Reliable preclinical models for assessing drug-induced cardiotoxicity are essential to reduce the high rate of drug withdrawals during development. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a promising platform for such assessments due to their expression of cardiacspecific ion channels and electrophysiological properties. In this study, we investigated the effects of eight arrhythmogenic drugs—E4031, nifedipine, mexiletine, JNJ303, flecainide, moxifloxacin, quinidine, and ranolazine—on hiPSC-CMs derived from both healthy individuals and a long QT syndrome (LQTS) patient using multielectrode array systems. The results demonstrated dose-dependent changes in field potential duration and arrhythmogenic risk, with LQTS-derived hiPSC-CMs showing increased sensitivity to hERG channel blockers such as E4031. Furthermore, the study highlights the potential of hiPSC-CMs to model disease-specific cardiac responses, providing insights into genetic predispositions and personalized drug responses.Despite challenges related to the immaturity of hiPSC-CMs, their ability to recapitulate human cardiac electrophysiology makes them a valuable tool for preclinical cardiotoxicity assessments. This study underscores the utility of integrating patientderived hiPSC-CMs with advanced analytical platforms, such as multi-electrode array systems, to evaluate drug-induced electrophysiological changes. These findings reinforce the role of hiPSC-CMs in drug development, facilitating safer and more efficient screening methods while supporting precision medicine applications.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

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.

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.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

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.

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.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.