Off-label utilization of antipsychotics

Résumé Ce travail s'inscrit dans un programme de recherche centré sur la pharmacovigilance en psychiatrie. Buts de l'étude Les nouveaux antipsychotiques atypiques sont prescrits avec beaucoup de succès, parce qu'ils présentent une sécurité dans leur emploi bien supérieure à celle des antipsychotiques classiques. Cette situation a conduit à une large prescription «off-label» (hors indication admise). Le but de ce travail a été d'étudier la pratique en matière de prescription des psychiatres hospitaliers en ce qui concerne les antipsychotiques en comparant des patients traités pour des psychoses ou d'autres indications officielles aux patients recevant un traitement antipsychotique «off-label». Méthode Dans le cadre d'un programme de pharmacovigilance - pharmacoépidemiologie, tous les médicaments prescrits à 5 jours de référence (entre 1999 et 2001) à l'hôpital psychiatrique universitaire de Lausanne (98 lits) ont été enregistrés, avec des données sur l'âge, le sexe et le diagnostic des patients. Les prescriptions de 202 patients ont été évaluées. Les patients ont été classés dans 3 groupes diagnostiques : (1) patient présentant des troubles psychotiques, (2) patient présentant des épisodes maniaques et des épisodes dépressifs avec des symptômes psychotiques, et (3) patient présentant d'autres troubles. Les groupes (1) et (2) forment une classe de patients recevant un antipsychotique pour une indication officielle, et les prescriptions dans le groupe (3) ont été considérées comme «off-label». Résultats principaux Moins de patients psychotiques ont reçu un antidépresseur (p<0.05) ou des hypnotiques non-benzodiazepine (p<0.001) comparés aux patients des deux autres groupes. Les patients présentant des troubles affectifs recevaient seulement exceptionnellement une combinaison d'un antipsychotique atypique et conventionnel, tandis qu'un nombre inférieur de patients avec des indications « off-label » ont reçu moins .souvent des antipsychotiques atypiques que ceux des deux groupes de comparaison (p<0.05). L'analyse statistique (stepwise logistic regression) a révélé que les patients présentant des troubles psychotiques avaient un risque plus élevé de recevoir un médicament antipsychotique d'une dose moyenne ou élevée, (p<0.001) en comparaison aux deux autres groupes. Conclusion Les nouveaux médicaments antipsychotiques semblent être prescrits avec moins d'hésitation principalement pour des indications admises. Les médecins prescrivent de nouveaux médicaments « off-label » seulement après avoir acquis une certaine expérience dans le domaine des indications approuvées, et ils étaient plus prudents en ce qui concerne la dose en traitant sur la base «off-label». Abstract Objective The new brands of atypical antipsychotics are very successfully prescribed because of their enhanced safety profiles and their larger pharmacological profile in comparison to the conventional antipsychotic. This has led to broad off-label utilisation. The aim of the present survey was to study the prescription practice of hospital psychiatrists with regard to antipsychotic drugs, comparing patients treated for psychoses or other registered indications to patients receiving an off-label antipsychotic treatment. Method As part of a pharmacovigilance/pharmacoepidemiology program, all drugs given on 5 reference days (1999 - 2001) in the 98-bed psychiatric hospital of the University of Lausanne, Switzerland, were recorded along with age, sex and diagnosis. The prescriptions of 202 patients were assessed. Patients were classified in 3 diagnostic groups: (1) patient with psychotic disorders, (2) patients with manic episodes and depressive episodes with psychotic symptoms, and (3) patients with other disorders. Group (1) and (2) formed the class of patients receiving an antipsychotic for a registered indication, and the prescriptions in group (3) were considered as off-label. Main results A lesser number of psychotic patients received antidepressant (p<0.05) and nonbenzodiazepine hypnotics (p<0.001) compared to the patients of the other two groups. The patients with affective disorders received only exceptionally a combination of an atypical and a conventional antipsychotic, whereas a lesser number of patients with off-label indications received less often atypical antipsychotics than those of the two comparison groups (p<0.05). Stepwise logistic regression revealed that patients with psychotic disorder were at higher risk of receiving an antipsychotic medication in medium or high dose (p<0.001), in comparison to the two other groups. Conclusions The new antipsychotic drugs seem to be prescribed with less hesitation mainly for approved indications. Physicians prescribe new drugs on off-label application only after having gained some experience in the field of the approved indications, and were more cautious with regard to dose when treating on an off-label basis.

