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.

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.

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.

The global coronavirus disease 2019 (COVID-19) pandemic has placed patients with end-stage kidney disease (ESKD) at heightened risk owing to their vulnerability to infections. Our study focused on patients with ESKD, examining COVID-19 incidence, hospitalization, and mortality in relation to their renal replacement therapy (RRT) type and identifying factors influencing COVID-19 hospitalization. Methods: We conducted a retrospective cohort study using health insurance claims data from the Health Insurance Review and Assessment Service for patients with ESKD between July 2017 and June 2022. COVID-19 data for the general population were sourced from the Korea Disease Control and Prevention Agency. Results: Patients undergoing hemodialysis (HD) constituted 90.7% of the cohort, followed by kidney transplantation (KT) recipients and peritoneal dialysis (PD). After adjusting for every 10,000 individuals, KT recipients exhibited the highest COVID-19 incidence, followed by those undergoing HD and PD, whereas the general population showed a higher infection rate of 43.64. Patients undergoing HD had the highest hospitalization rates, followed by KT recipients and those undergoing PD. The mortality rate per 10,000 individuals was highest in HD, followed by PD, the general population, and KT. Multivariate analysis indicated that age, RRT duration, residence in a nursing hospital, and comorbidities were associated with COVID-19 hospitalization. Conclusion: Among RRT modalities, KT recipients displayed the highest COVID-19 incidence, whereas those undergoing HD exhibited the highest hospitalization and mortality rates. This study contributes to our understanding of infectious diseases in patients on RRT and aids in preparedness for future infectious disease outbreaks.

Purpose: Endoscopic nipple-sparing mastectomy (E-NSM) is a minimally invasive surgical technique that shows good results in patients with breast cancer. The authors compared 3 different types of commercial energy devices to examine their efficacy and safety in E-NSM performed with breast reconstruction. Methods: A total of 36 cases of E-NSM were conducted with either Sonicision (S group, n = 11), Harmonic (H group, n = 6), or Thunderbeat (T group, n = 19). The clinicopathologic factors and postoperative complications, including nipple or skin necrosis and surgical site seroma volume, were evaluated for 3 months after surgery. Results: The surgical duration of E-NSM was significantly shorter in the S group than in the H group (P = 0.043) and T group (P = 0.037). However, the total surgical duration including E-NSM and breast reconstruction, and the total and daily drainage volume of postoperative seroma did not differ significantly among the 3 groups. Even when the energy devices were compared according to their working principle, i.e., ultrasonic (S and H) vs. hybrid (T), the total breast surgery duration and total and daily drainage volume of seroma showed no difference between the 2 groups. Although surgeon satisfaction did not significantly differ when using 3 devices for E-NSM (P = 0.428), surgeon’s fatigue was found to be lowest in the S group, though it was not significant (P = 0.064). Conclusion Any energy device can be safely used for E-NSM with breast reconstruction without causing any major complications. However, cordless ultrasonic energy devices allow greater mobility for the surgeon and, therefore, may shorten surgical time in breast surgery.

The machining accuracy of zirconia prostheses fabricated by the subtractive (SM) and additive manufacturing (AM) was evaluated using the Merlon fracture test model in ISO 18675 (2022). The SM specimens were fabricated by a DWX-51D (Roland, Sydney, NSW, Australia) using two zirconia blocks (Katana Zirconia HT; KH, Katana Zirconia STML; KS). The AM specimens were prepared by a DLP type 3D printer INNI-Ⅱ (AON, Gunpo, Korea) using zirconia liquid slurry (INNI-CERA; PZ). The specimen STL image was acquired using a model scanner (E3, 3 Shape A/S, Copenhagen, Denmark). The machining accuracy of the specimens was analyzed by the RMS method superimposing the reference STL image and the specimen STL image in image analysis software (Geomagic Control X, 3D Systems, Rock Hill, SC, USA). From the results of the machining accuracy analysis, the KH and KS groups showed statistically significantly better machining accuracy (lower RMS) than the PZ group (P<0.05). The KH and KS groups showed higher machining accuracy as the thickness decreased, and the 0.2 mm and 0.3 mm experimental groups showed statistically significantly better machining accuracy than the 0.4 mm experimental group (P<0.05). On the other hand, the PZ group showed better machining accuracy as the thickness increased, with the 0.4 mm group showing statistically significantly better machining accuracy than the 0.2 mm and 0.3 mm groups (P<0.05). Within the limitation of this study, the thickness of the final zirconia prosthesis fabricated by additive manufacturing should be at least 0.4 mm for clinical use in dentistry.