Which subgroup of patients with rheumatoid arthritis benefits from switching to rituximab versus alternative anti-tumour necrosis factor (TNF) agents after previous failure of an anti-TNF agent?

BACKGROUND: Patients with rheumatoid arthritis (RA) with an inadequate response to TNF antagonists (aTNFs) may switch to an alternative aTNF or start treatment from a different class of drugs, such as rituximab (RTX). It remains unclear in which clinical settings these therapeutic strategies offer most benefit. OBJECTIVE: To analyse the effectiveness of RTX versus alternative aTNFs on RA disease activity in different subgroups of patients. METHODS: A prospective cohort study of patients with RA who discontinued at least one aTNF and subsequently received either RTX or an alternative aTNF, nested within the Swiss RA registry (SCQM-RA) was carried out. The primary outcome, longitudinal improvement in 28-joint count Disease Activity Score (DAS28), was analysed using multivariate regression models for longitudinal data and adjusted for potential confounders. RESULTS: Of the 318 patients with RA included; 155 received RTX and 163 received an alternative aTNF. The relative benefit of RTX varied with the type of prior aTNF failure: when the motive for switching was ineffectiveness to previous aTNFs, the longitudinal improvement in DAS28 was significantly better with RTX than with an alternative aTNF (p = 0.03; at 6 months, -1.34 (95% CI -1.54 to -1.15) vs -0.93 (95% CI -1.28 to -0.59), respectively). When the motive for switching was other causes, the longitudinal improvement in DAS28 was similar for RTX and alternative aTNFs (p = 0.40). These results were not significantly modified by the number of previous aTNF failures, the type of aTNF switches, or the presence of co-treatment with a disease-modifying antirheumatic drug. CONCLUSION: This observational study suggests that in patients with RA who have stopped a previous aTNF treatment because of ineffectiveness changing to RTX is more effective than switching to an alternative aTNF.

Genotype 3 is associated with rapid histological progression in chronic HCV infection

While several risk factors for the histological progression of chronic hepatitis C have been identified, the contribution of HCV genotypes to liver fibrosis evolution remains controversial. The aim of the present study was to assess independent predictors for fibrosis progression. Methods: We identified 1540 patients from the Swiss Hepatitis C Cohort database with at least one liver biopsy prior to antiviral treatment. Factors associated with fibrosis stage, steatosis and histological activity were assessed in univariate and multivariate regression models. Fibrosis progression rate per year was calculated in a subgroup of 1263 patients, in whom risk factors were assessed by cumulative incidence curves, logistic and linear regression models. Results: Independent risk factors for rapid fibrosis progression included male sex (OR = 1.66, 95% CI 1.25-2.21, P <0.001), age at infection (OR = 1.08, 95% CI 1.06-1.10, P <0.001), histological activity (OR = 2.14, 95% CI 1.61-2.85, P <0.001) and genotype 3 (OR = 1.97, 95% CI 1.43-2.72, P <0.001). Genotype 2 was associated with slow progression (OR = 0.51, 95% CI 0.30-0.89, P = 0.02), but this observation may be due to the decreased prevalence of genotype 2 over the last decades, leading to an overrepresentation of subjects with genotype 2 with a slow progression rate. Conclusion: This study shows a significant association of genotype 3 with accelerated fibrosis. While assessing risk factors for fibrosis progression, the changing epidemiology of HCV genotypes over time needs to be taken into account.

Genotype 3 is associated with accelerated fibrosis progression in chronic hepatitis C.

