Epidemiology, Patient Characteristics, and Treatment Patterns of Myasthenia Gravis in Taiwan: A Population-Based Study.

INTRODUCTION: Myasthenia gravis (MG) is a chronic neuromuscular disease leading to significant disease burden. This study aimed to investigate the epidemiology of MG in Taiwan. METHODS: A retrospective study was conducted using the Taiwan National Health Insurance Research Database. Prevalent patients with MG diagnosis (either ocular or generalized MG) from 2013 to 2019 were identified, and 2813 patients with initial MG diagnosis from 2014 to 2019 were further defined as the incident cohort. Patient characteristics, treatment patterns, and the occurrence of MG-related events were analyzed. RESULTS: The number of prevalent patients with MG increased from 4476 in 2013 to 5752 in 2019, with the prevalence rate increasing from 19 to 24 per 100,000 population. The incidence rate also slightly increased from 1.9 to 2.3 per 100,000 population during the study period. Almost all incident patients (99%, n = 2791) received MG-related treatment during the follow-up period. Among 1876 patients who received monotherapy as their initial treatment in the outpatient setting, the mean time from the index date to initial treatment was 48.8 (standard deviation 164.3) days, and most patients received acetylcholinesterase inhibitors (88.5%, n = 1661) as their initial treatment. During the first year after the index date, 133 (4.7%) incident patients experienced their first myasthenic crisis, and 96.2% of these events occurred within 3 months. CONCLUSION: The prevalence of MG increased steadily in Taiwan, and the treatment of patients with MG was consistent with guidelines. Despite a high treatment rate, patients still experienced MG-related events, highlighting the limitation of current treatments and emphasizing the need for early intervention and novel treatment approaches.

Community-based randomized intervention trial for periodontal disease after 18-month follow-up [Keelung Community-based Integrated Screening (KCIS) No. 4].

OBJECTIVES: As periodontal disease preponderates in adults, early detection and interventional regime is urgently needed. However, there is lack of evidence-based data on evaluation of population-based intervention programme related to periodontal disease. The aim of this study was to assess the efficacy of intervention regime on early periodontal disease identified from a community-based periodontal survey. METHOD: By randomization, 60 subjects were allocated to the intervention group and 49 to the control group respectively. Status on periodontal disease of participants was evaluated at entry and re-evaluated after intervention at 1-month and 18-month follow-up respectively. Primary outcome evaluated was based on Community Periodontal Index and Loss of Attachment on sextant level. RESULTS: The efficacy of intervention was significant in Community Periodontal Index (P<0.001) but not in Loss of Attachment (P=0.53) at 1-month and 18-month follow-up. CONCLUSION: The improvement of periodontal disease owing to intervention regime was seen in Community Periodontal Index but not Loss of Attachment as yet at 18-month follow-up after intervention.

Risk prediction for Down's syndrome in young pregnant women using maternal serum biomarkers: determination of cut-off risk from receiver operating characteristic curve analysis.

OBJECTIVE: The aim of this study was to establish a predictive model for Down's syndrome using maternal age as well as maternal serum levels of alpha-fetoprotein (AFP) and human chorionic gonadotropin (hCG), and to identify an optimal cut-off risk in women under the age of 35 years to improve sensitivity. METHODS: Logistic regression models were utilized to predict fetal Down's syndrome as a function of maternal age and logarithm of levels of AFP as well as hCG using training data of 20 pregnancies with fetal Down's syndrome and 9730 unaffected pregnancies. Validation was performed using data of another nine affected pregnancies and 3496 unaffected pregnancies. Receiver operating characteristic (ROC) curves were plotted. RESULTS: Based on the newly established logistic regression equations, the optimal cut-off risk from the ROC curve analysis was at 1:499, with a 17.8% false-positive rate and a 90.0% sensitivity. A suboptimal cut-off risk was estimated at 1:332, with a 12.0% false-positive rate and an 80% sensitivity. CONCLUSION: A predictive model for Down's syndrome was developed using logistic regression. By ROC curve analysis and clinical consideration, the cut-off risk for young pregnant women could be determined.