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Métodos Terapéuticos y Terapias MTCI
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1.
Clin Infect Dis ; 74(8): 1372-1381, 2022 04 28.
Artículo en Inglés | MEDLINE | ID: mdl-34286843

RESUMEN

BACKGROUND: Moxifloxacin is a recommended drug for rifampin-resistant tuberculosis (RR-TB) treatment, but there is limited pediatric pharmacokinetic and safety data, especially in young children. We characterize moxifloxacin population pharmacokinetics and QT interval prolongation and evaluate optimal dosing in children with RR-TB. METHODS: Pharmacokinetic data were pooled from 2 observational studies in South African children with RR-TB routinely treated with oral moxifloxacin once daily. The population pharmacokinetics and Fridericia-corrected QT (QTcF)-interval prolongation were characterized in NONMEM. Pharmacokinetic simulations were performed to predict expected exposure and optimal weight-banded dosing. RESULTS: Eighty-five children contributed pharmacokinetic data (median [range] age of 4.6 [0.8-15] years); 16 (19%) were aged <2 years, and 8 (9%) were living with human immunodeficiency virus (HIV). The median (range) moxifloxacin dose on pharmacokinetic sampling days was 11 mg/kg (6.1 to 17). Apparent clearance was 6.95 L/h for a typical 16-kg child. Stunting and HIV increased apparent clearance. Crushed or suspended tablets had faster absorption. The median (range) maximum change in QTcF after moxifloxacin administration was 16.3 (-27.7 to 61.3) ms. No child had QTcF ≥500 ms. The concentration-QTcF relationship was nonlinear, with a maximum drug effect (Emax) of 8.80 ms (interindividual variability = 9.75 ms). Clofazimine use increased Emax by 3.3-fold. Model-based simulations of moxifloxacin pharmacokinetics predicted that current dosing recommendations are too low in children. CONCLUSIONS: Moxifloxacin doses above 10-15 mg/kg are likely required in young children to match adult exposures but require further safety assessment, especially when coadministered with other QT-prolonging agents.


Asunto(s)
Infecciones por VIH , Tuberculosis Resistente a Múltiples Medicamentos , Tuberculosis , Adulto , Niño , Preescolar , Electrocardiografía , Fluoroquinolonas/efectos adversos , Humanos , Moxifloxacino/efectos adversos , Rifampin/efectos adversos , Rifampin/farmacocinética , Tuberculosis/tratamiento farmacológico , Tuberculosis Resistente a Múltiples Medicamentos/tratamiento farmacológico
2.
Transplantation ; 104(4): 795-803, 2020 04.
Artículo en Inglés | MEDLINE | ID: mdl-31403554

RESUMEN

BACKGROUND: The number of patients waiting to receive a kidney transplant outstrips the supply of donor organs. We sought to quantify trade-offs associated with different approaches to deceased donor kidney allocation in terms of quality-adjusted life years (QALYs), costs, and access to transplantation. METHODS: An individual patient simulation model was developed to compare 5 different approaches to kidney allocation, including the 2006 UK National Kidney Allocation Scheme (NKAS) and a QALY maximization approach designed to maximize health gains from a limited supply of donor organs. We used various sources of patient-level data to develop multivariable regression models to predict survival, health state utilities, and costs. We simulated the allocation of kidneys from 2200 deceased donors to a waiting list of 5500 patients and produced estimates of total lifetime costs and QALYs for each allocation scheme. RESULTS: Among patients who received a transplant, the QALY maximization approach generated 48 045 QALYs and cost £681 million, while the 2006 NKAS generated 44 040 QALYs and cost £625 million. When also taking into consideration outcomes for patients who were not prioritized to receive a transplant, the 2006 NKAS produced higher total QALYs and costs and an incremental cost-effectiveness ratio of £110 741/QALY compared with the QALY maximization approach. CONCLUSIONS: Compared with the 2006 NKAS, a QALY maximization approach makes more efficient use of deceased donor kidneys but reduces access to transplantation for older patients and results in greater inequity in the distribution of health gains between patients who receive a transplant and patients who remain on the waiting list.


Asunto(s)
Simulación por Computador , Selección de Donante , Asignación de Recursos para la Atención de Salud , Accesibilidad a los Servicios de Salud , Disparidades en Atención de Salud , Trasplante de Riñón , Donantes de Tejidos/provisión & distribución , Listas de Espera , Adolescente , Adulto , Factores de Edad , Análisis Costo-Beneficio , Selección de Donante/economía , Femenino , Costos de la Atención en Salud , Asignación de Recursos para la Atención de Salud/economía , Accesibilidad a los Servicios de Salud/economía , Estado de Salud , Disparidades en Atención de Salud/economía , Humanos , Trasplante de Riñón/efectos adversos , Trasplante de Riñón/economía , Trasplante de Riñón/mortalidad , Masculino , Persona de Mediana Edad , Formulación de Políticas , Calidad de Vida , Años de Vida Ajustados por Calidad de Vida , Medición de Riesgo , Factores de Riesgo , Factores de Tiempo , Resultado del Tratamiento , Estados Unidos , Listas de Espera/mortalidad , Adulto Joven
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