Background/Objective: Asthma-related quality of life is related to multiple clinical, physiological, and behavioral factors. Nonetheless, the domain-specific associations of asthma control, inhaler adherence, lung function, and demographic characteristics remain poorly understood. This study aimed to examine the adjusted associations of asthma control, inhaler adherence, lung function, and age with individual domains of asthma-related quality of life. Methods: This cross-sectional observational study included 92 adults with asthma who demonstrated correct inhaler technique and adequate knowledge of their prescribed inhaler regimen. Asthma control was measured using the Asthma Control Test (ACT), inhaler adherence using the Test of Adherence to Inhalers (TAI), and quality of life using the Asthma Quality of Life Questionnaire (AQLQ). Pulmonary function was determined through spirometry. Spearman correlation analyses were initially conducted to identify associations between variables. Subsequently, separate multivariable linear regression models were created for each AQLQ domain, including ACT score, TAI score, age, and FEV₁ % predicted as predictors. Results: A total of 92 adult patients with asthma were studied. Asthma control was significantly positively correlated with all AQLQ domains (all p < 0.001). In multivariable analyses, ACT had the largest absolute standardized coefficient within each of the four domain-specific models (standardized β range: 0.339–0.791). After adjustment, age was associated with the activity limitation and symptom domains, whereas FEV₁ % predicted was associated only with the environmental stimuli domain. Inhaler adherence showed an inverse association with emotional functioning in the fully adjusted model (B = −0.094, 95% CI −0.158–−0.031; p = 0.0038). However, this association was absent in the bivariate analysis and in a sensitivity model excluding ACT (B = −0.015, 95% CI −0.067–0.037; p = 0.562), suggesting a possible suppression effect. Conclusions: ACT showed the largest standardized association within each domain-specific model, although the magnitude of its associations with the symptom and activity-limitation domains may partly reflect conceptual overlap between the instruments. The inverse TAI–emotional-functioning coefficient was model-dependent, did not meet the conservative multiplicity benchmark, and should be considered exploratory and hypothesis-generating. Additionally, lung function and age showed domain-specific associations, highlighting the need for a comprehensive, multidimensional approach in asthma management.

Background and Objectives: Ovarian cancer remains the most lethal gynecologic malignancy, largely due to late diagnosis and the limitations of currently available diagnostic tools. Systemic inflammatory markers derived from routine blood tests have emerged as potential low-cost biomarkers, reflecting the interaction between tumor biology and the host immune response. This study aimed to evaluate the association and diagnostic value of preoperative inflammatory markers in distinguishing malignant from non-malignant ovarian tumors. Materials and Methods: This retrospective, single-center observational study included 780 adult female patients diagnosed with ovarian tumors and treated surgically between January 2020 and December 2025. Preoperative hematological parameters were obtained from complete blood count analyses performed before any therapeutic intervention. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) were calculated. Comparisons were performed among benign, borderline, and malignant tumors. To avoid collinearity between mathematically interrelated inflammatory indices, three separate multivariable logistic regression models were constructed, each including age, CA-125, and one inflammatory index. Diagnostic performance of the individual inflammatory indices was assessed using receiver operating characteristic (ROC) curve analysis. Results: Patients with malignant tumors were significantly older and exhibited higher NLR and PLR values and lower LMR values than patients with non-malignant tumors (all p < 0.001). In separate multivariable models adjusted for age and CA-125, higher NLR (OR = 1.79, 95% CI: 1.41–2.27, p < 0.001) and PLR (OR = 1.43, 95% CI: 1.17–1.75, p = 0.001) remained significantly associated with malignant ovarian tumors, whereas higher LMR was inversely associated with malignancy (OR = 0.66, 95% CI: 0.52–0.85, p = 0.001). ROC analysis demonstrated moderate discriminative ability for NLR and PLR (AUC = 0.72 for both), whereas LMR showed lower discriminative performance (AUC = 0.64). Conclusions: Preoperative systemic inflammatory indices are significantly associated with ovarian tumor malignancy. NLR and PLR were positively associated with malignant disease, whereas LMR showed an inverse association, and these relationships remained significant after adjustment for age and CA-125. However, their individual discriminative performance was modest, suggesting that these readily available inflammatory indices should be considered complementary rather than standalone biomarkers for preoperative risk assessment.