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.

Objectives: This study aims to examine the differences in spectral analysis of waking electroencephalography (EEG) patterns between patients with moderate to severe obstructive sleep apnea (OSA) experiencing excessive daytime sleepiness (EDS) and matched healthy participants, to gain insights into the neurophysiological underpinnings of daytime impairments. Methods: A cross-sectional analysis was conducted involving 17 patients with moderate to severe OSA confirmed by overnight polysomnography (PSG). These patients had ≥15 per hour apnea–hypopnea index (AHI) and ≥11 Epworth Sleepiness Scale (ESS). EEG recordings were captured within 30 minutes of awakening. A corresponding group of the equal number of age and sex-matched healthy participants was also analyzed for comparative purposes. Spectral analysis of quantitative EEG (qEEG) of patients with OSA compared with that of an equal number of age- and sex-matched healthy participants. Results: The analysis included 17 patients (16 males, average age 57.2 years) with moderate to severe OSA experiencing EDS (mean AHI 38.1±20.5; ESS 14.4±3.2). The patients with OSA exhibited altered sleep architecture during diagnostic PSG, significantly higher EEG delta band power in the frontal regions upon awakening after night sleep, and decreased connection of delta band in frontal area than normal participants (3.78±5.53 vs. 3.22±0.98 μV2, p=0.03). Conclusions The study demonstrated difference in delta activity and connectivity in the frontal area between patients with OSA experiencing EDS and the control group. These findings suggest awakening qEEG in OSA may helpful to guide or enhance understanding of daytime functional impairment and EDS.

Objectives: This study aims to examine the differences in spectral analysis of waking electroencephalography (EEG) patterns between patients with moderate to severe obstructive sleep apnea (OSA) experiencing excessive daytime sleepiness (EDS) and matched healthy participants, to gain insights into the neurophysiological underpinnings of daytime impairments. Methods: A cross-sectional analysis was conducted involving 17 patients with moderate to severe OSA confirmed by overnight polysomnography (PSG). These patients had ≥15 per hour apnea–hypopnea index (AHI) and ≥11 Epworth Sleepiness Scale (ESS). EEG recordings were captured within 30 minutes of awakening. A corresponding group of the equal number of age and sex-matched healthy participants was also analyzed for comparative purposes. Spectral analysis of quantitative EEG (qEEG) of patients with OSA compared with that of an equal number of age- and sex-matched healthy participants. Results: The analysis included 17 patients (16 males, average age 57.2 years) with moderate to severe OSA experiencing EDS (mean AHI 38.1±20.5; ESS 14.4±3.2). The patients with OSA exhibited altered sleep architecture during diagnostic PSG, significantly higher EEG delta band power in the frontal regions upon awakening after night sleep, and decreased connection of delta band in frontal area than normal participants (3.78±5.53 vs. 3.22±0.98 μV2, p=0.03). Conclusions The study demonstrated difference in delta activity and connectivity in the frontal area between patients with OSA experiencing EDS and the control group. These findings suggest awakening qEEG in OSA may helpful to guide or enhance understanding of daytime functional impairment and EDS.

Objectives: This study aims to examine the differences in spectral analysis of waking electroencephalography (EEG) patterns between patients with moderate to severe obstructive sleep apnea (OSA) experiencing excessive daytime sleepiness (EDS) and matched healthy participants, to gain insights into the neurophysiological underpinnings of daytime impairments. Methods: A cross-sectional analysis was conducted involving 17 patients with moderate to severe OSA confirmed by overnight polysomnography (PSG). These patients had ≥15 per hour apnea–hypopnea index (AHI) and ≥11 Epworth Sleepiness Scale (ESS). EEG recordings were captured within 30 minutes of awakening. A corresponding group of the equal number of age and sex-matched healthy participants was also analyzed for comparative purposes. Spectral analysis of quantitative EEG (qEEG) of patients with OSA compared with that of an equal number of age- and sex-matched healthy participants. Results: The analysis included 17 patients (16 males, average age 57.2 years) with moderate to severe OSA experiencing EDS (mean AHI 38.1±20.5; ESS 14.4±3.2). The patients with OSA exhibited altered sleep architecture during diagnostic PSG, significantly higher EEG delta band power in the frontal regions upon awakening after night sleep, and decreased connection of delta band in frontal area than normal participants (3.78±5.53 vs. 3.22±0.98 μV2, p=0.03). Conclusions The study demonstrated difference in delta activity and connectivity in the frontal area between patients with OSA experiencing EDS and the control group. These findings suggest awakening qEEG in OSA may helpful to guide or enhance understanding of daytime functional impairment and EDS.

Purpose: This study examines the association between child maltreatment and the perpetration and victimization of intimate partner violence (IPV) in adulthood, exploring the moderating effects of gender, age, and household income level. Methods: This cross-sectional study analyzed secondary data from the 2016 Domestic Violence Survey in South Korea, including 1,765 married individuals aged 65 or younger who responded to key variables. Structural equation modeling was used to analyze associations among the variables. Results: The paths from child maltreatment to IPV perpetration (β=.22, p<.001) and victimization (β=.22, p<.001) were statistically significant. Gender, age, and household income level significantly moderated this relationship. Women under 40 were more likely to be IPV victims than perpetrators. Low-income level increased the likelihood of being both perpetrators and victims. Women under 40 who had experienced child maltreatment and had a low-income level showed different probabilities of being victims or perpetrators of IPV. Conclusion Our findings highlight the need to mitigate the negative impact of child maltreatment in adulthood by designing specific interventions for vulnerable groups, such as women, younger individuals, and those with low-income levels. Ensuring lifelong prevention of child maltreatment and establishing tailored programs for IPV is crucial.