Population pharmacokinetics of teicoplanin in children.

Teicoplanin is frequently administered to treat Gram-positive infections in pediatric patients. However, not enough is known about the pharmacokinetics (PK) of teicoplanin in children to justify the optimal dosing regimen. The aim of this study was to determine the population PK of teicoplanin in children and evaluate the current dosage regimens. A PK hospital-based study was conducted. Current dosage recommendations were used for children up to 16 years of age. Thirty-nine children were recruited. Serum samples were collected at the first dose interval (1, 3, 6, and 24 h) and at steady state. A standard 2-compartment PK model was developed, followed by structural models that incorporated weight. Weight was allowed to affect clearance (CL) using linear and allometric scaling terms. The linear model best accounted for the observed data and was subsequently chosen for Monte Carlo simulations. The PK parameter medians/means (standard deviation [SD]) were as follows: CL, [0.019/0.023 (0.01)] × weight liters/h/kg of body weight; volume, 2.282/4.138 liters (4.14 liters); first-order rate constant from the central to peripheral compartment (Kcp), 0.474/3.876 h(-1) (8.16 h(-1)); and first-order rate constant from peripheral to central compartment (Kpc), 0.292/3.994 h(-1) (8.93 h(-1)). The percentage of patients with a minimum concentration of drug in serum (Cmin) of <10 mg/liter was 53.85%. The median/mean (SD) total population area under the concentration-time curve (AUC) was 619/527.05 mg · h/liter (166.03 mg · h/liter). Based on Monte Carlo simulations, only 30.04% (median AUC, 507.04 mg · h/liter), 44.88% (494.1 mg · h/liter), and 60.54% (452.03 mg · h/liter) of patients weighing 50, 25, and 10 kg, respectively, attained trough concentrations of >10 mg/liter by day 4 of treatment. The teicoplanin population PK is highly variable in children, with a wider AUC distribution spread than for adults. Therapeutic drug monitoring should be a routine requirement to minimize suboptimal concentrations. (This trial has been registered in the European Clinical Trials Database Registry [EudraCT] under registration number 2012-005738-12.).

Effectiveness of glatiramer acetate compared to other multiple sclerosis therapies.

OBJECTIVE To assess the effectiveness of glatiramer acetate (GA) compared to other multiple sclerosis (MS) therapies in routine clinical practice. MATERIALS AND METHODS Observational cohort study carried out in MS patients treated with GA (GA cohort) or other MS therapies -switched from GA- (non-GA cohort). Study data were obtained through review of our MS patient database. The primary endpoint was the Expanded Disability Status Scale (EDSS) scores reached at the end of treatment/last check-up. RESULTS A total of 180 patients were included: GA cohort n = 120, non-GA cohort n = 60. Patients in the GA cohort showed better EDSS scores at the end of treatment/last check-up (mean ± SD, 2.8 ± 1.8 vs. 3.9 ± 2.2; P = 0.001) and were 1.65 times more likely to show better EDSS scores compared to the non-GA cohort (odds ratio, 0.606; 95%CI, 0.436-0.843; P = 0.003). Patients in the GA cohort showed longer mean time to reach EDSS scores of 6 (209.1 [95%CI, 187.6-230.6] vs. 164.3 [95% CI, 137.0-191.6] months; P = 0.004) and slower disability progression (hazard ratio, 0.415 [95%CI, 0.286-0.603]; P < 0.001). The annualized relapse rate was lower in the GA cohort (mean ± SD, 0.5 ± 0.5 vs. 0.8 ± 0.5; P = 0.001) and patients' quality of life was improved in this study cohort compared to the non-GA cohort (mean ± SD, 0.7 ± 0.1 vs. 0.6 ± 0.2; P = 0.01). CONCLUSIONS GA may slow down the progression of EDSS scores to a greater extent than other MS therapies, as well as achieving a greater reduction in relapses and a greater improvement in patients' quality of life. Switching from GA to other MS therapies has not proved to entail a better response to treatment.