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.

Background: The Controlling Nutritional Status (CONUT) score is an immunonutritional test tool based on serum albumin, total cholesterol, and lymphocyte counts. It has been studied as a simple prognostic predictor for various carcinomas. This study aimed to investigate the association between preoperative CONUT scores and the clinicopathological characteristics in papillary thyroid carcinoma (PTC) patients. Methods: This study included 2,403 PTC patients who underwent total thyroidectomy between 2012 and 2016 at a single tertiary medical center. The CONUT scores were calculated based on preoperative blood tests. The clinicopathological characteristics were retrospectively reviewed. The patients were categorized by the CONUT score (relatively low, 0–2; relatively high, 3–5). Results: Among the 2,997 PTC patients who underwent total thyroidectomy at Pusan National University Hospital between 2012 and 2016, those without preoperative blood test were excluded (n=149). Finally 2,403 patients were analyzed after excluding 439 patients taking lipid-lowering drugs and six patients without available T stage data after surgery. Based on the CONUT score, the relatively high score group had a lower body mass index (23.7±3.3 kg/m2 vs. 21.9±2.9 kg/m2, P<0.001), more advanced T stage (T stage 3/4, 5.9% vs. 11.4%, P=0.045), and higher extrathyroidal extension (2.1% vs. 7.6%, P=0.005). Conclusion Patients included in this large, single-center study all had a preoperative CONUT score of 0–5, but this study demonstrated that higher preoperative CONUT scores were significantly associated with advanced T stage and extrathyroidal extension. The CONUT score, which can be easily used in clinical practice, is thought to be helpful in predicting the aggressiveness of PTC.

Background: The Controlling Nutritional Status (CONUT) score is an immunonutritional test tool based on serum albumin, total cholesterol, and lymphocyte counts. It has been studied as a simple prognostic predictor for various carcinomas. This study aimed to investigate the association between preoperative CONUT scores and the clinicopathological characteristics in papillary thyroid carcinoma (PTC) patients. Methods: This study included 2,403 PTC patients who underwent total thyroidectomy between 2012 and 2016 at a single tertiary medical center. The CONUT scores were calculated based on preoperative blood tests. The clinicopathological characteristics were retrospectively reviewed. The patients were categorized by the CONUT score (relatively low, 0–2; relatively high, 3–5). Results: Among the 2,997 PTC patients who underwent total thyroidectomy at Pusan National University Hospital between 2012 and 2016, those without preoperative blood test were excluded (n=149). Finally 2,403 patients were analyzed after excluding 439 patients taking lipid-lowering drugs and six patients without available T stage data after surgery. Based on the CONUT score, the relatively high score group had a lower body mass index (23.7±3.3 kg/m2 vs. 21.9±2.9 kg/m2, P<0.001), more advanced T stage (T stage 3/4, 5.9% vs. 11.4%, P=0.045), and higher extrathyroidal extension (2.1% vs. 7.6%, P=0.005). Conclusion Patients included in this large, single-center study all had a preoperative CONUT score of 0–5, but this study demonstrated that higher preoperative CONUT scores were significantly associated with advanced T stage and extrathyroidal extension. The CONUT score, which can be easily used in clinical practice, is thought to be helpful in predicting the aggressiveness of PTC.

Background: The Controlling Nutritional Status (CONUT) score is an immunonutritional test tool based on serum albumin, total cholesterol, and lymphocyte counts. It has been studied as a simple prognostic predictor for various carcinomas. This study aimed to investigate the association between preoperative CONUT scores and the clinicopathological characteristics in papillary thyroid carcinoma (PTC) patients. Methods: This study included 2,403 PTC patients who underwent total thyroidectomy between 2012 and 2016 at a single tertiary medical center. The CONUT scores were calculated based on preoperative blood tests. The clinicopathological characteristics were retrospectively reviewed. The patients were categorized by the CONUT score (relatively low, 0–2; relatively high, 3–5). Results: Among the 2,997 PTC patients who underwent total thyroidectomy at Pusan National University Hospital between 2012 and 2016, those without preoperative blood test were excluded (n=149). Finally 2,403 patients were analyzed after excluding 439 patients taking lipid-lowering drugs and six patients without available T stage data after surgery. Based on the CONUT score, the relatively high score group had a lower body mass index (23.7±3.3 kg/m2 vs. 21.9±2.9 kg/m2, P<0.001), more advanced T stage (T stage 3/4, 5.9% vs. 11.4%, P=0.045), and higher extrathyroidal extension (2.1% vs. 7.6%, P=0.005). Conclusion Patients included in this large, single-center study all had a preoperative CONUT score of 0–5, but this study demonstrated that higher preoperative CONUT scores were significantly associated with advanced T stage and extrathyroidal extension. The CONUT score, which can be easily used in clinical practice, is thought to be helpful in predicting the aggressiveness of PTC.

