Prechemoradiotherapy Systemic Inflammation Response Index Stratifies Stage IIIB/C Non-Small-Cell Lung Cancer Patients into Three Prognostic Groups: A Propensity Score-Matching Analysis

Utility of the Systemic Inflammation Response Index as a Predictor of Pneumonia After Spontaneous Intracerebral Hemorrhage

OBJECTIVE

We sought to determine whether the initial Systemic Inflammatory Response Index (SIRI) was associated with pneumonia after spontaneous intracerebral hemorrhage (SICH) in hospitalized patients.

PATIENTS AND METHODS

Patients with SICH admitted to Taizhou People's Hospital between January 2019 and December 2021 were retrospectively analyzed. Baseline variables were compared between stroke-associated pneumonia (SAP) and non-SAP groups. Multivariable logistic regression analyses were utilized to calculate the relationship between SIRI and SAP risk.

RESULTS

Of 495 patients included in this research, 192 (38.79%) developed SAP ultimately. The SIRI values exhibited the highest area under the curve value for SAP incidence (area under the curve = 0.736, 95% CI: 0.692-0.781), with respective sensitivity and specificity values of 0.646 and 0.749 at the optimal cutoff threshold of 2.53. In multivariate analysis, high SIRI (≥2.53) was a significant independent predictor of post-SICH SAP even after controlling for other possible confounding variables (odds ratio: 5.11, 95% CI: 2.89-9.04, P < 0.001). According to the restricted cubic splines model, SAP risk increases as SIRI increases.

CONCLUSIONS

We observed that SIRI values may offer high diagnostic utility as a predictor of SAP risk among patients with SICH during the early stages of the disease.

Prognostic significance of SIRI in patients with late-stage lung adenocarcinoma receiving EGFR-TKI treatment

OBJECTIVE

In this study, we examined the relationship between the Systemic Inflammatory Response Index (SIRI) and the overall prognosis of patients with late-stage lung adenocarcinoma who harbor epidermal growth factor receptor (EGFR) mutations and are undergoing first-line treatment with EGFR-tyrosine kinase inhibitors (EGFR-TKIs).

METHODS

A cohort comprising 52 patients with late-stage lung adenocarcinoma, who received treatment at Jinzhou Central Hospital between January 2018 and December 2022, were carefully selected. Patient data spanning from pre-treatment assessments through follow-up periods were meticulously collected from electronic medical records and subsequently subjected to a comprehensive retrospective analysis. The collected data was subjected to in-depth processing and analyzed using SPSS 27.0 statistical software. To determine the optimal cut-off value of the pre-treatment SIRI, a receiver operating characteristic (ROC) curve was employed. Survival analysis was performed using the Kaplan-Meier method, and both univariate and multivariate prognostic analyses were conducted using Cox regression.

RESULTS

The optimal SIRI cut-off value was determined to be 1.659 (with a specificity of 0.964 and sensitivity of 0.652, P = 0.000). Based on this value, patients were categorized into high and low SIRI groups. Chi-squared tests demonstrated that SIRI exhibited statistically significant correlations with patient age and smoking history (P < 0.05). Survival analysis revealed that the group with a lower SIRI had a significantly extended progression-free survival (PFS) (P < 0.001). Cox univariate analysis identified hypertension, pleural metastasis, liver metastasis, and SIRI as factors associated with PFS (P < 0.05). In the subsequent multivariate analysis, liver metastasis and SIRI ≥ 1.659 (P < 0.001) were identified as independent risk factors for patients.

CONCLUSION

Pre-treatment SIRI holds predictive significance for the prognosis of patients with late-stage lung adenocarcinoma with EGFR mutations undergoing first-line treatment EGFR-TKI treatment.

High pre-chemoradiotherapy pan-immune-inflammation value levels predict worse outcomes in patients with stage IIIB/C non-small-cell lung cancer

BACKGROUND AND OBJECTIVES

We explored the prognostic usefulness of the pan-immune-inflammation value (PIV) in patients with stage IIIB/C non-small-cell lung cancer (NSCLC) who underwent concurrent chemoradiotherapy (CCRT).

METHODS AND PATIENTS

For all patients, the PIV was calculated using platelet (P), monocyte (M), neutrophil (N), and lymphocyte (L) measures obtained on the first day of CCRT: PIV = P × M × N ÷ L. Using receiver operating characteristic (ROC) curve analysis, we searched for the existence of an ideal cutoff that may partition patients into two groups with unique progression-free- (PFS) and overall survival (OS) results. The primary endpoint of this retrospective cohort research was to determine whether there were any significant relationships between pretreatment PIV measures and post-CCRT OS outcomes.