Validation of the French version of the Hierarchical Personality Inventory for Children (HiPIC): Influence of gender and age on personality traits from 8 to 12 years

The study was designed to investigate the psychometric properties of the French version and the cross-language replicability of the Hierarchical Personality Inventory for Children (HiPIC). The HiPIC is an instrument aimed at assessing the five dimensions of the Five-Factor Model for Children. Subjects were 552 children aged between 8 and 12 years, rated by one or both parents. At the domain level, reliability ranged from .83 to .93 and at the facet level, reliability ranged from .69 to .89. Differences between genders were congruent with those found in the Dutch sample. Girls scored higher on Benevolence and Conscientiousness. Age was negatively correlated with Extraversion and Imagination. For girls, we also observed a decrease of Emotional Stability. A series of exploratory factor analyses confirmed the overall five-factor structure for girls and boys. Targeted factor analyses and congruence coefficients revealed high cross-language replicability at the domain and at the facet levels. The results showed that the French version of the HiPIC is a reliable and valid instrument for assessing personality with children and has a particularly high cross-language replicability.

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.

A prospective, randomized, open label, phase iii clinical trial of novottf-100a vs best standard of care chemotherapy in patients with recurrent glioblastoma

BACKGROUND: Glioblastoma, the most common adult primary malignant brain tumor, confers poor prognosis (median survival of 15 months) notwithstanding aggressive treatment. Combination chemotherapy including carmustine (BCNU) or temozolomide (TMZ) with the MGMT inhibitor O6-benzylguanine (O6BG) has been used, but has been associated with dose-limiting hematopoietic toxicity. OBJECTIVE: To assess safety and efficacy of a retroviral vector encoding the O6BG-resistant MGMTP140K gene for transduction and autologous transplantation of hematopoietic stem cells (HSCs) in MGMT unmethylated, newly diagnosed glioblastoma patients in an attempt to chemoprotect bone marrowduring combination O6BG/TMZ therapy. METHODS: Three patients have been enrolled in the first cohort. Patients underwent standard radiation therapy without TMZ followed by G-CSF mobilization, apheresis, and conditioning with 600 mg/m2 BCNU prior to infusion of gene-modified cells. Posttransplant, patients were treated with 28-day cycles of single doseTMZ (472 mg/m2) with 48-hour intravenous O6BG (120 mg/m2 bolus, then 30 mg/m2/d). RESULTS: The BCNU dose was nonmyeloablative with ANC ,500/mL for ≤3 d and nadir thrombocytopenia of 28,000/mL. Gene marking in pre-infusion colony forming units (CFUs) was 70.6%, 79.0%, and 74.0% in Patients 1, 2, and 3, respectively, by CFU-PCR. Following engraftment, gene marking in white blood cells and sorted granulocytes ranged between 0.37-0.84 and 0.33-0.83 provirus copies, respectively, by real-time PCR. Posttransplant gene marking in CFUs from CD34-selected cells ranged from 28.5% to 47.4%. Patients have received 4, 3, and 2 cycles of O6BG/TMZ, respectively, with evidence for selection of gene-modified cells. One patient has received a single dose-escalated cycle at 590 mg/m2 TMZ. No additional extra-hematopoietic toxicity has been observed thus far and all three patients exhibit stable disease at 7-8 months since diagnosis CONCLUSIONS: We believe that these data demonstrate the feasibility of achieving significant engraftment of MGMTP140K-modified cells with a well-tolerated dose of BCNU. Further follow-up will determine whether this approach will allow for further dose escalation of TMZ and improved survival.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

The hierarchical structures of the NEO-PI-R and the 16PF5

The present study compares the higher-level dimensions and the hierarchical structures of the fifth edition of the 16 PF with those of the NEO PI-R. Both inventories measure personality according to five higher-level dimensions. These inventories were however constructed according to different methods (bottom-up vs. top-down). 386 participants filled out both questionnaires. Correlations, regressions and canonical correlations made it possible to compare the inventories. As expected they roughly measure the same aspects of personality. There is a coherent association among four of the five dimensions measured in the tests. However Agreeableness, the remaining dimension in the NEO PI-R, is not represented in the 16 PF 5. Our analyses confirmed the hierarchical structures of both instruments, but this confirmation was more complete in the case of the NEO PI-R. Indeed, a parallel analysis indicated that a four-factor solution should be considered in the case of the 16 PF 5. On the other hand, the NEO PI-R's five-factor solution was confirmed. The top-down construction of this instrument seems to make for a more legible structure. Of the two five-dimension constructs, the NEO PI-R thus seems the more reliable. This confirms the relevance of the Five Factor Model of personality.

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

Clustering of risk behaviors with cigarette consumption: a population-based survey.

