Retention Rates and Successful Treatment with Antiseizure Medications in Newly-Diagnosed Epilepsy Patients.

PURPOSE: Treatment for epilepsy primarily involves antiseizure medications (ASMs), which can be characterized using the clinical data warehouse (CDW) database. In this study, we compared retention rates and time to successful treatment for various ASMs to reflect both efficacy and adverse effects in patients with newly diagnosed epilepsy. MATERIALS AND METHODS: We identified newly diagnosed epilepsy patients with ASM treatment for more than 12 months using CDW of a tertiary referral hospital. Clinical characteristics were compared between groups with successful and unsuccessful treatment. Cox regression analysis was performed to evaluate independent variables of age, sex, comorbidities, and attributes of ASM regimens. RESULTS: Of 2515 eligible participants, 46.2% were successfully treated with the first ASM regimen, and 74.7% with all ASM regimens with the median time-to-treatment success of 14 months. Participants with second-generation ASM as the first ASM were more likely to be successfully treated with the first regimen compared to those with first-generation ASM (51.6% vs. 42.3%, p<0.001) and more successfully treated [hazard ratio (HR)=1.26; 95% confidence interval (CI): 1.15-1.39]. Overall, valproic acid was the most common ASM across a wide range of ages under 65 years, while levetiracetam in patients aged over 65 years or lamotrigine in female adult patients. Clinical factors associated with less favorable treatment outcomes included renal disease (HR=0.78; 95% CI: 0.66-0.92), liver disease (HR=0.65; 95% CI: 0.52-0.81), depression (HR=0.70; 95% CI: 0.57-0.84), and mechanical ventilation (HR=0.58; 95% CI: 0.50-0.67). CONCLUSION: Second-generation ASMs have the advantage of more successful treatment with fewer ASM regimen changes compared with first-generation drugs. Various comorbid conditions as well as age and sex should be considered when selecting ASMs.

Heat wave exposure and increased heat-related hospitalizations in young children in South Korea: A time-series study.

BACKGROUND: Numerous studies have investigated the association between heat wave exposure increased heat-related hospitalizations in the general population. However, little is known about heat-related morbidity in young children who are more vulnerable than the general population. Therefore, we aimed to evaluate the association between hospitalization for heat-related illness in children and heat wave exposure in South Korea. METHODS: We used the National Health Insurance Service (NHIS) database, which provides medical records from 2015 to 2019 in South Korea. We defined daily hospitalizations for heat-related illness of children younger than five years during the summer period (June to August). We considered the definition of heat waves considering the absolute temperature and percentile. A total of 12 different heat waves were used. A time-series analysis was used to investigate the association between heat wave exposure and heat-related hospitalization among children younger than five years. We used a two-stage design involving a meta-analysis after modeling by each region. RESULTS: We included 16,879 daily heat-related hospitalizations among children younger than five years. Overall, heat wave exposure within two days was most related for heat-related hospitalizations in young children. The relative risk (RR) due to heat wave exposure within two days (lag2) (12 definitions: 70th to 90th percentile of maximum temperature) ranged from 1.038 (95% confidence interval (CI): 0.971, 1.110) to 1.083 (95% CI: 1.036, 1.133). We found that boys were more vulnerable to heat exposure than girls. In addition, we found that urban areas were more vulnerable to heat exposure than rural areas. CONCLUSIONS: In our study, heat wave exposure during summer was found to be associated with an increased risk of hospitalization for heat-related illness among children younger than five years. Our findings suggest the need for summer heat wave management and prevention for children.

Hyperglycemia and Hypoglycemia Are Associated with In-Hospital Mortality among Patients with Coronavirus Disease 2019 Supported with Extracorporeal Membrane Oxygenation.

