Clinical impact of the systemic immune-inflammation index in non-small cell lung cancer patients

Serum inflammatory marker levels in serous macular detachment secondary to diabetic macular edema

PURPOSE

To evaluate the serum inflammatory marker levels in serous macular detachment (SMD) secondary to diabetic macular edema (DME).

MATERIAL AND METHODS

Patients with DME were divided into two groups according to the presence of SMD. Group 1 consisted of 40 patients with SMD, Group 2 consisted of 40 patients without SMD, and Group 3 consisted of 40 healthy subjects. Neutrophil and mean platelet volume (MPV) were obtained from blood samples. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and the systemic immune inflammation index (SII) were calculated. In Group 1 and 2 sub-group analysis was done according to grade of diabetic retinopathy (DR) and the results were analyzed in these subgroups.

RESULTS

The neutrophils, MPV, NLR, and SII levels were significantly higher in Group 1 (p = 0.000, p = 0.004, p = 0.000, p = 0.001, respectively). In subgroup analysis; the neutrophils, NLR, and SII levels were significantly higher in patients with proliferative DR (p = 0.044, p = 0.046, p = 0.046, respectively) and the SII levels were significantly higher in patients with severe nonproliferative DR in Group 1 (p = 0.039). The mean CMT values were 548.8 ± 138.3 µm in Group 1 and 420.1 ± 112.7 µm in Group 2. The CMT values were significantly higher in Group 1 (p: 0.000). However, there was no significant correlation between the CMT values and the systemic inflamatuar markers levels (p>0.05) in both of the groups.

CONCLUSIONS

NLR and SII levels were significantly higher in DME with SMD, especially in advanced cases. Elevated serum inflammatory markers might be associated with a higher incidence of SMD.

Systemic Inflammation Index and Tumor Glycolytic Heterogeneity Help Risk Stratify Patients with Advanced Epidermal Growth Factor Receptor-Mutated Lung Adenocarcinoma Treated with Tyrosine Kinase Inhibitor Therapy

Simple Summary

Patients with advanced epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma have been known to respond to first-line tyrosine kinase inhibitor (TKI) treatment. However, a subgroup of patients are non-responsive to the treatment, with poor survival outcomes, and those who are initially responsive may still experience resistance. A reliable prognostic tool may provide a valuable direction for tailoring individual treatment strategies in this clinical setting. With this aim, the present study explores the prognostic power of the combination of the systemic inflammation index (portrayed by hematological markers) and tumor glycolytic heterogeneity (characterized by ¹⁸F-fluorodeoxyglucose positron emission tomography images). The model integrating these two biomarkers could be used to improve risk stratification, and the subsequent personalized management strategy in patients with advanced EGFR-mutated lung adenocarcinoma.

Abstract

Tyrosine kinase inhibitors (TKIs) are the first-line treatment for patients with advanced epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma. Over half of patients failed to achieve prolonged survival benefits from TKI therapy. Awareness of a reliable prognostic tool may provide a valuable direction for tailoring individual treatments. We explored the prognostic power of the combination of systemic inflammation markers and tumor glycolytic heterogeneity to stratify patients in this clinical setting. One hundred and five patients with advanced EGFR-mutated lung adenocarcinoma treated with TKIs were retrospectively analyzed. Hematological variables as inflammation-induced biomarkers were collected, including the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII). First-order entropy, as a marker of heterogeneity within the primary lung tumor, was obtained by analyzing ¹⁸F-fluorodeoxyglucose positron emission tomography images. In a univariate Cox regression analysis, sex, smoking status, NLR, LMR, PLR, SII, and entropy were associated with progression-free survival (PFS) and overall survival (OS). After adjusting for confounders in the multivariate analysis, smoking status, SII, and entropy, remained independent prognostic factors for PFS and OS. Integrating SII and entropy with smoking status represented a valuable prognostic scoring tool for improving the risk stratification of patients. The integrative model achieved a Harrell’s C-index of 0.687 and 0.721 in predicting PFS and OS, respectively, outperforming the traditional TNM staging system (0.527 for PFS and 0.539 for OS, both p < 0.001). This risk-scoring model may be clinically helpful in tailoring treatment strategies for patients with advanced EGFR-mutated lung adenocarcinoma.

Prognostic Model to Predict Overall Survival for Metastatic Non-Small Cell Lung Cancer Patients Treated With Chemotherapy Combined With Concurrent Radiation Therapy to the Primary Tumor: Analysis From Two Prospective Studies

Purpose

The role of radiotherapy, in addition to chemotherapy, has not been thoroughly determined in metastatic non-small cell lung cancer (NSCLC). The purpose of the study was to investigate the prognostic factors and to establish a model for the prediction of overall survival (OS) in metastatic NSCLC patients who received chemotherapy combined with the radiation therapy to the primary tumor.

Methods

The study retrospectively reviewed 243 patients with metastatic NSCLC in two prospective studies. A prognostic model was established based on the results of the Cox regression analysis.

Results

Multivariate analysis showed that being male, Karnofsky Performance Status score < 80, the number of chemotherapy cycles <4, hemoglobin level ≤120 g/L, the count of neutrophils greater than 5.8 ×10⁹/L, and the count of platelets greater than 220 ×10⁹/L independently predicted worse OS. According to the number of risk factors, patients were further divided into one of three risk groups: those having ≤ 2 risk factors were scored as the low-risk group, those having 3 risk factors were scored as the moderate-risk group, and those having ≥ 4 risk factors were scored as the high-risk group. In the low-risk group, 1-year OS is 67.7%, 2-year OS is 32.1%, and 3-year OS is 19.3%; in the moderate-risk group, 1-year OS is 59.6%, 2-year OS is 18.0%, and 3-year OS is 7.9%; the corresponding OS rates for the high-risk group were 26.2%, 7.9%, and 0% (P<0.001) respectively.

Conclusion

Metastatic NSCLC patients treated with chemotherapy in combination with thoracic radiation may be classified as low-risk, moderate-risk, or high-risk group using six independent prognostic factors. This prognostic model may help design the study and develop the plans of individualized treatment.