Background: and Purpose Treatments for neuromyelitis optica spectrum disorder (NMOSD) such as eculizumab, ravulizumab, satralizumab, and inebilizumab have significantly advanced relapse prevention, but they remain expensive. Rituximab is an off-label yet popular alternative that offers a cost-effective solution, but its real-world efficacy needs better quantification for guiding the application of newer approved NMOSD treatments (ANTs). This study aimed to determine real-world rituximab failure rates to anticipate the demand for ANTs and aid in resource allocation. Methods: We conducted a nationwide retrospective study involving 605 aquaporin-4-antibody-positive NMOSD patients from 22 centers in South Korea that assessed the efficacy and safety of rituximab over a median follow-up of 47 months. Results: The 605 patients treated with rituximab included 525 (87%) who received continuous therapy throughout the follow-up period (median=47 months, interquartile range=15–87 months). During this period, 117 patients (19%) experienced at least 1 relapse. Notably, 68 of these patients (11% of the total cohort) experienced multiple relapses or at least 1 severe relapse.Additionally, 2% of the patients discontinued rituximab due to adverse events, which included severe infusion reactions, neutropenia, and infections. Conclusions This study has confirmed the efficacy of rituximab in treating NMOSD, as evidenced by an 87% continuation rate among patients over a 4-year follow-up period. Nevertheless, the occurrence of at least one relapse in 19% of the cohort, including 11% who experienced multiple or severe relapses, and a 2% discontinuation rate due to adverse events highlight the urgent need for alternative therapeutic options.

Background: and Purpose Treatments for neuromyelitis optica spectrum disorder (NMOSD) such as eculizumab, ravulizumab, satralizumab, and inebilizumab have significantly advanced relapse prevention, but they remain expensive. Rituximab is an off-label yet popular alternative that offers a cost-effective solution, but its real-world efficacy needs better quantification for guiding the application of newer approved NMOSD treatments (ANTs). This study aimed to determine real-world rituximab failure rates to anticipate the demand for ANTs and aid in resource allocation. Methods: We conducted a nationwide retrospective study involving 605 aquaporin-4-antibody-positive NMOSD patients from 22 centers in South Korea that assessed the efficacy and safety of rituximab over a median follow-up of 47 months. Results: The 605 patients treated with rituximab included 525 (87%) who received continuous therapy throughout the follow-up period (median=47 months, interquartile range=15–87 months). During this period, 117 patients (19%) experienced at least 1 relapse. Notably, 68 of these patients (11% of the total cohort) experienced multiple relapses or at least 1 severe relapse.Additionally, 2% of the patients discontinued rituximab due to adverse events, which included severe infusion reactions, neutropenia, and infections. Conclusions This study has confirmed the efficacy of rituximab in treating NMOSD, as evidenced by an 87% continuation rate among patients over a 4-year follow-up period. Nevertheless, the occurrence of at least one relapse in 19% of the cohort, including 11% who experienced multiple or severe relapses, and a 2% discontinuation rate due to adverse events highlight the urgent need for alternative therapeutic options.

