Ruofei Liang1, Ni Chen2, Mao Li1, Xiang Wang1, Qing Mao1, Yanhui Liu3. 1. Department of Neurosurgery, West China Hospital, Sichuan University, China. 2. Department of Pathology, West China Hospital, Sichuan University, China. 3. Department of Neurosurgery, West China Hospital, Sichuan University, China. Electronic address: yhliu2001@163.com.
Abstract
OBJECTIVE: Circulating biomarkers have been increasingly appreciated in the grading of gliomas. This study aimed to assess the value of the systemic immune-inflammation index (SII) as a possible marker in the grading of gliomas. MATERIALS AND METHODS: In our study, 153 patients with gliomas were included-53 patients had histologically verified low grade gliomas (LGG) and 100 patients had high grade gliomas (HGG). Preoperative complete blood count (CBC) and clinicopathological data were collected. The optimal SII cut-off value for grading of gliomas was calculated by receiver operating characteristics curve (ROC) analysis. RESULTS: Based on the ROC analysis, the most optimal cut-off value of SII to distinguish HGG and LGG was determined as 392.48×109/L. For this cut-off value, SII had a sensitivity of 75%, specificity of 66%, and area under the curve (AUC) of 0.773. Furthermore, we found that patients in the high-SII group had a significantly higher Ki-67 index than that in patients in the low-SII group (P=0.002). CONCLUSION: Our results demonstrate that SII has a moderate diagnostic accuracy for differentiating HGG from LGG. More studies are needed to confirm these results.
OBJECTIVE: Circulating biomarkers have been increasingly appreciated in the grading of gliomas. This study aimed to assess the value of the systemic immune-inflammation index (SII) as a possible marker in the grading of gliomas. MATERIALS AND METHODS: In our study, 153 patients with gliomas were included-53 patients had histologically verified low grade gliomas (LGG) and 100 patients had high grade gliomas (HGG). Preoperative complete blood count (CBC) and clinicopathological data were collected. The optimal SII cut-off value for grading of gliomas was calculated by receiver operating characteristics curve (ROC) analysis. RESULTS: Based on the ROC analysis, the most optimal cut-off value of SII to distinguish HGG and LGG was determined as 392.48×109/L. For this cut-off value, SII had a sensitivity of 75%, specificity of 66%, and area under the curve (AUC) of 0.773. Furthermore, we found that patients in the high-SII group had a significantly higher Ki-67 index than that in patients in the low-SII group (P=0.002). CONCLUSION: Our results demonstrate that SII has a moderate diagnostic accuracy for differentiating HGG from LGG. More studies are needed to confirm these results.
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