Purpose: This study aims to systematically analyze the radioactive waste generated from treatments using radioactive Iodine-131 (I-131), Lutetium-177 (Lu-177), and Actinium-225 (Ac-225) to facilitate safe waste management practices. Methods: I-131 is primarily used in thyroid cancer treatment, while Lu-177 and Ac-225 are used to treat prostate cancer. Radioactive waste generated after these treatments was collected from patients at the Korea Cancer Center Hospital and categorized into clothing, slippers, syringes, and other items. The radioactivity concentration of each item was measured using a calibrated highpurity germanium detector. Using measurements, the self-disposal date of each waste item was calculated according to the permissible disposal levels defined by the Nuclear Safety and Security Commission (NSSC) under domestic nuclear safety regulations. Results: For the I-131 radioactive waste, clothing, towels, and tableware exhibited high radioactivity concentrations, with most items exceeding the permissible self-disposal levels.Conversely, the type and quantity of waste generated from Lu-177 and Ac-225 that were intravenously injected were relatively minimal, with certain items below the self-disposal thresholds, enabling immediate disposal. For Ac-225, no permissible self-disposal concentration is specified by the NSSC, unlike other therapeutic nuclides. Hence, additional studies are required to establish clear guidelines. Conclusions These findings provide valuable data for optimizing radioactive waste management, potentially reducing disposal time and costs, minimizing radiation exposure, and enhancing hospital safety practices.

Purpose: This study aims to systematically analyze the radioactive waste generated from treatments using radioactive Iodine-131 (I-131), Lutetium-177 (Lu-177), and Actinium-225 (Ac-225) to facilitate safe waste management practices. Methods: I-131 is primarily used in thyroid cancer treatment, while Lu-177 and Ac-225 are used to treat prostate cancer. Radioactive waste generated after these treatments was collected from patients at the Korea Cancer Center Hospital and categorized into clothing, slippers, syringes, and other items. The radioactivity concentration of each item was measured using a calibrated highpurity germanium detector. Using measurements, the self-disposal date of each waste item was calculated according to the permissible disposal levels defined by the Nuclear Safety and Security Commission (NSSC) under domestic nuclear safety regulations. Results: For the I-131 radioactive waste, clothing, towels, and tableware exhibited high radioactivity concentrations, with most items exceeding the permissible self-disposal levels.Conversely, the type and quantity of waste generated from Lu-177 and Ac-225 that were intravenously injected were relatively minimal, with certain items below the self-disposal thresholds, enabling immediate disposal. For Ac-225, no permissible self-disposal concentration is specified by the NSSC, unlike other therapeutic nuclides. Hence, additional studies are required to establish clear guidelines. Conclusions These findings provide valuable data for optimizing radioactive waste management, potentially reducing disposal time and costs, minimizing radiation exposure, and enhancing hospital safety practices.

Purpose: This study aims to systematically analyze the radioactive waste generated from treatments using radioactive Iodine-131 (I-131), Lutetium-177 (Lu-177), and Actinium-225 (Ac-225) to facilitate safe waste management practices. Methods: I-131 is primarily used in thyroid cancer treatment, while Lu-177 and Ac-225 are used to treat prostate cancer. Radioactive waste generated after these treatments was collected from patients at the Korea Cancer Center Hospital and categorized into clothing, slippers, syringes, and other items. The radioactivity concentration of each item was measured using a calibrated highpurity germanium detector. Using measurements, the self-disposal date of each waste item was calculated according to the permissible disposal levels defined by the Nuclear Safety and Security Commission (NSSC) under domestic nuclear safety regulations. Results: For the I-131 radioactive waste, clothing, towels, and tableware exhibited high radioactivity concentrations, with most items exceeding the permissible self-disposal levels.Conversely, the type and quantity of waste generated from Lu-177 and Ac-225 that were intravenously injected were relatively minimal, with certain items below the self-disposal thresholds, enabling immediate disposal. For Ac-225, no permissible self-disposal concentration is specified by the NSSC, unlike other therapeutic nuclides. Hence, additional studies are required to establish clear guidelines. Conclusions These findings provide valuable data for optimizing radioactive waste management, potentially reducing disposal time and costs, minimizing radiation exposure, and enhancing hospital safety practices.

Purpose: This study aims to systematically analyze the radioactive waste generated from treatments using radioactive Iodine-131 (I-131), Lutetium-177 (Lu-177), and Actinium-225 (Ac-225) to facilitate safe waste management practices. Methods: I-131 is primarily used in thyroid cancer treatment, while Lu-177 and Ac-225 are used to treat prostate cancer. Radioactive waste generated after these treatments was collected from patients at the Korea Cancer Center Hospital and categorized into clothing, slippers, syringes, and other items. The radioactivity concentration of each item was measured using a calibrated highpurity germanium detector. Using measurements, the self-disposal date of each waste item was calculated according to the permissible disposal levels defined by the Nuclear Safety and Security Commission (NSSC) under domestic nuclear safety regulations. Results: For the I-131 radioactive waste, clothing, towels, and tableware exhibited high radioactivity concentrations, with most items exceeding the permissible self-disposal levels.Conversely, the type and quantity of waste generated from Lu-177 and Ac-225 that were intravenously injected were relatively minimal, with certain items below the self-disposal thresholds, enabling immediate disposal. For Ac-225, no permissible self-disposal concentration is specified by the NSSC, unlike other therapeutic nuclides. Hence, additional studies are required to establish clear guidelines. Conclusions These findings provide valuable data for optimizing radioactive waste management, potentially reducing disposal time and costs, minimizing radiation exposure, and enhancing hospital safety practices.

