Preoperative systemic inflammation response index indicates poor prognosis in patients treated with resection of renal cell carcinoma with inferior vena cava tumor thrombus

Predictive effect of the systemic inflammation response index (SIRI) on the efficacy and prognosis of neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

BACKGROUND

Inflammation is a part of tumours, and inflammatory cells can affect the proliferation, invasion, and development of tumour cells. An increasing number of peripheral blood inflammatory markers have been found to play very important roles in the treatment and prognosis of cancer patients. The systemic inflammatory response index (SIRI) is a newer inflammatory marker, and its role in colorectal cancer, especially in locally advanced rectal cancer, is still unclear.

METHODS

From 2015 to 2020, 198 patients with locally advanced rectal cancer (LARC) who underwent surgery following neoadjuvant chemoradiotherapy (Neo-CRT) were analysed. Patients were categorized into good- and poor- response groups according to their pathological results, and clinical characteristics and baseline parameters were compared between the two groups. The optimal cutoff values for inflammatory indicators were determined using receiver operating characteristic (ROC) analysis. Univariate and multivariate analyses were performed using the Cox proportional hazard model. Survival analysis was performed via the Kaplan‒Meier method.

RESULTS

After patients were grouped into good and poor response groups, indicator differences were found in CEA, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and SIRI. According to the ROC analysis, the NLR (P = 0.015), SII (P = 0.001), and SIRI (P = 0.029) were significant prognostic factors. After univariate and multivariate analyses of the Cox proportional hazards regression model, only the SIRI was found to be an independent prognostic factor for overall survival (OS) and disease-free survival (DFS). Finally, Kaplan‒Meier survival curves also confirmed the ability of the SIRI to predict survival.

CONCLUSION

The preoperative SIRI can be used to predict the response to Neo-CRT in LARC patients and is an independent predictor of OS and DFS in postoperative patients. A high SIRI was associated with poor radiotherapy response and predicted poor OS and DFS.

Predictive value of systemic inflammatory response-related indices for survival in tongue cancer

OBJECTIVES

We assessed the potential prognostic significance of the preoperative systemic inflammation index, platelet-to-lymphocyte ratio, and neutrophil-to-lymphocyte ratio in patients who underwent surgical resection.

SUBJECTS AND METHODS

This retrospective study included 224 patients with clinicopathologically confirmed squamous carcinoma of the tongue who underwent surgery between August 2009 and December 2017. The optimal cut-off values for the indices were determined by receiver operating characteristic curves. Correlations between the indices and clinicopathological variables were determined by Pearson chi-square or Fisher exact tests. The Kaplan-Meier test was used to compare overall survival between groups (high and low values); the log-rank or Breslow test was used to assess differences in survival. Univariate and multivariate Cox regression models were used to analyze predictive values of the indices as independent indicators of overall survival. Bilateral p values of <0.05 were considered statistically significant.

RESULTS

Significant association was found between the indices and sex, tissue grade, tumor location, and lymph nodes metastases (p < 0.05). On Kaplan-Meier analysis, patients with lower values of the indices had longer overall survival (p < 0.05). Univariate and multivariate Cox regression models identified age, lymph node metastases, and neutrophil-to-lymphocyte ratio as independent predictors of overall survival.

CONCLUSION

The studied indices have potential prognostic significance in patients with squamous tongue cancer.

Association between systemic inflammation response index and chronic kidney disease: a population-based study

Introduction

Our objective was to explore the potential link between systemic inflammation response index (SIRI) and chronic kidney disease (CKD).

Methods

The data used in this study came from the National Health and Nutrition Examination Survey (NHANES), which gathers data between 1999 and 2020. CKD was diagnosed based on the low estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or albuminuria (urinary albumin-to-creatinine ratio (ACR) of more than 30 mg/g). Using generalized additive models and weighted multivariable logistic regression, the independent relationships between SIRI and other inflammatory biomarkers (systemic immune-inflammation index (SII), monocyte/high-density lipoprotein ratio (MHR), neutrophil/high-density lipoprotein ratio (NHR), platelet/high-density lipoprotein ratio (PHR), and lymphocyte/high-density lipoprotein ratio (LHR)) with CKD, albuminuria, and low-eGFR were examined.

