Background/Objectives: Iodine intake influences thyroid-related and metabolic diseases that have important public health implications. However, longitudinal evidence of the association between iodine intake and mortality remains scarce and limited to Western populations. Given the markedly high iodine intake among Asians and possible ethnic or regional differences in iodine sensitivity, population-based data from Asian cohorts are needed. Methods: We analyzed 5497 adults from the Korean National Health and Nutrition Examination Survey (2013-2015) linked with mortality follow-up through 2021. Urinary iodine concentration (UIC) was quantified from spot urine samples using inductively coupled plasma mass spectrometry. Iodine intake was estimated from UIC and categorized into four groups: below the estimated average requirement, low-normal, high-normal, and above the tolerable upper level (UL). The primary outcome was all-cause mortality. Cardiovascular disease-specific and cancer-specific mortality were also assessed. Multivariable Cox proportional hazards models accounting for the complex survey design were used to estimate hazard ratios and 95% confidence intervals. Sensitivity analysis excluded participants with thyroid disease or early death, and subgroup analyses by age and sex were also conducted. Results: During a median 8.4-year follow-up, 139 deaths occurred. Compared with the low-normal intake group, excessive iodine intake (above UL) was not associated with all-cause mortality (HR 1.09, 95% CI 0.36-3.27), cardiovascular mortality (HR 1.27, 95% CI 0.21-7.61), or cancer mortality (HR 1.71, 95% CI 0.40-7.29). No significant trends were observed across intake categories (p > 0.2), and similar findings were obtained when UIC levels were analyzed. Excluding participants with thyroid disease or early death did not change the results, and no significant interaction was observed by age or sex. Conclusions: In this first population-based Asian study on iodine intake to mortality, neither estimated iodine intake nor UIC was associated with all-cause mortality. These results suggest that the relationship between iodine exposure and mortality may differ across populations, underscoring the need for further large-scale studies.

Background and Objectives: Emerging evidence suggests that the genitourinary microbiota may influence the development and progression of urological malignancies, including bladder cancer. This study aimed to characterize the urinary microbiota at diagnosis in patients with bladder cancer and compare findings with healthy controls. Materials and Methods: Urine samples were collected from 30 patients with treatment-naïve bladder cancer and 20 age- and sex-matched healthy individuals. Microbiota composition was analyzed using 16S rRNA sequencing, and subgroup comparisons were made between muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Differentially abundant taxa were identified using linear discriminant analysis effect size (LEfSe) with an LDA threshold > 2 and p < 0.05. Results: No significant differences were observed in alpha or beta diversity between patients and controls or between MIBC and NMIBC. At the phylum level, Firmicutes was dominant in both groups but relatively more abundant in bladder cancer cases. Enterococcus was the most abundant genus in the cancer group (35.0%) and especially in MIBC (58.0%), while Lactobacillus was more prevalent in healthy controls (19.8% vs. 9.5%). At the species level, Veillonella dispar was notably enriched in MIBC cases (70.9%) compared to NMIBC (3.9%). LEfSe analysis revealed significant enrichment of Ralstonia, Microbacterium, and Facklamia in patients with bladder cancer, while Parvimonas, Sneathia, Gemella, and Acinetobacter guillouiae were more abundant in controls. Conclusions: These findings highlight preliminary microbiota differences associated with bladder cancer and tumor invasiveness; however, the results are exploratory and larger studies are required to evaluate their diagnostic or clinical relevance.

Background and Objectives: Breast cancer remains a leading cause of cancer-related morbidity and mortality worldwide, and robust, interpretable artificial intelligence (AI) pipelines are increasingly being explored to support mammography-based detection. This study combines a PRISMA 2020-compliant systematic review with an original experimental validation to characterize current evidence and address identified gaps in reproducibility and interpretability. Materials and Methods: A PRISMA 2020-guided systematic review and an original experimental study were conducted. The review searched PubMed and Scopus/ScienceDirect for studies using convolutional neural networks (CNNs), support vector machines (SVMs) or eXtreme Gradient Boosting (XGBoost) for breast cancer detection in mammography and related imaging modalities, and identified 45 eligible articles. In parallel, we implemented and evaluated representative CNN (ResNet-50, EfficientNetB0 and MobileNetV3-Small) and classical machine learning (SVM and XGBoost) pipelines on the CBIS-DDSM dataset, following a CRISP-DM-inspired workflow and using Grad-CAM and SHAP to provide image- and feature-level explanations within a reproducible machine-learning-operations (MLOps)-oriented framework. Results: The systematic review revealed substantial heterogeneity in datasets, preprocessing pipelines, and validation strategies, with a predominant reliance on internal validation and limited use of explainable AI methods. In our experimental evaluation, ResNet-50 achieved the best performance (AUC-ROC 0.95; sensitivity 89%), followed by XGBoost (AUC-ROC 0.90; sensitivity 74%) and SVM (AUC-ROC 0.84; sensitivity 66%), while EfficientNetB0 and MobileNetV3-Small showed lower discrimination. Grad-CAM produced qualitatively plausible heatmaps centered on annotated lesions, and SHAP analyses indicated that simple global image-intensity and size descriptors dominated the predictions of the classical models. Conclusions: By integrating systematic evidence and large-scale experiments on CBIS-DDSM, this study highlights both the potential and the limitations of current AI pipelines for mammography-based breast cancer detection, underscoring the need for more standardized preprocessing, rigorous external validation, and routine use of explainable AI before clinical deployment.

