Relationships between imatinib plasma levels and efficacy

Purpose: While imatinib has revolutionized the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumors (GIST), its pharmacokinetic-pharmacodynamic relationships have been poorly studied. This study aimed to explore the issue in oncologic patients, and to evaluate the specific influence of the target genotype in a GIST subpopulation. Patients and methods: Data from 59 patients (321 plasma samples) were collected during a previous pharmacokinetic study. Based on a population model purposely developed, individual post-hoc Bayesian estimates of pharmacokinetic parameters were derived, and used to estimate drug exposure (AUC; area under curve). Free fraction parameters were deduced from a model incorporating plasma alpha1-acid glycoprotein levels. Associations between AUC (or clearance) and therapeutic response (coded on a 3-point scale), or tolerability (4-point scale), were explored by ordered logistic regression. Influence of KIT genotype on response was also assessed in GIST patients. Results: Total and free drug exposure correlated with the number of side effects (p < 0.005). A relationship with response was not evident in the whole patient set (with good-responders tending to receive lower doses and bad-responders higher doses). In GIST patients however, higher free drug exposure predicted better responses. A strong association was notably observed in patients harboring an exon 9 mutation or a wild type KIT, known to decrease tumor sensitivity towards imatinib (p < 0.005). Conclusions: Our results are arguments to further evaluate the potential benefit of a therapeutic monitoring program for imatinib. Our data also suggest that stratification by genotype will be important in future trials.

Benchmarking therapeutic drug monitoring software: A review of available computer tools

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Oligocene CO2 decline promoted C4 photosynthesis in grasses.

C4 photosynthesis is an adaptation derived from the more common C3 photosynthetic pathway that confers a higher productivity under warm temperature and low atmospheric CO2 concentration [1, 2]. C4 evolution has been seen as a consequence of past atmospheric CO2 decline, such as the abrupt CO2 fall 32-25 million years ago (Mya) [3-6]. This relationship has never been tested rigorously, mainly because of a lack of accurate estimates of divergence times for the different C4 lineages [3]. In this study, we inferred a large phylogenetic tree for the grass family and estimated, through Bayesian molecular dating, the ages of the 17 to 18 independent grass C4 lineages. The first transition from C3 to C4 photosynthesis occurred in the Chloridoideae subfamily, 32.0-25.0 Mya. The link between CO2 decrease and transition to C4 photosynthesis was tested by a novel maximum likelihood approach. We showed that the model incorporating the atmospheric CO2 levels was significantly better than the null model, supporting the importance of CO2 decline on C4 photosynthesis evolvability. This finding is relevant for understanding the origin of C4 photosynthesis in grasses, which is one of the most successful ecological and evolutionary innovations in plant history.

Disentangling the effects of key innovations on the diversification of Bromelioideae (bromeliaceae).

The evolution of key innovations, novel traits that promote diversification, is often seen as major driver for the unequal distribution of species richness within the tree of life. In this study, we aim to determine the factors underlying the extraordinary radiation of the subfamily Bromelioideae, one of the most diverse clades among the neotropical plant family Bromeliaceae. Based on an extended molecular phylogenetic data set, we examine the effect of two putative key innovations, that is, the Crassulacean acid metabolism (CAM) and the water-impounding tank, on speciation and extinction rates. To this aim, we develop a novel Bayesian implementation of the phylogenetic comparative method, binary state speciation and extinction, which enables hypotheses testing by Bayes factors and accommodates the uncertainty on model selection by Bayesian model averaging. Both CAM and tank habit were found to correlate with increased net diversification, thus fulfilling the criteria for key innovations. Our analyses further revealed that CAM photosynthesis is correlated with a twofold increase in speciation rate, whereas the evolution of the tank had primarily an effect on extinction rates that were found five times lower in tank-forming lineages compared to tank-less clades. These differences are discussed in the light of biogeography, ecology, and past climate change.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

Comparison of time-lapse GPR data collected under natural and forced infiltration conditions to estimate vadose zone hydraulic parameters

Time-lapse crosshole ground-penetrating radar (GPR) data, collected while infiltration occurs, can provide valuable information regarding the hydraulic properties of the unsaturated zone. In particular, the stochastic inversion of such data provides estimates of parameter uncertainties, which are necessary for hydrological prediction and decision making. Here, we investigate the effect of different infiltration conditions on the stochastic inversion of time-lapse, zero-offset-profile, GPR data. Inversions are performed using a Bayesian Markov-chain-Monte-Carlo methodology. Our results clearly indicate that considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions

Endogenous steroid profiling in the athlete biological passport.