Results

Among the recruited 41,089 participants, males accounted for 49.77% of the total. Low-eGFR, albuminuria, and CKD were prevalent in 8.30%, 12.16%, and 17.68% of people, respectively. SIRI and CKD were shown to be positively correlated in the study (OR = 1.24; 95% CI: 1.19, 1.30). Furthermore, a nonlinear correlation was discovered between SIRI and CKD. SIRI and CKD are both positively correlated on the two sides of the breakpoint (SIRI = 2.04). Moreover, increased SIRI levels were associated with greater prevalences of low-eGFR and albuminuria (albuminuria: OR = 1.27; 95% CI: 1.21, 1.32; low-eGFR: OR = 1.11; 95% CI: 1.05, 1.18). ROC analysis demonstrated that, compared to other inflammatory indices (SII, NHR, LHR, MHR, and PHR), SIRI exhibited superior discriminative ability and accuracy in predicting CKD, albuminuria, and low-eGFR.

Discussion

When predicting CKD, albuminuria, and low-eGFR, SIRI may show up as a superior inflammatory biomarker when compared to other inflammatory biomarkers (SII, NHR, LHR, MHR, and PHR). American adults with elevated levels of SIRI, SII, NHR, MHR, and PHR should be attentive to the potential risks to their kidney health.

Prognostic Value of Systemic Inflammatory Response Index for the Prognosis of Diabetic Maintenance Hemodialysis Patients: A Retrospective Observational Study

Background

The systemic inflammatory response index (SIRI) had been identified as an inflammatory marker and has been linked to determining clinical outcomes in several diseases. We advocated the relationship between the initial SIRI and the prognosis of diabetic maintenance hemodialysis (MHD) patients.

Methods

A total of 153 diabetic MHD patients who accepted regular HD treatment at our hospital were enrolled in this study. SIRI was calculated as neutrophil × monocyte/lymphocyte. All patients were separated into two groups based on the levels of SIRI. LASSO regression and Cox regression analyses were then made to determine the prognostic value of SIRI for diabetic MHD patients.

Results

During a median 33-month follow-up period, 50 (32.7%) patients died. The higher SIRI value (≥ 2.5) had a higher risk of death (adjusted HR=4.00, 95% CI 1.77-9.07, P=0.001) after adjusting for other confounding clinical features. The devised nomogram ground on SIRI value and clinical features had great predictive value for overall survival in diabetic MHD patients. The nomogram proved both prominent calibration competence and therapeutic subservience.

Conclusion

SIRI is a relatively excellent predictor for OS, and the suggested nomogram ground on SIRI leads to an accurate prediction value for diabetic MHD patients.

The Four-Feature Prognostic Models for Cancer-Specific and Overall Survival after Surgery for Localized Clear Cell Renal Cancer: Is There a Place for Inflammatory Markers?

We aimed at a determination of the relevance of comorbidities and selected inflammatory markers to the survival of patients with primary non-metastatic localized clear cell renal cancer (RCC). We retrospectively analyzed data from a single tertiary center on 294 patients who underwent a partial or radical nephrectomy in the years 2012–2018. The following parameters were incorporated in the risk score: tumor stage, grade, size, selected hematological markers (SIRI—systemic inflammatory response index; SII—systemic immune-inflammation index) and a comorbidities assessment tool (CCI—Charlson Comorbidity Index). For further analysis we compared our model with existing prognostic tools. In a multivariate analysis, tumor stage (p = 0.01), tumor grade (p = 0.03), tumor size (p = 0.006) and SII (p = 0.02) were significant predictors of CSS, while tumor grade (p = 0.02), CCI (p = 0.02), tumor size (p = 0.01) and SIRI (p = 0.03) were significant predictors of OS. We demonstrated that our model was characterized by higher accuracy in terms of OS prediction compared to the Leibovich and GRANT models and outperformed the GRANT model in terms of CSS prediction, while non-inferiority to the VENUSS model was revealed. Four different features were included in the predictive models for CSS (grade, size, stage and SII) and OS (grade, size, CCI and SIRI) and were characterized by adequate or even superior accuracy when compared with existing prognostic tools.

Prognosis of hepatocellular carcinoma and its association with immune cells using systemic inflammatory response index

Aim: To explore the prognostic value of the systemic inflammatory response index (SIRI) and peripheral blood T-cell subsets in patients with hepatocellular carcinoma (HCC) and the relationship between them. Materials & methods: We treated 352 patients with HCC with sorafenib and/or immune checkpoint inhibitors (ICIs) and analyzed SIRI and peripheral blood T cells. Results: SIRI was an independent prognostic factor for patients with HCC receiving systemic therapy. Patients with high SIRI and low baseline peripheral blood T-cell counts showed a poor response to ICIs. SIRI was significantly and negatively correlated with CD3⁺, CD4⁺ and CD8⁺ T-cell counts. Conclusion: SIRI markers can be employed to noninvasively assess the presence of cancer-promoting inflammation in the tumor microenvironment and predict the efficacy of targeted therapy and immunotherapy.