OBJECTIVE: This study assessed clustering of multiple risk behaviors (i.e., low leisure-time physical activity, low fruits/vegetables intake, and high alcohol consumption) with level of cigarette consumption. METHODS: Data from the 2002 Swiss Health Survey, a population-based cross-sectional telephone survey assessing health and self-reported risk behaviors, were used. 18,005 subjects (8052 men and 9953 women) aged 25 years old or more participated. RESULTS: Smokers more frequently had low leisure time physical activity, low fruits/vegetables intake, and high alcohol consumption than non- and ex-smokers. Frequency of each risk behavior increased steadily with cigarette consumption. Clustering of risk behaviors increased with cigarette consumption in both men and women. For men, the odds ratios of multiple (> or =2) risk behaviors other than smoking, adjusted for age, nationality, and educational level, were 1.14 (95% confidence interval: 0.97, 1.33) for ex-smokers, 1.24 (0.93, 1.64) for light smokers (1-9 cigarettes/day), 1.72 (1.36, 2.17) for moderate smokers (10-19 cigarettes/day), and 3.07 (2.59, 3.64) for heavy smokers (> or =20 cigarettes/day) versus non-smokers. Similar odds ratios were found for women for corresponding groups, i.e., 1.01 (0.86, 1.19), 1.26 (1.00, 1.58), 1.62 (1.33, 1.98), and 2.75 (2.30, 3.29). CONCLUSIONS: Counseling and intervention with smokers should take into account the strong clustering of risk behaviors with level of cigarette consumption.

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Impact of tamoxifen dose on tamoxifen and its active metabolites exposure in breast cancer patients: preliminary results from a prospective, open-label trial

Background: CYP2D6 is the key enzyme responsible for tamoxifen bioactivation mainly into endoxifen. This gene is highly polymorphic and breast cancer patients classified as CYP2D6 poor metabolizers (PM) or intermediate metabolizers (IM) appear to show low concentrations of endoxifen and to achieve less benefit from tamoxifen treatment. Purpose: This prospective, open-label trial aimed to assess how the increase of tamoxifen dose influences the level of endoxifen in the different genotype groups (poor-, intermediate-, and extensive-metabolizers (EM)). We examined the impact of doubling tamoxifen dose to 20mg twice daily on endoxifen plasma concentrations across these genotype groups. Patients and methods: Patients were assayed for CYP2D6 genotype and phenotype using dextromethorphan test. Tamoxifen, N-desmethyltamoxifen, 4-hydroxytamoxifen and endoxifen plasma levels were determined on 2 occasions at baseline (20mg/day of tamoxifen) and at day 30, 90 and 120 after dose increase (20 mg twice daily) using liquid chromatography-tandem-mass spectrometry. Endoxifen plasma levels were measured 6 to 24 hours after last drug intake to evaluate its accumulation before and after doubling tamoxifen dosage. ANOVA was used to evaluate endoxifen levels increase and difference between genotype groups. Results: 63 patients are available for analysis to date. Tamoxifen, N-desmethyltamoxifen, 4-hydroxytamoxifen and endoxifen plasma reached steady state at 30 day after tamoxifen dose escalation, with a significant increase compared to baseline by 1.6 to 1.8 fold : geometric mean plasma concentrations (CV %) were 140 ng/mL (45%) at baseline vs 255 (47%) at day 30 for tamoxifen (P < 0.0001); 256 (49%) vs 408 (64%) for N-desmethyltamoxifen (P < 0.0001); 2.4 (46%) vs 3.9 (51%) for 4-OH-tamoxifen (P < 0.0001); and 20 (91%) vs 33 (91%) for endoxifen (P < 0.02). On baseline, endoxifen levels tended to be lower in PM: 7 ng/mL (36%), than IM: 16 ng/mL (70%), P=0.08, and EM: 24 ng/mL (71%), P<0.001. After doubling tamoxifen dosage, endoxifen concentrations rose similarly in PM, IM and EM with respectively, 1.5 (18%), 1.5 (28%) and 1.7 (30%) fold increase from baseline, P=0.18. Conclusion: Endoxifen exposure varies widely under standard tamoxifen dosage, with CYP2D6 genotype explaining only a minor part of this variability. It increases consistently on doubling tamoxifen dose, similarly across genotypes. This would enable exposure optimization based on concentration monitoring.

Hierarchical analyses of genetic differentiation in a hybrid zone of Sorex araneus (Insectivora : Soricidae)

Microsatellites are used to unravel the fine-scale genetic structure of a hybrid zone between chromosome races Valais and Cordon of the common shrew (Sorex araneus) located in the French Alps. A total of 269 individuals collected between 1992 and 1995 was typed for seven microsatellite loci. A modified version of the classical multiple correspondence analysis is carried out. This analysis clearly shows the dichotomy between the two races. Several approaches are used to study genetic structuring. Gene flow is clearly reduced between these chromosome races and is estimated at one migrant every two generations using X-statistics and one migrant per generation using F-statistics. Hierarchical F- and R-statistics are compared and their efficiency to detect inter- and intraracial patterns of divergence is discussed. Within-race genetic structuring is significant, but remains weak. F-ST displays similar values on both sides of the hybrid zone, although no environmental barriers are found on the Cordon side, whereas the Valais side is divided by several mountain rivers. We introduce the exact G-test to microsatellite data which proved to be a powerful test to detect genetic differentiation within as well as among races. The genetic background of karyotypic hybrids was compared with the genetic background of pure parental forms using a CRT-MCA. Our results indicate that, without knowledge of the karyotypes, we would not have been able to distinguish these hybrids from karyotypically pure samples.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.