Background: Health statistics of pharmaceutical use and expenditure are essential to make and implement evidence-based pharmaceutical policy. This study aims to demonstrate the methods and results of pharmaceutical consumption and sales in 2018 according to the sources and methods given by the Organization for Economic Cooperation and Development (OECD). Methods: The medication list contains 39,346 medicines both reimbursed and non-reimbursed by the National Health Insurance in 2018. We used the therapeutic categories based on Anatomic Therapeutic Chemical Classification of World Health Organization. This study analyzed National Health Insurance claims data and supply data generated from wholesalers to health care facilities. The indicators are defined daily dose (DDD), per 1,000 inhabitants per day and US$ per capita. Results: In South Korea, the number of medications to which DDD were assigned was 18,055 and it was 45.9% of the total number of medications on the list. The consumption in anti-infective for systemic use (J) and musculo-skeletal system (M) was higher than the mean consumption among the OECD countries. The pharmaceutical sales per person in Korea was also higher than the mean sales per person across the OECD countries. Conclusion We sought to explain the methods to produce pharmaceutical consumption and sales statistics which we had submitted annually to OECD. Considering the characteristics of pharmaceutical statistics, a direct comparison should be approached with caution. Since the growth in pharmaceutical spending has greatly increased over the past decade, we need to monitor pharmaceutical consumption and expenditure consistently.

Purpose: Lower-grade gliomas of histologic grades 2 and 3 follow heterogenous clinical outcomes, which necessitates risk stratification. This study aimed to evaluate whether diffusion-weighted and perfusion-weighted MRI radiomics allow overall survival (OS) prediction in patients with lower-grade gliomas and investigate its prognostic value. Materials and Methods: In this retrospective study, radiomic features were extracted from apparent diffusion coefficient, relative cerebral blood volume map, and Ktrans map in patients with pathologically confirmed lower-grade gliomas (January 2012–February 2019). The radiomics risk score (RRS) calculated from selected features constituted a radiomics model. Multivariable Cox regression analysis, including clinical features and RRS, was performed. The models’ integrated area under the receiver operating characteristic curves (iAUCs) were compared. The radiomics model combined with clinical features was presented as a nomogram. Results: The study included 129 patients (median age, 44 years; interquartile range, 37–57 years; 63 female): 90 patients for training set and 39 patients for test set. The RRS was an independent risk factor for OS with a hazard ratio of 6.01. The combined clinical and radiomics model achieved superior performance for OS prediction compared to the clinical model in both training (iAUC, 0.82 vs.0.72, p=0.002) and test sets (0.88 vs. 0.76, p=0.04). The radiomics nomogram combined with clinical features exhibited good agreement between the actual and predicted OS with C-index of 0.83 and 0.87 in the training and test sets, respectively. Conclusion Adding diffusion- and perfusion-weighted MRI radiomics to clinical features improved survival prediction in lowergrade glioma.