Predictive value of immune-inflammation indices in metabolic response and outcome after curative radiotherapy in patients with non-small cell lung cancer

Prognostic value of neutrophil-to-lymphocyte ratio change in patients with locally advanced non-small cell lung cancer treated with thoracic radiotherapy

In prior investigations, a correlation was established between patient outcomes in locally advanced non-small cell lung cancer (LA-NSCLC) following thoracic irradiation and parameters, such as pre/post-treatment neutrophil-to-lymphocyte ratio (NLR) and NLR change (ΔNLR). However, these parameters could potentially be influenced by radiation-related variables, such as gross tumor volume (GTV). The primary aim of this study was to elucidate the factors impacting post-treatment NLR and ΔNLR and to further assess their prognostic relevance. In this retrospective study, a cohort of 188 LA-NSCLC patients who underwent thoracic radiation between 2012 and 2017 was assessed. The calculation of pre/post-treatment NLR involved the use of absolute neutrophil and lymphocyte counts. ΔNLR was defined as the difference between post- and pre-treatment NLR values. To assess the relationships between various variables and overall survival (OS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS), the Kaplan-Meier technique and Cox proportional hazards regression were employed. Additionally, Spearman's rank correlation analysis was carried out to investigate correlations between the variables. The analysis revealed that both post-treatment NLR (r = 0.315, P < 0.001) and ΔNLR (r = 0.156, P = 0.032) were associated with GTV. However, OS, LPFS, and DMFS were not independently correlated with pre/post-treatment NLR. ΔNLR, on the other hand, exhibited independent associations with OS and DMFS (HR = 1.054, P = 0.020, and P = 0.046, respectively). Elevated ΔNLR values were linked to poorer OS (P = 0.023) and DMFS (P = 0.018) in the Kaplan-Meier analysis. Furthermore, when stratifying by GTV, a higher ΔNLR remained to be associated with worse OS and DMFS (P = 0.047 and P = 0.035, respectively) in the GTV ≤ 67.41 cm3 group, and in the GTV > 67.41 cm3 group (P = 0.028 and P = 0.042, respectively), highlighting ΔNLR as the sole independent predictive factor for survival and metastasis, irrespective of GTV.

Prediction of severe radiation-induced oral mucositis in locally advanced nasopharyngeal carcinoma using the combined systemic immune-inflammatory index and prognostic nutritional index

OBJECTIVE

Severe radiation-induced oral mucositis (sRIOM) can seriously affect patients' quality of life and treatment compliance. This study was to investigate the utility of the systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI) in predicting sRIOM in patients with locally advanced nasopharyngeal carcinoma (LANPC).

METHODS

295 patients with LANPC were retrospectively screened. The pre-radiotherapy SII and PNI were calculated based on peripheral blood samples. A receiver operating characteristic (ROC) curve was used to determine the cut-off value. Logistic regression was used for univariate and multivariate analyses. Patients were classified into three groups based on the SII-PNI score: score of 2, high SII (> cut-off value) and low PNI (≤ cut-off value); score of 1, either high SII or low PNI; score of 0, neither high SII nor low PNI.

RESULTS

The SII-PNI demonstrated significant predictive ability for sRIOM occurrence, as evidenced by an area under the curve (AUC) of 0.738. The incidence rates of sRIOM with SII-PNI score of 2, 1, and 0 were 73.86%, 44.35%, and 18.07%, respectively. Multivariate analysis confirmed that the SII-PNI score was an independent risk factor for sRIOM.

CONCLUSION

The SII-PNI score is a reliable and convenient indicator for predicting sRIOM in patients with LANPC.

Development and validation of a prognostic nomogram model in locally advanced NSCLC based on metabolic features of PET/CT and hematological inflammatory indicators

BACKGROUND

We combined the metabolic features of 18F-FDG-PET/CT and hematological inflammatory indicators to establish a predictive model of the outcomes of patients with locally advanced non-small cell lung cancer (LA-NSCLC) receiving concurrent chemoradiotherapy.

