Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Transient temperature rise in a mouse due to low-frequency regional hyperthermia

A refined nonlinear heat transfer model of a mouse has been developed to simulate the transient temperature rise in a neoplastic tumour and neighbouring tissue during regional hyperthermia using a 150 kHz inductive coil. In this study, we incorporate various bio-energetic enhancements to the heat transfer equation and numerical validations based on experimental findings for the mouse, in terms of nonlinear metabolic heat production, homeothermy, blood perfusion parameters, thermoregulation, psychological and physiological effects. The discretized bio-heat transfer equation has been validated with the commercial software FEMLAB on a canonical multi-sphere object before applying the scheme to the inhomogeneous mouse voxel phantom. The time-dependent numerical results of regional hyperthermia of mouse thigh have been compared with the available experimental temperature results with only a few small disparities. During the first 20 min of local unfocused heating, the temperature in the tumour and the surrounding tissue increased by around 7.5 degrees C. The objective of this preliminary study was to develop a validated electrothermal numerical scheme for inductive hyperthermia of a small mammal with the intention of expanding the model into a complete numerical solution involving ferromagnetic nanoparticles for targeted heating of tumours at low frequencies. In addition, the numerical scheme herein could assist in optimizing and tailoring of focused electromagnetic fields for hyperthermia.

Methods for Categorical Longitudinal Survey Data: Understanding Employment Status of Australian Women

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.

Paediatric population pharmacokinetics of itraconazole and its active metabolite hydroxy-itraconazole in cystic fibrosis and bone marrow transplant patients

Objectives: The aim of the study was to characterise the population pharmacokinetics (popPK) properties of itraconazole (ITRA) and its active metabolite hydroxy-ITRA in a representative paediatric population of cystic fibrosis (CF) and bone marrow transplant (BMT) patients. The goals were to determine the relative bioavailability between the two oral formulations, and to explore improved dosage regimens in these patients. Methods: All paediatric patients with CF taking oral ITRA for the treatment of allergic bronchopulmonary aspergillosis and patients undergoing BMT who were taking ITRA for prophylaxis of any fungal infection were eligible for the study. A minimum of two blood samples were drawn after the capsules and also after switching to oral solution, or vice versa. ITRA and hydroxy-ITRA plasma concentrations were measured by HPLC[1]. A nonlinear mixed-effect modelling approach (NONMEM 5.1.1) was used to describe the PK of ITRA and hydroxy-ITRA simultaneously. Simulations were used to assess dosing strategies in these patients. Results: Forty-nine patients (29CF, 20 BMT) were recruited to the study who provided 227 blood samples for the population analysis. A 1-compartment model with 1st order absorption and elimination best described ITRA kinetics, with 1st order conversion to hydroxy-ITRA. For ITRA, the apparent clearance (ClItra/F) and volume of distribution (Vitra/F) was 35.5L/h and 672L, respectively; the absorption rate constant for the capsule formulation was 0.0901 h-1 and for the oral solution formulation it was 0.959 h-1. The capsule comparative bioavailability (vs. solution) was 0.55. For hydroxy-ITRA, the apparent volume of distribution and clearance were 10.6 L and 5.28 L/h, respectively. Of several screened covariates only allometrically scaled total body weight significantly improved the fit to the data. No difference between the two populations was found. Conclusion: The developed popPK model adequately described the pharmacokinetics of ITRA and hydroxy-ITRA in paediatric patients with CF and patients undergoing BMT. High inter-patient variability confirmed previous data in CF[2], leukaemia and BMT[3] patients. From the population model, simulations showed the standard dose (5 mg/kg/day) needs to be doubled for the solution formulation and even 4 times more given of the capsules to achieve an adequate target therapeutic trough plasma concentration of 0.5 mg/L[4] in these patients.

Effect of metabolic inhibitors on cyclosporine pharmacokinetics using a population approach