BACKGROUND/AIMS: While several risk factors for the histological progression of chronic hepatitis C have been identified, the contribution of HCV genotypes to liver fibrosis evolution remains controversial. The aim of this study was to assess independent predictors for fibrosis progression. METHODS: We identified 1189 patients from the Swiss Hepatitis C Cohort database with at least one biopsy prior to antiviral treatment and assessable date of infection. Stage-constant fibrosis progression rate was assessed using the ratio of fibrosis Metavir score to duration of infection. Stage-specific fibrosis progression rates were obtained using a Markov model. Risk factors were assessed by univariate and multivariate regression models. RESULTS: Independent risk factors for accelerated stage-constant fibrosis progression (>0.083 fibrosis units/year) included male sex (OR=1.60, [95% CI 1.21-2.12], P<0.001), age at infection (OR=1.08, [1.06-1.09], P<0.001), histological activity (OR=2.03, [1.54-2.68], P<0.001) and genotype 3 (OR=1.89, [1.37-2.61], P<0.001). Slower progression rates were observed in patients infected by blood transfusion (P=0.02) and invasive procedures or needle stick (P=0.03), compared to those infected by intravenous drug use. Maximum likelihood estimates (95% CI) of stage-specific progression rates (fibrosis units/year) for genotype 3 versus the other genotypes were: F0-->F1: 0.126 (0.106-0.145) versus 0.091 (0.083-0.100), F1-->F2: 0.099 (0.080-0.117) versus 0.065 (0.058-0.073), F2-->F3: 0.077 (0.058-0.096) versus 0.068 (0.057-0.080) and F3-->F4: 0.171 (0.106-0.236) versus 0.112 (0.083-0.142, overall P<0.001). CONCLUSIONS: This study shows a significant association of genotype 3 with accelerated fibrosis using both stage-constant and stage-specific estimates of fibrosis progression rates. This observation may have important consequences for the management of patients infected with this genotype.

Microvascular changes in late-life schizophrenia and mood disorders: stereological assessment of capillary diameters in anterior cingulate cortex.

AIMS: Previous neuroimaging reports described morphological and functional abnormalities in anterior cingulate cortex (ACC) in schizophrenia and mood disorders. In earlier neuropathological studies, microvascular changes that could affect brain perfusion in these disorders have rarely been studied. Here, we analysed morphological parameters of capillaries in this area in elderly cases affected by these psychiatric disorders. METHODS: We analysed microvessel diameters in the dorsal and subgenual parts of the ACC in eight patients with schizophrenia, 10 patients with sporadic bipolar disorder, eight patients with sporadic major depression, and seven age- and gender-matched control cases on sections stained with modified Gallyas silver impregnation using a stereological counting approach. All individuals were drug-naïve or had received psychotropic medication for less than 6 months, and had no history of substance abuse. Statistical analysis included Kruskal-Wallis group comparisons with Bonferroni correction as well as multivariate regression models. RESULTS: Mean capillary diameter was significantly decreased in the dorsal and subgenual parts of areas 24 in bipolar and unipolar depression cases, both in layers III and V, whereas schizophrenia patients were comparable with controls. These differences persisted when controlling for age, local neuronal densities, and cortical thickness. In addition, cortical thickness was significantly smaller in both layers in schizophrenia patients. CONCLUSIONS: Our findings indicate that capillary diameters in bipolar and unipolar depression but not in schizophrenia are reduced in ACC. The significance of these findings is discussed in the light of the cytoarchitecture, brain metabolism and perfusion changes observed in ACC in mood disorders.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Polymorphisms in toll-like receptor 4 and toll-like receptor 9 influence viral load in a seroincident cohort of HIV-1-infected individuals.

