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PubMed1995

A population pharmacokinetic study of alminoprofen penetration into synovial fluid.

The pharmacokinetics of alminoprofen in plasma and synovial fluid (SF) at steady state (300 mg t.i.d.) was studied in 45 patients with knee effusion. Plasma and SF samples, one each per patient, were obtained. Six groups were made according to the time of sampling after ingestion of the 13th dose: 1 h (n = 7), 2 h (n = 7), 4 h (n = 7), 6 h (n = 10), 8 h (n = 6), 12 h (n = 8). A three-compartment model was used to describe alminoprofen kinetics in plasma and SF, with two parameterizations, a 'classical' and a 'physiological' one. The non-linear mixed effect model approach was used to estimate the mean and variance of the pharmacokinetic parameters. The mean +/- SE of the estimates (coefficient of variation of interindividual variability as a percentage) were volume of distribution, 11.0 +/- 1.711 (12%); elimination rate constant, 0.236 +/- 0.025 h-1 (18%); absorption rate constant 2.80 +/- 0.31 h-1 (464%), clearance of influx into SF, 0.29 +/- 0.14 mL min-1; clearance of efflux into plasma, 0.56 +/- 0.25 mL min-1. These two clearances were not significantly different, which indicates that passive diffusion occurs in both directions. The mean +/- SD alminoprofen concentration versus time curve in plasma and SF at steady state was simulated and showed that the mean +/- SD maximal concentration in SF was 8.1 +/- 6.3 mg L-1 and was obtained 4 h after dose administration.

Absorption↗
PubMedDate not supplied

The subjects as a simple random effect fallacy: subject variability and morphological family effects in the mental lexicon.

This is a methodological study addressing the appropriateness of standard by-subject and by-item averaging procedures for the analysis of repeated-measures designs. By means of a reanalysis of published data (Schreuder & Baayen, 1997), using random regression models, we present a proof of existence of systematic variability between participants that is ignored in the standard psycholinguistic analytical procedures. By applying linear mixed effects modeling (Pinheiro & Bates, 2000), we call attention to the potential lack of power of the by-subject and by-item analyses, which in this case study fail to reveal the coexistence of a facilitatory family size effect and an inhibitory family frequency effect in visual and auditory lexical processing.

Auditory Perception↗
PubMed2005

Application of a finite mixture model to somatic cell scores of Italian goats.

The objectives of this study were to apply a finite mixture model (FMM) to data for somatic cell count in goats and to compare the fit of the FMM with that of a standard linear mixed effects model. Bacteriological information was used to assess the ability of the model to classify records from healthy or infected goats. Data were 4518 observations of somatic cell score (SCS) and bacterial infection from both udder halves of 310 goats from 5 herds in Northern Italy. The records were from a complete production season, and were taken monthly from February to November 2000. Explanatory factors in both models included a 3-parameter regression on days in milk (DIM); fixed class effects of herd-test-day, parity group, and udder side (left or right); and random effects of goat and udder half within goat. In addition, the 2-component FMM included a fixed mean for the second component of the model (theoretically corresponding to infected udder halves), as well as an unknown probability of membership to a given putative infection status. A Bayesian statistical approach was used for the analysis with Gibbs sampling used to obtain draws from posterior distributions of parameters of interest. Two sampling chains of 200,000 cycles each were generated for each model. The FMM yielded a much lower estimate of residual variance than the standard model (1.28 vs. 3.02 SCS2), and a slightly higher estimate for the between-goat variance (1.79 vs. 1.48). The deviance information criterion (DIC) was used to compare the fit of the 2 models. The DIC was much lower for the FMM, indicating a better fit to the data. The FMM was able to classify correctly 60 and 48% of the healthy and infected observations, respectively. This was slightly higher than what would be expected from random classification, but not high enough for useful mastitis diagnosis. Nevertheless, increased precision of genetic evaluation is the goal of applying the FMM, rather than timely and accurate mastitis diagnosis. The results suggest that more research on FMM for SCS is merited and necessary for proper application.

