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

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.

The combined tumor-nodal glycolytic entropy improves survival stratification in nonsmall cell lung cancer with locoregional disease

“…For example, the total lesion glycolysis (TLG) is a feature frequently used to predict the survival outcomes of NSCLC [12]. Besides, 18 F-FDG PET-derived entropy links to the prognosis by featuring tumor heterogeneity, representing the tumor evolutionary process, and correlates with aggressiveness, metastatic potential, and immune evasion [13][14][15]. Therefore, heterogeneity featured by entropy portrays distinct biological meaning from intensity and volumetric features (such as TLG).…”

“…In locoregional NSCLC patients, combining the TLG from the primary tumor and metastatic nodes improves the prognostic value [18]. Currently, most studies on NSCLC have only assessed glycolytic heterogeneity of the primary tumor for prognostic evaluation [5,13,19]. Because the cancer genome evolves continuously, the primary tumor and metastatic lesions may have substantial clonal or subclonal differences [20][21][22].…”

Prognostic Value of 18F-FDG PET/CT Radiomics in Extranodal Nasal-Type NK/T Cell Lymphoma

“…Radiomics offers potential pathophysiological information through high-throughput extraction of features from medical images, quantitatively analyzes tumor heterogeneity, and selects features for constructing prognostic prediction models through specific algorithms and statistical analysis to promote the development of precise and individualized tumor treatment [ 12 13 ]. Tumor heterogeneity is a key factor in determining disease aggressiveness and is closely related to proliferation, differentiation, and metabolism [ 14 ]. Radiomics overcomes the limitations of clinical dependence on the subjective experience of diagnostic physicians and significantly expands the guiding value of medical imaging in clinical practice.…”

Genomic and Glycolytic Entropy Are Reliable Radiogenomic Heterogeneity Biomarkers for Non-Small Cell Lung Cancer

“…Higher 18 F-FDG PET-derived glycolytic activity and heterogeneity are associated with regional nodal metastasis and unfavorable survival outcomes. These features also reportedly predict pathological response after neoadjuvant chemoradiotherapy in patients with NSCLC [ 4 , 5 , 6 ]. The combination of gene tests and metabolic radiomics of 18 F-FDG PET (radiogenomics) has gained increasing attention in NSCLC research [ 7 , 8 ].…”