Reliability of methods used for the risk assessment of mixture of micropollutants in aquatic enviromments : from theoretical concepts to field observations

Ces dernières années, de nombreuses recherches ont mis en évidence les effets toxiques des micropolluants organiques pour les espèces de nos lacs et rivières. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, alors que les organismes sont exposés tous les jours à des milliers de substances en mélange. Or les effets de ces cocktails ne sont pas négligeables. Cette thèse de doctorat s'est ainsi intéressée aux modèles permettant de prédire le risque environnemental de ces cocktails pour le milieu aquatique. Le principal objectif a été d'évaluer le risque écologique des mélanges de substances chimiques mesurées dans le Léman, mais aussi d'apporter un regard critique sur les méthodologies utilisées afin de proposer certaines adaptations pour une meilleure estimation du risque. Dans la première partie de ce travail, le risque des mélanges de pesticides et médicaments pour le Rhône et pour le Léman a été établi en utilisant des approches envisagées notamment dans la législation européenne. Il s'agit d'approches de « screening », c'est-à-dire permettant une évaluation générale du risque des mélanges. Une telle approche permet de mettre en évidence les substances les plus problématiques, c'est-à-dire contribuant le plus à la toxicité du mélange. Dans notre cas, il s'agit essentiellement de 4 pesticides. L'étude met également en évidence que toutes les substances, même en trace infime, contribuent à l'effet du mélange. Cette constatation a des implications en terme de gestion de l'environnement. En effet, ceci implique qu'il faut réduire toutes les sources de polluants, et pas seulement les plus problématiques. Mais l'approche proposée présente également un biais important au niveau conceptuel, ce qui rend son utilisation discutable, en dehors d'un screening, et nécessiterait une adaptation au niveau des facteurs de sécurité employés. Dans une deuxième partie, l'étude s'est portée sur l'utilisation des modèles de mélanges dans le calcul de risque environnemental. En effet, les modèles de mélanges ont été développés et validés espèce par espèce, et non pour une évaluation sur l'écosystème en entier. Leur utilisation devrait donc passer par un calcul par espèce, ce qui est rarement fait dû au manque de données écotoxicologiques à disposition. Le but a été donc de comparer, avec des valeurs générées aléatoirement, le calcul de risque effectué selon une méthode rigoureuse, espèce par espèce, avec celui effectué classiquement où les modèles sont appliqués sur l'ensemble de la communauté sans tenir compte des variations inter-espèces. Les résultats sont dans la majorité des cas similaires, ce qui valide l'approche utilisée traditionnellement. En revanche, ce travail a permis de déterminer certains cas où l'application classique peut conduire à une sous- ou sur-estimation du risque. Enfin, une dernière partie de cette thèse s'est intéressée à l'influence que les cocktails de micropolluants ont pu avoir sur les communautés in situ. Pour ce faire, une approche en deux temps a été adoptée. Tout d'abord la toxicité de quatorze herbicides détectés dans le Léman a été déterminée. Sur la période étudiée, de 2004 à 2009, cette toxicité due aux herbicides a diminué, passant de 4% d'espèces affectées à moins de 1%. Ensuite, la question était de savoir si cette diminution de toxicité avait un impact sur le développement de certaines espèces au sein de la communauté des algues. Pour ce faire, l'utilisation statistique a permis d'isoler d'autres facteurs pouvant avoir une influence sur la flore, comme la température de l'eau ou la présence de phosphates, et ainsi de constater quelles espèces se sont révélées avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps. Fait intéressant, une partie d'entre-elles avait déjà montré des comportements similaires dans des études en mésocosmes. En conclusion, ce travail montre qu'il existe des modèles robustes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques, et qu'ils peuvent être utilisés pour expliquer le rôle des substances dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application. - Depuis plusieurs années, les risques que posent les micropolluants organiques pour le milieu aquatique préoccupent grandement les scientifiques ainsi que notre société. En effet, de nombreuses recherches ont mis en évidence les effets toxiques que peuvent avoir ces substances chimiques sur les espèces de nos lacs et rivières, quand elles se retrouvent exposées à des concentrations aiguës ou chroniques. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, c'est à dire considérées séparément. Actuellement, il en est de même dans les procédures de régulation européennes, concernant la partie évaluation du risque pour l'environnement d'une substance. Or, les organismes sont exposés tous les jours à des milliers de substances en mélange, et les effets de ces "cocktails" ne sont pas négligeables. L'évaluation du risque écologique que pose ces mélanges de substances doit donc être abordé par de la manière la plus appropriée et la plus fiable possible. Dans la première partie de cette thèse, nous nous sommes intéressés aux méthodes actuellement envisagées à être intégrées dans les législations européennes pour l'évaluation du risque des mélanges pour le milieu aquatique. Ces méthodes sont basées sur le modèle d'addition des concentrations, avec l'utilisation des valeurs de concentrations des substances estimées sans effet dans le milieu (PNEC), ou à partir des valeurs des concentrations d'effet (CE50) sur certaines espèces d'un niveau trophique avec la prise en compte de facteurs de sécurité. Nous avons appliqué ces méthodes à deux cas spécifiques, le lac Léman et le Rhône situés en Suisse, et discuté les résultats de ces applications. Ces premières étapes d'évaluation ont montré que le risque des mélanges pour ces cas d'étude atteint rapidement une valeur au dessus d'un seuil critique. Cette valeur