Background and Objectives: Grade 4 adult-type diffuse gliomas remain the most aggressive primary central nervous system malignancies, with limited prognostic tools beyond molecular classification. This study introduces the HALLMOUNT score, a multidimensional prognostic index integrating hematologic, biochemical, and clinical parameters to capture the interplay between tumor biology and systemic host response. Materials and Methods: A total of 227 patients with histologically confirmed grade 4 adult-type diffuse glioma were retrospectively analyzed. The HALLMOUNT score incorporated nine pretreatment variables: hemoglobin, albumin, lactate dehydrogenase (LDH), lymphocyte, monocyte, Eastern Cooperative Oncology Group (ECOG) performance status, uric acid, neutrophil, and thrombocyte counts. Receiver operating characteristic (ROC) analyses determined optimal cut-offs, and Cox regression models evaluated prognostic performance for overall (OS) and progression-free survival (PFS). Results: High HALLMOUNT scores (≥2.5) were significantly associated with older age, comorbidities, poor ECOG status, isocitrate dehydrogenase (IDH)-wild phenotype, lower resection rates, and reduced treatment responses. ROC analysis showed predictive accuracy comparable to CAR and PIV (AUC = 0.650). High scores independently predicted inferior OS (HR = 2.78, p < 0.001) and PFS (HR = 2.76, p < 0.001). Conclusions: The HALLMOUNT score provides a simple, cost-effective, and biologically grounded biomarker reflecting both tumor aggressiveness and host vulnerability. It enables refined risk stratification, supports individualized therapeutic planning, and warrants prospective validation in molecularly defined and multicenter cohorts.

Background and Objectives: Anastomotic leakage (AL) is a major complication following sphincter-preserving surgeries for left-sided colorectal cancer. In this study, we aimed to evaluate the association between circular stapler diameter and the risk of AL. As a secondary objective, we investigated whether preoperative serum protein levels were associated with leakage development. Materials and Methods: We conducted a retrospective case-control study including 99 patients who underwent elective colorectal surgery with stapled anastomosis for left-sided colorectal cancer between January 2020 and May 2024. A total of 99 patients were included (60.6% male), with a mean age of 66.1 ± 10.7 years. The patients were categorized into small (≤29 mm) and large (≥30 mm) stapler groups. Demographic, clinical, and laboratory variables were collected. Anastomotic leakage was defined as an International Study Group of Rectal Cancer (ISREC) Grade B or C leak requiring intervention. Univariate analyses and multivariate logistic regression analyses were performed, and results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). A STROBE-compliant flow diagram was prepared. Results: Anastomotic leakage occurred in 10 patients (10.1%), and leakage rates were not significantly different between stapler-size groups (≤29 mm: 10.9% vs. ≥30 mm: 7.5%, p = 0.365). In multivariate analysis, stapler size was not independently associated with leakage (OR 1.68, 95% CI 0.40-6.97, p = 0.480). Lower preoperative serum protein levels were identified as the only independent predictor of leakage (OR 0.28, 95% CI 0.10-0.74, p = 0.011). Postoperative hospital stay was significantly longer for patients with leakage (median 17 vs. 7 days, p < 0.001). Conclusions: We found no significant associations between circular stapler diameter and anastomotic leakage in left-sided colorectal cancer surgery. Conversely, low serum protein levels were independently associated with increased leakage risk, highlighting the importance of preoperative nutritional assessment. Given the retrospective design, small number of leakage cases, and unmeasured confounders, these findings should be interpreted with caution. Further multicenter, prospective studies should be conducted to clarify the influence of stapler size and patient-related factors on anastomotic outcomes.