OBJECTIVES: Toll-like receptors (TLRs) are innate immune sensors that are integral to resisting chronic and opportunistic infections. Mounting evidence implicates TLR polymorphisms in susceptibilities to various infectious diseases, including HIV-1. We investigated the impact of TLR single nucleotide polymorphisms (SNPs) on clinical outcome in a seroincident cohort of HIV-1-infected volunteers. DESIGN: We analyzed TLR SNPs in 201 antiretroviral treatment-naive HIV-1-infected volunteers from a longitudinal seroincident cohort with regular follow-up intervals (median follow-up 4.2 years, interquartile range 4.4). Participants were stratified into two groups according to either disease progression, defined as peripheral blood CD4(+) T-cell decline over time, or peak and setpoint viral load. METHODS: Haplotype tagging SNPs from TLR2, TLR3, TLR4, and TLR9 were detected by mass array genotyping, and CD4(+) T-cell counts and viral load measurements were determined prior to antiretroviral therapy initiation. The association of TLR haplotypes with viral load and rapid progression was assessed by multivariate regression models using age and sex as covariates. RESULTS: Two TLR4 SNPs in strong linkage disequilibrium [1063 A/G (D299G) and 1363 C/T (T399I)] were more frequent among individuals with high peak viral load compared with low/moderate peak viral load (odds ratio 6.65, 95% confidence interval 2.19-20.46, P < 0.001; adjusted P = 0.002 for 1063 A/G). In addition, a TLR9 SNP previously associated with slow progression was found less frequently among individuals with high viral setpoint compared with low/moderate setpoint (odds ratio 0.29, 95% confidence interval 0.13-0.65, P = 0.003, adjusted P = 0.04). CONCLUSION: This study suggests a potentially new role for TLR4 polymorphisms in HIV-1 peak viral load and confirms a role for TLR9 polymorphisms in disease progression.

Safety and functional outcome of thrombolysis in dissection-related ischemic stroke: a meta-analysis of individual patient data.

Background and Purpose-The safety and efficacy of thrombolysis in cervical artery dissection (CAD) are controversial. The aim of this meta-analysis was to pool all individual patient data and provide a valid estimate of safety and outcome of thrombolysis in CAD.Methods-We performed a systematic literature search on intravenous and intra-arterial thrombolysis in CAD. We calculated the rates of pooled symptomatic intracranial hemorrhage and mortality and indirectly compared them with matched controls from the Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register. We applied multivariate regression models to identify predictors of excellent (modified Rankin Scale=0 to 1) and favorable (modified Rankin Scale=0 to 2) outcome.Results-We obtained individual patient data of 180 patients from 14 retrospective series and 22 case reports. Patients were predominantly female (68%), with a mean +/- SD age of 46 +/- 11 years. Most patients presented with severe stroke (median National Institutes of Health Stroke Scale score=16). Treatment was intravenous thrombolysis in 67% and intra-arterial thrombolysis in 33%. Median follow-up was 3 months. The pooled symptomatic intracranial hemorrhage rate was 3.1% (95% CI, 1.3 to 7.2). Overall mortality was 8.1% (95% CI, 4.9 to 13.2), and 41.0% (95% CI, 31.4 to 51.4) had an excellent outcome. Stroke severity was a strong predictor of outcome. Overlapping confidence intervals of end points indicated no relevant differences with matched controls from the Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register.Conclusions-Safety and outcome of thrombolysis in patients with CAD-related stroke appear similar to those for stroke from all causes. Based on our findings, thrombolysis should not be withheld in patients with CAD. (Stroke. 2011;42:2515-2520.)

Fatigue and weight loss predict survival on circadian chemotherapy for metastatic colorectal cancer.