Metabolic abnormalities, such as preexisting diabetes or hyperglycemia or hypoglycemia during hospitalization aggravated the severity of COVID-19. We evaluated whether diabetes history, hyperglycemia before and during extracorporeal membrane oxygenation (ECMO) support, and hypoglycemia were risk factors for mortality in patients with COVID-19. This study included data on 195 patients with COVID-19, who were aged ≥19 years and were treated with ECMO. The proportion of patients with diabetes history among nonsurvivors was higher than that among survivors. Univariate Cox regression analysis showed that in-hospital mortality after ECMO support was associated with diabetes history, renal replacement therapy (RRT), and body mass index (BMI) < 18.5 kg/m2. Glucose at admission >200 mg/dL and glucose levels before ventilator >200 mg/dL were not associated with in-hospital mortality. However, glucose levels before ECMO >200 mg/dL and minimal glucose levels during hospitalization <70 mg/dL were associated with in-hospital mortality. Multivariable Cox regression analysis showed that glucose >200 mg/dL before ECMO and minimal glucose <70 mg/dL during hospitalization remained risk factors for in-hospital mortality after adjustment for age, BMI, and RRT. In conclusion, glucose >200 mg/dL before ECMO and minimal glucose level <70 mg/dL during hospitalization were risk factors for in-hospital mortality among COVID-19 patients who underwent ECMO.

Multivariate Assessment for Bioequivalence Based on the Correlation of Random Effect.

BACKGROUND AND OBJECTIVE: Bioequivalence tests are fundamental step in assessing the equivalence in bioavailability between a test and reference product. In practice, two separate linear mixed models (LMMs) with random subject effects, which have an area under the concentration-time curve (AUC) and the peak concentration (Cmax) as the responses, have become the gold standard for evaluating bioequivalence. Recently, Lee et al developed a multivariate hierarchical generalized linear model (HGLM) for several responses that modeled correlations among multivariate responses via correlated random effects. The objective of this study was to apply this multivariate analysis to the bioequivalence test in practice and to compare the performance of multivariate HGLM and separate LMMs. METHODS: Three pharmacokinetic datasets, fixed-dose combination (naproxen and esomeprazole), tramadol and fimasartan data were analyzed. We compared the 90% confidence interval (CI) for the geometric mean ratio (GMR) of a test product to a reference product using the multivariate HGLM and two conventional separate LMMs. RESULTS: We found that the 90% CIs for the GMRs of both AUC and Cmax from the multivariate HGLM were narrower than those from the separate LMMs: (0.843, 1.152) vs (0.825, 1.177) for Cmax of esomeprazole in fixed-dose combination data; (0.805, 0.931) vs (0.797, 0.941) for Cmax in tramadol data; (0.801, 1.501) vs (0.762, 1.578) for Cmax and (1.163, 1.332) vs (1.009, 1.341) for AUC in fimasartan data, consistent with the random subject effects from two separate LMMs being highly correlated in the three datasets (correlation coefficient r = 0.883; r = 0.966; r = 0.832). CONCLUSION: This multivariate HGLM had good performance in the bioequivalence test with multiple endpoints. This method would provide a more reasonable option to reduce the 90% CI by adding correlation parameters and thus an advantage especially in evaluating the bioequivalence of highly variable drugs with broad 90% CIs.

Comparison of the modified unbounded penalty and the LASSO to select predictive genes of response to chemotherapy in breast cancer.

Covariate selection is a fundamental step when building sparse prediction models in order to avoid overfitting and to gain a better interpretation of the classifier without losing its predictive accuracy. In practice the LASSO regression of Tibshirani, which penalizes the likelihood of the model by the L1 norm of the regression coefficients, has become the gold-standard to reach these objectives. Recently Lee and Oh developed a novel random-effect covariate selection method called the modified unbounded penalty (MUB) regression, whose penalization function can equal minus infinity at 0 in order to produce very sparse models. We sought to compare the predictive accuracy and the number of covariates selected by these two methods in several high-dimensional datasets, consisting in genes expressions measured to predict response to chemotherapy in breast cancer patients. These comparisons were performed by building the Receiver Operating Characteristics (ROC) curves of the classifiers obtained with the selected genes and by comparing their area under the ROC curve (AUC) corrected for optimism using several variants of bootstrap internal validation and cross-validation. We found consistently in all datasets that the MUB penalization selected a remarkably smaller number of covariates than the LASSO while offering a similar-and encouraging-predictive accuracy. The models selected by the MUB were actually nested in the ones obtained with the LASSO. Similar findings were observed when comparing these results to those obtained in their first publication by other authors or when using the area under the Precision-Recall curve (AUCPR) as another measure of predictive performance. In conclusion, the MUB penalization seems therefore to be one of the best options when sparsity is required in high-dimension. Further investigation in other datasets is however required to validate these findings.