Background and Objectives: Oral Squamous Cell Carcinoma (OSCC) requires early diagnosis for favorable outcomes, but global healthcare disruptions caused by the COVID-19 pandemic severely affected cancer care delivery. This study aimed to investigate the pandemic's influence on OSCC pathological staging and disease-related characteristics at a single medical center. Materials and Methods: A retrospective study was conducted on 148 patients who underwent curative-intent surgery for newly diagnosed OSCC between March 2018 and October 2024. Patients were stratified into a Pre-COVID-19 group (March 2018-January 2020, N = 52) and a Post-COVID-19 group (February 2020-October 2024, N = 96). Patient demographics and risk factors were compared using Chi-squared and Wilcoxon rank-sum tests, while pathological stage, Depth of Invasion (DOI), and surgical outcomes were analyzed. Results: Patient demographics, risk factors, and comorbidities were comparable between the two groups. The Post-COVID-19 cohort presented with significantly more advanced pathological disease, evidenced by an increase in overall TNM stage, including a dramatically higher rate of Stage 4 diagnosis (35% vs. 3.2% in the Pre-COVID-19 group). This group also showed a significantly higher Depth of Invasion (median DOI: 5.0 mm vs. 3.0 mm). Consequently, the Post-COVID-19 group required more aggressive treatment (e.g., higher rates of adjuvant radiotherapy) and experienced worse short-term outcomes, including significantly longer hospitalization (median 15 days vs. 6 days) and higher rates of postoperative pulmonary infection and tracheostomy. Conclusions: The COVID-19 pandemic was associated with a dramatic shift toward the diagnosis of OSCC at advanced pathological stages. This diagnostic delay necessitated more complex surgical management and resulted in significantly worse short-term outcomes. These findings underscore the urgent need for resilient strategies to prevent systemic diagnostic delays during public health crises.

Background and Objectives: Thyroid nodules are common, and distinguishing benign from malignant lesions is essential for clinical decision-making. While EU-TIRADS provides ultrasound-based risk stratification, fine-needle aspiration biopsy (FNAB) and the Bethesda System remain central diagnostic tools. This study aimed to compare the diagnostic performance of EU-TIRADS and Bethesda classifications and to identify ultrasonographic features independently associated with malignancy. Materials and Methods: This retrospective single-center study included 824 patients (1132 nodules) who underwent FNAB between August 2021 and June 2024. All ultrasound examinations and FNAB procedures were performed by the same endocrinologist. Sonographic features, EU-TIRADS categories, Bethesda classes, surgical indications, and histopathology were analyzed. Diagnostic accuracy was assessed using ROC curves, and multivariable logistic regression was applied to determine independent predictors of malignancy. Results: Among all nodules, 51.0% were EU-TIRADS 3, 28.6% were EU-TIRADS 4, and 19.2% were EU-TIRADS 5. Bethesda class II constituted 62.7% of FNAB results. Of the 289 surgically treated nodules, 53.3% were malignant. Malignant nodules were smaller, more often solitary and unilateral, and more frequently located in the upper pole (p < 0.05). Irregular margins (OR = 8.15, p < 0.001) and microcalcifications (OR = 10.01, p = 0.003) were independent predictors of malignancy. Taller-than-wide shape also showed significant association. ROC analyses demonstrated that EU-TIRADS (AUC = 0.808) and Bethesda (AUC = 0.869) were both significant predictors, with Bethesda showing higher specificity. Malignancy rates were 0% in EU-TIRADS II, 4.3% in III, 14.5% in IV, and 37.8% in V. Conclusions: EU-TIRADS is a practical and sensitive non-invasive tool for malignancy risk stratification; however, Bethesda classification remains superior in overall diagnostic accuracy. Microcalcification and irregular margins were the strongest ultrasonographic predictors of malignancy, while macrocalcification, parenchymal heterogeneity, and thyroiditis showed no significant association. These findings support the complementary roles of EU-TIRADS and FNAB and highlight key sonographic markers that enhance malignancy prediction in thyroid nodule evaluation.