The Athlete Biological Passport (ABP) is an individual electronic document that collects data regarding a specific athlete that is useful in differentiating between natural physiologic variations of selected biomarkers and deviations caused by artificial manipulations. A subsidiary of the endocrine module of the ABP, that which here is called Athlete Steroidal Passport (ASP), collects data on markers of an altered metabolism of endogenous steroidal hormones measured in urine samples. The ASP aims to identify not only doping with anabolic-androgenic steroids, but also most indirect steroid doping strategies such as doping with estrogen receptor antagonists and aromatase inhibitors. Development of specific markers of steroid doping, use of the athlete's previous measurements to define individual limits, with the athlete becoming his or her own reference, the inclusion of heterogeneous factors such as the UDPglucuronosyltransferase B17 genotype of the athlete, the knowledge of potentially confounding effects such as heavy alcohol consumption, the development of an external quality control system to control analytical uncertainty, and finally the use of Bayesian inferential methods to evaluate the value of indirect evidence have made the ASP a valuable alternative to deter steroid doping in elite sports. The ASP can be used to target athletes for gas chromatography/combustion/ isotope ratio mass spectrometry (GC/C/IRMS) testing, to withdraw temporarily the athlete from competing when an abnormality has been detected, and ultimately to lead to an antidoping infraction if that abnormality cannot be explained by a medical condition. Although the ASP has been developed primarily to ensure fairness in elite sports, its application in endocrinology for clinical purposes is straightforward in an evidence-based medicine paradigm.

Decision analysis for the genotype designation in low-template-DNA profiles

What genotype should the scientist specify for conducting a database search to try to find the source of a low-template-DNA (lt-DNA) trace? When the scientist answers this question, he or she makes a decision. Here, we approach this decision problem from a normative point of view by defining a decision-theoretic framework for answering this question for one locus. This framework combines the probability distribution describing the uncertainty over the trace's donor's possible genotypes with a loss function describing the scientist's preferences concerning false exclusions and false inclusions that may result from the database search. According to this approach, the scientist should choose the genotype designation that minimizes the expected loss. To illustrate the results produced by this approach, we apply it to two hypothetical cases: (1) the case of observing one peak for allele xi on a single electropherogram, and (2) the case of observing one peak for allele xi on one replicate, and a pair of peaks for alleles xi and xj, i ≠ j, on a second replicate. Given that the probabilities of allele drop-out are defined as functions of the observed peak heights, the threshold values marking the turning points when the scientist should switch from one designation to another are derived in terms of the observed peak heights. For each case, sensitivity analyses show the impact of the model's parameters on these threshold values. The results support the conclusion that the procedure should not focus on a single threshold value for making this decision for all alleles, all loci and in all laboratories.

Pharmacokinetic (PK)-based dosage individualization of imatinib: evaluation of efficiency and clinical usefulness

Background: Retrospective analyses suggest that personalized PK-based dosage might be useful for imatinib, as treatment response correlates with trough concentrations (Cmin) in cancer patients. Our objectives were to improve the interpretation of randomly measured concentrations and to confirm its efficiency before evaluating the clinical usefulness of systematic PK-based dosage in chronic myeloid leukemia patients. Methods and Results: A Bayesian method was validated for the prediction of individual Cmin on the basis of a single random observation, and was applied in a prospective multicenter randomized controlled clinical trial. 28 out of 56 patients were enrolled in the systematic dosage individualization arm and had 44 follow-up visits (their clinical follow-up is ongoing). PK-dose-adjustments were proposed in 39% having predicted Cmin significantly away from the target (1000 ng/ml). Recommendations were taken up by physicians in 57%, patients were considered non-compliant in 27%. Median Cmin at study inclusion was 754 ng/ml and differed significantly from the target (p=0.02, Wilcoxon test). On follow-up, Cmin was 984 ng/ml (p=0.82) in the compliant group. CV decreased from 46% to 27% (p=0.02, F-test). Conclusion: PK-based (Bayesian) dosage adjustment is able to bring individual drug exposure closer to a given therapeutic target. Its influence on therapeutic response remains to be evaluated.

Repeated unidirectional introgression towards Populus balsamifera in contact zones of exotic and native poplars.

