Systemic Immune-Inflammation Index as a Prognostic Marker of Late Recurrence in Operable Gastric Cancer: a Dual-Center Study

Systemic immune inflammation index and gastric cancer prognosis: A systematic review and meta‑analysis

The present study aimed to pool the available data on the associations between the systemic immune inflammation index (SII) and overall survival (OS) or recurrence-free survival (RFS) in patients with gastric cancer (GC). A systematic search was conducted in the PubMed, EMBASE and Scopus databases for observational studies, and a random effects model was used to conduct the statistical analysis. Pooled effect sizes were reported as hazard ratios (HRs) with corresponding 95% confidence intervals (CI). Data from 30 studies (24 conducted in China) with follow-ups ranging between 15.5 and 65.6 months were analyzed. Patients with GC and high SII levels had poor OS (HR, 1.53; 95% CI, 1.34-1.75) and recurrence free survival (HR, 1.41; 95% CI, 1.17-1.70). These increased risks were present irrespective of the treatment strategy (surgical or non-surgical management), the sample size (<500 and ≥500) and the cut-off used to define high and low SII (<600 and ≥600 x109 cells/l). The results of this meta-analysis suggest that high pretreatment SII levels were associated with poor OS and RFS in patients with GC.

Exploring the connection between microsatellite instability and inflammatory indicators in cancers

Aim: This study aimed to investigate the association between microsatellite instability (MSI) status and inflammatory indicators in patients with cancer. Patients & methods: A total of 204 patients with various cancer diagnoses, including 102 with MSI-high (MSI-H) and 102 with microsatellite stable tumors, were enrolled. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), C-reactive protein (CRP)-to-albumin ratio and systemic immune-inflammation index were evaluated. Results: In microsatellite stable patients, NLR, LMR, PLR and systemic immune-inflammation index were significantly linked to worse survival in univariate analysis, and having a LMR ≤2.6 negatively affected survival in multivariate analysis, although these indicators did not affect the survival of MSI-H patients. Conclusion: The impact of chronic inflammation on survival varies with MSI status. Further research is needed for targeted therapies in different tumors.

Application of systemic inflammation indices and lipid metabolism-related factors in coronary artery disease

OBJECTIVE

We aimed to investigate the relationship between coronary artery disease (CAD) and systemic inflammation indices and lipid metabolism-related factors and subsequently, discuss the clinical application of these factors in CAD.

METHODS

We enrolled 284 consecutive inpatients with suspected CAD and divided them into a CAD group and a non-CAD group according to coronary angiography results. Serum levels of angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like protein 4 (ANGPTL4), fatty acid-binding protein 4 (FABP4), and tumor necrosis factor-α (TNF-α) levels were assessed using the ELISA and the systemic inflammation indices were calculated. Multivariate logistic regression was used to assess the risk factors of CAD. The receiver operating characteristic curve was used to determine the cutoff and diagnostic values.

RESULTS

The neutrophil-to-high density lipoprotein cholesterol ratio (5.04 vs. 3.47), neutrophil-to-lymphocyte ratio (3.25 vs. 2.45), monocyte-to-high density lipoprotein cholesterol ratio (MHR) (0.46 vs. 0.36), monocyte-to-lymphocyte ratio (0.31 vs. 0.26), systemic immune-inflammation index (SII) (696.00 vs. 544.82), serum TNF-α (398.15 ng/l vs. 350.65 ng/l), FABP4 (1644.00 ng/l vs. 1553.00 ng/l), ANGPTL3 (57.60 ng/ml vs. 52.85 ng/ml), and ANGPTL4 (37.35 ng/ml vs. 35.20 ng/ml) values showed a significant difference between the CAD and non-CAD groups ( P  < 0.05). After adjusting for confounding factors, the following values were obtained: ANGPTL3 > 67.53 ng/ml [odds ratio (OR) = 8.108, 95% confidence interval (CI) (1.022-65.620)]; ANGPTL4 > 29.95 ng/ml [OR = 5.599, 95% CI (1.809-17.334)]; MHR > 0.47 [OR = 4.872, 95% CI (1.715-13.835)]; SII > 589.12 [OR = 5.131, 95% CI (1.995-13.200)]. These factors were found to be independently associated with CAD ( P  < 0.05). Diabetes combined with MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l had the highest diagnostic value for CAD [area under the curve: 0.921, 95% CI, (0.881-0.960), Sensitivity: 88.9%, Specificity: 82.2%, P  < 0.001].

CONCLUSION

MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l were identified as independent CAD risk factors and have valuable clinical implications in the diagnosis and treatment of CAD.

Correlation of systemic immune-inflammation Index with surgical necrotizing enterocolitis

BACKGROUND

Systemic Immune-Inflammation Index (SII), known as an easy, economical and useful marker, correlates with the severity of inflammatory response. However, the usefulness of SII in necrotizing enterocolitis (NEC) remains unclear. Therefore, we evaluated the correlation of SII at NEC diagnosis and subsequent surgery.

METHODS

Retrospective review of 131 neonates with NEC in a tertiary-level pediatric referral hospital was conducted with assessments of demographic data, general blood examination results at NEC diagnosis, treatment strategies and clinical outcomes. The receiver operating characteristic (ROC) curve determined the optimal cut-off values of SII, platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio. Univariate/multivariate logistic regression analysis and ROC curve were conducted to evaluate the predictive significance of SII in identifying the patients who eventually received surgery. Additionally, NEC-related deaths were assessed.

RESULTS

Overall, 49 (37.4%) cases received surgical intervention and mortality was 12.3% (14/131). The area under ROC curve of SII at NEC diagnosis to predict subsequent surgery was 0.833 (optimal cut-off value: 235.85). The SII value in surgical intervention group was significantly higher than that in medical treatment group (332.92 ± 158.52 vs. 158.84 ± 106.82, P < 0.001). Independent influencing factors for surgical NEC were SII (95% confidence interval [CI]: 4.568∼36.449, odds ratio [OR]:12.904, P < 0.001) and PLR (95% CI: 1.071∼7.356, OR:2.807, P = 0.036). SII ≤ 235.85 could identify patients at high risk for surgery, with 87.76% sensitivity, 73.17% specificity, outperformed PLR. Furthermore, mortality was significantly higher in patients with SII ≤ 235.85 than those with SII > 235.85 (20.0% vs. 1.5%, P < 0.001).

CONCLUSION

SII and PLR at NEC diagnosis were independent influencing factors for subsequent surgery. SII ≤ 235.85 may be a useful predictive marker for the identification of surgical NEC and mortality.