Pharmacokinetic and pharmacodynamic interaction between ezetimibe and rosuvastatin in healthy male subjects.

BACKGROUND AND OBJECTIVE: Rosuvastatin and ezetimibe are commonly applied in lipid-lowering pharmacotherapy. However, the pharmacokinetic (PK) interaction was not clear by the coadministration of rosuvastatin and ezetimibe. This study investigated the pharmacodynamic (PD) and PK interactions between rosuvastatin and ezetimibe through a crossover clinical trial. SUBJECTS AND METHODS: A randomized, open-label, multiple-dose, two-treatment, two-period, two-sequence crossover study with two treatment parts was conducted in healthy male subjects. Study part A involved rosuvastatin, and study part B involved ezetimibe. A total of 25 subjects in both parts completed the PK and PD evaluations. Rosuvastatin (20 mg) or ezetimibe (10 mg) was administered once daily for 7 days as monotherapy or co-therapy. The plasma concentrations of rosuvastatin, total ezetimibe and free ezetimibe were measured for 72 h after day 7. Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and total cholesterol (TC) were investigated for the PD assessments on day 1 (pretreatment) and day 8. RESULTS: Rosuvastatin and ezetimibe presented multiple peaks. The 90% confidence intervals (CIs) of the geometric mean ratios for the peak plasma concentration at steady state (Cmax,ss) and area under the plasma concentration-time curve during the dosing interval at steady state (AUCτ,ss) of rosuvastatin and total ezetimibe were within the range 0.8-1.25. However, the coadministration increased the systemic exposure of free ezetimibe. In the PD assessments, rosuvastatin and ezetimibe monotherapy reduced the LDL-C and TC levels effectively. In addition, the lipid-lowering effects of the coadministration corresponded to an approximate summation of the effects of rosuvastatin and ezetimibe monotherapy. However, no significant changes in HDL-C were observed with rosuvastatin or ezetimibe treatment. No significant safety issue was noted. CONCLUSION: The coadministration of rosuvastatin and ezetimibe revealed a bioequivalent PK interaction. Additional lipid-lowering effects, including decreased LDL-C and TC, were observed as expected in combination therapy without significant safety concern.

An analysis of QTc prolongation with atypical antipsychotic medications and selective serotonin reuptake inhibitors using a large ECG record database.

BACKGROUND: This study evaluated the effects of atypical antipsychotic drugs and selective serotonin reuptake inhibitors (SSRIs) on the corrected QT (QTc) interval using a large database obtained from clinical settings. Additionally, the effects of factors including age on QTc intervals were estimated. METHODS: Using an open-access QT database (ECG-ViEW), QTc-lengthening effects of 14 selected atypical antipsychotics and SSRIs were compared to those of a positive control drug, cilostazol, and a negative control drug, diazepam. We also evaluated effects of age, sexgender, and select electrolyte levels on observed QTc intervals. RESULTS: The frequency of QTc prolongation with the pooled data of the 14 study drugs was lower than that with cilostazol (age-adjusted odds ratio (OR) = 0.43, 95% confidence interval (CI) = 0.27-0.69), but no significant difference was found relative to when compared with that with diazepam (age-adjusted OR = 0.89, 95% CI = 0.55-1.47). Furthermore, administration of the 14 study drugs significantly increased the QTc interval by 2.89 ms after each 10-year age increment (p-value < 0.0001). CONCLUSIONS: This study suggests that atypical antipsychotic drugs and SSRIs are less likely to be associated with QTc prolongation in clinical settings. In addition, age showed a significant association with the QTc interval. Further studies with well-characterized cohorts are warranted.

A pharmacokinetic comparison of two voriconazole formulations and the effect of CYP2C19 polymorphism on their pharmacokinetic profiles.