atteinte est généralement due à deux ou trois substances principales. Les procédures proposées permettent donc d'identifier les substances les plus problématiques pour lesquelles des mesures de gestion, telles que la réduction de leur entrée dans le milieu aquatique, devraient être envisagées. Cependant, nous avons également constaté que le niveau de risque associé à ces mélanges de substances n'est pas négligeable, même sans tenir compte de ces substances principales. En effet, l'accumulation des substances, même en traces infimes, atteint un seuil critique, ce qui devient plus difficile en terme de gestion du risque. En outre, nous avons souligné un manque de fiabilité dans ces procédures, qui peuvent conduire à des résultats contradictoires en terme de risque. Ceci est lié à l'incompatibilité des facteurs de sécurité utilisés dans les différentes méthodes. Dans la deuxième partie de la thèse, nous avons étudié la fiabilité de méthodes plus avancées dans la prédiction de l'effet des mélanges pour les communautés évoluant dans le système aquatique. Ces méthodes reposent sur le modèle d'addition des concentrations (CA) ou d'addition des réponses (RA) appliqués sur les courbes de distribution de la sensibilité des espèces (SSD) aux substances. En effet, les modèles de mélanges ont été développés et validés pour être appliqués espèce par espèce, et non pas sur plusieurs espèces agrégées simultanément dans les courbes SSD. Nous avons ainsi proposé une procédure plus rigoureuse, pour l'évaluation du risque d'un mélange, qui serait d'appliquer d'abord les modèles CA ou RA à chaque espèce séparément, et, dans une deuxième étape, combiner les résultats afin d'établir une courbe SSD du mélange. Malheureusement, cette méthode n'est pas applicable dans la plupart des cas, car elle nécessite trop de données généralement indisponibles. Par conséquent, nous avons comparé, avec des valeurs générées aléatoirement, le calcul de risque effectué selon cette méthode plus rigoureuse, avec celle effectuée traditionnellement, afin de caractériser la robustesse de cette approche qui consiste à appliquer les modèles de mélange sur les courbes SSD. Nos résultats ont montré que l'utilisation de CA directement sur les SSDs peut conduire à une sous-estimation de la concentration du mélange affectant 5 % ou 50% des espèces, en particulier lorsque les substances présentent un grand écart- type dans leur distribution de la sensibilité des espèces. L'application du modèle RA peut quant à lui conduire à une sur- ou sous-estimations, principalement en fonction de la pente des courbes dose- réponse de chaque espèce composant les SSDs. La sous-estimation avec RA devient potentiellement importante lorsque le rapport entre la EC50 et la EC10 de la courbe dose-réponse des espèces est plus petit que 100. Toutefois, la plupart des substances, selon des cas réels, présentent des données d' écotoxicité qui font que le risque du mélange calculé par la méthode des modèles appliqués directement sur les SSDs reste cohérent et surestimerait plutôt légèrement le risque. Ces résultats valident ainsi l'approche utilisée traditionnellement. Néanmoins, il faut garder à l'esprit cette source d'erreur lorsqu'on procède à une évaluation du risque d'un mélange avec cette méthode traditionnelle, en particulier quand les SSD présentent une distribution des données en dehors des limites déterminées dans cette étude. Enfin, dans la dernière partie de cette thèse, nous avons confronté des prédictions de l'effet de mélange avec des changements biologiques observés dans l'environnement. Dans cette étude, nous avons utilisé des données venant d'un suivi à long terme d'un grand lac européen, le lac Léman, ce qui offrait la possibilité d'évaluer dans quelle mesure la prédiction de la toxicité des mélanges d'herbicide expliquait les changements dans la composition de la communauté phytoplanctonique. Ceci à côté d'autres paramètres classiques de limnologie tels que les nutriments. Pour atteindre cet objectif, nous avons déterminé la toxicité des mélanges sur plusieurs années de 14 herbicides régulièrement détectés dans le lac, en utilisant les modèles CA et RA avec les courbes de distribution de la sensibilité des espèces. Un gradient temporel de toxicité décroissant a pu être constaté de 2004 à 2009. Une analyse de redondance et de redondance partielle, a montré que ce gradient explique une partie significative de la variation de la composition de la communauté phytoplanctonique, même après avoir enlevé l'effet de toutes les autres co-variables. De plus, certaines espèces révélées pour avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps, ont montré des comportements similaires dans des études en mésocosmes. On peut en conclure que la toxicité du mélange herbicide est l'un des paramètres clés pour expliquer les changements de phytoplancton dans le lac Léman. En conclusion, il existe diverses méthodes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques et celui-ci peut jouer un rôle dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application, avant d'utiliser leurs résultats pour la gestion des risques environnementaux. - For several years now, the scientists as well as the society is concerned by the aquatic risk organic micropollutants may pose. Indeed, several researches have shown the toxic effects these substances may induce on organisms living in our lakes or rivers, especially when they are exposed to acute or chronic concentrations. However, most of the studies focused on the toxicity of single compounds, i.e. considered individually. The same also goes in the current European regulations concerning the risk assessment procedures for the environment of these substances. But aquatic organisms are typically exposed every day simultaneously to thousands of organic compounds. The toxic effects resulting of these "cocktails" cannot be neglected. The ecological risk assessment of mixtures of such compounds has therefore to be addressed by scientists in the most reliable and appropriate way. In the first part