Background and Objectives: The systemic immune-inflammation index (SII), derived from peripheral blood parameters, has emerged as a novel marker reflecting the balance between host immunity and tumor-related inflammatory burden. This study aimed to investigate the prognostic impact of baseline SII on survival outcomes in patients with gastric or gastroesophageal junction (GEJ) cancer undergoing perioperative FLOT (5-fluorouracil, leucovorin, oxaliplatin, and docetaxel) chemotherapy. Materials and Methods: In this retrospective study, 168 patients with histologically confirmed gastric or GEJ cancer who received perioperative FLOT therapy were included. SII was calculated using the formula: SII = (Platelets × Neutrophils)/Lymphocytes. ROC curve analysis determined the optimal SII cutoff for predicting mortality. Patients were categorized into low (SII ≤685) and high (SII >685) groups. Overall survival (OS) and disease-free survival (DFS) were evaluated using Kaplan–Meier analysis and compared via the log-rank test. Cox proportional hazards regression models were used for univariate and multivariate analysis. Results: The optimal cutoff value for SII was determined to be 685 (AUC: 0.652, 95% CI: 0.558–0.747, p = 0.003). High SII was significantly shorter OS (17.4 vs. 28.2 months, p = 0.001) Multivariate analysis identified high SII (HR = 1.88, 95% CI: 1.36–2.89, p = 0.039), advanced T stage (HR = 3.693, p < 0.001), poor treatment response (HR = 0.36, p < 0.001), and ECOG-PS ≥1 (HR = 3.297, p < 0.001) as independent predictors of mortality. Conclusions: Elevated baseline SII is an independent predictor of worse OS and DFS in gastric and GEJ cancer patients receiving perioperative FLOT chemotherapy. SII may serve as a practical and inexpensive biomarker to support risk stratification and personalized treatment decisions.

Background and Objectives: CRC is one of the leading causes of cancer-related deaths worldwide. New biomarkers are needed to identify the high-risk patient population after primary treatment and to personalize and perfect treatment and follow-up. Indicators of cancer-associated systemic inflammatory response, such as the LMR, have been widely investigated and have yielded conflicting results. The aim of this study was to investigate the effect of preoperative LMR on the prognosis of recurrent CRC. Materials and Methods: We included 204 patients admitted to our center for recurrent CRC between January 2010 and January 2015. Retrospectively, we investigated the preoperative LMR data and its effect on RFS and OS. Results: The cut-off value of LMR was 24.72 and, according to this value, we created two groups: LMR-H and LMR-L. There were 104 (50.9%) patients in the H group and 100 (49.1%) patients in the L group. The median OS was 38.0 months (95% confidence interval (CI): 30.66–45.33) for the L group and 49.0 months (95% CI: 44.06–53.94) for the H group. Overall population median OS was calculated as 44.0 months (95% CI: 40.1–47.8, p = 0.004). Median RFS was 21.3 months (95% CI: 18.3–24.2) for the LMR-L group and 28.39 months (95% CI: 24.9–31.8) for the LMR-H group (p = 0.004). Conclusions: The association between the LMR at diagnosis and early recurrence, as well as survival outcomes, was investigated in patients with recurrent CRC. Higher preoperative LMR levels were found to correlate with improved OS and RFS.

Objectives: This study aimed to investigate the prognostic value of the Naples Prognostic Score (NPS), a composite index of inflammation and nutrition markers, in patients with non-small cell lung cancer (NSCLC) and to assess its role in predicting survival across clinical subgroups. Methods: A retrospective analysis was conducted on 250 patients diagnosed with NSCLC between 2018 and 2023. Patients were categorized into low (≤2) and high (>2) NPS groups based on the scoring system derived from neutrophil–lymphocyte ratio (NLR), lymphocyte–monocyte ratio (LMR), serum albumin, and total cholesterol levels. Survival outcomes were analyzed using Kaplan–Meier curves, log-rank tests, and univariate and multivariate Cox regression analyses. Receiver operating characteristic (ROC) analysis was performed to determine the discriminatory ability of NPS. Results: Patients with high NPS (>2) had significantly lower overall survival (median OS: 10.4 vs. 18.2 months, p < 0.001) and progression-free survival (median PFS: 7.3 vs. 12.5 months, p < 0.001) than those with low NPS. High NPS was found to be an independent prognostic factor in multivariate Cox regression analysis (HR: 1.98, 95% CI: 1.42–2.76, p < 0.001). ROC analysis showed an AUC of 0.78 for NPS in predicting survival. Subgroup analyses demonstrated the consistent prognostic impact of high NPS across histological subtypes, TNM stages, smoking status, albumin levels, and age groups. Conclusions: NPS is an independent and practical prognostic tool in NSCLC. Its use may enhance risk stratification and support personalized treatment planning, particularly in advanced-stage patients.