PURPOSE: SYP-1018 is a lyophilized polymeric nanoparticle formulation of voriconazole that is under development for intravenous dosing. This study compared the pharmacokinetic and tolerability profiles of SYP-1018 with those of Vfend(®), the marketed formulation of voriconazole. The effect of CYP2C19 polymorphism on the voriconazole pharmacokinetics was also evaluated. METHODS: An open-label, two-treatment, two-period, two-sequence crossover study was conducted in 52 healthy male volunteers, who randomly received a single intravenous infusion of either of the two voriconazole formulations at 200 mg. Blood samples were collected up to 24 hours after drug administration for pharmacokinetic analysis. The plasma concentrations of voriconazole were determined using liquid chromatography with tandem mass spectrometry, and the pharmacokinetic parameters were estimated using a noncompartmental method. CYP2C19 genotype was identified in 51 subjects. RESULTS: The geometric mean ratio (90% confidence interval) of SYP-1018 to Vfend(®) was 0.99 (0.93-1.04) for the maximum plasma concentrations (Cmax) and 0.97 (0.92-1.01) for the area under the concentration-time curve (AUC) from dosing to the last quantifiable concentration (AUClast). Nineteen homozygous extensive metabolizers (EMs, *1/*1), 19 intermediate metabolizers (IMs, *1/*2 or *1/*3), and ten poor metabolizers (PMs, *2/*2, *2/*3, or *3/*3) were identified, and the pharmacokinetic comparability between SYP-1018 and Vfend(®) was also noted when analyzed separately by genotype. The systemic exposure to voriconazole was greatest in the PM group, followed by the IM, and then the EM groups. Furthermore, the intrasubject variability for Cmax and AUClast was greater in IMs and PMs than in EMs. No serious adverse event occurred, and both treatments were well tolerated. CONCLUSION: SYP-1018 had comparable pharmacokinetic and tolerability profiles to Vfend(®) after a single intravenous infusion. CYP2C19 genotype affected not only the pharmacokinetics of voriconazole, but its intrasubject variability. SYP-1018 can be further developed as a clinically effective alternative to Vfend(®).

Predictive performance of gentamicin dosing nomograms.

BACKGROUND: Several nomograms have been proposed to facilitate the determination of initial gentamicin dosing regimens in clinical settings. This study aimed to assess the predictive performance of these nomograms in Korean patients. METHODS: Gentamicin concentrations were determined in 84 patients with infective endocarditis (IE) and in 95 patients with other infections. All patients underwent therapeutic drug monitoring in Seoul National University Hospital from 2006 to 2012. Individual pharmacokinetic parameters were estimated using a Bayesian method, which predicted steady state peak and trough serum concentrations. Six nomograms were evaluated in patients with "other" infections: the Thomson guidelines, Hull-Sarubbi table, and Rule of Eights, for multiple daily dosing; and the Hartford nomogram, Barnes-Jewish Hospital nomogram, and Sanford Guide, for extended-interval dosing. In IE patients, synergistic combination dosing nomograms, based on the American Heart Association dosing interval guidelines, were evaluated. RESULTS: Gentamicin dosing nomograms performed poorly in attaining the target peak serum concentrations. Multiple-daily dosing nomograms predicted peak serum gentamicin concentrations better than did the extended-interval dosing nomograms (31.9%-72.3% vs 4.3%-45.7%, respectively). Similarly, in patients with IE, the once-daily dosing nomogram resulted in a significantly lower percentage of patients achieving target peak gentamicin concentrations than that associated with the thrice-daily dosing nomogram (P=0.0015). All of the multiple-daily dosing, extended-interval dosing, and synergistic combination dosing nomograms predicted the nontoxic target trough concentrations in >80% of patients. CONCLUSION: Gentamicin dosing nomograms performed poorly in achieving the target peak serum concentrations. New gentamicin nomograms may be required in patients with IE, particularly for once-daily dosing. Therapeutic drug monitoring is highly recommended for gentamicin to ensure that the target concentrations are achieved.

Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment.

BACKGROUND: Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. METHODS: The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. RESULTS: On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson's correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. CONCLUSION: Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.

The effects of moxifloxacin on QTc interval in healthy Korean male subjects.

