Purpose: Finasteride and dutasteride are used to treat benign prostatic hyperplasia (BPH) and reduce the risk of developing prostate cancer. Finasteride blocks only the type 2 form of 5-alpha-reductase, whereas dutasteride blocks both type 1 and 2 forms of the enzyme. Previous studies suggest the possibility that dutasteride may be superior to finasteride in preventing prostate cancer. We directly compared the effects of finasteride and dutasteride on the risk of prostate cancer in patients with BPH using a pooled analysis of 15 real-world databases. Materials and Methods: We conducted a multicenter, cohort study of new-users of finasteride and dutasteride. We include patients who were prescribed 5 mg finasteride or dutasteride for the first time to treat BPH and had at least 180 days of prescription. We excluded patients with a history of prostate cancer or a prostate-specific antigen level ≥ 4 ng/mL before the study drug prescription. Cox regression analysis was performed to examine the hazard ratio (HR) for prostate cancer after propensity score (PS) matching. Results: A total of 8,284 patients of new-users of finasteride and 8,670 patients of new-users of dutasteride were included across the 15 databases. In the overall population, compared to dutasteride, finasteride was associated with a lower risk of prostate cancer in both on-treatment and intent-to-treat time-at-risk periods. After 1:1 PS matching, 4,897 patients using finasteride and 4,897 patients using dutasteride were enrolled in the present study. No significant differences were observed for risk of prostate cancer between finasteride and dutasteride both on-treatment (HR=0.66, 95% confidence interval [CI]: 0.44–1.00; p=0.051) and intent-to-treat time-at-risk periods (HR=0.87, 95% CI: 0.67–1.14; p=0.310). Conclusions Using real-world databases, the present study demonstrated that dutasteride was not associated with a lower risk of prostate cancer than finasteride in patients with BPH.

Objective: To improve our understanding of EPEC, this study focused on analyzing and comparing the genomic characteristics of EPEC isolates from humans and companion animals in Korea. Methods: The whole genome of 26 EPEC isolates from patients with diarrhea and 20 EPEC isolates from companion animals in Korea were sequenced using the Illumina HiSeq X (Illumina, USA) and Oxford Nanopore MinION (Oxford Nanopore Technologies, UK) platforms. Results: Most isolates were atypical EPEC, and did not harbor the bfpA gene. The most prevalent virulence genes were found to be ompT (humans: 61.5%; companion animals:60.0%) followed by lpfA (humans: 46.2%; companion animals: 60.0%). Although pangenome analyses showed no apparent correlation among the origin of the strains, virulence profiles, and antimicrobial resistance profiles, isolates included in clade A obtained from both humans and companion animals exhibited high similarity. Additionally, all the isolates included in clade A encoded the ompT gene and did not encode the hlyE gene. The two isolates from companion animals harbored an incomplete bundle-forming pilus region encoding bfpA and bfpB. Moreover, the type IV secretion system-associated genes tra and trb were found in the bfpA-encoding isolates from humans. Conclusions and Relevance: Whole-genome sequencing enabled a more accurate analysis of the phylogenetic structure of EPEC and provided better insights into the understanding of EPEC epidemiology and pathogenicity.

Purpose: Finasteride and dutasteride are used to treat benign prostatic hyperplasia (BPH) and reduce the risk of developing prostate cancer. Finasteride blocks only the type 2 form of 5-alpha-reductase, whereas dutasteride blocks both type 1 and 2 forms of the enzyme. Previous studies suggest the possibility that dutasteride may be superior to finasteride in preventing prostate cancer. We directly compared the effects of finasteride and dutasteride on the risk of prostate cancer in patients with BPH using a pooled analysis of 15 real-world databases. Materials and Methods: We conducted a multicenter, cohort study of new-users of finasteride and dutasteride. We include patients who were prescribed 5 mg finasteride or dutasteride for the first time to treat BPH and had at least 180 days of prescription. We excluded patients with a history of prostate cancer or a prostate-specific antigen level ≥ 4 ng/mL before the study drug prescription. Cox regression analysis was performed to examine the hazard ratio (HR) for prostate cancer after propensity score (PS) matching. Results: A total of 8,284 patients of new-users of finasteride and 8,670 patients of new-users of dutasteride were included across the 15 databases. In the overall population, compared to dutasteride, finasteride was associated with a lower risk of prostate cancer in both on-treatment and intent-to-treat time-at-risk periods. After 1:1 PS matching, 4,897 patients using finasteride and 4,897 patients using dutasteride were enrolled in the present study. No significant differences were observed for risk of prostate cancer between finasteride and dutasteride both on-treatment (HR=0.66, 95% confidence interval [CI]: 0.44–1.00; p=0.051) and intent-to-treat time-at-risk periods (HR=0.87, 95% CI: 0.67–1.14; p=0.310). Conclusions Using real-world databases, the present study demonstrated that dutasteride was not associated with a lower risk of prostate cancer than finasteride in patients with BPH.

