Fourth order pseudo maximum likelihood methods

We extend PML theory to account for information on the conditional moments up to order four, but without assuming a parametric model, to avoid a risk of misspecification of the conditional distribution. The key statistical tool is the quartic exponential family, which allows us to generalize the PML2 and QGPML1 methods proposed in Gourieroux et al. (1984) to PML4 and QGPML2 methods, respectively. An asymptotic theory is developed. The key numerical tool that we use is the Gauss-Freud integration scheme that solves a computational problem that has previously been raised in several fields. Simulation exercises demonstrate the feasibility and robustness of the methods [Authors]

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

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.

Methods for detection and confirmation of Hematide?/peginesatide in anti-doping samples.

Since the 1990's, cheating athletes have abused substances to increase their oxygen transport capabilities; among these substances, recombinant EPO is the most well known. Currently, other investigational pharmaceutical products are able to produce an effect similar to EPO but without having chemical structures related to EPO; these are the synthetic erythropoiesis stimulating agents (ESAs). Peginesatide (also known as Hematide?) is being developed by Affymax and Takeda and, if approved by regulatory authorities, could soon be released on the international market. To detect potential athletic abuse of this product and deter athletes who consider cheating, we initiated a collaboration to implement a detection test for anti-doping purposes. Peginesatide is a synthetic, PEGylated, investigational, peptide-based erythropoiesis-stimulating agent that is designed and engineered to stimulate specifically the erythropoietin receptor dimer that governs erythropoiesis. It is undetectable using current anti-doping tests due to its lack of sequence homology to EPO. To detect and deter potential abuse of peginesatide, we initiated an industry/antidoping laboratory collaboration to develop and validate screening and confirmation assays so that they would be available before peginesatide reaches the market. We describe a screening ELISA and a confirmation assay consisting of immune-purification followed by separation with SDS-PAGE and revelation with Western double blotting. Both assays can detect 0.5 ng/mL concentrations of peginesatide in blood samples, enabling detection for several days after administration of a physiologically relevant dose. This initial report describes experimental characterization of these assays, including testing with a blinded set of samples from a clinical study conducted in healthy volunteers.

Relevé des consultations et des transferts de patients par enquête directe auprès des médecins: méthode d'une enquête, acceptabilité et limites d'interprétation. [Summary of consultations and transfer of patients by a direct survey of physicians: survey methods, acceptability and limits of interpretation].

A survey of medical ambulatory practice was carried out in February-March 1981 in the two Swiss cantons of Vaud and Fribourg (total population: 700,000), in which 205 physicians participated. The methodology used was inspired from the U.S. National Ambulatory Medical Care Survey, the data collection instrument of which was adapted to our conditions; in addition, data were gathered on all referrals prescribed by 154 physicians during two weeks. (The instruments used are presented.) The potential and limits of this type of survey are discussed, as well as the representativity of the participating physicians and of the recorded visits, which are a systematic sample of over 43,000 visits.

A direct approach to the discounted penalty function

This paper provides a new and accessible approach to establishing certain results concerning the discounted penalty function. The direct approach consists of two steps. In the first step, closed-form expressions are obtained in the special case in which the claim amount distribution is a combination of exponential distributions. A rational function is useful in this context. For the second step, one observes that the family of combinations of exponential distributions is dense. Hence, it suffices to reformulate the results of the first step to obtain general results. The surplus process has downward and upward jumps, modeled by two independent compound Poisson processes. If the distribution of the upward jumps is exponential, a series of new results can be obtained with ease. Subsequently, certain results of Gerber and Shiu [H. U. Gerber and E. S. W. Shiu, North American Actuarial Journal 2(1): 48–78 (1998)] can be reproduced. The two-step approach is also applied when an independent Wiener process is added to the surplus process. Certain results are related to Zhang et al. [Z. Zhang, H. Yang, and S. Li, Journal of Computational and Applied Mathematics 233: 1773–1 784 (2010)], which uses different methods.

Social influences on fertility : a comparative mixed methods study in eastern and western Germany

This article uses a mixed methods design to investigate the effects of social influence on family formation in a sample of eastern and western German young adults at an early stage of their family formation. Theoretical propositions on the importance of informal interaction for fertility and family behavior are still rarely supported by systematic empirical evidence. Major problems are the correct identification of salient relationships and the comparability of social networks across population subgroups. This article addresses the two issues through a combination of qualitative and quantitative data collection and analysis. In-depth interviewing, network charts, and network grids are used to map individual personal relationships and their influence on family formation decisions. In addition, an analysis of friendship dyads is provided.