Purpose: This study aims to systematically analyze the radioactive waste generated from treatments using radioactive Iodine-131 (I-131), Lutetium-177 (Lu-177), and Actinium-225 (Ac-225) to facilitate safe waste management practices. Methods: I-131 is primarily used in thyroid cancer treatment, while Lu-177 and Ac-225 are used to treat prostate cancer. Radioactive waste generated after these treatments was collected from patients at the Korea Cancer Center Hospital and categorized into clothing, slippers, syringes, and other items. The radioactivity concentration of each item was measured using a calibrated highpurity germanium detector. Using measurements, the self-disposal date of each waste item was calculated according to the permissible disposal levels defined by the Nuclear Safety and Security Commission (NSSC) under domestic nuclear safety regulations. Results: For the I-131 radioactive waste, clothing, towels, and tableware exhibited high radioactivity concentrations, with most items exceeding the permissible self-disposal levels.Conversely, the type and quantity of waste generated from Lu-177 and Ac-225 that were intravenously injected were relatively minimal, with certain items below the self-disposal thresholds, enabling immediate disposal. For Ac-225, no permissible self-disposal concentration is specified by the NSSC, unlike other therapeutic nuclides. Hence, additional studies are required to establish clear guidelines. Conclusions These findings provide valuable data for optimizing radioactive waste management, potentially reducing disposal time and costs, minimizing radiation exposure, and enhancing hospital safety practices.

Purpose: The genetic attribution for pancreatic ductal adenocarcinoma (PDAC) has been reported as 5%-10%. However, the incidence of germline pathogenic variants (PVs) in Korean PDAC patients has not been thoroughly investigated. Therefore, we studied to identify the risk factors and prevalence of PV for future treatment strategies in PDAC. Materials and Methods: Total of 300 (155 male) patients with a median age of 65 years (range, 33 to 90 years) were enrolled in National Cancer Center in Korea. Cancer predisposition genes, clinicopathologic characteristics, and family history of cancer were analyzed. Results: PVs were detected in 20 patients (6.7%, median age 65) in ATM (n=7, 31.8%), BRCA1 (n=3, 13.6%), BRCA2 (n=3), and RAD51D (n=3). Each one patient showed TP53, PALB2, PMS2, RAD50, MSH3, and SPINK1 PV. Among them, two likely PVs were in ATM and RAD51D, respectively. Family history of various types of cancer including pancreatic cancer (n=4) were found in 12 patients. Three patients with ATM PVs and a patient with three germline PVs (BRCA2, MSH3, and RAD51D) had first-degree relatives with pancreatic cancer. Familial pancreatic cancer history and PVs detection had a significant association (4/20, 20% vs. 16/264, 5.7%; p=0.035). Conclusion Our study demonstrated that germline PVs in ATM, BRCA1, BRCA2, and RAD51D are most frequent in Korean PDAC patients and it is comparable to those of different ethnic groups. Although this study did not show guidelines for germline predisposition gene testing in patients with PDAC in Korea, it would be emphasized the need for germline testing for all PDAC patients.

Background/Aims: Cirrhosis is the most important risk factor of hepatocellular carcinoma (HCC), and patients with cirrhosis are recommended to receive semiannual surveillance for early HCC detection. However, early cirrhosis is often asymptomatic and can go undiagnosed for years, leading to underuse of HCC surveillance in clinical practice. We characterized the frequency and associated factors of unrecognized cirrhosis in a national sample of patients with HCC from the United States. Methods: HCC patients aged 68 years and older, diagnosed during 2011 to 2015 were included from the SEERMedicare Linked Database. If cirrhosis was diagnosed within 6 months immediately preceding HCC diagnosis or after HCC diagnosis, cases were categorized as unrecognized cirrhosis. Factors associated with unrecognized cirrhosis were identified using logistic regression analyses. Factors associated with overall survival were evaluated using Cox regression analyses. Results: Among 5,098 HCC patients, 74.8% patients had cirrhosis. Among those with cirrhosis, 57.4% had unrecognized cirrhosis, with the highest proportion (76.3%) among those with NAFLD-related HCC. Male sex (aOR: 2.12, 95% CI: 1.83–2.46), non-Hispanic Black race (aOR: 1.93, 95% CI: 1.45–2.57), and NAFLD etiology (aOR: 4.46, 95% CI: 3.68–5.41) were associated with having unrecognized cirrhosis. Among NAFLD-related HCC patients, male sex (aOR: 2.32, 95% CI: 1.71–3.14) was associated with unrecognized cirrhosis. Unrecognized cirrhosis was independently associated with worse overall survival (aHR: 1.17, 95% CI: 1.08–1.27) compared to recognized cirrhosis. Conclusions Unrecognized cirrhosis is common in NAFLD-related HCC, particularly among male and Black patients, highlighting these groups as important intervention targets to improve HCC surveillance uptake and outcomes.