Purpose: Finasteride and dutasteride are used to treat benign prostatic hyperplasia (BPH) and reduce the risk of developing prostate cancer. Finasteride blocks only the type 2 form of 5-alpha-reductase, whereas dutasteride blocks both type 1 and 2 forms of the enzyme. Previous studies suggest the possibility that dutasteride may be superior to finasteride in preventing prostate cancer. We directly compared the effects of finasteride and dutasteride on the risk of prostate cancer in patients with BPH using a pooled analysis of 15 real-world databases. Materials and Methods: We conducted a multicenter, cohort study of new-users of finasteride and dutasteride. We include patients who were prescribed 5 mg finasteride or dutasteride for the first time to treat BPH and had at least 180 days of prescription. We excluded patients with a history of prostate cancer or a prostate-specific antigen level ≥ 4 ng/mL before the study drug prescription. Cox regression analysis was performed to examine the hazard ratio (HR) for prostate cancer after propensity score (PS) matching. Results: A total of 8,284 patients of new-users of finasteride and 8,670 patients of new-users of dutasteride were included across the 15 databases. In the overall population, compared to dutasteride, finasteride was associated with a lower risk of prostate cancer in both on-treatment and intent-to-treat time-at-risk periods. After 1:1 PS matching, 4,897 patients using finasteride and 4,897 patients using dutasteride were enrolled in the present study. No significant differences were observed for risk of prostate cancer between finasteride and dutasteride both on-treatment (HR=0.66, 95% confidence interval [CI]: 0.44–1.00; p=0.051) and intent-to-treat time-at-risk periods (HR=0.87, 95% CI: 0.67–1.14; p=0.310). Conclusions Using real-world databases, the present study demonstrated that dutasteride was not associated with a lower risk of prostate cancer than finasteride in patients with BPH.

Objective: To improve our understanding of EPEC, this study focused on analyzing and comparing the genomic characteristics of EPEC isolates from humans and companion animals in Korea. Methods: The whole genome of 26 EPEC isolates from patients with diarrhea and 20 EPEC isolates from companion animals in Korea were sequenced using the Illumina HiSeq X (Illumina, USA) and Oxford Nanopore MinION (Oxford Nanopore Technologies, UK) platforms. Results: Most isolates were atypical EPEC, and did not harbor the bfpA gene. The most prevalent virulence genes were found to be ompT (humans: 61.5%; companion animals:60.0%) followed by lpfA (humans: 46.2%; companion animals: 60.0%). Although pangenome analyses showed no apparent correlation among the origin of the strains, virulence profiles, and antimicrobial resistance profiles, isolates included in clade A obtained from both humans and companion animals exhibited high similarity. Additionally, all the isolates included in clade A encoded the ompT gene and did not encode the hlyE gene. The two isolates from companion animals harbored an incomplete bundle-forming pilus region encoding bfpA and bfpB. Moreover, the type IV secretion system-associated genes tra and trb were found in the bfpA-encoding isolates from humans. Conclusions and Relevance: Whole-genome sequencing enabled a more accurate analysis of the phylogenetic structure of EPEC and provided better insights into the understanding of EPEC epidemiology and pathogenicity.

