free survival (PFS) and overall survival (OS) of the two groups.

Results

The study involved the categorization of patients into two groups based on their SII levels, namely high SII (> 604.8) and low SII (≤ 604.8) groups. Forward stepwise logistic regression revealed that high SII (p < 0.001) and tumor size ≥ 50 mm (p < 0.001) were significantly related to early recurrence of gliomas. Furthermore, the results indicate that PFS and OS were significantly shorter in the high SII group compared to the low SII group, both before and after PSM (p < 0.05).

Conclusion

Preoperative biomarker SII can serve as a prognostic biomarker for early recurrence and prognosis in patients with high-grade gliomas undergoing radical resection. Furthermore, the combination of tumor size and SII demonstrates a robust predictive capacity for early recurrence and prognosis in this patient population.