BACKGROUND: Chemotherapy-induced neutropenia has been associated with prolonged survival selectively in patients on a conventional schedule (combined 5-fluorouracil, leucovorin, and oxaliplatin [FOLFOX2]) but not on a chronomodulated schedule of the same drugs administered at specific circadian times (chronoFLO4). The authors hypothesized that the early occurrence of chemotherapy-induced symptoms correlated with circadian disruption would selectively hinder the efficacy of chronotherapy. METHODS: Fatigue and weight loss (FWL) were considered to be associated with circadian disruption based on previous data. Patients with metastatic colorectal cancer (nâeuro0/00=âeuro0/00543) from an international phase 3 trial comparing FOLFOX2 with chronoFLO4 were categorized into 4 subgroups according to the occurrence of FWL or other clinically relevant toxicities during the initial 2 courses of chemotherapy. Multivariate Cox models were used to assess the role of toxicity on the time to progression (TTP) and overall survival (OS). RESULTS: The proportions of patients in the 4 subgroups were comparable in both treatment arms (Pâeuro0/00=âeuro0/00.77). No toxicity was associated with TTP or OS on FOLFOX2. The median OS on FOLFOX2 ranged from 16.4 (95% confidence limits [CL], 7.2-25.6 months) to 19.8 months (95% CL, 17.7-22.0 months) according to toxicity subgroup (Pâeuro0/00=âeuro0/00.45). Conversely, FWL, but no other toxicity, independently predicted for significantly shorter TTP (Pâeuro0/00<âeuro0/00.0001) and OS (Pâeuro0/00=âeuro0/00.001) on chronoFLO4. The median OS on chronoFLO4 was 13.8 months (95% CL, 10.4-17.2 months) or 21.1 months (95% CL, 19.0-23.1 months) according to presence or absence of chemotherapy-induced FWL, respectively. CONCLUSIONS: Early onset chemotherapy-induced FWL was an independent predictor of poor TTP and OS only on chronotherapy. Dynamic monitoring to detect early chemotherapy-induced circadian disruption could allow the optimization of rapid chronotherapy and concomitant improvements in safety and efficacy.

Clinical Prognostic Factors Predicting Outcomes Of Patients With Recurrent Gbm And Nomograms

BACKGROUND: Prognostic models and nomograms were recently developed to predict survival of patients with newly diagnosed glioblastoma multiforme (GBM).1 To improve predictions, models should be updated with the most recent patient and disease information. Nomograms predicting patient outcome at the time of disease progression are required. METHODS: Baseline information from 299 patients with recurrent GBM recruited in 8 phase I or II trials of the EORTC Brain Tumor Group was used to evaluate clinical parameters as prognosticators of patient outcome. Univariate (log rank) and multivariate (Cox models) analyses were made to assess the ability of patients' characteristics (age, sex, performance status [WHO PS], and MRC neurological deficit scale), disease history (prior treatments, time since last treatment or initial diagnosis, and administration of steroids or antiepileptics) and disease characteristics (tumor size and number of lesions) to predict progression free survival (PFS) and overall survival (OS). Bootstrap technique was used for models internal validation. Nomograms were computed to provide individual patients predictions. RESULTS: Poor PS and more than 1 lesion had a significant prognostic impact for both PFS and OS. Antiepileptic drug use was significantly associated with worse PFS. Larger tumors (split by the median of the largest tumor diameter >42.5 mm) and steroid use had shorter OS. Age, sex, neurologic deficit, prior therapies, and time since last therapy or initial diagnosis did not show independent prognostic value for PFS or OS. CONCLUSIONS: This analysis confirms that PS but not age is a major prognostic factor for PFS and OS. Multiple or large tumors and the need to administer steroids significantly increase the risk of progression and death. Nomograms at the recurrence could be used to obtain accurate predictions for the design of new targeted therapy trials or retrospective analyses. (1. T. Gorlia et al., Nomograms for predicting survival of patients with newly diagnosed glioblastoma. Lancet Oncol 9 (1): 29-38, 2008.)

Potential health-care service utilization substitution effects induced by case management for emergency department frequent users

