The Prognostic Value of Preoperative Systemic Inflammatory Response Index (SIRI) in Patients With High-Grade Glioma and the Establishment of a Nomogram

Li, Longhao; Ren, Qinglan

doi:10.3389/fonc.2021.671811

Cited by 28 publications

(30 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“… 8 As inflammatory indicators, the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and red blood cell distribution width (RDW) have been reported to be predictive of stroke prognosis, but their formulations are relatively homogeneous and not comprehensive. 9 , 10 It has been reported that the novel chronic low-grade inflammatory index systemic immunity-inflammation index (SIRI) has excellent predictive power in glioma, 11 breast cancer 12 and nasopharyngeal carcinoma; 13 however, no studies have attempted to investigate its role in prediction in stroke prognosis.…”

Section: Introductionmentioning

confidence: 99%

The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients

Zhang¹,

Xing²,

Zhou³

et al. 2021

CIA

106

View full text Add to dashboard Cite

Purpose Stroke is a disease associated with high mortality. Many inflammatory indicators such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and red blood cell distribution width (RDW) have been documented to predict stroke prognosis, their predictive power is limited. A novel inflammatory indicator called systemic inflammatory response index (SIRI) has been advocated to have an essential role in the prognostic assessment of cancer and infectious diseases. In this study, we attempted to assess the prognosis of stroke by SIRI. Moreover, we compared SIRI with other clinical parameters, including NLR, PLR, LMR and RDW. Methods This was a retrospective cohort study. We obtained data of 2450 stroke patients from the Multiparametric Intelligent Monitoring in Intensive Care III database. We used the Cox proportional hazards models to evaluate the relationship between SIRI and all-cause mortality and sepsis. Receiver operating curve (ROC) analysis was used to assess the predictive power of SIRI compared to NLR, PLR, LMR and RDW for the prognosis of stroke. We collected data of 180 patients from the First Affiliated Hospital of Wenzhou Medical University, which used the Pearson’s correlation coefficient to assess the relationship between SIRI and the National Institute of Health stroke scale (NIHSS). Results After adjusting multiple covariates, we found that SIRI was associated with all-cause mortality in stroke patients. Rising SIRI accompanied by rising mortality. Besides, ROC analysis showed that the area under the curve of SIRI was significantly greater than for NLR, PLR, LMR and RDW. Besides, Pearson’s correlation test confirmed a significant positive correlation between SIRI and NIHSS. Conclusion Elevated SIRI was associated with higher risk of mortality and sepsis and higher stroke severity. Therefore, SIRI is a promising low-grade inflammatory factor for predicting stroke prognosis that outperformed NLR, PLR, LMR, and RDW in predictive power.

show abstract

Section: Introductionmentioning

confidence: 99%

The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients

Zhang¹,

Xing²,

Zhou³

et al. 2021

CIA

106

View full text Add to dashboard Cite

show abstract

“…Some previous studies [ 34 – 38 ] have investigated the role of NLR, PLR, MLR, and AGR in GBM, but there was no consistent conclusion. In our study, we did not find the prognostic values of NLR, PLR, MLR, and AGR for the survival of GBM.…”

Section: Discussionmentioning

confidence: 92%

“…Although the SIRI (M × N/L) formula is similar to the SII (P × N/L) formula, where simply the monocytes in the SIRI substitute the platelets of the SII, a relationship between SIRI and GBM survival results was not found. According to Erkan Topkan’s conclusions, SIRI played a crucial role in survival prediction in glioblastoma multiforme patients treated with standard protocol [ 34 ]. We speculated that the causes presumably were that SIRI served as a dynamic indicator, and its value fluctuates during treatment, affecting final results.…”

Section: Discussionmentioning

confidence: 99%

The prognostic value of the preoperative inflammatory index on the survival of glioblastoma patients

