BACKGROUND: Osteoporosis, characterized by decreased bone mineral density due to an imbalance between osteoblast and osteoclast activity, poses significant challenges in bone healing, particularly in postmenopausal women. Current treatments, such as bisphosphonates, are effective but associated with adverse effects like medication-related osteonecrosis of the jaw, necessitating safer alternatives. METHODS: This study investigated the use of L-serine-incorporated gelatin sponges for bone regeneration in calvarial defects in an ovariectomized rat model of osteoporosis. Thirty rats were divided into three groups: a control group, a group treated with a gelatin sponge containing an amino acid mixture, and a group treated with a gelatin sponge containing L-serine. Bone regeneration was assessed using micro-computed tomography (micro-CT) and histological analyses. RESULTS: The L-serine group showed a significant increase in bone volume (BV) and bone area compared to the control and amino acid groups. The bone volume to total volume (BV/TV) ratio was also significantly higher in the L-serine group.Immunohistochemical analysis demonstrated that L-serine treatment suppressed the expression of cathepsin K, a marker of osteoclast activity, while increasing serine racemase activity. CONCLUSION These findings suggest that L-serine-incorporated gelatin sponges not only enhance bone formation but also inhibit osteoclast-mediated bone resorption, providing a promising and safer alternative to current therapies for osteoporosis-related bone defects. Further research is needed to explore its clinical applications in human patients.

Purpose: Emphysematous pyelonephritis (EPN) is a life-threatening disease requiring immediate treatment. This multicenter retrospective cohort study aimed to analyze the mortality rate and risk factors associated with EPN. Materials and Methods: Between January 2011 and February 2021, 217 patients diagnosed with EPN via computed tomography who visited 14 teaching hospitals were retrospectively analyzed. Clinical data, including age, sex, comorbidities, Huang and Tseng classification, hydronephrosis, acute kidney injury, blood and urine tests, surgical interventions, percutaneous drainage, and conservative treatments, were compared between the survival and death groups. Risk factors for mortality due to EPN were analyzed using univariate and multivariate methods. Results: The mean age of survivors and deceased patients was 67.8 and 69.0 years, respectively (p=0.136). The sex distribution (male/female) was 48/146 and 8/15, respectively (p=0.298). Of the 217 patients, 23 died, resulting in a mortality rate of 10.6%. In univariate analysis, the Huang and Tseng classification (p=0.004), platelet count (p=0.005), and acute kidney injury (p=0.007) were significantly associated with mortality from EPN. In multivariate analysis, only the Huang and Tseng classification (p=0.029) was identified as a risk factor. Mortality rates according to the Huang and Tseng classification were as follows: class I (5.88%), class II (7.50%), class IIIa (14.28%), class IIIb (25.00%), and class IV (23.07%). Conclusions EPN is associated with a high mortality rate. Among various clinical factors, the Huang and Tseng classification was the most significant indicator for predicting mortality.

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.

Anticancer treatment for acute lymphocytic leukemia is based on drugs such as methotrexate, 6-mercaptopurine, vincristine, and asparaginase. Asparaginase-related pancreatitis is known to have an incidence of up to 18%, and is a major cause of discontinuation of anticancer treatment for leukemia due to acute onset and chronic complications. There were various cases of treatment of peripancreatic fluid retention caused by anticancer drugs in leukemia patients. Use of lumen-apposing metal stents (LAMS) for walled-off necrosis (WON) drainage has recently increased. The electrocautery-enhanced delivery system allowed simpler and faster stent placement, streamlining the overall procedure and potentially reducing procedure time. Therefore, favorable outcomes have been reported with the use of LAMS for endoscopic drainage of various conditions. In this paper, we discuss a case in which hot-system LAMS was performed to treat L-asparaginase-induced acute pancreatitis and pancreatic pseudocyst in an adult patient with acute lymphoblastic leukemia.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Purpose: Recent development in perioperative treatment of resectable non–small cell lung cancer (NSCLC) have changed the landscape of early lung cancer management. The ADAURA trial has demonstrated the efficacy of adjuvant osimertinib treatment in resectable NSCLC patients; however, studies are required to show which subgroup of patients are at a high risk of relapse and require adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor treatment. This study evaluated risk factors for postoperative relapse among patients who underwent complete resection. Materials and Methods: Data were obtained from the Korean Association for Lung Cancer Registry (KALC-R), a database created using a retrospective sampling survey by the Korean Central Cancer Registry (KCCR) and the Lung Cancer Registration Committee. Results: A total of 3,176 patients who underwent curative resection was evaluated. The mean observation time was approximately 35.4 months. Among stage I to IIIA NSCLC patients, the EGFR-mutant subgroup included 867 patients, and 75.2%, 11.2%, and 11.8% were classified as stage I, stage II, and stage III, respectively. Within the EGFR-mutant subgroup, 44 (5.1%) and 121 (14.0%) patients showed early and late recurrence, respectively. Multivariate analysis on association with postoperative relapse among the EGFR-mutant subgroup showed that age, pathologic N and TNM stages, pleural invasion status, and surgery type were independent significant factors. Conclusion Among the population that underwent complete resection for early NSCLC with EGFR mutation, patients with advanced stage, pleural invasion, or limited resection are more likely to show postoperative relapse.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Background: and Purpose: This clinical practice guideline provides evidence-based recommendations for treatment of dementia, focusing on cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists for Alzheimer’s disease (AD) and other types of dementia. Methods: Using the Population, Intervention, Comparison, Outcomes (PICO) framework, we developed key clinical questions and conducted systematic literature reviews. A multidisciplinary panel of experts, organized by the Korean Dementia Association, evaluated randomized controlled trials and observational studies. Recommendations were graded for evidence quality and strength using Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. Results: Three main recommendations are presented: (1) For AD, cholinesterase inhibitors (donepezil, rivastigmine, galantamine) are strongly recommended for improving cognition and daily function based on moderate evidence; (2) Cholinesterase inhibitors are conditionally recommended for vascular dementia and Parkinson’s disease dementia, with a strong recommendation for Lewy body dementia; (3) For moderate to severe AD, NMDA receptor antagonist (memantine) is strongly recommended, demonstrating significant cognitive and functional improvements. Both drug classes showed favorable safety profiles with manageable side effects. Conclusions This guideline offers standardized, evidence-based pharmacologic recommendations for dementia management, with specific guidance on cholinesterase inhibitors and NMDA receptor antagonists. It aims to support clinical decision-making and improve patient outcomes in dementia care. Further updates will address emerging treatments, including amyloid-targeting therapies, to reflect advances in dementia management.