1.Validation of the Korean Version of the Huntington’s Disease Quality of Life Battery for Carers
Hee Jin CHANG ; Eungseok OH ; Won Tae YOON ; Chan Young LEE ; Kyum-Yil KWON ; Yun Su HWANG ; Chaewon SHIN ; Jee-Young LEE
Journal of Movement Disorders 2025;18(2):160-164
Objective:
The Huntington’s Disease Quality of Life Battery for Carers (HDQoL-C) is used to evaluate caregiver quality of life. This study aimed to develop and validate the Korean version of the HDQoL-C (K-HDQoL-C) to assess the burden on Korean caregivers of Huntington’s disease (HD) patients.
Methods:
A total of 19 HD caregivers (7 females, mean age 55.4±14.6 years) participated in this study. The K-HDQoL-C, a translation of the English version, consisted of demographic information, caring aspects, life satisfaction, and feelings about life. It was administered twice, 2 weeks apart. Internal consistency was evaluated using Cronbach’s α, and test-retest reliability was assessed with intraclass correlation coefficients. The relationship with the Zarit Burden Interview-12 (ZBI-12) was analyzed.
Results:
The internal consistencies of the K-HDQoL-C were 0.771 (part 2), 0.938 (part 3), and 0.891 (part 4). The test-retest reliability ranged from 0.908 to 0.936. Part 3 was negatively correlated with the ZBI-12, and part 4 was positively correlated with the ZBI-12 (r=-0.780, 0.923; p<0.001).
Conclusion
The K-HDQoL-C effectively evaluates the challenges faced by HD caregivers, particularly in terms of care aspects and life satisfaction.
2.Nasal Nitric Oxide as an Objective Evaluation Tool for Treatment Response in Chronic Rhinitis
Sangeun LEE ; Su Mi SEONG ; Hyeop OH ; Jihun YOON ; Bo Hae KIM ; Joo Hyun PARK ; Yun-Sung LIM ; Chang Gun CHO ; Seok-Won PARK ; Jin Youp KIM
Journal of Rhinology 2025;32(1):40-47
Background and Objectives:
Inconsistencies in nasal nitric oxide (nNO) values, due to anatomical variations and comorbidities, challenge the accurate assessment of upper airway inflammation severity. We hypothesized that changes in nNO levels following treatment for chronic rhinitis would be consistent and provide relative value. This study aimed to evaluate the correlation between changes in nNO levels and symptomatic improvements following treatment for chronic rhinitis.
Methods:
This prospective observational study included 46 participants diagnosed with chronic rhinitis between December 2021 and November 2023. nNO measurements, evaluations of four nasal and two ocular symptoms, and quality of life questionnaires were conducted at baseline and after one month of treatment. Baseline laboratory tests included serum total immunoglobulin E levels, blood eosinophil percentages, and skin prick tests.
Results:
The Total Nasal Symptom Score (TNSS), TNSS with ocular symptoms (TNSS eye), and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores significantly decreased following treatment (all p<0.001). nNO levels also decreased significantly after treatment (p=0.036). Moreover, changes in nNO were significantly correlated with changes in TNSS, TNSS eye, and RQLQ scores (p=0.047, r=0.294; p=0.021, r=0.340; and p=0.004, r=0.419, respectively).
Conclusion
In patients with chronic rhinitis, changes in TNSS, TNSS eye, and RQLQ scores were correlated with changes in nNO levels after treatment. nNO may serve as a potential objective evaluation tool for chronic rhinitis, particularly in patients who have difficulty reporting symptoms.
3.A Novel Point-of-Care Prediction Model for Steatotic Liver Disease:Expected Role of Mass Screening in the Global Obesity Crisis
Jeayeon PARK ; Goh Eun CHUNG ; Yoosoo CHANG ; So Eun KIM ; Won SOHN ; Seungho RYU ; Yunmi KO ; Youngsu PARK ; Moon Haeng HUR ; Yun Bin LEE ; Eun Ju CHO ; Jeong-Hoon LEE ; Su Jong YU ; Jung-Hwan YOON ; Yoon Jun KIM
Gut and Liver 2025;19(1):126-135
Background/Aims:
The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD.
Methods:
We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms.
Results:
A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models.
Conclusions
As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.
