Diabetic foot ulcers (DFUs) are among the most serious and common complications of diabetes mellitus. They significantly affect patients’ quality of life and impose a substantial economic burden on healthcare systems worldwide. In Korea, the prevalence of diabetes and related complications, such as DFUs, has been increasing, reflecting a broader global trend. DFUs are associated with severe complications, including infections, neuropathy, and peripheral arterial disease, often leading to amputation. In Korea, diabetic foot complications are a major cause of non-traumatic lower-extremity amputations, with high mortality rates following amputation. DFUs also significantly reduce patients’ quality of life and increase healthcare costs. The management of DFUs requires a multidisciplinary approach that integrates medical, surgical, and advanced therapeutic interventions to prevent severe outcomes, such as amputation. This comprehensive review of DFU management in patients with diabetes was developed in collaboration with the Diabetic Study Group of the Korean Diabetes Association and Korean Society for Diabetic Foot. This review examines the epidemiology, clinical significance, diagnosis, and evidence-based treatment of DFUs.

Background: Various strategies are being explored to improve outcomes in advanced ovarian cancer. This study evaluated the survival outcomes of a sequential treatment strategy comprising dose-dense weekly chemotherapy, selective adjuvant radiotherapy, and poly(ADP-ribose) polymerase (PARP) inhibitor maintenance following primary debulking surgery. Methods: We retrospectively reviewed 12 patients with newly diagnosed advanced high-grade serous ovarian cancer (HGSOC) who underwent a sequential treatment strategy (debulking surgery followed by dose-dense chemotherapy, selective adjuvant radiotherapy, and PARP inhibitor maintenance) at Kosin University Gospel Hospital between December 2019 and March 2023. Survival outcomes were analyzed using the Kaplan-Meier method, and treatment-related adverse effects were evaluated. Results: All 12 patients achieved complete remission after the sequential treatment strategy. At the cutoff date (June 20, 2025), all patients were alive, with a median follow-up duration of 48.1 months (range, 28.7–66.5 months). The median progression-free survival (PFS) was 43.8 months. Acute toxicities, including bone marrow suppression and alopecia, were transient and manageable. Peripheral neuropathy and extremity edema were observed as persistent late toxicities. Conclusions This study highlights promising outcomes with a multimodal sequential treatment strategy in newly diagnosed advanced HGSOC. All patients remained alive at the time of analysis, and the median PFS reached 43.8 months, suggesting a potential benefit of this sequential approach compared with conventional treatment strategies. Prospective studies are warranted to validate these findings.

Purpose: Distant metastasis of breast cancer significantly affects the prognosis. Serum markers such as CEA and cancer antigen (CA) 15-3 are used for surveillance. However, the nonspecificity and nonmalignant elevation of CEA limit its absolute value in predicting metastatic recurrence. We reevaluated the clinical value of CEA kinetics in predicting metastatic recurrence in breast cancer. Methods: In this multicenter retrospective cohort study, we utilized electronic medical record data from eight institutions (2008–2023), including 4,872 surgically treated patients with invasive breast cancer. Novel CEA kinetic indices were defined.Predictive capabilities were assessed using logistic regression, Kaplan-Meier survival curves, and Cox proportional hazards models. Results: CEA velocity (vCEA) and last-interval vCEA (vCEA-L) showed higher accuracy and sensitivity in predicting distant metastasis than absolute CEA indices. All tumor marker indices were independent predictors; vCEA, vCEA-L, and maximum vCEA (vCEAmax) showed the highest association. In the 5-year distant disease-free survival analysis of patients, vCEA showed the most significant difference based on whether its cutoff value was exceeded (84.1% vs. 47.2%) (P < 0.001).Cox analysis showed that vCEA was the strongest predictor (hazard ratio, 4.509; P < 0.001). vCEAmax remained prognostic even when CEAmax was below its cutoff value. Conclusion Analysis of dynamic CEA changes, particularly velocity-based indices, offers superior predictive power than the static-based CEA indices for metastatic recurrence in breast cancer. These kinetic markers enhance prognostic accuracy when combined with CA 15-3. Future research should integrate these markers with imaging, liquid biopsy, and artificial intelligence for personalized follow-up.

Purpose: This study aimed to project cancer incidence and mortality for 2026 to estimate Korea’s current cancer burden. Materials and Methods: Cancer incidence data from 1999 to 2023 were obtained from the Korea National Cancer Incidence Database, while cancer mortality data from 1993 to 2024 were acquired from the Ministry of Data and Statistics. Cancer incidence and mortality were projected by fitting a linear regression model to observed age-specific cancer rates against their respective years and then by the projected age-specific rates by the anticipated age-specific population for 2026. A joinpoint regression model was applied to identify significant changes in trends, using only the most recent trend data for predictions. Results: A total of 308,876 new cancer cases and 86,317 cancer deaths are expected in Korea in 2026. The most commonly diagnosed cancer is projected to be thyroid cancer, followed by the colorectal, lung, breast, prostate and stomach cancers. These six cancers are expected to account for 63.5% of all newly diagnosed cancers. Lung cancer is expected to be the leading cause of cancer-related deaths, followed by liver, colorectal, pancreatic, gallbladder, and stomach cancers, together comprising 65.9% of all cancer deaths. Conclusion Korea’s cancer burden continues to shift toward malignancies prevalent in older populations. The sustained increase in prostate cancer among men and the rising mortality impact of pancreatic cancer reflect structural changes in the national cancer profile amid rapid population aging.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

In cases of partially edentulous patients with insufficient remaining teeth, rotational movement of the denture occurs and prognosis of the remaining teeth is uncertain when restoring with a removable partial denture. Recently, implant-assisted removable partial dentures, where a small number of implants are placed and surveyed crowns are fabricated on the implants to be used as abutments, have been suggested. In this case, the patient had only one remaining tooth in the mandible and implants were placed in both posterior regions to be used as surveyed crowns to restore the patient with an implant-assisted removable partial denture. This approach improved the support, retention, and stability of the denture, resulting in functionally and aesthetically satisfactory outcomes.

Background/Aims: Cardiovascular disease is the leading cause of death worldwide. This study aimed to investigate the recent nationwide trends in major dietary risk factors for dyslipidemia and atherosclerosis. Methods: We estimated age-standardized mean intakes of fresh fruits, fresh vegetables, whole grains, dietary fiber, and sugar-sweetened beverages (SSBs); and mean percentage of energy intake from protein, total fat, saturated fat, and polyunsaturated fat using nationally representative samples from the Korean National Health Examination and Nutrition Survey 2013–2022. To assess overall diet quality, we calculated mean Korean Healthy Eating Index (KHEI) (range 0–100, higher scores indicating greater diet quality). Results: In 2013–2022, there were overall decreasing trends in age-standardized mean KHEI score and intakes of fresh fruits and vegetables, whole grains, and dietary fiber; and overall increasing trends in mean intakes of SSBs, protein, and dietary fat among both male and female. The KHEI score increased in older adults aged ≥ 60 years, whereas it decreased among younger adults. Throughout the study period, younger adults tended to have lower intakes of fresh fruits, fresh vegetables, and whole grains; higher intakes of SSBs, protein, and dietary fat; and lower KHEI score. The mean KHEI score was lower in male (vs. female) and lower (vs. higher) income groups. Conclusions Our data suggest that, from 2013 to 2022, there was a trend toward an unhealthy diet in Korean adults. Our findings also suggest dietary inequalities among age, sex, and income groups, suggesting the need for more intense interventions targeting the vulnerable populations.

Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.