Analysis of Variance↗
PubMed1997

Population pharmacokinetics of lamotrigine monotherapy in patients with epilepsy: retrospective analysis of routine monitoring data.

AIMS: To examine the population pharmacokinetics of lamotrigine in patients newly diagnosed with epilepsy and receiving oral lamotrigine monotherapy for up to 48 weeks. METHODS: The population consisted of 158 Caucasians and 5 Asians of whom 81 were males and 82 females. Age and weight ranged between 14 and 76 years and 41-107 kg, respectively. A one-compartment compartment model with first-order absorption and elimination was fitted to plasma lamotrigine concentration-time profiles from retrospective drug monitoring, using non-linear mixed effect modelling (NONMEM), with first-order estimation. Oral clearance (CLo), apparent volume of distribution (V/F) and absorption rate constant (Ka) were the main pharmacokinetic parameters. RESULTS: CLo was not significantly influenced by body weight, age, gender, oral contraceptives and dose. However, due to auto-induction CLo increased by 17.3% during the 48 weeks of therapy, from 1.94 to 2.28 l h(-1), and was 28.7% lower in Asians than Caucasian. The final magnitude in interpatient variability was 32%. The effect of the covariates weight, age, race and gender on V/F was examined and none was statistically significant. The final population estimate of V/F was 77.4 l with an interpatient variability of 34%. CONCLUSIONS: In view of the wide therapeutic margin of lamotrigine and the 21% residual variability in plasma concentrations, the modest significant effects of race and auto-induction on clearance are unlikely to be clinically significant and, thus, no dosage adjustment is warranted for these effects.

Adolescent↗
PubMed2004

Endocrinologic response to vasopressin infusion in advanced vasodilatory shock.

OBJECTIVES: To evaluate the endocrinologic response to a combined arginine vasopressin and norepinephrine (AVP/NE) infusion in advanced vasodilatory shock, and to examine the relationship between baseline plasma AVP concentrations and the hemodynamic response to AVP. DESIGN: Preliminary, prospective, randomized, controlled clinical study. SETTING: Twenty-three-bed general and surgical intensive care unit. PATIENTS: Thirty-eight patients with advanced vasodilatory shock. Hemodynamic and laboratory data of 34 patients have already been presented in a recently published prospective, randomized, controlled study. INTERVENTIONS: Continuous AVP (4 units/hr) and NE infusion in study patients; NE infusion only in control patients. MEASUREMENTS AND MAIN RESULTS: At baseline, 24 hrs, and 48 hrs after randomization, plasma concentrations of AVP, adrenocorticotropic hormone, cortisol, renin, angiotensin II, aldosterone, prolactin, endothelin I, and atrial natriuretic factor were determined. Hemodynamic variables were recorded at baseline and 1, 12, and 24 hrs after randomization. Linear mixed effects models were used to test for differences between groups. The relationship between AVP plasma concentrations and hemodynamic response to AVP was analyzed using linear regression analyses. AVP/NE patients exhibited significantly higher AVP (p <.001) and prolactin (p <.001) plasma concentrations during the study period; there were no significant differences in plasma concentrations of other hormones. No significant correlation was detected between plasma AVP concentrations and the increase in mean arterial pressure after 1 hr (Pearson's correlation coefficient =.134, p =.584) and after 24 hrs (Pearson's correlation coefficient = -.198, p =.417). There were further no correlations between AVP plasma concentrations and the 24-hr response to AVP therapy in heart rate (Pearson's correlation coefficient = -.065, p =.791), stroke volume index (Pearson's correlation coefficient = -.106, p =.687), and NE requirements (Pearson's correlation coefficient =.04, p =.869). CONCLUSIONS: The preliminary results of this study indicate that a combined AVP and NE infusion increases prolactin plasma concentrations in advanced vasodilatory shock. Hemodynamic effects of AVP infusion are independent of baseline plasma AVP concentrations.

Adrenocorticotropic Hormone↗
PubMed2003

Statistical methods for chip calibration and saturation effects in antibody-spiked gene expression data.

