Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Real-time antifungal susceptibility testing of Mucor spp., Fusarium spp. and Scedosporium spp. by isothermal microcalorimetry

Objective: Aspergillus species are the main pathogens causing invasive fungal infections but the prevalence of other mould species is rising. Resistance to antifungals among these new emerging pathogens presents a challenge for managing of infections. Conventional susceptibility testing of non-Aspergillus species is laborious and often difficult to interpret. We evaluated a new method for real-time susceptibility testing of moulds based on their of growth-related heat production.Methods: Laboratory and clinical strains of Mucor spp. (n = 4), Scedoporium spp. (n = 4) and Fusarium spp. (n = 5) were used. Conventional MIC was determined by microbroth dilution. Isothermal microcalorimetry was performed at 37 C using Sabouraud dextrose broth (SDB) inoculated with 104 spores/ml (determined by microscopical enumeration). SDB without antifungals was used for evaluation of growth characteristics. Detection time was defined as heat flow exceeding 10 lW. For susceptibility testing serial dilutions of amphotericin B, voriconazole, posaconazole and caspofungin were used. The minimal heat inhibitory concentration (MHIC) was defined as the lowest antifungal concentration, inhbiting 50% of the heat produced by the growth control at 48 h or at 24 h for Mucor spp. Susceptibility tests were performed in duplicate.Results: Tested mould genera had distinctive heat flow profiles with a median detection time (range) of 3.4 h (1.9-4.1 h) for Mucor spp, 11.0 h (7.1-13.7 h) for Fusarium spp and 29.3 h (27.4-33.0 h) for Scedosporium spp. Graph shows heat flow (in duplicate) of one representative strain from each genus (dashed line marks detection limit). Species belonging to the same genus showed similar heat production profiles. Table shows MHIC and MIC ranges for tested moulds and antifungals.Conclusions: Microcalorimetry allowed rapid detection of growth of slow-growing species, such as Fusarium spp. and Scedosporium spp. Moreover, microcalorimetry offers a new approach for antifungal susceptibility testing of moulds, correlating with conventional MIC values. Interpretation of calorimetric susceptibility data is easy and real-time data on the effect of different antifungals on the growth of the moulds is additionally obtained. This method may be used for investigation of different mechanisms of action of antifungals, new substances and drug-drug combinations.

Trends in overweight and obesity levels in Geneva: time for optimism?

Background/Introduction: ln Switzerland, most trends in overweight and obesity levels have been assessed using reported data, a methodology which is prone to reporting bias. ln this study, we aimed at assessing trends in overweight and obesity levels using objectively measured data. Methods: We used independent cross-sectional data collected between 2005 and 2011 by the Bus Santé study on representative samples of the Geneva population. Trends were assessed overall and according to different characteristics of the participants. Overweight and obesity were defined as a body mass index (BMI) between 25 and 29.9 kg/m2 and >=30 kg/m2, respectively. Results: Data from 4093 participants (2012 men) was assessed. Mean BMI was 25.2 ± 4.3 kg/m2 (mean ±standard deviation) in 2005 and 25.4 ± 4.3 in 2011 (p for trend using linear regression=0.98). For men, mean BMI was 26.3 ± 3.8 kg/m2 in 2005 and 26.1 ± 3.7 in 2011 (p for trend=0.37); for women, the corresponding values were 24.3 ± 4.6 and 24.7 ± 4.7 kg/m2 (p for trend=0.42). Overall prevalence of overweight and obesity was 32.2% and 13.3%, respectively, in 2005 and 33.6% and 13.7% in 2011 (p for trend using polytomous logistic regression adjusting for gender, age and smoking=0.49 and 0.94 for overweight and obesity, respectively). For men, prevalence of overweight and obesity was 45.9% and 12.2% in 2005 and 42.1 % and 14.6% in 2011 (P for trend=0.03 for overweight and 0.81 for obesity); for women, the corresponding values were 20.4% and 14.2% in 2005 and 25.4% and 12.9% in 2011 (p for trend=0.13 for overweight and 0.99 for obesity). Conclusion: Overweight and obesity levels appear to have levelled in Geneva, with a possible decrease in overweight levels in men. These favorable findings should be replicated in other geographical locations.