As the evolutionary significance of hybridization is largely dictated by its extent beyond the first generation, we broadly surveyed patterns of introgression across a sympatric zone of two native poplars (Populus balsamifera, Populus deltoides) in Quebec, Canada within which European exotic Populus nigra and its hybrids have been extensively planted since the 1800s. Single nucleotide polymorphisms (SNPs) that appeared fixed within each species were characterized by DNA-sequencing pools of pure individuals. Thirty-five of these diagnostic SNPs were employed in a high-throughput assay that genotyped 635 trees of different age classes, sampled from 15 sites with various degrees of anthropogenic disturbance. The degree of admixture within sampled trees was then assessed through Bayesian clustering of genotypes. Hybrids were present in seven of the populations, with 2.4% of all sampled trees showing spontaneous admixture. Sites with hybrids were significantly more disturbed than pure stands, while hybrids comprised both immature juveniles and trees of reproductive age. All three possible F1s were detected. Advanced-generation hybrids were consistently biased towards P. balsamifera regardless of whether hybridization had occurred with P. deltoides or P. nigra. Gene exchange between P. deltoides and P. nigra was not detected beyond the F1 generation; however, detection of a trihybrid demonstrates that even this apparent reproductive isolation does not necessarily result in an evolutionary dead end. Collectively, results demonstrate the natural fertility of hybrid poplars and suggest that introduced genes could potentially affect the genetic integrity of native trees, similar to that arising from introgression between natives.

DNA evidence, probabilistic evaluation and collaborative tests.

Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.

On estimation and identifiability issues of sex-linked inheritance with a case study of pigmentation in Swiss barn owl (Tyto alba)

Genetic evaluation using animal models or pedigree-based models generally assume only autosomal inheritance. Bayesian animal models provide a flexible framework for genetic evaluation, and we show how the model readily can accommodate situations where the trait of interest is influenced by both autosomal and sex-linked inheritance. This allows for simultaneous calculation of autosomal and sex-chromosomal additive genetic effects. Inferences were performed using integrated nested Laplace approximations (INLA), a nonsampling-based Bayesian inference methodology. We provide a detailed description of how to calculate the inverse of the X- or Z-chromosomal additive genetic relationship matrix, needed for inference. The case study of eumelanic spot diameter in a Swiss barn owl (Tyto alba) population shows that this trait is substantially influenced by variation in genes on the Z-chromosome (sigma(2)(z) = 0.2719 and sigma(2)(a) = 0.4405). Further, a simulation study for this study system shows that the animal model accounting for both autosomal and sex-chromosome-linked inheritance is identifiable, that is, the two effects can be distinguished, and provides accurate inference on the variance components.

Large multi-gene phylogenetic trees of the grasses (Poaceae): progress towards complete tribal and generic level sampling.

In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

Ganciclovir Exposure under a 450 mg Daily Dosage of Valganciclovir for the Prevention of Cytomegalovirus Disease in Kidney Transplant Recipients.

Background: It is suggested that a low dose of valganciclovir can be equally effective than a standard dose for cytomegalovirus (CMV) prophylaxis after kidney transplantation. The aim of our study was to determine the ganciclovir exposure observed under a routine daily dosage of 450 mg valganciclovir in kidney transplant recipients with a wide range of renal function. Methods: In this prospective study, kidney transplant recipients with a GFR MDRD above 25 mL/min at risk for CMV (donor or recipient seropositive for CMV) received a dose of valganciclovir (450 mg daily) prophylaxis for 3 months. Ganciclovir levels at trough (Ctrough) and at peak (C3h) were measured monthly. Ganciclovir exposure (AUC0-24) was estimated using Bayesian non-linear mixed-effect modelling (NONMEM) and compared between 3 groups of patients according to their kidney function: GFRMDRD 26-39 mL/min (Group 1), GFRMDRD 40-59 mL/min (Group 2) and GFRMDRD 60-90 mL/min (Group 3). CMV DNAemia was assessed during and after prophylaxis using PCR. Results: Thirty-six patients received 450 mg daily of valganciclovir for 3 months. Median ganciclovir C3h was 3.9 mg/L (range: 1.3-7.1) and Ctrough was 0.4 mg/L (range 0.1-2.7). Median (range) AUC0-24 of ganciclovir was 59.3 mg.h/L (39.0-85.3) in Group 1 patients, 35.8 mg.h/L (24.9-55.8) in Group 2 patients and 29.6 mg.h/L (22.0- 43.2) in Group 3 patients (p<0.001). Anemia was more common in Group 1 patients compared to patients on the other groups (p=0.01). No differences in other adverse events according to ganciclovir exposure were observed. CMV DNAemia was not detected during prophylaxis. After discontinuing prophylaxis, CMV DNAemia was seen in 8/34 patients (23.5%) and 4/36 patients (11%) developed CMV disease. Conclusion: A routine dosage of valganciclovir achieved plasma levels of ganciclovir in patients with GFR>60 mL/min similar to those previously reported using oral ganciclovir. A daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.