Purpose: We aimed to identify changes in surgical indications in patients with ulcerative colitis (UC) in the biologics era in a single tertiary center. Methods: In this retrospective observational study, 108 patients with UC who underwent abdominal surgery for UC at Seoul National University Hospital from 2000 to 2021 were included. We compared the total number of patients undergoing UC before and after the introduction of biologic therapy. Results: Of the 108 patients with UC (male, 59 and female, 49; mean age, 46.8 years), 30 (27.8%) underwent surgery for neoplasms and 78 (72.2%) for medical intractability without neoplasms. The duration between diagnosis and surgery varied significantly (126.00 months vs. 60.50 months, P = 0.001). A significant difference was also noted in the surgical indications according to time (P = 0.02). Between 2000 and 2010, 12 patients (19.4%) underwent surgery for UC with neoplasms and 50 (80.6%) for UC without neoplasms, while between 2011 and 2021, 18 (39.1%) and 28 patients (60.9%) underwent surgery for UC with and without neoplasms, respectively. Conclusion Since 2011, when biological agents were covered by insurance in South Korea, there has been a relative increase in the incidence of surgical indications for neoplasia cases. Focusing on closely monitoring individuals with longterm UC for neoplasms is necessary.

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: 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.

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.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

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: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: We investigated the clinical features, current negative-pressure wound therapy (NPWT) management strategies, and outcomes of pelvic-perineal soft tissue infection after open pelvic fractures. Materials and Methods: We analyzed the data of patients admitted to our trauma center with pelvic-perineal soft tissue after open pelvic fractures over a 7-year period. We investigated the injury severity score (ISS), medical costs, number of NPWTs, time required to reach definite wound coverage, complications, fracture classifications, transfusion requirements, interventions, length of stay (LOS) in hospital and intensive care unit (ICU), and prognosis. Results: Twenty patients with open pelvic fractures were treated with NPWT, and one patient who underwent NPWT died of pelvic sepsis during ICU treatment. The median LOS in hospital and medical costs were 98 [56–164] days and 106400 [65600–171100] USD, respectively. Patients treated with instillation NPWT (iNPWT, n=10) had a shorter NPWT duration (24 [13–39] vs. 46 [42–91] days, p=0.023), time to definite wound coverage (30 [21–43] vs. 49 [42–93] days, p=0.026), and hospital LOS (56 [43–72] vs. 158 [101–192] days, p=0.001), as well as lower medical costs (67800 [42500–102500] vs. 144200 [110400–236000] USD, p=0.009) compared to those treated with conventional NPWT. Conclusion NPWT is a feasible method for treating pelvic soft tissue infections in patients with open pelvic fractures. iNPWT can reduce the duration of NPWT, hospital LOS, and medical costs.