Vancomycin, a vital antibiotic for treating gram-positive bacterial infections, requires therapeutic drug monitoring (TDM) because of its substantial pharmacokinetic variability. While traditional TDM relies on steady-state trough concentrations, recent guidelines advocate the area under the concentration–time curve (AUC) as the target index. However, detailed protocols for AUC estimation are lacking, leading to potential discrepancies among institutions. We surveyed medical institutions in Korea regarding vancomycin TDM, including AUC estimation. Nineteen participants responded to the TDM case challenge under three patient scenarios. For an ordinary patient in Case 1, the overall CV for AUC values was 0.4% when both trough and peak concentrations were included in the AUC calculation and 1.9% when utilizing only the trough concentration. For Case 2, an older patient with obesity, the corresponding CV was 6.6%. For Case 3 with multiple trough concentrations, the CV was 15.6%, reflecting variations in the selective use of data. Although the agreements in Case 1 were good, significant variability in AUC estimation was noted in cases involving atypical patient characteristics or old TDM data. Our study provides insight into the current status of vancomycin TDM in Korea and underscores the need for standardized operational protocols for AUC estimation.

Background: Korea National Health and Nutrition Examination Survey (KNHANES) triglyceride testing changed from the glycerol blanking method (2005–2021) to the glycerol nonblanking method (2022). We converted triglyceride data from 2005–2021 to that obtained since 2022 with different analytical methods. Methods: To develop a conversion equation, 98 fresh serum specimen pairs were compared using Passing–Bablok regression analysis. Implications of the conversion equation on epidemiological data were evaluated using KNHANES data from 2019–2021. Bias estimations determined using the Lipid Standardization Program (LSP) of the United States Centers for Disease Control and Prevention (CDC) enhanced the accuracy and comparability of the triglyceride results. Results: Triglyceride concentrations measured via the glycerol non-blanking method were 10.7 mg/dL (0.12 mmol/L, 10.0%) higher than those from the glycerol blanking method, with a 9.9 mg/dL (0.11 mmol/L, 5.0%) difference at a concentration of 200 mg/dL (2.26 mmol/L, N = 98). The conversion equation y (glycerol non-blanking, 2022) = 11.94+0.99x (glycerol blanking, 2005–2021) changed the mean triglyceride concentrations of the KNHANES 2019–2021 data (N = 16,015) from 123.7 mg/dL (1.40 mmol/L, 95% confidence interval [CI]: 122.2–125.1 mg/dL [1.38–1.41 mmol/L]) to 134.3 mg/dL (1.52 mmol/L, 95% CI: 132.9–135.8 mg/dL [1.50–1.53 mmol/L]). Since 2022, bias monitoring using the CDC’s LSP has remained within a 5.0% limit. Conclusions KNHANES triglyceride values in 2022 (non-blanking) were substantially higher than those from 2005–2021 (blanking). Conversion equations helped effectively adjust 2005–2021 data. Researchers should consider adjusting the KNHANES triglyceride data based on their study characteristics.

Background: Ensuring reference material (RM) commutability is crucial for evaluating measurement traceability in order to standardize laboratory tests. However, commutability assessment is not routinely performed. We assessed whether RMs prepared following CLSI C37-A guidelines could be used without assessing commutability by evaluating their commutability for four lipid measurements using the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) and CLSI EP14 protocols. Methods: We analyzed total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in frozen sera from 20 individuals and 11 RMs, prepared by the Korea Disease Control and Prevention AgencyLaboratory Standardization Project (per CLSI C37-A), using six routine measurement procedures (MPs). Regression equations and 95% prediction intervals derived from single-donor sera were analyzed following CLSI EP14. The IFCC protocol was used to assess differences in inter-MP biases between RM and clinical samples. The effect of the TG concentration on commutability was evaluated by analyzing biases between MP results and reference procedure-assigned values. Results: RMs were commutable for most MP pairs for TC and TG. Commutability for HDL-C and LDL-C varied across RMs, with RM10 and RM11 showing higher TG levels (2.38 and 2.95 mmol/L, respectively) and lower commutability. Increased bias percentages from assigned values were observed for RMs with higher TG levels. Conclusions RMs prepared per CLSI C37-A were commutable with most MP pairs for TC and TG. Elevated TG levels affected HDL-C and LDL-C commutability, highlighting the need to consider TG concentrations during RM preparation and assess commutability to standardize laboratory tests.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.