BACKGROUND AND OBJECTIVE: Moxifloxacin 400 mg is a widely used positive control in thorough QT (TQT) studies, but its QT-prolonging effects in Korean subjects have not been studied. The present study was conducted to collect pilot data in Korean subjects after moxifloxacin administration to evaluate the adequacy of moxifloxacin as a positive control. METHODS: Thirty-eight, healthy, Korean, male subjects were recruited for pharmacokinetic (PK) blood sampling and electrocardiography (ECG) recordings at three different study sites. On day 1, a baseline 12-lead ECG was recorded, and on day 2, ECG recordings were conducted after placebo, or moxifloxacin 400- or 800-mg administration. Baseline-corrected, placebo-adjusted, corrected QT (ΔΔQTc) values were calculated. Blood samples were collected after moxifloxacin administration and PK parameters were assessed. RESULTS: A total of 33 subjects completed the study. The largest time-matched ΔΔQTc occurred approximately 4 h after dosing, with ΔΔQTcI (QT interval corrected by individual QT-RR regression model) values of 11.66 ms (moxifloxacin 400 mg) and 20.96 ms (800 mg). The mean and 90 % confidence intervals of ΔΔQTcI did not include zero at any of the measurement time points. There was a positive correlation between plasma moxifloxacin concentration and ΔΔQTcI (r = 0.422). Dose-proportional PK profiles were observed. CONCLUSION: Moxifloxacin 400 mg is an adequate positive control in Korean TQT studies. Our results indicate that moxifloxacin 400 mg can be used to evaluate the cardiac safety of a drug in Korean subjects.

Trough concentration over 12.1 mg/L is a major risk factor of vancomycin-related nephrotoxicity in patients with therapeutic drug monitoring.

BACKGROUND: High doses of vancomycin increase the risk of nephrotoxicity, but the quantitative relationship between vancomycin exposure and nephrotoxicity is still controversial. This study evaluated the relationship between vancomycin trough concentration and nephrotoxicity, and risk factors for nephrotoxicity in patients undergoing therapeutic drug monitoring. METHODS: A total of 1269 cases from patients who underwent therapeutic drug monitoring were collected from 2006 to 2010. Receiver operating characteristic curve analysis was used to evaluate the relationship between trough concentration and the incidence of nephrotoxicity. Logistic regression using the generalized Least Absolute Shrinkage and Selection Operator (lasso) method was used to evaluate possible risk factors for nephrotoxicity. The data were divided into high/low-concentration groups by the cutoff value obtained from the receiver operating characteristic curve, and additional logistic regression using the generalized lasso method was performed for each group. RESULTS: The cutoff value of the vancomycin trough concentration was 12.1 mg/L. Patients with high concentrations (>12.1 mg/L) were more likely to develop nephrotoxicity (odds ratio = 16.0, 95% confidence interval, 8.2-31.1). The vancomycin trough concentration was the only significant risk factor for nephrotoxicity identified using the generalized lasso (P < 0.001). In contrast, no factor was associated with nephrotoxicity in the low-concentration group. CONCLUSIONS: Vancomycin trough concentrations over 12.1 mg/L were associated with an increased risk of nephrotoxicity. This is lower than the known threshold. Trough vancomycin concentration over the threshold was the only risk factor of nephrotoxicity among demographic factors, dosing regimen, and other clinical conditions in this study. It is suggested that vancomycin trough concentrations greater than 12.1 mg/L require close monitoring for nephrotoxicity.

[The decline of health-related quality of life associated with some diseases in Korean adults].

OBJECTIVES: This study was conducted to measure the decline in the health-related quality of life (HRQoL) associated with some diseases in South Korean adults. METHODS: The EQ-5D health states in the 2005 National Health and Nutrition Examination Survey (NHNES) and the Korean EQ-5D valuation set were used to obtain the EQ-5D indexes of the study subjects. Each disease group was defined when the subjects reported to the NHNES that they were diagnosed with the corresponding disease during the previous 1 year by physicians. Since the distributions of the EQ-5D indexes in each subgroup were negatively skewed, median regression analysis was used to estimate the effects of specific diseases on the HRQoL. Median regression analysis produced estimates that approximated the median of the EQ-5D indexes and there are more robust for analyzing data with many outliers. RESULTS: A total of 16,692 subjects (6,667 patients and 10,025 people without any disease) were included in the analysis. As a result of the median regression analysis, stroke had the strongest impact on the HRQoL for both males and females, followed by osteoporosis, osteoarthritis, rheumatic arthritis, and herniation of an intervertebral disc. While asthma had a significant impact on the HRQoL only in men, cataract, temporo-mandibular dysfunction, and peptic ulcer significantly affected the HRQoL only in women. CONCLUSIONS: Stroke and musculoskeletal diseases were associated with the largest losses of the HRQoL in Korean adults.