RESULTS

A predictive nomogram was developed based on sex, CEA, systemic immune-inflammation index (SII), mean SUV (SUVmean), and total lesion glycolysis (TLG). The nomogram presents nice discrimination that yielded an AUC of 0.76 (95% confidence interval: 0.66-0.86) to predict 1-year PFS, with a sensitivity of 63.6%, a specificity of 83.3%, a positive predictive value of 83.7%, and a negative predictive value of 62.9% in the training set. The calibration curves and DCA suggested that the nomogram had good calibration and fit, as well as promising clinical effectiveness in the training set. In addition, survival analysis indicated that patients in the low-risk group had a significantly longer mPFS than those in the high-risk group (16.8 months versus 8.4 months, P < 0.001). Those results were supported by the results in the internal and external test sets.

CONCLUSIONS

The newly constructed predictive nomogram model presented promising discrimination, calibration, and clinical applicability and can be used as an individualized prognostic tool to facilitate precision treatment in clinical practice.

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.

Dynamic changes in the systemic immune-inflammation index predict the prognosis of EGFR-mutant lung adenocarcinoma patients receiving brain metastasis radiotherapy

BACKGROUND

The systemic immune-inflammation index (SII) has recently emerged as a predictor of survival in non-small cell lung cancer patients. There is also tight correlation between radiotherapy and immune status, and brain metastases (BM) radiotherapy is an important treatment in patients with BM from lung adenocarcinoma harboring epidermal growth factor receptor (EGFR) mutations. Hence, this study aimed to present the prognostic value of SII and its dynamic changes during BM radiotherapy in EGFR-mutant lung adenocarcinoma patients with BM.

METHODS

Patients with EGFR-mutant lung adenocarcinoma who received BM radiotherapy between November 2011 and April 2021 were included in this retrospective study. The SII was calculated using data acquired within 1 week before the start of radiation treatment and 1 week before its completion. According to the cutoff value of SII before radiation treatment determined using receiver operating characteristic curve analyses, we divided the patients into a high group and a low group. Patients were further classified into high-high, high-low, low-low, and low-high groups based on dynamic changes in SII. Prognostic values of the SII and other factors were determined using the Kaplan-Meier method, as well as univariate and multivariate Cox analysis.

RESULTS

A total of 202 patients met the inclusion criteria, and the median overall survival (OS) of the entire cohort was 36 months. According to the SII cutoff of 859.79, an SII value below this cutoff was associated with longer OS (hazard ratio 0.6653, 95% confidence interval 0.4708-0.9402, P < 0.05). The patients in the low-low group, whose SII within 1 week before the start and end of BM radiotherapy were below the cutoff, had a median OS of 55.2 months, which was significantly longer than the OS in all other groups (P < 0.05). Univariate and multivariate analyses confirmed that dynamic SII change (P = 0.032), Lung-molGPA (P < 0.001), and thoracic radiation (P = 0.048) were independently correlated with OS.

CONCLUSIONS

The SII and its dynamic change may have a prognostic value in patients with EGFR-mutant lung adenocarcinoma treated with BM radiotherapy.

Systemic Immune-Inflammation Index Is a Prognostic Factor for Breast Cancer Patients After Curative Resection

Background

The preoperative systemic immune-inflammation index (SII) is correlated with prognosis in several malignancies. The aim of this study was to investigate the prognosis value of SII in patients with resected breast cancer.

Materials and Methods

A total of 784 breast cancer patients who underwent surgical resection were consecutively investigated. The optimal cutoff value of SII was evaluated using the receiver operating characteristic (ROC) curve. The collection of SII with clinicopathological characteristic and prognosis was further evaluated.

Results

The optimal cutoff value for SII in the prediction of survival was 514 according to ROC curve analysis. A high SII was significantly correlated with younger age (P = 0.037), PR status (P < 0.001), and HER2 status (P = 0.035). Univariate analysis revealed that SII (P < 0.001), T-stage (P < 0.001), lymph node involvement post-surgery (P = 0.024), and histological grade (P < 0.001) were significantly related to DFS, and SII (P < 0.001), T-stage (P = 0.003), lymph node involvement post-surgery (P = 0.006), and histological grade (P < 0.001) were significantly associated with OS. In multivariate analysis, a high SII was an independent worse prognostic factor for DFS (HR, 4.530; 95% CI, 3.279-6.258; P < 0.001) and OS (HR, 3.825; 95% CI, 2.594-5.640; P < 0.001) in all the enrolled patients. Furthermore, subgroup analysis of molecular subtype revealed that SII was significantly associated with prognosis in all subtypes.