Background: and Purpose Treatments for neuromyelitis optica spectrum disorder (NMOSD) such as eculizumab, ravulizumab, satralizumab, and inebilizumab have significantly advanced relapse prevention, but they remain expensive. Rituximab is an off-label yet popular alternative that offers a cost-effective solution, but its real-world efficacy needs better quantification for guiding the application of newer approved NMOSD treatments (ANTs). This study aimed to determine real-world rituximab failure rates to anticipate the demand for ANTs and aid in resource allocation. Methods: We conducted a nationwide retrospective study involving 605 aquaporin-4-antibody-positive NMOSD patients from 22 centers in South Korea that assessed the efficacy and safety of rituximab over a median follow-up of 47 months. Results: The 605 patients treated with rituximab included 525 (87%) who received continuous therapy throughout the follow-up period (median=47 months, interquartile range=15–87 months). During this period, 117 patients (19%) experienced at least 1 relapse. Notably, 68 of these patients (11% of the total cohort) experienced multiple relapses or at least 1 severe relapse.Additionally, 2% of the patients discontinued rituximab due to adverse events, which included severe infusion reactions, neutropenia, and infections. Conclusions This study has confirmed the efficacy of rituximab in treating NMOSD, as evidenced by an 87% continuation rate among patients over a 4-year follow-up period. Nevertheless, the occurrence of at least one relapse in 19% of the cohort, including 11% who experienced multiple or severe relapses, and a 2% discontinuation rate due to adverse events highlight the urgent need for alternative therapeutic options.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Background: During the coronavirus disease 2019 (COVID-19) pandemic, patients with myasthenia gravis (MG) were more susceptible to poor outcomes owing to respiratory muscle weakness and immunotherapy. Several studies conducted in the early stages of the COVID-19 pandemic reported higher mortality in patients with MG compared to the general population. This study aimed to investigate the clinical course and prognosis of COVID-19 in patients with MG and to compare these parameters between vaccinated and unvaccinated patients in South Korea. Methods: This multicenter, retrospective study, which was conducted at 14 tertiary hospitals in South Korea, reviewed the medical records and identified MG patients who contracted COVID-19 between February 2022 and April 2022. The demographic and clinical characteristics associated with MG and vaccination status were collected. The clinical outcomes of COVID-19 infection and MG were investigated and compared between the vaccinated and unvaccinated patients. Results: Ninety-two patients with MG contracted COVID-19 during the study. Nine (9.8%) patients required hospitalization, 4 (4.3%) of whom were admitted to the intensive care unit. Seventy-five of 92 patients were vaccinated before contracting COVID-19 infection, and 17 were not. During the COVID-19 infection, 6 of 17 (35.3%) unvaccinated patients were hospitalized, whereas 3 of 75 (4.0%) vaccinated patients were hospitalized (P < 0.001). The frequencies of ICU admission and mechanical ventilation were significantly lower in the vaccinated patients than in the unvaccinated patients (P = 0.019 and P = 0.032, respectively). The rate of MG deterioration was significantly lower in the vaccinated patients than in the unvaccinated patients (P = 0.041). Logistic regression after weighting revealed that the risk of hospitalization and MG deterioration after COVID-19 infection was significantly lower in the vaccinated patients than in the unvaccinated patients. Conclusion This study suggests that the clinical course and prognosis of patients with MG who contracted COVID-19 during the dominance of the omicron variant of COVID-19 may be milder than those at the early phase of the COVID-19 pandemic when vaccination was unavailable. Vaccination may reduce the morbidity of COVID-19 in patients with MG and effectively prevent MG deterioration induced by COVID-19 infection.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Methods: We evaluated patients who underwent EPTLIF with a minimum 24-month follow-up. Clinical parameters of the Visual Analog Scale (VAS) and Oswestry Disability Index (ODI) were measured at the preoperative, 1-week postoperative mark, postoperative 3-month mark, and final follow-up. Preoperative and 1-year postoperative magnetic resonance imaging measurement of preoperative and postoperative Kjaer grade, right and left psoas muscle mass area, and right and left paraspinal muscle mass area was performed. Results: EPTLIF with a minimum 24-month follow-up of 35 levels was included. The complication rate was 6%, and the mean Bridwell’s fusion grade was 1.37 (1–2). There was statistically significant improvement at 1 week, 3 months, and 2 years in VAS (4.11±1.23, 4.94±1.30, and 5.46±1.29) and in ODI (40.34±10.06, 46.69±9.14, and 49.63±8.68), respectively (p <0.05). Successful operation rate with excellent and good MacNab’s criteria at 2 years was 97%. There was an increment of statistically significant bilateral psoas muscle cross-sectional area, right side (70.03±149.1 mm²) and left side (67.59±113.2 mm²) (p <0.05). Conclusions Uniportal EPTLIF achieved good fusion and improved clinical outcomes with favorable paraspinal musculature bulk at the 2-year follow-up.