Background and Objectives: Bethesda Category IV thyroid nodules present a diagnostic challenge due to their variable risk of malignancy and uncertain cytological features. Therefore, determining the risk of malignancy before surgery is important. This study aims to identify clinical, biochemical, and ultrasonographic factors associated with malignancy and to explore the performance of a multivariable analysis based on routinely available preoperative features in thyroid nodules. Methods: This retrospective, single-center study included 105 patients who underwent thyroidectomy for Bethesda Category IV cytology. The mean age was 50.13 ± 11.78 years. 87 patients (82.9%) were female, and 18 (17.1%) were male. Patients were classified into benign/borderline (n = 79) and malignant (n = 26) groups based on their postoperative histopathological findings. Demographic characteristics, serum thyroid function tests, thyroid autoantibody levels, and ultrasonographic findings were compared. Variables significantly associated with malignancy were included in a Firth bias-reduced penalized multivariable logistic regression analysis. The discriminative performance of the multivariable analysis was evaluated using ROC curve analysis, and internal validation was performed using bootstrap resampling. The AUC was compared with that of ACR TI-RADS using DeLong’s test. Results: The malignant group showed a significantly higher prevalence of male sex, irregular margins, a taller-than-wide shape, and microcalcification (all p < 0.05). In the multivariable logistic regression analysis, only irregular margins (OR = 9.46, 95% CI: 1.88–47.59; p = 0.006) were independently associated with malignancy. The model demonstrated acceptable discrimination in this study population (n = 105), with an AUC of 0.717. The AUC of the multivariable analysis was 0.717, compared with 0.704 for ACR TI-RADS, and the difference was not statistically significant (ΔAUC = 0.013; DeLong p = 0.803). Conclusions: In Bethesda Category IV thyroid nodules, irregular margins remained independently associated with malignancy. The multivariable analysis did not demonstrate significantly better discrimination than ACR TI-RADS. These findings should be considered exploratory and require external validation in larger cohorts.

Breast cancer (BC) is a heterogeneous disease with distinct molecular subtypes that exhibit variable immune responses and metabolic profiles. Recent studies have suggested that immunometabolic pathways play a role in tumor progression and treatment resistance. This study investigates the expression patterns of ALKBH7 and NLRP3 across BC molecular subtypes and explores their relationships with clinicopathological parameters and potential immunometabolic profiles. A total of 118 BC patients were classified into HER2+, TNBC, Luminal A, and Luminal B subtypes. Gene expression levels of ALKBH7 and NLRP3 were analyzed using quantitative real-time PCR (qRT-PCR), and correlations with clinical markers were assessed. ALKBH7 and NLRP3 expression levels varied significantly between subtypes, with the highest expression observed in HER2+ tumors. Strong positive correlations were found between ALKBH7 and NLRP3 in all subtypes, particularly in HER2+ (r = 0.812, p < 0.001). Additionally, NLRP3 correlated with Ki-67 in Luminal B tumors, indicating a link between inflammation and proliferative capacity. These findings suggest that ALKBH7 may function as a dual-role biomarker involved in metabolic adaptation and immune signaling in BC. The strong co-expression of ALKBH7 and NLRP3 suggests a functional association between these molecules that may be critical in shaping the tumor microenvironment. This co-expression set, particularly in aggressive subtypes (HER2+ and TNBC), warrants further mechanistic validation as a potential prognostic marker and a novel therapeutic vulnerability.