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      Population pharmacokinetics and dosing optimization of cefathiamidine in children with hematologic infection

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          Cefathiamidine, a first-generation cephalosporin, has approval from the China Food and Drug Administration for the treatment of infections caused by susceptible bacteria in both adults and children. As pharmacokinetic data are limited in the pediatric population, we aimed to evaluate the population pharmacokinetics of cefathiamidine in children and to define the appropriate dose in order to optimize cefathiamidine treatment.


          Blood samples were collected from children treated with cefathiamidine, and concentrations were quantified by high-performance liquid chromatography and tandem mass spectrometry. Population pharmacokinetic analysis was conducted using NONMEM software.


          Fifty-four children (age range: 2.0–11.8 years) were included. Sparse pharmacokinetic samples (n=120) were available for analysis. A two-compartment model with first-order elimination showed the best fit with the data. A covariate analysis identified that bodyweight had a significant impact on cefathiamidine pharmacokinetics. Monte Carlo simulation demonstrated that the currently used dosing regimen of 100 mg/kg/day q12h was associated with a high risk of underdosing in pediatric patients. To reach the target 70% fT>MIC, a dose of 100 mg/kg/day cefathiamidine q6h is required for effective treatment against Haemophilus influenzae.


          A population pharmacokinetics model of cefathiamidine in children with hematologic disease was established. A dosing regimen of 100 mg/kg/day cefathiamidine q6h should be used in clinical practice against H. influenza infections.

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          Most cited references 24

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          Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models.

          Informative diagnostic tools are vital to the development of useful mixed-effects models. The Visual Predictive Check (VPC) is a popular tool for evaluating the performance of population PK and PKPD models. Ideally, a VPC will diagnose both the fixed and random effects in a mixed-effects model. In many cases, this can be done by comparing different percentiles of the observed data to percentiles of simulated data, generally grouped together within bins of an independent variable. However, the diagnostic value of a VPC can be hampered by binning across a large variability in dose and/or influential covariates. VPCs can also be misleading if applied to data following adaptive designs such as dose adjustments. The prediction-corrected VPC (pcVPC) offers a solution to these problems while retaining the visual interpretation of the traditional VPC. In a pcVPC, the variability coming from binning across independent variables is removed by normalizing the observed and simulated dependent variable based on the typical population prediction for the median independent variable in the bin. The principal benefit with the pcVPC has been explored by application to both simulated and real examples of PK and PKPD models. The investigated examples demonstrate that pcVPCs have an enhanced ability to diagnose model misspecification especially with respect to random effects models in a range of situations. The pcVPC was in contrast to traditional VPCs shown to be readily applicable to data from studies with a priori and/or a posteriori dose adaptations.
            • Record: found
            • Abstract: found
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            Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: the npde add-on package for R.

            Pharmacokinetic/pharmacodynamic data are often analysed using nonlinear mixed-effect models, and model evaluation should be an important part of the analysis. Recently, normalised prediction distribution errors (npde) have been proposed as a model evaluation tool. In this paper, we describe an add-on package for the open source statistical package R, designed to compute npde. npde take into account the full predictive distribution of each individual observation and handle multiple observations within subjects. Under the null hypothesis that the model under scrutiny describes the validation dataset, npde should follow the standard normal distribution. Simulations need to be performed before hand, using for example the software used for model estimation. We illustrate the use of the package with two simulated datasets, one under the true model and one with different parameter values, to show how npde can be used to evaluate models. Model estimation and data simulation were performed using NONMEM version 5.1.
              • Record: found
              • Abstract: found
              • Article: not found

              Conditional weighted residuals (CWRES): a model diagnostic for the FOCE method.

              Population model analyses have shifted from using the first order (FO) to the first-order with conditional estimation (FOCE) approximation to the true model. However, the weighted residuals (WRES), a common diagnostic tool used to test for model misspecification, are calculated using the FO approximation. Utilizing WRES with the FOCE method may lead to misguided model development/evaluation. We present a new diagnostic tool, the conditional weighted residuals (CWRES), which are calculated based on the FOCE approximation. CWRES are calculated as the FOCE approximated difference between an individual's data and the model prediction of that data divided by the root of the covariance of the data given the model. Using real and simulated data the CWRES distributions behave as theoretically expected under the correct model. In contrast, in certain circumstances, the WRES have distributions that greatly deviate from the expected, falsely indicating model misspecification. CWRES/WRES comparisons can also indicate if the FOCE estimation method will improve the results of an FO model fit to data. Utilization of CWRES could improve model development and evaluation and give a more accurate picture of if and when a model is misspecified when using the FO or FOCE methods.

                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                17 April 2018
                : 12
                : 855-862
                [1 ]Department of Pharmacy, Children’s Hospital of Hebei Province, Shijiazhuang, People’s Republic of China
                [2 ]Pediatric Research Institute, Children’s Hospital of Hebei Province, Shijiazhuang, People’s Republic of China
                [3 ]Department of Pediatric Hematology-Oncology, Children’s Hospital of Hebei Province, Shijiazhuang, People’s Republic of China
                [4 ]Department of Clinical Pharmacy, School of Pharmaceutical Sciences, Shandong University, Jinan, People’s Republic of China
                [5 ]Department of Pediatric Pharmacology and Pharmacogenetics, Hôpital Robert Debré, APHP, Paris, France
                [6 ]Clinical Investigation Center CIC1426, INSERM, Paris, France
                Author notes
                Correspondence: Zhong-Ren Shi; Wei Zhao, Pediatric Research Institute, Children’s Hospital of Hebei Province, Shijiazhuang 050000, People’s Republic of China, Tel +86 311 8591 1204, Email hbseryyeys@ 123456163.com ; zhao4wei2@ 123456hotmail.com

                These authors contributed equally to this work

                © 2018 Zhi et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Original Research

                Pharmacology & Pharmaceutical medicine

                cefathiamidine, pharmacokinetics, dosing, children


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