Objective: Inflammatory biomarkers have been shown to possess both prognostic and predictive significance in various cancers. Among the emerging biomarkers, the pan-immune-inflammation value (PIV) has recently been introduced as a novel indicator representing both the immune response and the systemic inflammatory state. This study aims to comprehensively evaluate the predictive value of inflammatory biomarkers on survival outcomes in cervical cancer patients undergoing chemoradiotherapy. Methods: A total of 90 patients who had undergone chemoradiotherapy for cervical cancer were included. Data on demographics, treatment protocols, pre-treatment blood parameters, and survival outcomes were collected. The association between inflammatory biomarkers and survival outcomes was investigated through univariate and multivariate analyses. Results: The univariate analysis identified the following as predictors of progression-free survival (PFS): neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), monocyte–lymphocyte ratio (MLR), systemic immune-inflammation index (SII), PIV, C-reactive protein (CRP), albumin, and tumor size. Multivariate analysis revealed that only the PIV significantly predicted PFS (HR 3.05, 95% CI 1.0 to 9.3, p = 0.04). In the univariate analysis, several variables were predictive of overall survival (OS), including NLR, PLR, MLR, SII, PIV, CRP, LDH, albumin, tumor size, and Eastern Cooperative Oncology Group Performance Status (ECOG PS). Multivariate analysis revealed CRP (HR 3.41, 95% CI 1.5 to 7.7, p = 0.003) and ECOG PS (HR 4.78, 95% CI 1.3 to 17.3, p = 0.01) predictive of OS, with PIV approaching statistical significance (HR 2.56, 95% CI 0.8 to 7.6, p = 0.09). Conclusions: This study provides the first comprehensive analysis of the association between cervical cancer and various inflammatory biomarkers. Many of these biomarkers have demonstrated predictive value for survival outcomes in patients with cervical cancer undergoing definitive chemoradiotherapy. Among the biomarkers evaluated, CRP and PIV were identified as the most predictive, warranting further exploration in future research.

Objectives: The principal objective of this study was to assess the predictive efficacy of the global immune–nutrition–inflammation index (GINI) and the albumin–bilirubin (ALBI) score among patients receiving chemoradiotherapy for esophageal cancer. Methods: A retrospective analysis was conducted on 46 patients who received definitive or neoadjuvant radiotherapy for esophageal cancer at our institution. Blood samples were collected from these patients prior to the initiation of radiotherapy to measure the biomarkers, including the C-reactive protein (CRP), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), monocyte–lymphocyte ratio (MLR), the global immune–nutrition–inflammation index (GINI), and the albumin–bilirubin (ALBI) grade. The predictive significance of these biomarkers for progression-free survival (PFS) and overall survival (OS) was evaluated using both univariate and multivariate Cox regression analyses. Results: The median follow-up time for this study was 19.5 months (range: 2.6–166.3 months). Univariate analysis revealed that the platelet count (p = 0.003) and monocyte count (p = 0.04) were significant predictors of PFS. In the multivariate analysis, only the platelet count (p = 0.005) remained an independent predictor of PFS. Univariate analysis demonstrated that the neutrophil count (p = 0.04), lymphocyte count (p = 0.01), NLR (p = 0.005), PLR (p = 0.004), CRP (p = 0.02), ALBI grade (p = 0.01), and GINI (p = 0.005) were significant predictors of OS. Multivariate analysis identified the GINI as a predictor of OS, approaching statistical significance (p = 0.08). Conclusion: The results of our study indicate that the pretreatment GINI and ALBI grades are significantly and independently associated with the OS rates in patients with esophageal cancer who are undergoing chemoradiotherapy.

Background and Objectives: Glioblastoma presents a significant challenge in oncology due to its aggressive nature and poor prognosis, despite advancements in treatment. This study aims to comprehensively evaluate the prognostic significance of coagulation biomarkers, including the novel albumin/D-dimer ratio, in adult glioblastoma patients. Material and Methods: This retrospective study included 74 adult glioblastoma patients who underwent Stupp protocol treatment. Blood samples were collected before radiotherapy to measure biomarkers, including prothrombin time (PT), activated partial thromboplastin time (aPTT), albumin, D-dimer, and the albumin/D-dimer ratio. The prognostic significance of these biomarkers for progression-free survival (PFS) and overall survival (OS) was assessed using both univariate and multivariate Cox regression analyses. Results: The median follow-up time was 12.2 months (range, 1–77.4 months). Univariate analysis revealed that ECOG performance status (p = 0.001), D-dimer (p = 0.03), and albumin (p = 0.001) were significant prognostic factors for PFS. Multivariate analysis identified albumin (p = 0.02) as an independent prognostic biomarker for PFS. For OS, univariate analysis showed that age (p = 0.004), ECOG performance status (p = 0.001), tumor volume (p = 0.007), extent of resection (p = 0.01), radiotherapy dose (p = 0.001), D-dimer (p = 0.02), albumin (p = 0.001), albumin/D-dimer ratio (p = 0.02), and PT (p = 0.002) were significant prognostic factors. Multivariate analysis revealed age (p = 0.04), extent of resection (p = 0.02), and PT (p = 0.04) as independent prognostic factors for OS. Conclusions: Our findings highlight the prognostic significance of coagulation biomarkers, particularly PT, D-dimer, albumin, and the albumin/D-dimer ratio, in glioblastoma. These biomarkers may serve as valuable tools for prognostic assessment and personalized treatment strategies, warranting further exploration in larger prospective studies.

Background: This retrospective study evaluated pretreatment masseter muscle index (MMI), masseter radiodensity (HUAC), and Global Immune–Nutrition–Inflammation Index (GINI) as prognostic markers in patients with laryngeal squamous cell carcinoma treated with definitive radiotherapy. Methods: MMI and HUAC were measured on simulation computed tomography, and GINI was calculated from pretreatment laboratory values. Biomarkers were analyzed continuously using Firth penalized Cox models adjusted for age, performance status, tumor site, and T and N categories. Nonlinearity was assessed using restricted cubic splines. Joint models and multiple imputation assessed robustness. HUAC associations were assessed over time. Exploratory cutoffs were derived using censoring-aware three-year time-dependent receiver operating characteristic analysis, with radiotherapy initiation as time zero. Results: Among 146 patients, 30 died and 48 experienced progression or death; GINI was available in 116. Each standard-deviation decrease in MMI was associated with worse overall survival (OS; adjusted hazard ratio 1.92, 95% confidence interval 1.21–3.05; p = 0.002) and progression-free survival (PFS; 1.91, 1.35–2.71; p < 0.001). These associations weakened after further adjustment for body mass index and concurrent systemic therapy. GINI findings were not robust in adjusted, joint, and missing-data analyses. Lower HUAC showed an exploratory association with poorer outcomes later in follow-up, based on few late events. Three-year OS/PFS estimates were 92.5%/81.1% versus 68.9%/59.5% for MMI > 2.830 versus ≤2.830 cm²/m², and 90.2%/81.9% versus 45.1%/38.0% for GINI < 139.67 versus ≥139.67. The GINI cutoff was unstable, with a 95% bootstrap interval of 20.104–180.985. Conclusions: Lower MMI showed the most consistent prognostic association. This initial evaluation of GINI in laryngeal cancer supports further investigation of its prognostic potential. HUAC findings and cohort-derived cutoffs remain exploratory and require external validation.