Self-reported health needs and use of primary health care services by adolescents enrolled in post-mandatory schools or vocational training programmes in Switzerland.

BACKGROUND: The second Swiss Multicenter Adolescent Survey on Health (SMASH02) was conducted among a representative sample (n = 7428) of students and apprentices aged 16 to 20 from the three language areas of Switzerland during the year 2002. This paper reports on health needs expressed by adolescents and their use of health care services over the 12 months preceding the survey. METHODS: Nineteen cantons representing 80% of the resident population agreed to participate. A complex iterative random cluster sample of 600 classes was drawn with classes as primary sampling unit. The participation rate was 97.7% for the classes and 99.8% for the youths in attendance. The self-administered questionnaire included 565 items. The median rate of item non-response was 1.8%. Ethical and legal requirements applying to surveys of adolescent populations were respected. RESULTS: Overall more than 90% of adolescents felt in good to excellent health. Suffering often or very often from different physical complaints or pain was also reported such as headache (boys: 15.9%, girls: 37.4%), stomach-ache (boys: 9.7%, girls: 30.0%), joint pain (boys: 24.7%, girls: 29.5%) or back pain (boys: 24.3%, girls: 34.7%). Many adolescents reported a need for help on psychosocial and lifestyle issues, such as stress (boys: 28.5%, girls: 47.7%) or depression (boys: 18.9%, girls: 34.4%). Although about 75% of adolescents reported having consulted a general practitioner and about one-third having seen another specialist, reported reasons for visits do not correspond to the expressed needs. Less than 10% of adolescents had visited a psychiatrist, a family planning centre or a social worker. CONCLUSIONS: The reported rates of health services utilisation by adolescents does not match the substantial reported needs for help in various areas. This may indicate that the corresponding problems are not adequately detected and/or addressed by professionals from the health and social sectors.

Willingness and preferred methods to help quitting smoking in Switzerland

Purpose: to assess among current smokers in Switzerland the willingness to quit and the preferred methods to help quitting smoking. Methods: cross-sectional study including 1265 current smokers (607 women and 658 men). Difficulty quitting smoking and the preferred methods to help quitting smoking were assessed by questionnaire. Results: 89% of women and 84% of men reported being "very difficult" or "difficult" to quit smoking. Almost three quarters of smokers (73% of women and 70% of men) reported some willingness to quit smoking, but less than 25% of them wanted to do so within the next 30 days, and only 64% within the next 6 months. Willingness to quit was stronger among younger smokers while no differences were found for gender, physical activity or education al Javel. The preferred methods to help quitting smoking were personalized counselling by a doctor (51.4%), acupuncture (35.9%); nicotine replacement therapy (37.6%); hypnosis (28.8%); information flyers (24.9%); autogenic training (15.3%); bupropion (15.2%); personalized counselling by a non-doctor (14.7%) and group interventions (13.2%). Acupuncture and hypnosis were more favoured by women, and autogenic training by younger smokers. Still, a sizable fraction (between 19 and 51%) of smokers did not know some of the methods to help quitting smoking. Conclusion: although more than two thirds of Swiss smokers want to quit, only a small fraction wishes to do so in the short term. Setter information regarding the different methods to help quitting is also necessary.

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

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.

Methods for the ex vivo characterization of human CD8+ T subsets based on gene expression and replicative history analysis.

The generation of an antigen-specific T-lymphocyte response is a complex multi-step process. Upon T-cell receptor-mediated recognition of antigen presented by activated dendritic cells, naive T-lymphocytes enter a program of proliferation and differentiation, during the course of which they acquire effector functions and may ultimately become memory T-cells. A major goal of modern immunology is to precisely identify and characterize effector and memory T-cell subpopulations that may be most efficient in disease protection. Sensitive methods are required to address these questions in exceedingly low numbers of antigen-specific lymphocytes recovered from clinical samples, and not manipulated in vitro. We have developed new techniques to dissect immune responses against viral or tumor antigens. These allow the isolation of various subsets of antigen-specific T-cells (with major histocompatibility complex [MHC]-peptide multimers and five-color FACS sorting) and the monitoring of gene expression in individual cells (by five-cell reverse transcription-polymerase chain reaction [RT-PCR]). We can also follow their proliferative life history by flow-fluorescence in situ hybridization (FISH) analysis of average telomere length. Recently, using these tools, we have identified subpopulations of CD8+ T-lymphocytes with distinct proliferative history and partial effector-like properties. Our data suggest that these subsets descend from recently activated T-cells and are committed to become differentiated effector T-lymphocytes.