RESULTS

The present research included a total of 807 stage IIIB/C NSCLC patients. According to ROC curve analysis, the ideal PIV cutoff was 516 [area under the curve (AUC): 67.7%; sensitivity: 66.4%; specificity: 66.1%], which divided the whole cohort into two: low PIV (L-PIV: PIV < 516; N = 436) and high PIV (H-PIV: PIV ≥ 516; N = 371). The comparisons between the PIV groups indicated that either the median PFS (9.2 vs. 13.4 months; P < 0.001) or OS (16.7 vs. 32.7 months; P < 0.001) durations in the H-PIV group were substantially inferior to their L-PIV counterpart. Apart from the H-PIV (P < 0.001), the N3 nodal stage (P = 0.006), IIIC disease stage (P < 0.001), and receiving only one cycle of concurrent chemotherapy (P = 0.005) were also determined to be significant predictors of poor PFS (P < 0.05, for each) and OS (P < 0.05, for each) outcomes in univariate analysis. The multivariate analysis findings revealed that all four variables had independent negative impacts on PFS (P < 0.05, for each) and OS (P < 0.05, for each).

CONCLUSIONS

The findings of this hypothesis-generating retrospective analysis claimed that the novel PIV was an independent and steadfast predictor of PFS and OS in stage IIIB/C NSCLC patients.

The Prognostic Value of the Novel Global Immune-Nutrition-Inflammation Index (GINI) in Stage IIIC Non-Small Cell Lung Cancer Patients Treated with Concurrent Chemoradiotherapy

BACKGROUND

We sought to determine the prognostic value of the newly developed Global Immune-Nutrition-Inflammation Index (GINI) in patients with stage IIIC non-small cell lung cancer (NSCLC) who underwent definitive concurrent chemoradiotherapy (CCRT).

METHODS

This study was conducted on a cohort of 802 newly diagnosed stage IIIC NSCLC patients who underwent CCRT. The novel GINI created first here was defined as follows: GINI = [C-reactive protein × Platelets × Monocytes × Neutrophils] ÷ [Albumin × Lymphocytes]. The receiver operating characteristic (ROC) curve analysis was used to determine the optimal pre-CCRT GINI cut-off value that substantially interacts with the locoregional progression-free (LRPFS), progression-free (PFS), and overall survival (OS).

RESULTS

The optimal pre-CCRT GINI cutoff was 1562 (AUC: 76.1%; sensitivity: 72.4%; specificity: 68.2%; Youden index: 0.406). Patients presenting with a GINI ≥ 1562 had substantially shorter median LRPFS (13.3 vs. 18.4 months; p < 0.001), PFS (10.2 vs. 14.3 months; p < 0.001), and OS (19.1 vs. 37.8 months; p < 0.001) durations than those with a GINI < 1562. Results of the multivariate analysis revealed that the pre-CCRT GINI ≥ 1562 (vs. <1562), T4 tumor (vs. T3), and receiving only 1 cycle of concurrent chemotherapy (vs. 2-3 cycles) were the factors independently associated with poorer LRPS (p < 0.05 for each), PFS (p < 0.05 for each), and OS (p < 0.05 for each).

CONCLUSION

The newly developed GINI index efficiently divided the stage IIIC NSCLSC patients into two subgroups with substantially different median and long-term survival outcomes.

Prognosis and complications of patients with primary gastrointestinal diffuse large B-cell lymphoma: Development and validation of the systemic inflammation response index-covered score

BACKGROUND

This study aimed to evaluate the predictive value of systemic inflammation response index (SIRI) in primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL) patients and establish a highly discriminating risk prediction model.

METHODS

This retrospective analysis included 153 PGI-DCBCL patients diagnosed between 2011 and 2021. These patients were divided into a training set (n = 102) and a validation set (n = 51). Univariate and multivariate Cox regression analyses were conducted to examine the significance of variables on overall survival (OS) and progression-free survival (PFS). An inflammation-covered score system was established according to the multivariate results.

RESULTS

The presence of high pretreatment SIRI (≥1.34, p < 0.001) was significantly associated with poorer survival and identified as an independent prognostic factor. Compared with NCCN-IPI, the prognostic and discriminatory capability of the novel model SIRI-PI showed a more precise high-risk assessment with a higher area under the curve (AUC) (0.916 vs 0.835) and C-index (0.912 vs 0.836) for OS in the training cohort, and similar results were obtained in the validation cohort. Moreover, SIRI-PI also showed good discriminative power for efficacy assessment. This new model identified patients at risk of developing severe gastrointestinal complications following chemotherapy.

CONCLUSIONS

The results of this analysis suggested that the pretreatment SIRI may be a potential candidate for identifying patients with a poor prognosis. And we established and validated a better-performing clinical model, which facilitated the prognostic stratification of PGI-DLBCL patients and can serve as a reference for clinical decision-making.