Background: KRAS mutations are among the most common oncogenic drivers in non-small cell lung cancer (NSCLC), with KRAS G12C emerging as a therapeutically targetable subtype. However, the prognostic relevance of KRAS G12C compared with non-G12C mutations in patients receiving immune checkpoint inhibitors (ICIs) remains unclear. Methods: We retrospectively analyzed 80 NSCLC patients treated with ICIs between January 2020 and July 2024; data were censored on 3 July 2025. The cohort included 32 KRAS-mutant (20 G12C, 12 non-G12C) and 48 KRAS wild-type patients. Clinicopathological features, treatment details, and survival outcomes were collected. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan–Meier method, with group comparisons made using the log-rank test. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic factors. Results: Among 80 NSCLC patients treated with ICIs, the median OS and PFS were 14.3 and 8.2 months, respectively. Survival outcomes were comparable between KRAS-mutant and wild-type patients. Within the KRAS-mutant subgroup (n = 32), baseline characteristics were generally balanced between G12C (n = 20) and non-G12C (n = 12) cases, with non-significant trends toward higher metastatic burden and PD-L1 ≥ 50% in the G12C group. Median OS was significantly longer in G12C patients than in non-G12C patients (20.7 vs. 6.4 months; p = 0.021), whereas PFS did not differ significantly (10.2 vs. 3.7 months; p = 0.181). In multivariate analysis, non-G12C mutation independently predicted increased mortality risk (HR 3.35, 95% CI 1.26–8.89; p = 0.015). For PFS, recurrent disease status was associated with improved outcomes in univariate analysis (HR 0.30, 95% CI 0.09–0.94; p = 0.040), but no independent predictors were identified in multivariate modeling. Conclusions: In NSCLC patients treated with ICIs, the KRAS G12C mutation was associated with significantly improved OS compared with other KRAS subtypes, independent of clinicopathological characteristics. These findings suggest distinct biological behavior of KRAS variants in immunotherapy response and warrant further prospective validation.

Background: Metastatic pancreatic cancer carries a poor prognosis, and reliable prognostic markers are needed to guide treatment decisions. The Controlling Nutritional Status (CONUT) score and Albumin-Bilirubin (ALBI) grade are simple measures of inflammatory, nutritional, and hepatic status, but their prognostic value in metastatic pancreatic cancer remains unclear. This study aimed to evaluate the prognostic significance of CONUT and ALBI scores in patients with metastatic pancreatic cancer. Methods: This retrospective study included 192 patients with metastatic pancreatic cancer treated at Adana City Education and Research Hospital between 1 May 2019, and 1 February 2025. Baseline CONUT scores and ALBI grades were calculated. All laboratory parameters, including those used for CONUT and ALBI calculation, were obtained prior to the initiation of any systemic therapy. Overall survival (OS) was analyzed using Kaplan–Meier survival curves and multivariate Cox proportional hazards regression to assess the independent prognostic value of both indices. Results: The median OS of the cohort was 14.0 months. Patients with high CONUT scores had significantly shorter OS compared to those with low–moderate scores (7.8 vs. 14.0 months, p < 0.001). Similarly, ALBI Grade 2 was associated with worse survival than ALBI Grade 1 (13.0 vs. 14.0 months, p = 0.049). In multivariate Cox regression analysis, high CONUT score (HR = 5.01, 95% CI: 2.27–10.98, p < 0.001) and ALBI Grade 2 (HR = 17.86, 95% CI: 9.63–31.04, p < 0.001) remained independent predictors of poor OS. Conclusions: The CONUT and ALBI scores are independent and clinically meaningful prognostic markers in metastatic pancreatic cancer. Their routine use may support risk-adapted, personalized treatment. These readily accessible biomarkers offer a simple and accessible tool to guide clinical decisions.

Aim: This study aimed to investigate the prognostic value of the Naples Prognostic Score (NPS), a composite index of inflammation and nutrition markers, in patients with non-small cell lung cancer (NSCLC), and to assess its role in predicting survival across clinical subgroups. Materials and Methods: A retrospective analysis was conducted on 250 patients diagnosed with NSCLC between 2018 and 2023. Patients were categorized into low (≤2) and high (>2) NPS groups based on the scoring system derived from neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), serum albumin, and total cholesterol levels. Survival outcomes were analyzed using Kaplan-Meier curves, log-rank tests, and univariate and multivariate Cox regression analyses. Receiver operating characteristic (ROC) analysis was performed to determine the discriminatory ability of NPS. Results: Patients with high NPS (>2) had significantly lower overall survival (median OS: 10.4 vs. 18.2 months, p< 0.001) and progression-free survival (median PFS: 7.3 vs. 12.5 months, p< 0.001) than those with low NPS. High NPS was found to be an independent prognostic factor in multivariate Cox regression analysis (HR: 1.98, 95% CI: 1.42–2.76, p< 0.001). ROC analysis showed an AUC of 0.78 for NPS in predicting survival. Subgroup analyses demonstrated the consistent prognostic impact of high NPS across histological subtypes, TNM stages, smoking status, albumin levels, and age groups. Conclusion: NPS is an independent and practical prognostic tool in NSCLC. Its use may enhance risk stratification and support personalized treatment planning, particularly in advanced-stage patients.