Population pharmacokinetic analysis of mycophenolic acid in renal transplant recipients following oral administration of mycophenolate mofetil

Aim To develop a population pharmacokinetic model for mycophenolic acid in adult kidney transplant recipients, quantifying average population pharmacokinetic parameter values, and between- and within-subject variability and to evaluate the influence of covariates on the pharmacokinetic variability. Methods Pharmacokinetic data for mycophenolic acid and covariate information were previously available from 22 patients who underwent kidney transplantation at the Princess Alexandra Hospital. All patients received mycophenolate mofetil 1 g orally twice daily. A total of 557 concentration-time points were available. Data were analysed using the first-order method in NONMEM (version 5 level 1.1) using the G77 FORTRAN compiler. Results The best base model was a two-compartment model with a lag time (apparent oral clearance was 271 h(-1), and apparent volume of the central compartment 981). There was visual evidence of complex absorption and time-dependent clearance processes, but they could not be successfully modelled in this study. Weight was investigated as a covariate, but no significant relationship was determined. Conclusions The complexity in determining the pharmacokinetics of mycophenolic acid is currently underestimated. More complex pharmacokinetic models, though not supported by the limited data collected for this study, may prove useful in the future. The large between-subject and between-occasion variability and the possibility of nonlinear processes associated with the pharmacokinetics of mycophenolic acid raise questions about the value of the use of therapeutic monitoring and limited sampling strategies.

Reliability measures for local nodes assessment in classification trees

Most of the modem developments with classification trees are aimed at improving their predictive capacity. This article considers a curiously neglected aspect of classification trees, namely the reliability of predictions that come from a given classification tree. In the sense that a node of a tree represents a point in the predictor space in the limit, the aim of this article is the development of localized assessment of the reliability of prediction rules. A classification tree may be used either to provide a probability forecast, where for each node the membership probabilities for each class constitutes the prediction, or a true classification where each new observation is predictively assigned to a unique class. Correspondingly, two types of reliability measure will be derived-namely, prediction reliability and classification reliability. We use bootstrapping methods as the main tool to construct these measures. We also provide a suite of graphical displays by which they may be easily appreciated. In addition to providing some estimate of the reliability of specific forecasts of each type, these measures can also be used to guide future data collection to improve the effectiveness of the tree model. The motivating example we give has a binary response, namely the presence or absence of a species of Eucalypt, Eucalyptus cloeziana, at a given sampling location in response to a suite of environmental covariates, (although the methods are not restricted to binary response data).

Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Interplay between plasma hormone profiles, sex and body condition in immature hawksbill turtles (Eretmochelys imbricata) subjected to a capture stress protocol

We investigated plasma hormone profiles of corticosterone and testosterone in immature hawksbill turtles (Eretmochelys imbricata) in response to a capture stress protocol. Further, we examined whether sex and body condition were covariates associated with variation in the adrenocortical response of immature turtles. Hawksbill turtles responded to the capture stress protocol by significantly increasing plasma levels of corticosterone over a 5 h period. There was no significant sex difference in the corticosterone stress response of immature turtles. Plasma testosterone profiles, while significantly different between the sexes, did not exhibit a significant change during the 5 h capture stress protocol. An index of body condition was not significantly associated with a turtle's capacity to produce plasma corticosterone both prior to and during exposure to the capture stress protocol. In summary, while immature hawksbill turtles exhibited an adrenocortical response to a capture stress protocol, neither their sex nor body condition was responsible for variation in endocrine responses. This lack of interaction between the adrenocortical response and these internal factors suggests that the inactive reproductive- and the current energetic- status of these immature turtles are important factors, that could influence plasma hormone profiles during stress. (C) 2003 Elsevier Inc. All rights reserved.

Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation

The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immuno suppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.

Quantitative justification for target concentration intervention - parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

Multicenter linkage study of schizophrenia loci on chromosome 22q

The hypothesis of the existence of one or more schizophrenia susceptibility loci on chromosome 22q is supported by reports of genetic linkage and association, meta-analyses of linkage, and the observation of elevated risk for psychosis in people with velocardiofacial syndrome, caused by 22q11 microdeletions. We tested this hypothesis by evaluating 10 microsatellite markers spanning 22q in a multicenter sample of 779 pedigrees. We also incorporated age at onset and sex into the analysis as covariates. No significant evidence for linkage to schizophrenia or for linkage associated with earlier age at onset, gender, or heterogeneity across sites was observed. We interpret these findings to mean that the population-wide effects of putative 22q schizophrenia susceptibility loci are too weak to detect with linkage analysis even in large samples.

Of sheep and rain: large-scale population dynamics of the red kangaroo

1. We analysed time-series data from populations of red kangaroos (Macropus rufus, Desmarest) inhabiting four areas in the pastoral zone of South Australia. We formulated a set of a priori models to disentangle the relative effects of the covariates: rainfall, harvesting, intraspecific competition, and domestic herbivores, on kangaroo population-growth rate. 2. The statistical framework allowed for spatial variation in the growth-rate parameters, response to covariates, and environmental variability, as well as spatially correlated error terms due to shared environment. 3. The most parsimonious model included all covariates but no area-specific parameter values, suggesting that kangaroo densities respond in the same way to the covariates across the areas. 4. The temporal dynamics were spatially correlated, even after taking into account the potentially synchronizing effect of rainfall, harvesting and domestic herbivores. 5. Counter-intuitively, we found a positive rather than negative effect of domestic herbivore density on the population-growth rate of kangaroos. We hypothesize that this effect is caused by sheep and cattle acting as a surrogate for resource availability beyond rainfall. 6. Even though our system is well studied, we must conclude that approximating resources by surrogates such as rainfall is more difficult than previously thought. This is an important message for studies of consumer-resource systems and highlights the need to be explicit about population processes when analysing population patterns.