Analytical validation of a lymphocytic choriomeningitis virus real-time RT-PCR assay.

Lymphocytic choriomeningitis virus (LCMV) is a rare cause of central nervous system disease in humans. Screening by real-time RT-PCR assay is of interest in the case of aseptic meningitis of unknown etiology. A specific LCMV real-time RT-PCR assay, based on the detection of genomic sequences of the viral nucleoprotein (NP), was developed to assess the presence of LCMV in cerebrospinal fluids (CSF) sent for viral screening to a Swiss university hospital laboratory. A 10-fold dilution series assay using a plasmid containing the cDNA of the viral NP of the LCMV isolate Armstrong (Arm) 53b demonstrated the high sensitivity of the assay with a lowest detection limit of ≤50 copies per reaction. High sensitivity was confirmed by dilution series assays in a pool of human CSF using four different LCMV isolates (Arm53b, WE54, Traub and E350) with observed detection limits of ≤10PFU/ml (Arm53b and WE54) and 1PFU/ml (Traub and E350). Analysis of 130 CSF showed no cases of acute infection. The absence of positive cases was confirmed by a published PCR assay detecting all Old World arenaviruses. This study validates a specific and sensitive real-time RT-PCR assay for the diagnosis of LCMV infections. Results showed that LCMV infections are extremely rare in hospitalized patients western in Switzerland.

Increased resistance to first-line agents among bacterial pathogens isolated from urinary tract infections in Latin America: time for local guidelines?

Emerging resistance phenotypes and antimicrobial resistance rates among pathogens recovered from community-acquired urinary tract infections (CA-UTI) is an increasing problem in specific regions, limiting therapeutic options. As part of the SENTRY Antimicrobial Surveillance Program, a total of 611 isolates were collected in 2003 from patients with CA-UTI presenting at Latin American medical centers. Each strain was tested in a central laboratory using Clinical Laboratory Standard Institute (CLSI) broth microdilution methods with appropriate controls. Escherichia coli was the leading pathogen (66%), followed by Klebsiella spp. (7%), Proteus mirabilis (6.4%), Enterococcus spp. (5.6%), and Pseudomonas aeruginosa (4.6%). Surprisingly high resistance rates were recorded for E. coli against first-line orally administered agents for CA-UTI, such as ampicillin (53.6%), TMP/SMX (40.4%), ciprofloxacin (21.6%), and gatifloxacin (17.1%). Decreased susceptibility rates to TMP/SMX and ciprofloxacin were also documented for Klebsiella spp. (79.1 and 81.4%, respectively), and P. mirabilis (71.8 and 84.6%, respectively). For Enterococcus spp., susceptibility rates to ampicillin, chloramphenicol, ciprofloxacin, and vancomycin were 88.2, 85.3, 55.9, and 97.1%, respectively. High-level resistance to gentamicin was detected in 24% of Enterococcus spp. Bacteria isolated from patients with CA-UTI in Latin America showed limited susceptibility to orally administered antimicrobials, especially for TMP/SMX and fluoroquinolones. Our results highlight the need for developing specific CA-UTI guidelines in geographic regions where elevated resistance to new and old compounds may influence prescribing decisions.

Incompletely resolved phylogenetic trees inflate estimates of phylogenetic conservatism.