Background/Aims: The protective effects of vitamin D and calcium on colorectal neoplasms are known. Bone mineral density (BMD) may be a reliable biomarker that reflects the long-term anticancer effect of vitamin D and calcium. This study aimed to evaluate the association between BMD and colorectal adenomas including high-risk adenoma. Methods: A multicenter, cross-sectional, case-control study was conducted among participants with average risk of colorectal cancer who underwent BMD and screening colonoscopy between 2015 and 2019. The main outcome was the detection of colorectal neoplasms. The variable under consideration was low BMD (osteopenia/osteoporosis). The logistic regression model included baseline demographics, components of metabolic syndrome, fatty liver disease status, and aspirin and multivitamin use. Results: A total of 2,109 subjects were enrolled. The mean age was 52.1±10.8 years and 42.6% were male. The adenoma detection rate was 43%. Colorectal adenoma and high-risk adenoma were both more prevalent in subjects with low BMD than those with normal BMD (48.2% vs 38.8% and 12.1% vs 9.1%). In the univariate analysis, old age, male sex, smoking, metabolic components, fatty liver, and osteoporosis were significantly associated with the risk of adenoma and high-risk adenoma. In the multivariate analysis, osteoporosis was independently associated with risk of colorectal adenoma (odds ratio [OR], 1.65; 95% confidence interval [CI], 1.11 to 2.46; p=0.014) and high-risk adenoma (OR, 1.94; 95% CI, 1.14 to 3.29; p=0.014). Conclusions Osteoporosis is an independent risk factor of colorectal adenoma and high-risk adenoma

Purpose: Diagnostic classification models (DCMs) were developed to identify the mastery or non-mastery of the attributes required for solving test items, but their application has been limited to very low-level attributes, and the accuracy and consistency of high-level attributes using DCMs have rarely been reported compared with classical test theory (CTT) and item response theory models. This paper compared the accuracy of high-level attribute mastery between deterministic inputs, noisy “and” gate (DINA) and Rasch models, along with sub-scores based on CTT. Methods: First, a simulation study explored the effects of attribute length (number of items per attribute) and the correlations among attributes with respect to the accuracy of mastery. Second, a real-data study examined model and item fit and investigated the consistency of mastery for each attribute among the 3 models using the 2017 Korean Medical Licensing Examination with 360 items. Results: Accuracy of mastery increased with a higher number of items measuring each attribute across all conditions. The DINA model was more accurate than the CTT and Rasch models for attributes with high correlations (>0.5) and few items. In the real-data analysis, the DINA and Rasch models generally showed better item fits and appropriate model fit. The consistency of mastery between the Rasch and DINA models ranged from 0.541 to 0.633 and the correlations of person attribute scores between the Rasch and DINA models ranged from 0.579 to 0.786. Conclusion Although all 3 models provide a mastery decision for each examinee, the individual mastery profile using the DINA model provides more accurate decisions for attributes with high correlations than the CTT and Rasch models. The DINA model can also be directly applied to tests with complex structures, unlike the CTT and Rasch models, and it provides different diagnostic information from the CTT and Rasch models.

Purpose: Diagnostic classification models (DCMs) were developed to identify the mastery or non-mastery of the attributes required for solving test items, but their application has been limited to very low-level attributes, and the accuracy and consistency of high-level attributes using DCMs have rarely been reported compared with classical test theory (CTT) and item response theory models. This paper compared the accuracy of high-level attribute mastery between deterministic inputs, noisy “and” gate (DINA) and Rasch models, along with sub-scores based on CTT. Methods: First, a simulation study explored the effects of attribute length (number of items per attribute) and the correlations among attributes with respect to the accuracy of mastery. Second, a real-data study examined model and item fit and investigated the consistency of mastery for each attribute among the 3 models using the 2017 Korean Medical Licensing Examination with 360 items. Results: Accuracy of mastery increased with a higher number of items measuring each attribute across all conditions. The DINA model was more accurate than the CTT and Rasch models for attributes with high correlations (>0.5) and few items. In the real-data analysis, the DINA and Rasch models generally showed better item fits and appropriate model fit. The consistency of mastery between the Rasch and DINA models ranged from 0.541 to 0.633 and the correlations of person attribute scores between the Rasch and DINA models ranged from 0.579 to 0.786. Conclusion Although all 3 models provide a mastery decision for each examinee, the individual mastery profile using the DINA model provides more accurate decisions for attributes with high correlations than the CTT and Rasch models. The DINA model can also be directly applied to tests with complex structures, unlike the CTT and Rasch models, and it provides different diagnostic information from the CTT and Rasch models.