4.Erratum: Korean Gastric Cancer Association-Led Nationwide Survey on Surgically Treated Gastric Cancers in 2023
Dong Jin KIM ; Jeong Ho SONG ; Ji-Hyeon PARK ; Sojung KIM ; Sin Hye PARK ; Cheol Min SHIN ; Yoonjin KWAK ; Kyunghye BANG ; Chung-sik GONG ; Sung Eun OH ; Yoo Min KIM ; Young Suk PARK ; Jeesun KIM ; Ji Eun JUNG ; Mi Ran JUNG ; Bang Wool EOM ; Ki Bum PARK ; Jae Hun CHUNG ; Sang-Il LEE ; Young-Gil SON ; Dae Hoon KIM ; Sang Hyuk SEO ; Sejin LEE ; Won Jun SEO ; Dong Jin PARK ; Yoonhong KIM ; Jin-Jo KIM ; Ki Bum PARK ; In CHO ; Hye Seong AHN ; Sung Jin OH ; Ju-Hee LEE ; Hayemin LEE ; Seong Chan GONG ; Changin CHOI ; Ji-Ho PARK ; Eun Young KIM ; Chang Min LEE ; Jong Hyuk YUN ; Seung Jong OH ; Eunju LEE ; Seong-A JEONG ; Jung-Min BAE ; Jae-Seok MIN ; Hyun-dong CHAE ; Sung Gon KIM ; Daegeun PARK ; Dong Baek KANG ; Hogoon KIM ; Seung Soo LEE ; Sung Il CHOI ; Seong Ho HWANG ; Su-Mi KIM ; Moon Soo LEE ; Sang Hyun KIM ; Sang-Ho JEONG ; Yusung YANG ; Yonghae BAIK ; Sang Soo EOM ; Inho JEONG ; Yoon Ju JUNG ; Jong-Min PARK ; Jin Won LEE ; Jungjai PARK ; Ki Han KIM ; Kyung-Goo LEE ; Jeongyeon LEE ; Seongil OH ; Ji Hun PARK ; Jong Won KIM ;
Journal of Gastric Cancer 2025;25(2):400-402
5.Korean Gastric Cancer AssociationLed Nationwide Survey on Surgically Treated Gastric Cancers in 2023
Dong Jin KIM ; Jeong Ho SONG ; Ji-Hyeon PARK ; Sojung KIM ; Sin Hye PARK ; Cheol Min SHIN ; Yoonjin KWAK ; Kyunghye BANG ; Chung-sik GONG ; Sung Eun OH ; Yoo Min KIM ; Young Suk PARK ; Jeesun KIM ; Ji Eun JUNG ; Mi Ran JUNG ; Bang Wool EOM ; Ki Bum PARK ; Jae Hun CHUNG ; Sang-Il LEE ; Young-Gil SON ; Dae Hoon KIM ; Sang Hyuk SEO ; Sejin LEE ; Won Jun SEO ; Dong Jin PARK ; Yoonhong KIM ; Jin-Jo KIM ; Ki Bum PARK ; In CHO ; Hye Seong AHN ; Sung Jin OH ; Ju-Hee LEE ; Hayemin LEE ; Seong Chan GONG ; Changin CHOI ; Ji-Ho PARK ; Eun Young KIM ; Chang Min LEE ; Jong Hyuk YUN ; Seung Jong OH ; Eunju LEE ; Seong-A JEONG ; Jung-Min BAE ; Jae-Seok MIN ; Hyun-dong CHAE ; Sung Gon KIM ; Daegeun PARK ; Dong Baek KANG ; Hogoon KIM ; Seung Soo LEE ; Sung Il CHOI ; Seong Ho HWANG ; Su-Mi KIM ; Moon Soo LEE ; Sang Hyun KIM ; Sang-Ho JEONG ; Yusung YANG ; Yonghae BAIK ; Sang Soo EOM ; Inho JEONG ; Yoon Ju JUNG ; Jong-Min PARK ; Jin Won LEE ; Jungjai PARK ; Ki Han KIM ; Kyung-Goo LEE ; Jeongyeon LEE ; Seongil OH ; Ji Hun PARK ; Jong Won KIM ; The Information Committee of the Korean Gastric Cancer Association
Journal of Gastric Cancer 2025;25(1):115-132
Purpose:
Since 1995, the Korean Gastric Cancer Association (KGCA) has been periodically conducting nationwide surveys on patients with surgically treated gastric cancer. This study details the results of the survey conducted in 2023.
Materials and Methods:
The survey was conducted from March to December 2024 using a standardized case report form. Data were collected on 86 items, including patient demographics, tumor characteristics, surgical procedures, and surgical outcomes. The results of the 2023 survey were compared with those of previous surveys.