Oligonucleotide microarrays are amongst, a set of technologies that allow for high throughput assessment of vast numbers of gene expressions. In order to evaluate gene expressions given detection limits, antibody spiking is often used providing one with an expression curve relating antibody treated expression and non-antibody treated expression. These curves can exhibit different functional shapes across chips and hence need to be standardized. In addition, each curve is subject to saturation effects, which are typically dealt with by extrapolating a linear fit to the subset of the data not visually subject to saturation. In this paper we introduce methods for the non-parametric standardization of expression curves using univariate smoothers. We also explore parametric methods for more efficient analysis of the standardized curves. We demonstrate an alternate method of parametric analysis using a weighted linear mixed effects model that does not arbitrarily delete data beyond an observed saturation point; allows for natural grouping of genes and provides significantly more accurate predictions than naive linear extrapolation. Both methodologies are studied through sets of simulations.

Antibodies↗
PubMed2005

Estimating the genetic component (RGC) in pharmacokinetic variability of the antiretroviral didanosine among healthy Brazilians.

BACKGROUND: We estimate the variance between between- and within-subjects, using mixed effect models, as a way to assess the genetic component in explaining the observed heterogeneity of ddl kinetics among healthy individuals. Our work expands on a previous reported method known as RGC. METHODS: Repeated measurements of ddl concentration in the serum were obtained from 48 healthy adult volunteers enrolled in two bioequivalence study. We use the NONMEM program (Non-linear Mixed Effect Model) to estimate the between- and within-subject variability and the corresponding pharmacokinetic parameters. We assess the genetic contribution to the variability of each pharmacokinetic parameter through the RGC method. RESULTS: Pharmacokinetic parameters, expressed as functions of covariates gender and creatinine clearance (CLCR), were: Oral clearance (CL = 55.1 + 240 * CLCR + 16.6 l/h for male and CL = 55.1 + 240 * CLCR for female), central volume (V2 = 9.82), inter-compartmental clearance (Q = 40.90/h), peripheral volume (V3 = 62.7 + 22.90 for male and V3 = 62.70 for female), absorption rate constant (Ka = 1.51 h(-1)) and duration of the dose administration (D = 0.44 h). The RGC of CL, Q, V3, Ka and D were 0.58, 0.97, 0.60, 0.53 and 0.88, respectively. CONCLUSION: We estimated parameter-specific RGC indices and rank them according to the potential genetic contribution as an explanation for the observed variance. Our study design improved precision by decreasing background noise and, thus, improved the chances that indices such as the RGC are in fact describing genetic variability.

Adult↗
PubMed2004

Pharmacokinetic basis for the use of extended interval dosage regimens of gentamicin in neonates.

OBJECTIVES: To analyse the pharmacokinetic basis for the use of extended-interval dosage regimens of gentamicin in neonates using population pharmacokinetics. PATIENTS AND METHODS: The population pharmacokinetics of gentamicin was studied retrospectively in a population of 113 neonates divided into two groups: one for computing the population model (n=97) and another for validation (n=36). A one-compartment pharmacokinetic model and non-linear mixed-effects modelling were used to assess the population pharmacokinetic model. RESULTS: Weight (W) and postnatal age (PA) were the covariates that influenced the pharmacokinetic parameters of gentamicin. The final population model obtained was: distribution volume, V (L)=0.636 x W (kg)0.852; clearance, Cl (L/h)=0.032 x W (kg)1.482+0.0024 x PA (days). The predictive performance of the model in the population validation was adequate for clinical purposes. The optimized population model allowed us to simulate gentamicin serum levels and their variability, in this kind of patient, when extended-interval dosage administration regimens were implemented. CONCLUSIONS: According to our pharmacokinetic population model, initial doses of gentamicin of 10 mg/kg, and dosage intervals between 36-48 h, appear to be appropriate to achieve target peak and trough serum levels of 15-20 and <0.5 mg/L, respectively, when extended-interval dosage regimens are implemented in newborns. The half-life of gentamicin in premature babies of very low weight and gestational age <31 weeks is long. Thus, to achieve serum concentrations in the 1-10 mg/L range, the use of dosage regimens of 5 mg/kg at 36-48 h dosage intervals seems suitable.