Conclusion

Preoperative SII is a simple and useful prognostic factor for predicting long-term outcomes for breast cancer patients undergoing surgery.

Prognostic impact of immune inflammation biomarkers in predicting survival and radiosensitivity in patients with non-small-cell lung cancer treated with chemoradiotherapy

INTRODUCTION

The purpose of this retrospective study was to investigate the prognostic impact of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), derived NLR (dNLR) and systemic immune-inflammation index (SII) in predicting outcomes for patients with locally advanced non-small-cell lung cancer (NSCLC). The secondary endpoint was to evaluate the radiosensitivity in terms of response rate.

METHODS

Newly diagnosed locally advanced NSCLC patients were enrolled. Immune inflammation biomarkers were calculated from baseline blood samples. Patients were stratified in two groups based on optimal cut-off values for each biomarker. The associations between biomarkers and overall survival (OS), progression-free survival (PFS), local regional recurrence-free survival (LRRFS), and also response to radiotherapy were analysed.

RESULTS

A total of 392 patients were included. Five-year OS, PFS and LRRFS rates were 14.6%, 12.1%, and 13.4% respectively. Optimal cut-off values for NLR, PLR, dNLR and SII were 3.07, 166, 2.02 and 817 respectively. Low NLR (HR 1.73, 95% CI 1.34-2.24, P < 0.001), low PLR (HR 1.37, 95% CI 1.06-1.76, P = 0.013), low dNLR (HR 1.66, 95% CI 1.29-2.13, P < 0.001) and low SII (HR 1.63, 95% CI 1.18-2.04, P < 0.001) were independent prognostic factors for OS. Low NLR, PLR, dNLR and SII were also significant prognostic factors for PFS and LRRFS. Low NLR, low dNLR and low SII groups had better radiosensitivity than compared with high NLR, high dNLR and high SII groups (P = 0.001, P = 0.001 and P = 0.012).

CONCLUSION

NLR, PLR, dNLR and SII were independently associated with improved OS, PFS and LRRFS. Low NLR, dNLR and SII groups had better radiosensitivity. Immune inflammation biomarkers are promising prognostic predictors which can be obtained easily and inexpensively.

Using the Systemic Immune-Inflammation Index (SII) as a Mid-Treatment Marker for Survival among Patients with Stage-III Locally Advanced Non-Small Cell Lung Cancer (NSCLC)

The Systemic Immune-Inflammation Index (SII) is an important marker of immune function, defined as the product of neutrophil-to-lymphocyte ratio (NLR) and platelet count (P). Higher baseline SII levels have been associated with improved survival in various types of cancers, including lung cancer. Data were obtained from PROCLAIM, a randomized phase III trial comparing two different chemotherapy regimens pemetrexed + cisplatin (PEM) vs. etoposide + cisplatin (ETO), in combination with radiotherapy (RT) for the treatment of stage III non-squamous non-small cell lung cancer (NSCLC). We aimed to determine if SII measured at the mid-treatment window for RT (weeks 3-4) is a significant predictor of survival, and if the effect of PEM vs. ETO differs by quartile (Q) level of SII. Hazard-ratios (HR) for survival were estimated using a proportional hazards model, accounting for the underlying correlated structure of the data. A total of 548 patients were included in our analysis. The median age at baseline was 59 years. Patients were followed for a median of 24 months. Adjusting for age, body mass index, sex, race, and chemotherapy regimen, SII was a significant mid-treatment predictor of both overall (adjusted HR (aHR) = 1.6, p < 0.0001; OS) and progression-free (aHR = 1.3, p = 0.0072; PFS) survival. Among patients with mid-RT SII values above the median (6.8), those receiving PEM (vs. ETO) had superior OS (p = 0.0002) and PFS (p = 0.0002). Our secondary analysis suggests that SII is an informative mid-treatment marker of OS and PFS in locally advanced non-squamous NSCLC.