Background and Objectives: Nasopharyngeal carcinoma (NPC) displays marked geographic and histopathological heterogeneity, and prognostic determinants in non-endemic regions remain incompletely defined. This study aimed to evaluate the impact of clinicopathological characteristics and treatment modalities on survival outcomes among patients with stage II-IVA NPC treated with curative intent at a single tertiary cancer center. Materials and Methods: A retrospective analysis was conducted on 81 consecutive patients with histologically confirmed NPC treated between 2000 and 2022. Demographic, clinical, and treatment parameters were extracted from institutional records. Survival outcomes-including disease-free survival (DFS), locoregional recurrence-free survival (LRFS), distant metastasis-free survival (DMFS), cancer-specific survival (CSS), and overall survival (OS)-were estimated using the Kaplan-Meier method and compared using the log-rank test. Prognostic variables identified in univariate analysis were further assessed by multivariable Cox proportional hazards regression (Cox's model). Results: The cohort included 59 men (72.8%) and 22 women (27.2%), with a median age of 50.8 years (range, 19-78). Most patients presented with locally advanced disease (T3-T4, 53.1%; N2, 60.5%; stage III-IVA, 87.7%). Non-keratinizing undifferentiated carcinoma (World Health Organization [WHO] type III) was the predominant histology (71.6%), followed by the non-keratinizing differentiated subtype (17.3%). Median DFS and OS were 94.6 and 139.4 months, respectively. According to the univariate analysis, histological subtypes and a family history of cancer were significantly associated with DFS, whereas comorbid systemic disease showed an unexpected association with longer DMFS. The multivariable Cox model identified the histological subtype as an independent predictor of disease recurrence (HR = 2.23, 95% CI: 1.00-4.94; p = 0.049). For OS, both histological subtype (HR = 2.40, 95% CI: 1.10-5.25; p = 0.029) and age at diagnosis (HR = 1.05, 95% CI: 1.02-1.09; p = 0.005) were independent adverse prognostic factors. Conclusions: In this long-term, single-center study from a non-endemic region, histological subtype emerged as the most powerful determinant of prognosis, significantly influencing both DFS and OS. Patients with non-keratinizing undifferentiated (WHO type III) carcinoma demonstrated superior outcomes compared with those with differentiated histology. Additionally, increasing age at diagnosis was independently associated with poorer OS. In contrast, inflammatory and nutritional biomarkers, the Pan-Immune-Inflammation Value (PIV) and the Prognostic Nutritional Index (PNI), showed no prognostic significance. These findings underscore the continued prognostic relevance of histopathologic classification and age and highlight the need for large-scale, standardized studies integrating Epstein-Barr virus (EBV) status and host-related factors in non-endemic NPC populations.

Background and Objectives: To evaluate the impact of gonadotropin-releasing hormone agonist (GnRHa) triggering compared to human chorionic gonadotropin (hCG) triggering on frozen-thawed and fresh embryo transfer outcomes in patients with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization (IVF). Materials and Methods: This retrospective cohort study analyzed 267 IVF cycles of 261 PCOS patients treated with GnRH antagonist protocols. Patients were divided into three groups: GnRHa-triggered frozen-thawed embryo transfer (ET) (n = 126), hCG-triggered frozen-thawed ET (n = 68), and hCG-triggered fresh ET (n = 73). Baseline characteristics, stimulation parameters, and cycle outcomes were compared between groups. A binary logistic regression analysis was established to identify independent predictors of clinical pregnancy. Results: The GnRHa-triggered group had significantly higher numbers of retrieved oocytes, mature (MII) oocytes, and fertilized oocytes compared to both hCG-triggered groups (p < 0.001). The number of obtained embryos and frozen embryos (good-quality embryos) was highest in the GnRHa group (p < 0.001). However, clinical pregnancy rates were comparable between the groups with a similar number and grade of transferred embryos (32.53%, 38.23%, and 32.87%, respectively). Multivariate regression analysis revealed that the grade of the transferred embryo was a significant predictor of clinical pregnancy (p = 0.034). Conclusions: This study provides insights into different triggering strategies for final oocyte maturation in PCOS patients. GnRH-agonist-triggered frozen-thawed cycles showed comparable clinical pregnancy outcomes to those of hCG-triggered cycles, with a potentially lower OHSS risk. The findings suggest that individualized triggering approaches based on patient characteristics and OHSS risk may be beneficial for PCOS patients undergoing IVF.

Background and Objectives: Para-aortic lymph node involvement is a key prognostic factor in high-risk endometrial cancer. This study aimed to identify factors associated with para-aortic lymph node metastasis and to assess their predictive value for surgical decision-making. Materials and Methods: A retrospective analysis was conducted on 81 patients with high-risk endometrial cancer who underwent systematic pelvic and para-aortic lymphadenectomy between January 2015 and December 2024. Factors evaluated included histologic subtype, lymphovascular space invasion (LVSI), cervical stromal involvement, depth of myometrial invasion, and tumor diameter. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of para-aortic metastasis. Receiver operating characteristic (ROC) analysis was used to determine the optimal tumor size threshold. Results: Para-aortic lymph node metastasis was identified in 21.0% of patients, and isolated para-aortic metastasis was observed in 2.5%. In univariate analysis, pelvic lymph node positivity, LVSI, cervical stromal invasion, deep myometrial invasion, and tumor size ≥ 3.55 cm were significantly associated with para-aortic spread. Multivariate analysis revealed that pelvic lymph node positivity was the only independent predictor (OR 39.0; 95% CI 5.06-301.46; p < 0.001). Conclusions: Pelvic lymph node status serves as a strong and independent predictor of para-aortic metastasis in high-risk endometrial cancer. A tumor diameter greater than 3.5 cm may also indicate an increased risk of para-aortic spread. These findings suggest that selective and individualized para-aortic assessment strategies may be considered to improve staging accuracy and optimize surgical planning in this patient population.