Role of smoking in global and regional cancer epidemiology: current patterns and data needs

Although smoking is widely recognized as a major cause of cancer, there is little information on how it contributes to the global and regional burden of cancers in combination with other risk factors that affect background cancer mortality patterns. We used data from the American Cancer Society's Cancer Prevention Study II (CPS-II) and the WHO and IARC cancer mortality databases to estimate deaths from 8 clusters of site-specific cancers caused by smoking, for 14 epidemiologic subregions of the world, by age and sex. We used lung cancer mortality as an indirect marker for accumulated smoking hazard. CPS-II hazards were adjusted for important covariates. In the year 2000, an estimated 1.42 (95% CI 1.27-1.57) million cancer deaths in the world, 21% of total global cancer deaths, were caused by smoking. Of these, 1.18 million deaths were among men and 0.24 million among women; 625,000 (95% CI 485,000-749,000) smoking-caused cancer deaths occurred in the developing world and 794,000 (95% CI 749,000-840,000) in industrialized regions. Lung cancer accounted for 60% of smoking-attributable cancer mortality, followed by cancers of the upper aerodigestive tract (20%). Based on available data, more than one in every 5 cancer deaths in the world in the year 2000 were caused by smoking, making it possibly the single largest preventable cause of cancer mortality. There was significant variability across regions in the role of smoking as a cause of the different site-specific cancers. This variability illustrates the importance of coupling research and surveillance of smoking with that for other risk factors for more effective cancer prevention. (C) 2005 Wiley-Liss, Inc.

Water quality condition and trend in North Queensland waterways

The Queensland Environmental Protection Agency monitored water quality at 133 sites in North Queensland waterways between Cooktown and Bundaburg from 1992 to 2001. Condition of the waterways was rated by comparing recent data with the Queensland Water Quality Guidelines. Long-term trends were analysed using a censored regression technique that incorporates the effects of flow, temperature, seasonality and allows for long-term non-linear trends. Many sites were in good condition; those in poor condition were usually impacted by point source discharges; those in moderate condition were usually impacted by agricultural land use. There were no consistent long-term trends across the whole region. Recommendations for future programs include incorporating pressure indicators, ensuring high standards of quality assurance, including covariates such as rainfall in trend assessment and continuing programs over more than 10 years to allow detection of trends due to changes in land-use. (c) 2004 Elsevier Ltd. All rights reserved.

Role of smoking in global and regional cardiovascular mortality

Background - Smoking is a major cause of cardiovascular disease mortality. There is little information on how it contributes to global and regional cause-specific mortality from cardiovascular diseases for which background risk varies because of other risks. Method and Results - We used data from the American Cancer Society's Cancer Prevention Study II (CPS II) and the World Health Organization Global Burden of Disease mortality database to estimate smoking-attributable deaths from ischemic heart disease, cerebrovascular disease, and a cluster of other cardiovascular diseases for 14 epidemiological subregions of the world by age and sex. We used lung cancer mortality as an indirect marker for accumulated smoking hazard. CPS-II hazards were adjusted for important covariates. In the year 2000, an estimated 1.62 (95% CI, 1.27 to 2.04) million cardiovascular deaths in the world, 11% of total global cardiovascular deaths, were due to smoking. Of these, 1.17 million deaths were among men and 450 000 among women. There were 670 000 (95% CI, 440 000 to 920 000) smoking-attributable cardiovascular deaths in the developing world and 960 000 (95% CI, 770 000 to 1 200 000) in industrialized regions. Ischemic heart disease accounted for 54% of smoking-attributable cardiovascular mortality, followed by cerebrovascular disease (25%). There was variability across regions in the role of smoking as a cause of various cardiovascular diseases. Conclusions - More than 1 in every 10 cardiovascular deaths in the world in the year 2000 were attributable to smoking, demonstrating that it is an important preventable cause of cardiovascular mortality.

Variance components analyses of multiple asthma traits in a large sample of Australian families ascertained through a twin proband

Background: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. Objective: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. Methods: A total of 3073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. Results: Overall 2716 participants completed an asthma questionnaire and 2087 were clinically tested, including 1289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV1) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV1 and atopy (0.05), airway obstruction and IgE (0.07) and FEV1 and D. pter (0.11). Conclusion: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

Genome-wide linkage scan for loci influencing plasma triglycerides

Background: Plasma triglyceride concentration is known to be a significant risk factor for cardiovascular disease (CVD). Previous studies have found that the level of triglycerides is strongly influenced by genetic factors. Methods: To identify quantitative trait loci influencing triglycerides, we conducted a genome-wide linkage scan on data from 485 Australian adult dizygotic twin pairs. Prior to linkage analysis, triglyceride values were adjusted for the effects of covariates including age, sex, time since last meal, time of blood collection (CT) and time to plasma separation. Results: The heritability estimate for ln(triglyceride) adjusted for all above fixed effects was 0.49. The highest multipoint LOD score observed was 2.94 (genome-wide p=0.049) on chromosome 7 (at 65cM). This 7p region contains several candidate genes. Two other regions with suggestive multipoint LOD scores were also identified on chromosome 4 (LOD score=2.26 at 62cM) and chromosome X (LOD score=2.01 at 81cM). Conclusions: The linkage peaks found represent newly identified regions for more detailed study, in particular the significant linkage observed on chromosome 7p13. \ (c) 2006 Elsevier B.V. All rights reserved.

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.