Breast cancer is the most common malignancy in women, with the Luminal A subtype generally associated with favorable survival. However, age and menopausal status may influence tumor biology and prognosis. To improve prediction beyond conventional models, we analyzed transcriptomic and clinical data from the METABRIC cohort. Patients with Luminal A breast cancer were stratified into premenopausal, postmenopausal–nongeriatric, and geriatric (≥70 years) groups. Differentially expressed genes (DEGs) were identified, and Boruta feature selection revealed 27 clinical and genomic variables. Random Forest, Logistic Regression, Multilayer Perceptron, and ensemble XGBoost models were trained with stratified 5-fold cross-validation, using SMOTE to correct class imbalance. Principal component analysis showed distinct clustering across age groups, while DEG analysis revealed 41 genes associated with age and survival. Key predictors included clinical variables (age, tumor size, NPI, radiotherapy) and molecular markers (ATM, HERC2, AKT2, FOXO3, CYP3A43). Among ML models, XGBoost demonstrated the highest performance (accuracy 98%, sensitivity 98%, specificity 97%, F1-score 0.99, AUC 0.86), outperforming other algorithms. These findings indicate that age-related transcriptomic changes impact survival in Luminal A breast cancer and that an ML-based integrative approach combining clinical and molecular variables provides superior prognostic accuracy, supporting its potential for clinical application.

Background and Objectives: Gastric cancer is one of the most common malignancies worldwide and continues to be associated with high mortality. The hemoglobin-to-red cell distribution width (HGB/RDW) ratio has emerged as a promising hematological prognostic biomarker in various cancers. However, its prognostic significance in patients with curative-intent resection of non-metastatic gastric cancer remains insufficiently investigated. This study aimed to evaluate the association between the pretreatment HGB/RDW ratio and progression-free survival (PFS) as well as overall survival (OS) in patients with non-metastatic gastric cancer. Materials and Methods: In this multicenter study, a total of 175 patients with non-metastatic gastric cancer who received perioperative FLOT chemotherapy (four preoperative and four postoperative cycles) and underwent curative-intent surgical resection were retrospectively analyzed. A cut-off value for the HGB/RDW ratio was calculated using receiver operating characteristic (ROC) curve analysis. Survival outcomes, including progression-free survival (PFS) and overall survival (OS), were analyzed using the Kaplan–Meier method. Multivariate Cox proportional hazards regression analysis was performed to identify independent prognostic factors. Results: Patients with an HGB/RDW ratio > 0.85 demonstrated significantly superior 2-year and 5-year OS rates (76.2% vs. 59.6% and 51.6% vs. 27.7%, respectively; p = 0.003) and PFS rates (69.4% vs. 49.6% and 53.7% vs. 36.4%, respectively; p = 0.047) compared to those with HGB/RDW ≤ 0.85. Multivariate analysis identified HGB/RDW ≤ 0.85 as an independent predictor of both increased mortality risk (HR: 1.88, 95% CI: 1.16–3.06; p = 0.011) and disease progression risk (HR: 1.79, 95% CI: 1.18–2.72; p = 0.006). Conclusions: The pretreatment HGB/RDW ratio is an independent prognostic factor for OS and PFS in patients with curative-intent resection of non-metastatic gastric cancer and may be considered a practical marker that could contribute to treatment planning in this patient population.

Background and Objectives: We evaluated the association of regional body circumferences, body mass index (BMI), and serum albumin with concurrent nutritional risk in gastric adenocarcinoma. Materials and Methods: This single-center retrospective cross-sectional study included patients assessed between January 2024 and January 2026. Nutritional risk was defined as a Nutritional Risk Screening 2002 (NRS-2002) score ≥ 3. Receiver operating characteristic analysis assessed discrimination of this screening outcome. Logistic models incorporating arm circumference alone or with albumin were evaluated in the same complete-case sample using 1000 bootstrap resamples for internal validation. Results: Among 102 patients, 100 had NRS-2002 scores and 20 (20.0%) had nutritional risk. In 95 complete cases, including 19 patients at risk, areas under the curve (AUCs) were 0.869 for arm circumference, 0.864 for BMI, and 0.858 for albumin. In the combined model, each 1-cm decrease in arm circumference and each 0.1-g/dL decrease in albumin were associated with higher odds of nutritional risk: mutually adjusted odds ratios were 1.67 (95% confidence interval [CI], 1.22–2.29) and 1.27 (95% CI, 1.08–1.51), respectively. Adding albumin improved model fit (p = 0.001). Exploratory, internally validated optimism-corrected AUCs were 0.926 for the combined model and 0.873 for arm circumference alone. Conclusions: Arm circumference and albumin were associated with NRS-2002-defined nutritional risk. The small number of outcome events, incomplete covariate information, and absence of external validation limit interpretation. These findings do not establish a diagnosis of malnutrition, improvement in screening, or clinical utility.