The clinical value of neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) for predicting the occurrence and severity of pneumonia in patients with intracerebral hemorrhage

Background

Inflammatory mechanisms play important roles in intracerebral hemorrhage (ICH) and have been linked to the development of stroke-associated pneumonia (SAP). The neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) are inflammatory indexes that influence systemic inflammatory responses after stroke. In this study, we aimed to compare the predictive value of the NLR, SII, SIRI and PLR for SAP in patients with ICH to determine their application potential in the early identification of the severity of pneumonia.

Methods

Patients with ICH in four hospitals were prospectively enrolled. SAP was defined according to the modified Centers for Disease Control and Prevention criteria. Data on the NLR, SII, SIRI and PLR were collected at admission, and the correlation between these factors and the clinical pulmonary infection score (CPIS) was assessed through Spearman's analysis.

Results

A total of 320 patients were enrolled in this study, among whom 126 (39.4%) developed SAP. The results of the receiver operating characteristic (ROC) analysis revealed that the NLR had the best predictive value for SAP (AUC: 0.748, 95% CI: 0.695-0.801), and this outcome remained significant after adjusting for other confounders in multivariable analysis (RR=1.090, 95% CI: 1.029-1.155). Among the four indexes, Spearman's analysis showed that the NLR was the most highly correlated with the CPIS (r=0.537, 95% CI: 0.395-0.654). The NLR could effectively predict ICU admission (AUC: 0.732, 95% CI: 0.671-0.786), and this finding remained significant in the multivariable analysis (RR=1.049, 95% CI: 1.009-1.089, P=0.036). Nomograms were created to predict the probability of SAP occurrence and ICU admission. Furthermore, the NLR could predict a good outcome at discharge (AUC: 0.761, 95% CI: 0.707-0.8147).

Conclusions

Among the four indexes, the NLR was the best predictor for SAP occurrence and a poor outcome at discharge in ICH patients. It can therefore be used for the early identification of severe SAP and to predict ICU admission.

Levels of systemic inflammation response index are correlated with tumor-associated bacteria in colorectal cancer

The relationship between systemic inflammation and tumor-associated bacteria is largely unknown in colorectal cancer (CRC). The primary aim of this study was to investigate the prognostic effects of the systemic inflammation response index (SIRI) on the survival outcomes of CRC patients who experienced surgical therapy, and the second aim was to reveal the potential association between SIRI levels and tumor-associated bacteria in CRC. We recruited a cohort of 298 CRC patients who experienced surgical resection in Wuhan Union Hospital. These patients were assigned to the low and high groups based on the cut-off value of SIRI. We utilized 1:1 propensity score matching (PSM) to reduce the potential confounding factors between the low SIRI group (N = 83) and the high SIRI group (N = 83). The total DNA of 166 paraffin-embedded tumor tissues and 24 frozen tumor tissues was extracted and amplified, and 16 S rRNA sequencing was employed to uncover the composition of microbiota between low and high SIRI groups. Survival analysis uncovered that the high SIRI cohort exhibited significantly shorter overall and disease-free survival time than low SIRI companions after PSM. The ROC analyses showed that the prediction abilities of SIRI were much higher than other serum inflammatory biomarkers for survival outcomes. The microbial richness and diversity in the low SIRI group were remarkably higher than those in the high SIRI group. At the phylum level, we found that Proteobacteria, Synergistetes, WPS-2, Thermil, Fusobacteria were enriched in the high SIRI group. Cupriavidus, Thermus, Ochrobactrum, Cupriavidus, Acidovorax were enriched in the high SIRI group at the genus level. 16 S rRNA based on frozen samples also obtained similar results. SIRI is a promising and novel prognostic biomarker among CRC sufferers who underwent surgical removal. There existed significant differences in the diversity and compositions of tumor-associated bacteria between the low and high SIRI groups.

Inflammatory response biomarkers nomogram for predicting pneumonia in patients with spontaneous intracerebral hemorrhage

Objectives

Inflammatory response biomarkers are promising prognostic factors to improve the prognosis of stroke-associated pneumonia (SAP) after ischemic stroke. This study aimed to investigate the prognostic significance of inflammatory response biomarkers on admission in SAP after spontaneous intracerebral hemorrhage (SICH) and establish a corresponding nomogram.

Methods

The data of 378 patients with SICH receiving conservative treatment from January 2019 to December 2021 at Taizhou People's Hospital were selected. All eligible patients were randomized into the training (70%, 265) and validation cohorts (30%, 113). In the training cohort, multivariate logistic regression analysis was used to establish an optimal nomogram, including inflammatory response biomarkers and clinical risk factors. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram's discrimination, calibration, and performance, respectively. Moreover, this model was further validated in a validation cohort.