Drugs known to inhibit the metabolism of cyclosporine are administered concomitantly to those who undergo cardiothoracic transplantation. The aim of this study was to examine in quantitative terms the relationship between cyclosporine oral dose rate and the trough concentration (Css(trough)) at steady state in patients who undergo cardiothoracic transplantation and are administered cyclosporine alone or in combination with drugs known to inhibit its metabolism. Dose and whole blood cyclosporine Css(tough) observations measured using the enzyme-multiplied immunoassay technique (EMIT) (396 observations) or the TDx assay (435 observations) were collected as part of routine blood concentration monitoring from 182 patients who underwent cardiothoracic transplantation. Data were analyzed using a linear mixed-effects modeling approach to examine the effect of metabolic inhibitors on dose-rate-Css(trough) ratio. The mean (and 95% confidence interval) dose-rate-Css(trough) ratio for cyclosporine generated from concentrations measured using EMIT was 94 (82.5-105.5) Lh(-1) for patients administered cyclosporine alone, 66.7 (58.1-75.3) Lh(-1) for patients administered concomitant diltiazem, 47.9 (15.4 -80.4) Lh(-1) for patients administered concomitant itraconazole, 21.7 (14.8-28.5) Lh(-1) for patients administered concomitant ketoconazole, and 14.9 (11.8-18.1) Lh(-1) for patients concomitantly administered diltiazem and ketoconazole. For patients administered concomitant cyclosporine, ketoconazole, and diltiazem, the dosage of cyclosporine, if it is administered alone, should be 20% to achieve the same blood concentrations. This will allow safer drug concentration targeting of cyclosporine after cardiothoracic transplantation.

Kinetics of propranolol uptake in muscle, skin, and fat of the isolated perfused rat hindlimb

The tissue distribution kinetics of a highly bound solute, propranolol, was investigated in a heterogeneous organ, the isolated perfused limb, using the impulse-response technique and destructive sampling. The propranolol concentration in muscle, skin, and fat as well as in outflow perfusate was measured up to 30 min after injection. The resulting data were analysed assuming (1) vascular, muscle, skin and fat compartments as well mixed (compartmental model) and (2) using a distributed-in-space model which accounts for the noninstantaneous intravascular mixing and tissue distribution processes but consists only of a vascular and extravascular phase (two-phase model). The compartmental model adequately described propranolol concentration-time data in the three tissue compartments and the outflow concentration-time curve (except of the early mixing phase). In contrast, the two-phase model better described the outflow concentration-time curve but is limited in accounting only for the distribution kinetics in the dominant tissue, the muscle. The two-phase model well described the time course of propranolol concentration in muscle tissue, with parameter estimates similar to those obtained with the compartmental model. The results suggest, first that the uptake kinetics of propranolol into skin and fat cannot be analysed on the basis of outflow data alone and, second that the assumption of well-mixed compartments is a valid approximation from a practical point of view las, e.g., in physiological based pharmacokinetic modelling). The steady-state distribution volumes of skin and fat were only 16 and 4%, respectively, of that of muscle tissue (16.7 ml), with higher partition coefficient in fat (6.36) than in skin (2.64) and muscle (2.79. (C) 2000 Elsevier Science B.V. All rights reserved.

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis-Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models-a fixed effects model and a random effects model-are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed. (c) 2004 Elsevier B.V. All rights reserved.

Characteristics and benefits of professional work - Assessment of their importance over a 30-year career

The Professions in Australia Study is the first longitudinal investigation of the professions in Australia; it spans 33 years. Self-administered questionnaires were distributed on at least eight occasions between 1965 and 1998 to cohorts of students and later practitioners from the professions of engineering, law and medicine. The longitudinal design of this study has allowed for an investigation of individual change over time of three archetypal characteristics of the professions, service, knowledge and autonomy and two of the benefits of professional work, financial rewards and prestige. A cumulative logit random effects model was used to statistically assess changes in the ordinal response scores for measuring importance of the characteristics and benefits through stages of the career path. Individuals were also classified by average trends in response scores over time and hence professions are described through their members' tendency to follow a particular path in attitudes either of change or constancy, in relation to the importance of the five elements (characteristics and benefits). Comparisons in trends are also made between the three professions.

The return to schooling: Estimates from a sample of young Australian twins

This study uses a sample of young Australian twins to examine whether the findings reported in [Ashenfelter, Orley and Krueger, Alan, (1994). 'Estimates of the Economic Return to Schooling from a New Sample of Twins', American Economic Review, Vol. 84, No. 5, pp.1157-73] and [Miller, P.W., Mulvey, C and Martin, N., (1994). 'What Do Twins Studies Tell Us About the Economic Returns to Education?: A Comparison of Australian and US Findings', Western Australian Labour Market Research Centre Discussion Paper 94/4] are robust to choice of sample and dependent variable. The economic return to schooling in Australia is between 5 and 7 percent when account is taken of genetic and family effects using either fixed-effects models or the selection effects model of Ashenfelter and Krueger. Given the similarity of the findings in this and in related studies, it would appear that the models applied by [Ashenfelter, Orley and Krueger, Alan, (1994). 'Estimates of the Economic Return to Schooling from a New Sample of Twins', American Economic Review, Vol. 84, No. 5, pp. 1157-73] are robust. Moreover, viewing the OLS and IV estimators as lower and upper bounds in the manner of [Black, Dan A., Berger, Mark C., and Scott, Frank C., (2000). 'Bounding Parameter Estimates with Nonclassical Measurement Error', Journal of the American Statistical Association, Vol. 95, No.451, pp.739-748], it is shown that the bounds on the return to schooling in Australia are much tighter than in [Ashenfelter, Orley and Krueger, Alan, (1994). 'Estimates of the Economic Return to Schooling from a New Sample of Twins', American Economic Review, Vol. 84, No. 5, pp. 1157-73], and the return is bounded at a much lower level than in the US. (c) 2005 Elsevier B.V. All rights reserved.