Algorithms↗
PubMed2005

Direct likelihood analysis versus simple forms of imputation for missing data in randomized clinical trials.

BACKGROUND: In many clinical trials, data are collected longitudinally over time. In such studies, missingness, in particular dropout, is an often encountered phenomenon. METHODS: We discuss commonly used but often problematic methods such as complete case analysis and last observation carried forward and contrast them with broadly valid and easy to implement direct-likelihood methods. We comment on alternatives such as multiple imputation and the expectation-maximization algorithm. RESULTS: We apply these methods in particular to data from a study with continuous outcomes. The outcomes are modelled using a general linear mixed-effects model. The bias with CC and LOCF is established in the case study and the advantages of the direct-likelihood approach shown. CONCLUSIONS: We have established formal but easy to understand arguments for a shift towards a direct-likelihood paradigm when analysing incomplete data from longitudinal clinical trials, necessitating neither imputation nor deletion.

Data Collection↗
PubMed2007

An approach to joint analysis of longitudinal measurements and competing risks failure time data.

Joint analysis of longitudinal measurements and survival data has received much attention in recent years. However, previous work has primarily focused on a single failure type for the event time. In this paper we consider joint modelling of repeated measurements and competing risks failure time data to allow for more than one distinct failure type in the survival endpoint which occurs frequently in clinical trials. Our model uses latent random variables and common covariates to link together the sub-models for the longitudinal measurements and competing risks failure time data, respectively. An EM-based algorithm is derived to obtain the parameter estimates, and a profile likelihood method is proposed to estimate their standard errors. Our method enables one to make joint inference on multiple outcomes which is often necessary in analyses of clinical trials. Furthermore, joint analysis has several advantages compared with separate analysis of either the longitudinal data or competing risks survival data. By modelling the event time, the analysis of longitudinal measurements is adjusted to allow for non-ignorable missing data due to informative dropout, which cannot be appropriately handled by the standard linear mixed effects models alone. In addition, the joint model utilizes information from both outcomes, and could be substantially more efficient than the separate analysis of the competing risk survival data as shown in our simulation study. The performance of our method is evaluated and compared with separate analyses using both simulated data and a clinical trial for the scleroderma lung disease.

Clinical Trials as Topic↗
PubMed1993

The estimation of population pharmacokinetic parameters using an EM algorithm.

An EM algorithm was used to analyse data arising from non-linear mixed-effects models. The fixed parameters were determined by maximum likelihood using simplex minimization, and the random effects were estimated using the EM algorithm after linearization with respect to the random effects. Applications to a simple linear model and population pharmacokinetics are described. The use of posterior parameter estimates to investigate covariate relationships is briefly described. The implementation of the estimation-maximization (EM) algorithm described here has proved in practice to be robust but slow. We intend to use a Newton-Raphson minimization routine in place of the simplex method to hasten convergence. The alternative linearization of the non-linear mixed effects model suggested by Lindstrom and Bates (Biometrics 46 (1990) 673-687) is much more unstable than the usual linearization, especially during the initial iterations. In the case of indomethacin the two linearizations produced very similar results. The individual posterior parameter estimates provided by the program are very useful for the detection of covariate relationships in population pharmacokinetic studies. In addition, the posterior means can be used in the estimation of pharmacokinetic-pharmacodynamic relationships from sparse pharmacokinetic data where individual modelling is impossible.

Algorithms↗
PubMed2000

Convergence diagnosis for Gibbs sampling output.

Gibbs sampling is a technique to calculate a complex posterior distribution as steady state measure of a Markov chain. The fundamental problem of inference from Markov chain simulation is that there will always be areas of the target distribution that have not been covered by the finite chain. Deciding when to stop the chain in order to have reached enough coverage of the support of the target distribution is an important matter. Techniques based on one long single chain and on multiple chains are discussed in the framework of a linear mixed effects model. The diagnostics used do not provide a consistent view on the convergence. Practical consequences on the estimates are shown.