BACKGROUND: In most of the emergency departments (ED) in developed countries, a subset of patients visits the ED frequently. Despite their small numbers, these patients are the source of a disproportionally high number of all ED visits, and use a significant proportion of healthcare resources. They place a heavy economic burden on hospital and healthcare systems budgets overall. Several interventions have been carried out to improve the management of these ED frequent users. Case management has been shown in some North American studies to reduce ED utilization and costs. In these studies, cost analyses have been carried out from the hospital perspective without examining the costs induced by healthcare consumed in the community. However, case management might reduce ED visits and costs from the hospital's perspective, but induce substitution effects, and increase health service utilization outside the hospital. This study examined if an interdisciplinary case-management intervention-compared to standard ED care -reduced costs generated by frequent ED users not only from the hospital perspective, but also from the healthcare system perspective-that is, from a broader perspective taking into account the costs of healthcare services used outside the hospital. METHODS: In this randomized controlled trial, 250 adult frequent emergency department users (5 or more visits during the previous 12 months) who visited the ED of the University Hospital of Lausanne, Switzerland, between May 2012 and July 2013 were allocated to one of two groups: case management intervention (CM) or standard ED care (SC), and followed up for 12 months. Depending on the perspective of the analysis, costs were evaluated differently. For the analysis from the hospital's perspective, the true value of resources used to provide services was used as a cost estimate. These data were obtained from the hospital's analytical accounting system. For the analysis from the health-care system perspective, all health-care services consumed by users and charged were used as an estimate of costs. These data were obtained from health insurance providers for a subsample of participants. To allow comparisons in a same time period, individual monthly average costs were calculated. Multivariate linear models including a fixed effect "group" were run using socio-demographic characteristics and health-related variables as controlling variables (age, gender, educational level, citizenship, marital status, somatic and mental health problems, and risk behaviors).

Impact on costs of a case management intervention for emergency department frequent users

Background: In most of the emergency departments (ED) in developed countries, a subset of patients visits the ED frequently. Despite their small numbers, these patients are the source of a disproportionally high number of all ED visits, and use a significant proportion of healthcare resources. They place a heavy economic burden on hospital and healthcare system budgets overall. In order to improve the management of these patients, the University hospital of Lausanne, Switzerland implemented a case management intervention (CM) between May 2012 and July 2013. In this randomized controlled trial, 250 frequent ED users (visits>5 during previous 12 months) were allocated to either the CM group or the standard ED care (SC) group and followed up for 12 months. The first result of the CM was to reduce significantly the ED visits. The present study examined whether the CM intervention also reduced the costs generated by the ED frequent users not only from the hospital perspective, but also from the healthcare system perspective. Methods: Cost data were obtained from the hospital's analytical accounting system and from health insurances. Multivariate linear models including a fixed effect "group" and socio-demographic characteristics and health-related variables were run.

Regional differences of physical activity and sedentary behaviour in Swiss children are not explained by socio-demographics or the built environment.

OBJECTIVE: We evaluated whether regional differences in physical activity (PA) and sedentary behaviour (SB) existed along language boundaries within Switzerland and whether potential differences would be explained by socio-demographics or environmental characteristics. METHODS: We combined data of 611 children aged 4 to 7 years from four regional studies. PA and SB were assessed by accelerometers. Information about the socio-demographic background was obtained by questionnaires. Objective neighbourhood attributes could be linked to home addresses. Multivariate regression models were used to test associations between PA and SB and socio-demographic characteristics and neighbourhood attributes. RESULTS: Children from the German compared to the French-speaking region were more physically active and less sedentary (by 10-15 %, p < 0.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences p < 0.001), these characteristics did not explain the differences in PA behaviour between French and German speaking. CONCLUSIONS: Factors related to the language region, which might be culturally rooted were among the strongest correlates of PA and SB among Swiss children, independent of individual, social and environmental factors.

Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.

Bayesian classification criterion for forensic multivariate data

This study presents a classification criteria for two-class Cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland, law enforcement authorities regularly ask laboratories to determine cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. In this study, the classification analysis is based on data obtained from the relative proportion of three major leaf compounds measured by gas-chromatography interfaced with mass spectrometry (GC-MS). The aim is to discriminate between drug type (illegal) and fiber type (legal) cannabis at an early stage of the growth. A Bayesian procedure is proposed: a Bayes factor is computed and classification is performed on the basis of the decision maker specifications (i.e. prior probability distributions on cannabis type and consequences of classification measured by losses). Classification rates are computed with two statistical models and results are compared. Sensitivity analysis is then performed to analyze the robustness of classification criteria.