Background/Objectives: Metabolic syndrome (MetS) is characterized by central adiposity, metabolic dysregulation, and low-grade inflammation, but body mass index (BMI) may not fully capture body-shape variation in established MetS. We investigated whether body-shape indices were associated with complete blood count (CBC)–derived systemic inflammatory indices after accounting for BMI. Methods: In this cross-sectional study with prospective data collection, 331 adults with MetS were evaluated. Weight-adjusted waist index (WWI) was the primary anthropometric variable and systemic inflammation response index (SIRI) the primary inflammatory variable. Body roundness index (BRI), a body shape index (ABSI), conicity index, waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR) were assessed as secondary anthropometric measures, together with the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). Multivariable linear regression models were adjusted for age, sex, current smoking, and BMI. Results: WWI was not significantly associated with log-SIRI after adjustment for age, sex, current smoking, and BMI (standardized β = 0.067, 95% CI −0.052 to 0.185; p = 0.268). Adding WWI increased R² from 0.091 to 0.094 (ΔR² = 0.0034; partial R² = 0.0038). None of the secondary anthropometric–inflammatory associations was statistically significant after false discovery rate (FDR) correction. Restricted cubic spline analysis showed no evidence of a nonlinear WWI–SIRI association (P-nonlinear = 0.582). Additional covariate analyses in which C-reactive protein, diabetes, estimated glomerular filtration rate, coronary artery disease and heart failure were added separately did not materially alter the WWI estimate. Conclusions: In adults with established MetS, we did not detect significant associations between WWI or other body-shape indices and CBC-derived systemic inflammatory indices after adjustment for BMI. These findings do not exclude smaller associations that may not have been detectable in this cohort.

Background/Objectives: Pathological complete response (pCR) is an important early endpoint in HER2-positive breast cancer treated with neoadjuvant therapy. Although tumor biology is a major determinant of response, the potential contribution of host-related factors such as body composition and systemic inflammatory-nutritional status remains uncertain. This study evaluated the associations of pretreatment skeletal muscle index (SMI), myosteatosis, an imaging-defined low-SMI obesity phenotype, and hemoglobin-albumin-lymphocyte-platelet (HALP) score with pCR. Methods: This retrospective single-center study included 114 patients with HER2-positive disease documented on pretreatment biopsy who received neoadjuvant systemic therapy followed by definitive surgery. CT-based body-composition measurements at the L3 level were available in 88 patients. SMI, skeletal muscle radiodensity, myosteatosis, an imaging-defined low-SMI obesity phenotype, and pretreatment HALP score were assessed. Factors associated with pCR were evaluated using Firth penalized logistic regression. Two multivariable models incorporated body-composition variables, HALP, hormone receptor status, simplified clinical T and N categories, HER2-treatment group, age, and Ki-67. Final multivariable analyses included 80 complete cases. Results: pCR was achieved in 59 of 114 patients (51.8%). Hormone receptor-negative tumors had a higher pCR rate than hormone receptor-positive tumors (74.4% vs. 40.0%; p < 0.001). Pretreatment SMI, myosteatosis, the imaging-defined low-SMI obesity phenotype, and HALP were not significantly associated with pCR in univariable analyses. In multivariable analyses, SMI and myosteatosis were not independently associated with pCR, whereas hormone receptor positivity remained associated with lower pCR odds. The treatment-group coefficient indicated lower adjusted pCR odds with trastuzumab alone than with dual HER2 blockade; however, this estimate was based on sparse complete-case subgroup data and should not be interpreted as a comparative treatment-effect estimate. Muscle attenuation and myosteatosis classification differed significantly by CT acquisition type, whereas SMI did not. Conclusions: Pretreatment SMI, myosteatosis, the imaging-defined low-SMI obesity phenotype, and HALP were not significantly associated with pCR in this cohort. Hormone receptor status remained strongly associated with response. Treatment-related estimates and attenuation-based body-composition measures should be interpreted cautiously because of sparse subgroup data, treatment-era confounding, and imaging heterogeneity. Larger prospective studies with standardized imaging are warranted.