Arteriosclerosis↗
PubMed2006

Task-based dermal exposure models for regulatory risk assessment.

The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of new measurements of dermal exposure together with detailed contextual information. This article describes the development of a set of generic task-based models capable of predicting potential dermal exposure to both solids and liquids in a wide range of situations. To facilitate modelling of the wide variety of dermal exposure situations six separate models were made for groupings of exposure scenarios called Dermal Exposure Operation units (DEO units). These task-based groupings cluster exposure scenarios with regard to the expected routes of dermal exposure and the expected influence of exposure determinants. Within these groupings linear mixed effect models were used to estimate the influence of various exposure determinants and to estimate components of variance. The models predict median potential dermal exposure rates for the hands and the rest of the body from the values of relevant exposure determinants. These rates are expressed as mg or microl product per minute. Using these median potential dermal exposure rates and an accompanying geometric standard deviation allows a range of exposure percentiles to be calculated.

Environmental Monitoring↗
PubMed2005

Population pharmacokinetics of caffeine and its metabolites theobromine, paraxanthine and theophylline after inhalation in combination with diacetylmorphine.

The stimulant effect of caffeine, as an additive in diacetylmorphine preparations for study purposes, may interfere with the pharmacodynamic effects of diacetylmorphine. In order to obtain insight into the pharmacology of caffeine after inhalation in heroin users, the pharmacokinetics of caffeine and its dimethylxanthine metabolites were studied. The objectives were to establish the population pharmacokinetics under these exceptional circumstances and to compare the results to published data regarding intravenous and oral administration in healthy volunteers. Diacetylmorphine preparations containing 100 mg of caffeine were used by 10 persons by inhalation. Plasma concentrations of caffeine, theobromine, paraxanthine and theophylline were measured by high performance liquid chromatography. Non-linear mixed effects modelling was used to estimate population pharmacokinetic parameters. The model was evaluated by the jack-knife procedure. Caffeine was rapidly and effectively absorbed after inhalation. Population pharmacokinetics of caffeine and its dimethylxanthine metabolites could adequately and simultaneously be described by a linear multi-compartment model. The volume of distribution for the central compartment was estimated to be 45.7 l and the apparent elimination rate constant of caffeine at 8 hr after inhalation was 0.150 hr(-1) for a typical individual. The bioavailability was approximately 60%. The presented model adequately describes the population pharmacokinetics of caffeine and its dimethylxanthine metabolites after inhalation of the caffeine sublimate of a 100 mg tablet. Validation proved the stability of the model. Pharmacokinetics of caffeine after inhalation and intravenous administration are to a large extent similar. The bioavailability of inhaled caffeine is approximately 60% in experienced smokers.

Administration, Inhalation↗
PubMedDate not supplied

Thirteen years of follow-up in patients with adjustable silicone gastric banding for obesity: weight loss and constant rate of late specific complications.

BACKGROUND: Despite its simplicity, safety and good short-term results, progressive weight regain and a high incidence of complications have been reported after the adjustable silicone gastric banding (ASGB). The aim of this study is to evaluate the long-term results of this operation in our patient population. METHODS: Between 1990 and 1996, 45 morbidly obese patients underwent insertion of an ASGB. The trend of the patients' BMI over time was studied using a linear mixed effect model adjusted for the preoperative BMI. So as to estimate the cumulative probability of band removal and the cumulative hazard function, Lambda(t) Kaplan-Meier analysis was used. RESULTS: 1 year after the operation, the average BMI was 79% of its preoperative value, which then increased linearly over time. The slope of the regression line was estimated at beta =0.42, indicating an average increase of 0.42 BMI units per year. 27 bands (60%) were removed because of specific late complications. The cumulative risk of band removal increased linearly with time. The hazard rate was estimated to be lambda =0.008 events/patient/month, corresponding to 0.1 events/patient/year. CONCLUSIONS: ASGB yielded good short-term results, but the progressive weight regain and constant risk of complications in the long term tend to nullify the optimism.