Results:
Data from 12,751 cases were collected from 66 institutions. The mean patient age was 64.6 years, and the proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023. The proportion of upper-third tumors slightly decreased to 16.8% compared to 20.9% in 2019. Early gastric cancer accounted for 63.1% of cases in 2023.Regarding operative procedures, a totally laparoscopic approach was most frequently applied (63.2%) in 2023, while robotic gastrectomy steadily increased to 9.5% from 2.1% in 2014.The most common anastomotic method was the Billroth II procedure (48.8%) after distal gastrectomy and double-tract reconstruction (51.9%) after proximal gastrectomy in 2023.However, the proportion of esophago-gastrostomy with anti-reflux procedures increased to 30.9%. The rates of post-operative mortality and overall complications were 1.0% and 15.3%, respectively.
Conclusions
The results of the 2023 nationwide survey demonstrate the current status of gastric cancer treatment in Korea. This information will provide a basis for future gastric cancer research.
6.Clinical practice guidelines for ovarian cancer: an update to the Korean Society of Gynecologic Oncology guidelines
Banghyun LEE ; Suk-Joon CHANG ; Byung Su KWON ; Joo-Hyuk SON ; Myong Cheol LIM ; Yun Hwan KIM ; Shin-Wha LEE ; Chel Hun CHOI ; Kyung Jin EOH ; Jung-Yun LEE ; Yoo-Young LEE ; Dong Hoon SUH ; Yong Beom KIM
Journal of Gynecologic Oncology 2025;36(1):e69-
We updated the Korean Society of Gynecologic Oncology (KSGO) practice guideline for the management of ovarian cancer as version 5.1. The ovarian cancer guideline team of the KSGO published announced the fifth version (version 5.0) of its clinical practice guidelines for the management of ovarian cancer in December 2023. In version 5.0, the selection of the key questions and the systematic reviews were based on the data available up to December 2022.Therefore, we updated the guidelines version 5.0 with newly accumulated clinical data and added 5 new key questions reflecting the latest insights in the field of ovarian cancer between 2023 and 2024. For each question, recommendation was provided together with corresponding level of evidence and grade of recommendation, all established through expert consensus.
7.A Novel Point-of-Care Prediction Model for Steatotic Liver Disease:Expected Role of Mass Screening in the Global Obesity Crisis
Jeayeon PARK ; Goh Eun CHUNG ; Yoosoo CHANG ; So Eun KIM ; Won SOHN ; Seungho RYU ; Yunmi KO ; Youngsu PARK ; Moon Haeng HUR ; Yun Bin LEE ; Eun Ju CHO ; Jeong-Hoon LEE ; Su Jong YU ; Jung-Hwan YOON ; Yoon Jun KIM
Gut and Liver 2025;19(1):126-135
Background/Aims:
The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD.
Methods:
We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms.
Results:
A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models.
Conclusions
As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.
8.A Novel Point-of-Care Prediction Model for Steatotic Liver Disease:Expected Role of Mass Screening in the Global Obesity Crisis
Jeayeon PARK ; Goh Eun CHUNG ; Yoosoo CHANG ; So Eun KIM ; Won SOHN ; Seungho RYU ; Yunmi KO ; Youngsu PARK ; Moon Haeng HUR ; Yun Bin LEE ; Eun Ju CHO ; Jeong-Hoon LEE ; Su Jong YU ; Jung-Hwan YOON ; Yoon Jun KIM
Gut and Liver 2025;19(1):126-135
Background/Aims:
The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD.
Methods:
We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms.
Results:
A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models.
Conclusions
As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.