In vitro heterogeneity of osteogenic cell populations at various equine skeletal sites

Bone cell cultures were evaluated to determine if osteogenic cell populations at different skeletal sites in the horse are heterogeneous. Osteogenic cells were isolated from cortical and cancellous bone in vitro by an explant culture method. Subcultured cells were induced to differentiate into bone-forming osteoblasts. The osteoblast phenotype was confirmed by immunohistochemical testing for osteocalcin and substantiated by positive staining of cells for alkaline phosphatase and the matrix materials collagen and glycosaminoglycans. Bone nodules were stained by the von Kossa method and counted. The numbers of nodules produced from osteogenic cells harvested from different skeletal sites were compared with the use of a mixed linear model. On average, cortical bone sites yielded significantly greater numbers of nodules than did cancellous bone sites. Between cortical bone sites, there was no significant difference in nodule numbers. Among cancellous sites, the radial cancellous bone yielded significantly more nodules than did the tibial cancellous bone. Among appendicular skeletal sites, tibial metaphyseal bone yielded significantly fewer nodules than did all other long bone sites. This study detected evidence of heterogeneity of equine osteogenic cell populations at various skeletal sites. Further characterization of the dissimilarities is warranted to determine the potential role heterogeneity plays in differential rates of fracture healing between skeletal sites.

Self-paced reading and sentence comprehension in Parkinson's disease

Parkinson's disease (PD) is associated with disturbances in sentence processing, particularly for noncanonical sentences. The present study aimed to analyse sentence processing in PD patients and healthy control participants, using a word-by-word self-paced reading task and an auditory comprehension task. Both tasks consisted of subject relative (SR) and object relative (OR) sentences, with comprehension accuracy measured for each sentence type. For the self-paced reading task, reading times (RTs) were also recorded for the non-critical and critical processing regions of each sentence. Analysis of RTs using mixed linear model statistics revealed a delayed sensitivity to the critical processing region of OR sentences in the PD group. In addition, only the PD group demonstrated significantly poorer comprehension of OR sentences compared to SR sentences during an auditory comprehension task. These results may be consistent with slower lexical retrieval in PD, and its influence on the processing of noncanonical sentences. (c) 2005 Elsevier Ltd. All rights reserved.

The importance of forest area and configuration relative to local habitat factors for conserving forest mammals: A case study of koalas in Queensland, Australia

The loss and fragmentation of forest habitats by human land use are recognised as important factors influencing the decline of forest-dependent fauna. Mammal species that are dependent upon forest habitats are particularly sensitive to habitat loss and fragmentation because they have highly specific habitat requirements, and in many cases have limited ability to move through and utilise the land use matrix. We addressed this problem using a case study of the koala (Phascolarctos cinereus) surveyed in a fragmented rural-urban landscape in southeast Queensland, Australia. We applied a logistic modelling and hierarchical partitioning analysis to determine the importance of forest area and its configuration relative to site (local) and patch-level habitat variables. After taking into account spatial auto-correlation and the year of survey, we found koala occurrence increased with the area of all forest habitats, habitat patch size and the proportion of primary Eucalyptus tree species; and decreased with mean nearest neighbour distance between forest patches, the density of forest patches, and the density of sealed roads. The difference between the effect of habitat area and configuration was not as strong as theory predicts, with the configuration of remnant forest becoming increasingly important as the area of forest habitat declines. We conclude that the area of forest, its configuration across the landscape, as well as the land use matrix, are important determinants of koala occurrence, and that habitat configuration should not be overlooked in the conservation of forest-dependent mammals, such as the koala. We highlight the implications of these findings for koala conservation. (c) 2006 Elsevier Ltd. All rights reserved.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.