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: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

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: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

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: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Background: To analyze the effects of socioeconomic status (type of insurance and income level) and cancer stage on the survival of patients with liver cancer in Korea. Methods: A retrospective cohort study was constructed using data from the Healthcare Big Data Platform project in Korea between January 1, 2007, and December 31, 2017. A total of 143,511 patients in Korea diagnosed with liver cancer (International Classification of Diseases, 10th Revision [ICD-10] codes C22, C220, and C221) were followed for an average of 11 years. Of these, 110,443 died. The patient’s insurance type and income level were used as indicators of socioeconomic status. Unadjusted and adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a Cox proportional hazards regression model to analyze the relationship between the effects of sex, age, and cancer stage at first diagnosis (Surveillance, Epidemiology, and the End Results; SEER), type of insurance, and income level on the survival of patients with liver cancer. The interactive effects of the type of insurance, income level, and cancer stage on liver cancer death were also analyzed. Results: The lowest income group (medical aid) showed a higher risk for mortality (HR (95% CI); 1.37 (1.27–1.47) for all patients, 1.44 (1.32–1.57) for men, and 1.16 (1.01–1.34) for women) compared to the highest income group (1–6) among liver cancer (ICD-10 code C22) patients. The risk of liver cancer death was also higher in the lowest income group with a distant cancer stage (SEER = 7) diagnosis than for any other group. Conclusion Liver cancer patients with lower socioeconomic status and more severe cancer stages were at greater risk of death. Reducing social inequalities is needed to improve mortality rates among patients in lower social class groups who present with advanced cancer.