Results

A logistic regression analysis showed that intraventricular hemorrhage (IVH), hypertension, dysphagia, Glasgow Coma Scale (GCS), National Institute of Health Stroke Scale (NIHSS), systemic inflammation response index (SIRI), and platelet/lymphocyte ratio (PLR) were correlated with SAP after SICH (P < 0.05). The nomogram was composed of all these statistically significant factors. The inflammatory marker-based nomogram showed strong prognostic power compared with the conventional factors, with an AUC of 0.886 (95% CI: 0.841-0.921) and 0.848 (95% CI: 0.799-0.899). The calibration curves demonstrated good homogeneity between the predicted risks and the observed outcomes. In addition, the model has a significant net benefit for SAP, according to DCA. Also, internal validation demonstrated the reliability of the prediction nomogram. The length of hospital stay was shorter in the non-SAP group than in the SAP group. At the 3-month follow-up, clinical outcomes were worse in the SAP group (P < 0.001).

Conclusion

SIRI and PLR at admission can be utilized as prognostic inflammatory biomarkers in patients with SICH in the upper brain treated with SAP. A nomogram covering SIRI and PLR can more accurately predict SAP in patients' supratentorial SICH. SAP can influence the length of hospital stay and the clinical outcome.

Prognostic value of preoperative modified Glasgow prognostic score in surgical non-small cell lung cancer: A meta-analysis

Background and purpose

The predictive role of modified Glasgow prognostic score (mGPS) for long-term survival in several types of cancers has been well manifested. We supposed that preoperative mGPS might also be associated with long-term survival of operated non-small cell lung cancer (NSCLC) patients. The aim of this meta-analysis was to identify the prognostic value of preoperative mGPS in surgical NSCLC patients.

Methods

The PubMed, Web of Science, EMBASE and CNKI databases were searched for relevant studies up to November 7, 2022. The primary and secondary outcomes were overall survival (OS) and disease-free survival (DFS), respectively. The hazard ratios (HRs) and 95% confidence intervals (CIs) were combined.

Results

A total of 3,803 patients from 11 studies were enrolled and analyzed. The combined results demonstrated elevated preoperative mGPS was significantly related to poorer OS (HR = 2.11, 95% CI: 1.83-2.44, P < 0.001) and DFS (HR = 1.70, 95% CI: 1.42-2.03, P < 0.001). Subgroup analysis for the OS further identified the predictive role of elevated preoperative mGPS for worse OS in NSCLC.

Conclusion

Preoperative mGPS was significantly associated with prognosis in NSCLC and patients with elevated preoperative mGPS experienced poorer long-term survival.

Prognostic Value of Inflammatory Markers in Nasopharyngeal Carcinoma Patients in the Intensity-Modulated Radiotherapy Era

Purpose

Inflammatory markers have been widely used in various cancers, but rarely in nasopharyngeal carcinoma (NPC). Here, we evaluated the prognostic value of pretreatment neutrophil-to-lymphocyte ratio (NLR), platelet-lymphocyte-ratio (PLR), systemic immune index (SII), and systemic inflammation response index (SIRI) on NPC in the intensity-modulated radiotherapy (IMRT) era.

Methods

We retrospectively analyzed data from NPC patients from the Renmin Hospital of Wuhan University, between January 2012 and July 2020. We used Chi-square test or Fisher’s exact test to compare the baseline characteristics, then applied Kaplan–Meier (K-M) survival analysis to compare the overall survival (OS) and progression-free survival (PFS) rates. Multivariate Cox proportional risk models were applied to identify independent prognostic factors.

Results

We enrolled a total of 342 NPC patients and found optimal cut-off values of 2.65, 184.91, 804.08, and 1.34 for NLR, PLR, SII, and SIRI, respectively. K-M survival analysis revealed that high NLR, PLR, SII, and SIRI were significantly associated with worse OS and PFS relative to those in the low groups. Results from univariate Cox analysis showed that clinical, T, and M stages, as well as NLR, PLR, SII, and SIRI were associated with OS, whereas age, alongside the aforementioned parameters, was associated with PFS. Moreover, multivariate Cox analysis showed that age ≥49 years (HR=2.48, 95% CI=1.21–5.05, P=0.013) and M1 stage (HR=3.84, 95% CI=1.52–9.73, P=0.013) were independent prognostic factors for OS, whereas SIRI ≥1.34 (HR=1.91, 95% CI=1.05–3.47, P=0.034) and M1 stage (HR=2.91, 95% CI=1.44–5.86, P=0.003) were independent prognostic factors for PFS.

Conclusion

Overall, our findings indicated that high NLR, PLR, SII, and SIRI were significantly associated with poor OS and PFS in NPC patients. High SIRI may be an independent risk factor for PFS of NPC patients in the IMRT era.