The tendency for more closely related species to share similar traits and ecological strategies can be explained by their longer shared evolutionary histories and represents phylogenetic conservatism. How strongly species traits co-vary with phylogeny can significantly impact how we analyze cross-species data and can influence our interpretation of assembly rules in the rapidly expanding field of community phylogenetics. Phylogenetic conservatism is typically quantified by analyzing the distribution of species values on the phylogenetic tree that connects them. Many phylogenetic approaches, however, assume a completely sampled phylogeny: while we have good estimates of deeper phylogenetic relationships for many species-rich groups, such as birds and flowering plants, we often lack information on more recent interspecific relationships (i.e., within a genus). A common solution has been to represent these relationships as polytomies on trees using taxonomy as a guide. Here we show that such trees can dramatically inflate estimates of phylogenetic conservatism quantified using S. P. Blomberg et al.'s K statistic. Using simulations, we show that even randomly generated traits can appear to be phylogenetically conserved on poorly resolved trees. We provide a simple rarefaction-based solution that can reliably retrieve unbiased estimates of K, and we illustrate our method using data on first flowering times from Thoreau's woods (Concord, Massachusetts, USA).

Ageing Prisoners' Disease Burden: Is Being Old a Better Predictor than Time Served in Prison?

Background: The number of older prisoners entering and ageing in prison has increased in the last few decades. Ageing prisoners pose unique challenges to the prison administration as they have differentiated social, custodial and healthcare needs than prisoners who are younger and relatively healthier. Objective: The goal of this study was to explore and compare the somatic disease burden of old and young prisoners, and to examine whether it can be explained by age group and/or time served in prison. Methods: Access to prisoner medical records was granted to extract disease and demographic information of older (>50 years) and younger (≤49 years) prisoners in different Swiss prisons. Predictor variables included the age group and the time spent in prison. The dependent variable was the total number of somatic diseases as reported in the medical records. Results were analysed using descriptive statistics and a negative binomial model. Results: Data of 380 male prisoners from 13 different prisons in Switzerland reveal that the mean ages of older and younger prisoners were 58.78 and 34.26 years, respectively. On average, older prisoners have lived in prison for 5.17 years and younger prisoners for 2.49 years. The average total number of somatic diseases reported by older prisoners was 2.26 times higher than that of prisoners below 50 years of age (95% CI 1.77-2.87, p < 0.001). Conclusion: This study is the first of its kind to capture national disease data of prisoners with a goal of comparing the disease burden of older and younger prisoners. Study findings indicate that older inmates suffer from more somatic diseases and that the number of diseases increases with age group. Results clearly illustrate the poorer health conditions of those who are older, their higher healthcare burden, and raises questions related to the provision of healthcare for inmates growing old in prison. © 2014 S. Karger AG, Basel.

Estimation of time of death in relation to gastric contents

Introduction: Estimation of the time since death based on the gastric content is still a controversy subject. Many studies have been achieved leaving the same incertitude: the intra- and inter-individual variability. Aim: After a homicidal case where a specialized gastroenterologist was cited to estimate the time of death based on the gastric contents and his experience in clinical practice. Consequently we decided to make a review of the scientific literature to see if that method was more reliable nowadays. Material and methods: We chose articles from 1979 that describe the estimation of the gastric emptying rate according to several factors and the forensic articles about the estimation of the time of death in relation with the gastric content. Results: Most of the articles cited by the specialized gastroenterologist were studies about living healthy people and the effects of several factors (medication, supine versus upside-down position, body mass index or different type of food). Forensic articles frequently concluded that the estimation of the time since death by analyzing the gastric content can be used but not as the unique method. Conclusion: Estimation of the time since death by analyze of the gastric contents is a method that can be used nowadays. But it cannot be the only method as the inter- and intra-individual variability remains an important bias.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Clinical presentation and time-course of postoperative venous thromboembolism: Results from the RIETE Registry