9.Erratum: Korean Gastric Cancer Association-Led Nationwide Survey on Surgically Treated Gastric Cancers in 2023
Dong Jin KIM ; Jeong Ho SONG ; Ji-Hyeon PARK ; Sojung KIM ; Sin Hye PARK ; Cheol Min SHIN ; Yoonjin KWAK ; Kyunghye BANG ; Chung-sik GONG ; Sung Eun OH ; Yoo Min KIM ; Young Suk PARK ; Jeesun KIM ; Ji Eun JUNG ; Mi Ran JUNG ; Bang Wool EOM ; Ki Bum PARK ; Jae Hun CHUNG ; Sang-Il LEE ; Young-Gil SON ; Dae Hoon KIM ; Sang Hyuk SEO ; Sejin LEE ; Won Jun SEO ; Dong Jin PARK ; Yoonhong KIM ; Jin-Jo KIM ; Ki Bum PARK ; In CHO ; Hye Seong AHN ; Sung Jin OH ; Ju-Hee LEE ; Hayemin LEE ; Seong Chan GONG ; Changin CHOI ; Ji-Ho PARK ; Eun Young KIM ; Chang Min LEE ; Jong Hyuk YUN ; Seung Jong OH ; Eunju LEE ; Seong-A JEONG ; Jung-Min BAE ; Jae-Seok MIN ; Hyun-dong CHAE ; Sung Gon KIM ; Daegeun PARK ; Dong Baek KANG ; Hogoon KIM ; Seung Soo LEE ; Sung Il CHOI ; Seong Ho HWANG ; Su-Mi KIM ; Moon Soo LEE ; Sang Hyun KIM ; Sang-Ho JEONG ; Yusung YANG ; Yonghae BAIK ; Sang Soo EOM ; Inho JEONG ; Yoon Ju JUNG ; Jong-Min PARK ; Jin Won LEE ; Jungjai PARK ; Ki Han KIM ; Kyung-Goo LEE ; Jeongyeon LEE ; Seongil OH ; Ji Hun PARK ; Jong Won KIM ;
Journal of Gastric Cancer 2025;25(2):400-402
10.Korean Gastric Cancer AssociationLed Nationwide Survey on Surgically Treated Gastric Cancers in 2023
Dong Jin KIM ; Jeong Ho SONG ; Ji-Hyeon PARK ; Sojung KIM ; Sin Hye PARK ; Cheol Min SHIN ; Yoonjin KWAK ; Kyunghye BANG ; Chung-sik GONG ; Sung Eun OH ; Yoo Min KIM ; Young Suk PARK ; Jeesun KIM ; Ji Eun JUNG ; Mi Ran JUNG ; Bang Wool EOM ; Ki Bum PARK ; Jae Hun CHUNG ; Sang-Il LEE ; Young-Gil SON ; Dae Hoon KIM ; Sang Hyuk SEO ; Sejin LEE ; Won Jun SEO ; Dong Jin PARK ; Yoonhong KIM ; Jin-Jo KIM ; Ki Bum PARK ; In CHO ; Hye Seong AHN ; Sung Jin OH ; Ju-Hee LEE ; Hayemin LEE ; Seong Chan GONG ; Changin CHOI ; Ji-Ho PARK ; Eun Young KIM ; Chang Min LEE ; Jong Hyuk YUN ; Seung Jong OH ; Eunju LEE ; Seong-A JEONG ; Jung-Min BAE ; Jae-Seok MIN ; Hyun-dong CHAE ; Sung Gon KIM ; Daegeun PARK ; Dong Baek KANG ; Hogoon KIM ; Seung Soo LEE ; Sung Il CHOI ; Seong Ho HWANG ; Su-Mi KIM ; Moon Soo LEE ; Sang Hyun KIM ; Sang-Ho JEONG ; Yusung YANG ; Yonghae BAIK ; Sang Soo EOM ; Inho JEONG ; Yoon Ju JUNG ; Jong-Min PARK ; Jin Won LEE ; Jungjai PARK ; Ki Han KIM ; Kyung-Goo LEE ; Jeongyeon LEE ; Seongil OH ; Ji Hun PARK ; Jong Won KIM ; The Information Committee of the Korean Gastric Cancer Association
Journal of Gastric Cancer 2025;25(1):115-132
Purpose:
Since 1995, the Korean Gastric Cancer Association (KGCA) has been periodically conducting nationwide surveys on patients with surgically treated gastric cancer. This study details the results of the survey conducted in 2023.
Materials and Methods:
The survey was conducted from March to December 2024 using a standardized case report form. Data were collected on 86 items, including patient demographics, tumor characteristics, surgical procedures, and surgical outcomes. The results of the 2023 survey were compared with those of previous surveys.
Results:
Data from 12,751 cases were collected from 66 institutions. The mean patient age was 64.6 years, and the proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023. The proportion of upper-third tumors slightly decreased to 16.8% compared to 20.9% in 2019. Early gastric cancer accounted for 63.1% of cases in 2023.Regarding operative procedures, a totally laparoscopic approach was most frequently applied (63.2%) in 2023, while robotic gastrectomy steadily increased to 9.5% from 2.1% in 2014.The most common anastomotic method was the Billroth II procedure (48.8%) after distal gastrectomy and double-tract reconstruction (51.9%) after proximal gastrectomy in 2023.However, the proportion of esophago-gastrostomy with anti-reflux procedures increased to 30.9%. The rates of post-operative mortality and overall complications were 1.0% and 15.3%, respectively.
Conclusions
The results of the 2023 nationwide survey demonstrate the current status of gastric cancer treatment in Korea. This information will provide a basis for future gastric cancer research.

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