Background: High-resolution chest computed tomography (CT) is a crucial assessment tool for diagnosing Birt-Hogg-Dubé (BHD) syndrome. This study aimed to analyze differences of lung cysts between BHD and other cystic lung diseases. Methods: From January 2020 to December 2022, patients with multiple lung cysts who underwent chest CT at Gangnam Severance Hospital were included. Results: Over a 3-year period (from January 2020 to December 2022), out of 52,823 patients who underwent a chest CT scan, 301 (0.6%) patients with multiple lung cysts were enrolled in this study. Of enrolled patients, 24 (8.0%) were diagnosed with BHD. In patients with BHD, 95.8% exhibited bilateral cysts, and 83.3% showed basal predominance. The cysts’ maximal diameter averaged 32.1 mm (interquartile range, 26.5 to 43.5). Additionally, 95.8% of patients with BHD had diverse cyst sizes and morphologies. Multivariate logistic regression analysis revealed that bilateral cysts (odds ratio [OR], 12.393; 95% confidence interval [CI], 1.613 to 274.682; p=0.038), basal predominance (OR, 8.511; 95% CI, 2.252 to 39.392; p=0.002), maximum diameter (OR, 1.053; 95% CI, 1.009 to 1.108; p=0.032), and diversity of morphology (OR, 19.513; 95% CI, 2.833 to 398.119; p=0.010) were significant factors associated with BHD diagnosis. A multivariate prediction model for BHD diagnosis demonstrated a sensitivity of 95.83%, a specificity of 81.22%, and an area under the receiver operating characteristic curve of 0.951 (95% CI, 0.914 to 0.987). Conclusion Distinguishing features of lung cysts from other cystic lung diseases include bilateral cysts, basal dominance, large size, and irregular shape.

Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

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.

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: High-resolution chest computed tomography (CT) is a crucial assessment tool for diagnosing Birt-Hogg-Dubé (BHD) syndrome. This study aimed to analyze differences of lung cysts between BHD and other cystic lung diseases. Methods: From January 2020 to December 2022, patients with multiple lung cysts who underwent chest CT at Gangnam Severance Hospital were included. Results: Over a 3-year period (from January 2020 to December 2022), out of 52,823 patients who underwent a chest CT scan, 301 (0.6%) patients with multiple lung cysts were enrolled in this study. Of enrolled patients, 24 (8.0%) were diagnosed with BHD. In patients with BHD, 95.8% exhibited bilateral cysts, and 83.3% showed basal predominance. The cysts’ maximal diameter averaged 32.1 mm (interquartile range, 26.5 to 43.5). Additionally, 95.8% of patients with BHD had diverse cyst sizes and morphologies. Multivariate logistic regression analysis revealed that bilateral cysts (odds ratio [OR], 12.393; 95% confidence interval [CI], 1.613 to 274.682; p=0.038), basal predominance (OR, 8.511; 95% CI, 2.252 to 39.392; p=0.002), maximum diameter (OR, 1.053; 95% CI, 1.009 to 1.108; p=0.032), and diversity of morphology (OR, 19.513; 95% CI, 2.833 to 398.119; p=0.010) were significant factors associated with BHD diagnosis. A multivariate prediction model for BHD diagnosis demonstrated a sensitivity of 95.83%, a specificity of 81.22%, and an area under the receiver operating characteristic curve of 0.951 (95% CI, 0.914 to 0.987). Conclusion Distinguishing features of lung cysts from other cystic lung diseases include bilateral cysts, basal dominance, large size, and irregular shape.

Background: High-resolution chest computed tomography (CT) is a crucial assessment tool for diagnosing Birt-Hogg-Dubé (BHD) syndrome. This study aimed to analyze differences of lung cysts between BHD and other cystic lung diseases. Methods: From January 2020 to December 2022, patients with multiple lung cysts who underwent chest CT at Gangnam Severance Hospital were included. Results: Over a 3-year period (from January 2020 to December 2022), out of 52,823 patients who underwent a chest CT scan, 301 (0.6%) patients with multiple lung cysts were enrolled in this study. Of enrolled patients, 24 (8.0%) were diagnosed with BHD. In patients with BHD, 95.8% exhibited bilateral cysts, and 83.3% showed basal predominance. The cysts’ maximal diameter averaged 32.1 mm (interquartile range, 26.5 to 43.5). Additionally, 95.8% of patients with BHD had diverse cyst sizes and morphologies. Multivariate logistic regression analysis revealed that bilateral cysts (odds ratio [OR], 12.393; 95% confidence interval [CI], 1.613 to 274.682; p=0.038), basal predominance (OR, 8.511; 95% CI, 2.252 to 39.392; p=0.002), maximum diameter (OR, 1.053; 95% CI, 1.009 to 1.108; p=0.032), and diversity of morphology (OR, 19.513; 95% CI, 2.833 to 398.119; p=0.010) were significant factors associated with BHD diagnosis. A multivariate prediction model for BHD diagnosis demonstrated a sensitivity of 95.83%, a specificity of 81.22%, and an area under the receiver operating characteristic curve of 0.951 (95% CI, 0.914 to 0.987). Conclusion Distinguishing features of lung cysts from other cystic lung diseases include bilateral cysts, basal dominance, large size, and irregular shape.

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.

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 Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

Background: High-resolution chest computed tomography (CT) is a crucial assessment tool for diagnosing Birt-Hogg-Dubé (BHD) syndrome. This study aimed to analyze differences of lung cysts between BHD and other cystic lung diseases. Methods: From January 2020 to December 2022, patients with multiple lung cysts who underwent chest CT at Gangnam Severance Hospital were included. Results: Over a 3-year period (from January 2020 to December 2022), out of 52,823 patients who underwent a chest CT scan, 301 (0.6%) patients with multiple lung cysts were enrolled in this study. Of enrolled patients, 24 (8.0%) were diagnosed with BHD. In patients with BHD, 95.8% exhibited bilateral cysts, and 83.3% showed basal predominance. The cysts’ maximal diameter averaged 32.1 mm (interquartile range, 26.5 to 43.5). Additionally, 95.8% of patients with BHD had diverse cyst sizes and morphologies. Multivariate logistic regression analysis revealed that bilateral cysts (odds ratio [OR], 12.393; 95% confidence interval [CI], 1.613 to 274.682; p=0.038), basal predominance (OR, 8.511; 95% CI, 2.252 to 39.392; p=0.002), maximum diameter (OR, 1.053; 95% CI, 1.009 to 1.108; p=0.032), and diversity of morphology (OR, 19.513; 95% CI, 2.833 to 398.119; p=0.010) were significant factors associated with BHD diagnosis. A multivariate prediction model for BHD diagnosis demonstrated a sensitivity of 95.83%, a specificity of 81.22%, and an area under the receiver operating characteristic curve of 0.951 (95% CI, 0.914 to 0.987). Conclusion Distinguishing features of lung cysts from other cystic lung diseases include bilateral cysts, basal dominance, large size, and irregular shape.