There is little literature about the clinical presentation and time-course of postoperative venous thromboembolism (VTE) in different surgical procedures. RIETE is an ongoing, prospective registry of consecutive patients with objectively confirmed, symptomatic acute VTE. In this analysis, we analysed the baseline characteristics, thromboprophylaxis and therapeutic patterns, time-course, and three-month outcome of all patients with postoperative VTE. As of January 2006, there were 1,602 patients with postoperative VTE in RIETE: 393 (25%) after major orthopaedic surgery (145 elective hip arthroplasty, 126 knee arthroplasty, 122 hip fracture); 207 (13%) after cancer surgery; 1,002 (63%) after other procedures. The percentage of patients presenting with clinically overt pulmonary embolism (PE) (48%, 48%, and 50% respectively), the average time elapsed from surgery to VTE (22 +/- 16, 24 +/- 16, and 21 +/- 15 days, respectively), and the three-month incidence of fatal PE (1.3%, 1.4%, and 0.8%, respectively), fatal bleeding (0.8%, 1.0%, and 0.2%, respectively), or major bleeding (2.3%, 2.9%, and 2.8%, respectively) were similar in the three groups. However, the percentage of patients who had received thromboprophylaxis (96%, 76% and 52%, respectively), the duration of prophylaxis (17 +/- 9.6, 13 +/- 8.9, and 12 +/- 11 days, respectively) and the mean daily doses of low-molecular-weight heparin (4,252 +/- 1,016, 3,260 +/- 1,141, and 3,769 +/- 1,650 IU, respectively), were significantly lower in those undergoing cancer surgery or other procedures. In conclusion, the clinical presentation, time-course, and three-month outcome of VTE was similar among the different subgroups of patients, but the use of prophylaxis in patients undergoing cancer surgery or other procedures was suboptimal.

Methods for testing association between uncertain genotypes and quantitative traits.

Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

Niche dynamics in space and time.

Niche conservatism, the tendency of a species niche to remain unchanged over time, is often assumed when discussing, explaining or predicting biogeographical patterns. Unfortunately, there has been no basis for predicting niche dynamics over relevant timescales, from tens to a few hundreds of years. The recent application of species distribution models (SDMs) and phylogenetic methods to analysis of niche characteristics has provided insight to niche dynamics. Niche shifts and conservatism have both occurred within the last 100 years, with recent speciation events, and deep within clades of species. There is increasing evidence that coordinated application of these methods can help to identify species which likely fulfill one key assumption in the predictive application of SDMs: an unchanging niche. This will improve confidence in SDM-based predictions of the impacts of climate change and species invasions on species distributions and biodiversity.

Detection of human bocavirus and human metapneumovirus by real-time PCR from patients with respiratory symptoms in Southern Brazil

The introduction of newer molecular methods has led to the discovery of new respiratory viruses, such as human metapneumovirus (hMPV) and human bocavirus (hBoV), in respiratory tract specimens. We have studied the occurrence of hMPV and hBoV in the Porto Alegre (PA) metropolitan area, one of the southernmost cities of Brazil, evaluating children with suspected lower respiratory tract infection from May 2007-June 2008. A real-time polymerase chain reaction method was used for amplification and detection of hMPV and hBoV and to evaluate coinfections with respiratory syncytial virus (RSV), influenza A and B, parainfluenza 1, 2 and 3, human rhinovirus and human adenovirus. Of the 455 nasopharyngeal aspirates tested, hMPV was detected in 14.5% of samples and hBoV in 13.2%. A unique causative viral agent was identified in 46.2% samples and the coinfection rate was 43.7%. For hBoV, 98.3% of all positive samples were from patients with mixed infections. Similarly, 84.8% of all hMPV-positive results were also observed in mixed infections. Both hBoV and hMPV usually appeared with RSV. In summary, this is the first confirmation that hMPV and hBoV circulate in PA; this provides evidence of frequent involvement of both viruses in children with clinical signs of acute viral respiratory tract infection, although they mainly appeared as coinfection agents.

Real-time molecular epidemiology of tuberculosis by direct genotyping of smear-positive clinical specimens.

We applied MIRU-VNTR (mycobacterial interspersed repetitive-unit-variable-number tandem-repeat typing) to directly analyze the bacilli present in 61 stain-positive specimens from tuberculosis patients. A complete MIRU type (24 loci) was obtained for all but one (no amplification in one locus) of the specimens (98.4%), and the allelic values fully correlated with those obtained from the corresponding cultures. Our study is the first to demonstrate that real-time genotyping of Mycobacterium tuberculosis can be achieved, fully transforming the way in which molecular epidemiology techniques can be integrated into control programs.