Nyalali

et al. 2022

Neurol Sci

View full text Add to dashboard Cite

Objectives The growth and development of tumors are closely related to the initiation and amplification of the inflammatory response. Various inflammatory biomarkers had attained growing attention for nearly two decades and were discovered strongly associated with cancer patients’ prognosis, indicating that systemic inflammatory response is possibly essential to cancer progression. However, little was known about the sensitive biomarkers associated with the detection, persistence, treatment, and prognosis of GBM. Hence, the retrospective research endeavored to evaluate the prognostic value of preoperative inflammatory biomarkers in patients with GBM who initially received standardized treatment. Methods The 232 glioblastoma patients eligible who were admitted to Qilu Hospitals in Shandong Province from January 2014 to January 2018 were collected for this analysis. Inflammatory markers, including the systemic immune-inflammation index (SII), systemic immune response index (SIRI), neutrophil–lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), and albumin/globulin ratio (AGR), were designed. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan–Meier method, and we calculated the area under the ROC curve to determine the AUC value. Besides, we used the Cox proportional hazard model to estimate the relationship between variables and PFS and OS. The statistical differences between variables and PFS and OS were tested through the log-rank test. What is more, the LR method was used to perform Cox multiple regression analysis. The results were represented by hazard ratio (HR), 95% CI, any 2-tailed P < 0.01 was accepted as statistically different. Results The multivariate Cox proportional hazard model presented that SII ≥ 659.1 was an independent risk factor affecting OS (HR = 2.238, 95% CI = 1.471–3.406, P < 0.001) and postoperative PFS (HR = 2.000, 95% CI = 1.472–2.716, P < 0.001) in GBM patients. The 1-, 3-, and 5-year OS of the SII < 659.1 group was 70.8%, 26.9%, and 14.1%, respectively, while the 1- and 3-year OS of the SII ≥ 659.1 group was 37.5% and 11.5% ( P < 0.001). The 1-, 3-, and 5-year PFS of the SII < 659.1 group was 36.3%, 19.6%, and 13%, respectively, while the 1-year PFS of the SII ≥ 659.1 group was 11.3% ( P < 0.001). Results of patients’ clinical and pathological characteristics paraded that in comparison to the lower SII group, the higher SII group had significantly inferior Karnofsky Performance Scale (KPS) scores ( P < 0.001) and more frequent cystic changes of the tumors ( P < 0.001), whereas the values of SIRI, NLR, PLR, MLR, and AGR were low. Conclusions SII is an independent inflammatory indicator for predicting the prognosis of GBM pa...

show abstract

“…32 Many studies have used similar approaches. 11,[33][34][35][36] Previous studies have evaluated the diagnostic potential of single or combined hematological indicators in gliomas. 11 They thought that NLR, as a single predictive marker, was the best predictor of glioma; however, age + PNI and age + AGR were the best combination indicators to forecast the diagnosis of glioblastoma or IDH-wt glioblastoma.…”

Section: Discussionmentioning

confidence: 99%

Temporal Muscle Thickness is an Independent Prognostic Biomarker in Patients with Glioma: Analysis of 261 Cases

Yan¹,

Teng²,

Fu³

et al. 2021

CMAR

View full text Add to dashboard Cite

Purpose: Temporal muscle thickness (TMT) has been proposed as a novel surrogate marker for skeletal muscle mass in head and neck malignancies. This study investigated the TMT prognostic relevance with gliomas and evaluated the influence of TMT values on survival in patients with gliomas of different grades and IDH subtypes. Methods: The patients' TMT was measured on contrast-enhanced T1-weighted magnetic resonance images before surgical treatment. Patients were divided into two cohorts based on their median TMT values. The Kaplan-Meier curve was used to compute the overall survival (OS) of different categories and all gliomas. Univariate and multivariate Cox regression analyses were conducted to assess the association between OS and TMT, hematological markers, and other clinical factors in glioma patients. Moreover, the clinical diagnostic efficiency of single and combination biomarkers was evaluated using receiver operating characteristic curve analysis. Results: We retrospectively analyzed 261 patients with newly diagnosed glioma between November 2016 and May 2020 at Hunan Cancer Hospital. Cox analysis indicated that higher TMT (HR 0.286, P< 0.001) and higher KPS score (HR 0.629, P= 0.012) were protective prognostic factors and IDH wildtype status (HR 2.946, P< 0.001), RDW > 12.6 (HR 1.513, P= 0.036), and NLR > 4 (HR 1.560, P= 0.042) were poor prognostic factors for gliomas. Subsequently, patients with thicker TMT were found to have significantly better overall survival (P<0.001) than patients with thinner TMT among WHO III and WHO IV grade and patients with or without IDH mutation. TMT was considered a better single biomarker than recently prevalent hematological biomarkers for predicting high-grade [0.856 (0.797-0.916)] and IDH-wild-type [0.864 (0.786-0.941)] gliomas. Conclusion:This study suggests that TMT is a positive biomarker for clinical prognosis in gliomas and that patients with thicker TMT have greater overall survival for gliomas of different grades and IDH subtypes.

show abstract

The Prognostic Value of Preoperative Systemic Inflammatory Response Index (SIRI) in Patients With High-Grade Glioma and the Establishment of a Nomogram

Cited by 28 publications

References 52 publications

The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients

The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients

The prognostic value of the preoperative inflammatory index on the survival of glioblastoma patients

Temporal Muscle Thickness is an Independent Prognostic Biomarker in Patients with Glioma: Analysis of 261 Cases

Contact Info

Product

Resources

About