Background/Objectives: Genomic profiling guides treatment in metastatic non-small-cell lung cancer (mNSCLC), yet country-level data from Türkiye remain limited. Methods: We retrospectively analyzed consecutive patients with mNSCLC diagnosed between January 2018 and March 2025 across tertiary centers in all seven regions. Variables included demographics, smoking, histology, testing modality (single-gene vs. next-generation sequencing [NGS]), targetable genomic alterations (TGAs) and co-mutations, and programmed death-ligand 1 (PD-L1) tumor proportion score. Results: Among 1023 patients (mean age 64 years; 76.4% male), tobacco exposure was frequent (mean 42.1 pack-years); 16.9% were never-smokers. NGS use increased over time, exceeding 90% by 2025. TGAs were detected in 28.3% (EGFR 16.0%, ALK 5.0%, KRAS G12C 2.6%, BRAF V600E 3.2%; ROS1, MET exon 14, HER2, NTRK ≤ 2.5%; no RET). EGFR alterations occurred in 19% of non-squamous carcinomas and 6% of squamous cell carcinomas (SCCs), suggesting an intermediate East–West pattern. Among NGS-tested samples, TP53 was the most frequent co-mutation (33.1%), followed by alterations in CDKN2A, PIK3CA, FGFR, STK11, and KEAP1. Conclusions: In this large, multicenter Turkish real-world cohort, the TGA spectrum broadly mirrors global patterns while revealing local nuances; EGFR mutations were more frequent than expected in SCC, and nationwide NGS adoption is accelerating. Limitations include retrospective design, non-centralized PD-L1 testing, and missing data. Prospective, standardized studies integrating outcomes and resistance mechanisms are warranted to refine regional precision oncology.

Introduction: This study aims to assess the impact of malnutrition and frailty on morbidity and mortality in geriatric patients in the internal intensive care unit. Materials and Method: The study is prospective, descriptive, and cross-sectional in design, conducted at intensive care unit. Demographic data, anthropometric measurements, clinical evaluations, and laboratory parameters are recorded for each patient. Various nutritional screening tools such as the modified NUTRIC score, Subjective Global Assessment, Nutritional Risk Screening, Mini Nutritional Assessment - Short Form, and frailty assessment scales like Edmonton Frailty Scale and Clinical Frailty Scale are used. Results: The patients were divided into two groups: survivors and non-survivors. The mean Nutritional Risk Screening -2002 score was 5.20±0.70 for the survivors group and 6.15±0.57 for the non-survivors group (p<0.001). The mean Mini Nutritional Assessment - Short Form score was 8.20±0.82 for the survivors group and 6.46±1.02 for the non-survivors group (p<0.001). According to the modified NUTRIC score, 40 patients (97.6%) in the non-survivors group were at high risk of malnutrition (p<0.001). According to the Edmonton Frailty Score, in the non-survivors group, 1 patient (2.4%) was classified as light frail, 21 patients (51.2%) as mild frail, and 19 patients (46.3%) as severe frail (p<0.001). The mean Clinical Frailty Score was 5.89±0.99 for the survivors group and 8.0±0.0 for the non-survivors group (p<0.001). Conclusion: Due to the significant prevalence of malnutrition and frailty in the critical patient population being monitored in the intensive care unit, both conditions should be regularly assessed. Keywords: Intensive Care Unit; Malnutrition; Frailty; Mortality; Geriatrics.

Background and Objectives: Clinical outcomes remain markedly heterogeneous in glioblastoma, isocitrate dehydrogenase (IDH)-wildtype, despite contemporary molecular classification and established clinicopathological risk factors. We investigated whether the pretreatment lactate dehydrogenase-to-albumin ratio (LAR), an accessible circulating index integrating systemic disease- and host-related information, provides complementary prognostic information. Materials and Methods: We retrospectively evaluated 134 patients with glioblastoma, IDH-wildtype, central nervous system (CNS) World Health Organization (WHO) grade 4. An exploratory, cohort-specific LAR threshold was derived for 12-month overall survival (OS) and retained without re-optimization across subsequent analyses. Associations with OS and progression-free survival (PFS) were evaluated using Cox regression, and incremental prognostic performance was assessed against a baseline clinicopathological model. Temporal and continuous associations with survival, internal model validation, and the relationship between LAR and treatment response during adjuvant temozolomide therapy were also examined. Results: The cohort-derived LAR threshold was 5.718. High pretreatment LAR was associated with shorter median OS (5.5 vs. 16.0 months) and PFS (5.2 vs. 10.6 months; both p < 0.001) and remained independently associated with OS (adjusted hazard ratio [HR], 4.51; 95% CI, 2.84–7.18) and PFS (adjusted HR, 3.60; 95% CI, 2.33–5.56). Adding LAR to the clinicopathological model increased Harrell’s C-index from 0.699 to 0.760 for OS and from 0.690 to 0.759 for PFS (both likelihood ratios, p < 0.001), with optimism-corrected C-indices of 0.743 and 0.742, respectively. Prognostic discrimination and adjusted effect estimates were greatest early in the follow-up period and attenuated over time, whereas continuous LAR showed nonlinear associations with both endpoints. Among the 104 patients who received adjuvant temozolomide, a high LAR was independently associated with progressive disease (adjusted odds ratio, 3.72; 95% CI, 1.28–10.81). Conclusions: Pretreatment LAR identified patients with IDH-wildtype glioblastoma who experienced poorer survival, and the prognostic effect was concentrated predominantly in the early disease course. Its incremental contribution beyond conventional clinicopathological characteristics supports the further evaluation of LAR as an accessible component of baseline risk characterization. However, independent external validation is required before clinical application.

Introduction: Predicting Air-Leak (AL) syndrome and knowing its risk factors in critically ill patients with Coronavirus Disease-2019 (COVID-19) can reduce morbidity and mortality. In this study, we aimed to investigate whether the thorax computed tomography severity score (CT-SS) can predict the development of AL. Methods and Materials: COVID-19 patients were divided into two groups based on whether they developed AL syndrome. CT-SS was calculated for all patients. The predictive power of CT-SS for the development of AL syndrome and possible risk factors for AL were investigated. Results: AL syndrome developed in 52 out of 272 patients included in the study (19.1%). The median CT-SS was significantly higher in the AL group. The CT-SS value in the AL group was 19 (2-25), while it was 13 (1-25) in the non-AL group (p-value <0.001). CT-SS was found to have good diagnostic performance in predicting the occurrence of AL (p<0.001). When comparing the ICU mortality rates of the groups, it was 42.3% in the non-AL group and 88.5% in the AL group. Discussion and Conclusion: CT-SS may have predictive potential for the development of AL syndrome associated with COVID-19. However, further studies are needed in this area.