Background: The Controlling Nutritional Status (CONUT) score is an immunonutritional test tool based on serum albumin, total cholesterol, and lymphocyte counts. It has been studied as a simple prognostic predictor for various carcinomas. This study aimed to investigate the association between preoperative CONUT scores and the clinicopathological characteristics in papillary thyroid carcinoma (PTC) patients. Methods: This study included 2,403 PTC patients who underwent total thyroidectomy between 2012 and 2016 at a single tertiary medical center. The CONUT scores were calculated based on preoperative blood tests. The clinicopathological characteristics were retrospectively reviewed. The patients were categorized by the CONUT score (relatively low, 0–2; relatively high, 3–5). Results: Among the 2,997 PTC patients who underwent total thyroidectomy at Pusan National University Hospital between 2012 and 2016, those without preoperative blood test were excluded (n=149). Finally 2,403 patients were analyzed after excluding 439 patients taking lipid-lowering drugs and six patients without available T stage data after surgery. Based on the CONUT score, the relatively high score group had a lower body mass index (23.7±3.3 kg/m2 vs. 21.9±2.9 kg/m2, P<0.001), more advanced T stage (T stage 3/4, 5.9% vs. 11.4%, P=0.045), and higher extrathyroidal extension (2.1% vs. 7.6%, P=0.005). Conclusion Patients included in this large, single-center study all had a preoperative CONUT score of 0–5, but this study demonstrated that higher preoperative CONUT scores were significantly associated with advanced T stage and extrathyroidal extension. The CONUT score, which can be easily used in clinical practice, is thought to be helpful in predicting the aggressiveness of PTC.

This paper provides a comprehensive overview of the Cancer Public Library Database (CPLD), established under the Korean Clinical Data Utilization for Research Excellence project (K-CURE). The CPLD links data from four major population-based public sources: the Korea National Cancer Incidence Database in the Korea Central Cancer Registry, cause-of-death data in Statistics Korea, the National Health Information Database in the National Health Insurance Service, and the National Health Insurance Research Database in the Health Insurance Review & Assessment Service. These databases are linked using an encrypted resident registration number. The CPLD, established in 2022 and updated annually, comprises 1,983,499 men and women newly diagnosed with cancer between 2012 and 2019. It contains data on cancer registration and death, demographics, medical claims, general health checkups, and national cancer screening. The most common cancers among men in the CPLD were stomach (16.1%), lung (14.0%), colorectal (13.3%), prostate (9.6%), and liver (9.3%) cancers. The most common cancers among women were thyroid (20.4%), breast (16.6%), colorectal (9.0%), stomach (7.8%), and lung (6.2%) cancers. Among them, 571,285 died between 2012 and 2020 owing to cancer (89.2%) or other causes (10.8%). Upon approval, the CPLD is accessible to researchers through the K-CURE portal. The CPLD is a unique resource for diverse cancer research to investigate medical use before a cancer diagnosis, during initial diagnosis and treatment, and long-term follow-up. This offers expanded insight into healthcare delivery across the cancer continuum, from screening to end-of-life care.

Background/Aims: Appropriate tissue tension and clear visibility of the dissection area using traction are essential for effective and safe endoscopic submucosal dissection (ESD). In this study, we developed a retractable robot-assisted traction device and evaluated its performance in colorectal ESD. Methods: An experienced endoscopist performed ESD 18 times on an ex vivo porcine colon using the robot and 18 times using the conventional method. The outcome measures were procedure time, dissection speed, procedure-related adverse events, and blind dissection rate. Results: Thirty-six colonic lesions were resected from ex vivo porcine colon samples. The total procedure time was significantly shorter in robot-assisted ESD (RESD) than in conventional ESD (CESD) (20.1±4.1 minutes vs 34.3±8.3 minutes, p<0.05). The submucosal dissection speed was significantly faster in the RESD group than in the CESD group (36.8±9.2 mm 2 /min vs 18.1±4.7 mm 2 /min, p<0.05). The blind dissection rate was also significantly lower in the RESD group (12.8%±3.4% vs 35.1%±3.9%, p<0.05). In an in vivo porcine feasibility study, the robotic device was attached to a colonoscope and successfully inserted into the proximal colon without damaging the colonic wall, and ESD was successfully performed. Conclusions The dissection speed and safety profile improved significantly with the retractable RESD. Thus, our robotic device has the potential to provide simple, effective, and safe multidirectional traction during colonic ESD.