Adult↗
PubMed2006

Genomic-assisted prediction of genetic value with semiparametric procedures.

Semiparametric procedures for prediction of total genetic value for quantitative traits, which make use of phenotypic and genomic data simultaneously, are presented. The methods focus on the treatment of massive information provided by, e.g., single-nucleotide polymorphisms. It is argued that standard parametric methods for quantitative genetic analysis cannot handle the multiplicity of potential interactions arising in models with, e.g., hundreds of thousands of markers, and that most of the assumptions required for an orthogonal decomposition of variance are violated in artificial and natural populations. This makes nonparametric procedures attractive. Kernel regression and reproducing kernel Hilbert spaces regression procedures are embedded into standard mixed-effects linear models, retaining additive genetic effects under multivariate normality for operational reasons. Inferential procedures are presented, and some extensions are suggested. An example is presented, illustrating the potential of the methodology. Implementations can be carried out after modification of standard software developed by animal breeders for likelihood-based or Bayesian analysis.

Algorithms↗
PubMed2004

Modelling neuromotor ratings with floor-effects.

Associated movements (AMs) are a classical diagnostic tool to assess differences between normal children and children with some motor dysfunction. This paper presents a methodology to produce age- and gender-dependent reference-curves for AMs of normal children, for various tasks of a test battery. Data available consist of separate ratings of duration and extent of AMs, which are ordinal quantities with few levels. Other problems are severe age- and gender-dependent floor-effects (as well as some ceiling-effects), leaving little information for analysis at older ages. To get a better scale, we combined the two ordinal ratings into one meaningful and quasi-continuous quantity referred to as intensity of AMs. In order to solve problems due to floor-effects, ceiling-effects and discreteness, we assumed left- , right- and interval-censored values, respectively. We considered a censored regression problem and postulated a truncated normal distribution for the non-censored values (after an appropriate transformation of the data). Using Wei and Tanner's poor man's data augmentation algorithm, together with the technique of linear mixed effects modelling, useful reference-curves could be produced. In contrast to the cumulative probabilities approach for ordinal data, our methodology allows the calculation of individual age- and gender-standardized values, which puts us in a position to investigate numerous scientific questions.

Adolescent↗
PubMed2005

A prospective cohort study among new Chinese coal miners: the early pattern of lung function change.

AIMS: To investigate the early pattern of longitudinal change in forced expiratory volume in 1 second (FEV1) among new Chinese coal miners, and the relation between coal mine dust exposure and the decline of lung function. METHODS: The early pattern of lung function changes in 317 newly hired Chinese underground coal miners was compared to 132 referents. This three year prospective cohort study involved a pre-employment and 15 follow up health surveys, including a questionnaire and spirometry tests. Twice a month, total and respirable dust area sampling was done. The authors used a two stage analysis and a linear mixed effects model approach to analyse the longitudinal spirometry data, and to investigate the changes in FEV1 over time, controlling for age, height, pack years of smoking, mean respirable dust concentration, the room temperature during testing, and the groupxtime interaction terms. RESULTS: FEV1 change over time in new miners is non-linear. New miners experience initial rapid FEV1 declines, primarily during the first year of mining, little change during the second year, and partial recovery during the third year. Both linear and quadratic time trends in FEV1 change are highly significant. Smoking miners lost more FEV1 than non-smokers. Referents, all age less than 20 years, showed continued lung growth, whereas the miners who were under age 20 exhibited a decline in FEV1. CONCLUSION: Dust and smoking affect lung function in young, newly hired Chinese coal miners. FEV1 change over the first three years of employment is non-linear. The findings have implications for both methods and interpretation of medical screening in coal mining and other dusty work: during the first several years of employment more frequent testing may be desirable, and caution is required in interpreting early FEV1 declines.

Adolescent↗