of this thesis, the procedures currently envisioned for the aquatic mixture risk assessment in European legislations are described. These methodologies are based on the mixture model of concentration addition and the use of the predicted no effect concentrations (PNEC) or effect concentrations (EC50) with assessment factors. These principal approaches were applied to two specific case studies, Lake Geneva and the River Rhône in Switzerland, including a discussion of the outcomes of such applications. These first level assessments showed that the mixture risks for these studied cases exceeded rapidly the critical value. This exceeding is generally due to two or three main substances. The proposed procedures allow therefore the identification of the most problematic substances for which management measures, such as a reduction of the entrance to the aquatic environment, should be envisioned. However, it was also showed that the risk levels associated with mixtures of compounds are not negligible, even without considering these main substances. Indeed, it is the sum of the substances that is problematic, which is more challenging in term of risk management. Moreover, a lack of reliability in the procedures was highlighted, which can lead to contradictory results in terms of risk. This result is linked to the inconsistency in the assessment factors applied in the different methods. In the second part of the thesis, the reliability of the more advanced procedures to predict the mixture effect to communities in the aquatic system were investigated. These established methodologies combine the model of concentration addition (CA) or response addition (RA) with species sensitivity distribution curves (SSD). Indeed, the mixture effect predictions were shown to be consistent only when the mixture models are applied on a single species, and not on several species simultaneously aggregated to SSDs. Hence, A more stringent procedure for mixture risk assessment is proposed, that would be to apply first the CA or RA models to each species separately and, in a second step, to combine the results to build an SSD for a mixture. Unfortunately, this methodology is not applicable in most cases, because it requires large data sets usually not available. Therefore, the differences between the two methodologies were studied with datasets created artificially to characterize the robustness of the traditional approach applying models on species sensitivity distribution. The results showed that the use of CA on SSD directly might lead to underestimations of the mixture concentration affecting 5% or 50% of species, especially when substances present a large standard deviation of the distribution from the sensitivity of the species. The application of RA can lead to over- or underestimates, depending mainly on the slope of the dose-response curves of the individual species. The potential underestimation with RA becomes important when the ratio between the EC50 and the EC10 for the dose-response curve of the species composing the SSD are smaller than 100. However, considering common real cases of ecotoxicity data for substances, the mixture risk calculated by the methodology applying mixture models directly on SSDs remains consistent and would rather slightly overestimate the risk. These results can be used as a theoretical validation of the currently applied methodology. Nevertheless, when assessing the risk of mixtures, one has to keep in mind this source of error with this classical methodology, especially when SSDs present a distribution of the data outside the range determined in this study Finally, in the last part of this thesis, we confronted the mixture effect predictions with biological changes observed in the environment. In this study, long-term monitoring of a European great lake, Lake Geneva, provides the opportunity to assess to what extent the predicted toxicity of herbicide mixtures explains the changes in the composition of the phytoplankton community next to other classical limnology parameters such as nutrients. To reach this goal, the gradient of the mixture toxicity of 14 herbicides regularly detected in the lake was calculated, using concentration addition and response addition models. A decreasing temporal gradient of toxicity was observed from 2004 to 2009. Redundancy analysis and partial redundancy analysis showed that this gradient explains a significant portion of the variation in phytoplankton community composition, even when having removed the effect of all other co-variables. Moreover, some species that were revealed to be influenced positively or negatively, by the decrease of toxicity in the lake over time, showed similar behaviors in mesocosms studies. It could be concluded that the herbicide mixture toxicity is one of the key parameters to explain phytoplankton changes in Lake Geneva. To conclude, different methods exist to predict the risk of mixture in the ecosystems. But their reliability varies depending on the underlying hypotheses. One should therefore carefully consider these hypotheses, as well as the limits of the approaches, before using the results for environmental risk management

Contribution of modifiable risk factors to social inequalities in type 2 diabetes: prospective Whitehall II cohort study.

OBJECTIVE: To assess the contribution of modifiable risk factors to social inequalities in the incidence of type 2 diabetes when these factors are measured at study baseline or repeatedly over follow-up and when long term exposure is accounted for. DESIGN: Prospective cohort study with risk factors (health behaviours (smoking, alcohol consumption, diet, and physical activity), body mass index, and biological risk markers (systolic blood pressure, triglycerides and high density lipoprotein cholesterol)) measured four times and diabetes status assessed seven times between 1991-93 and 2007-09. SETTING: Civil service departments in London (Whitehall II study). PARTICIPANTS: 7237 adults without diabetes (mean age 49.4 years; 2196 women). MAIN OUTCOME MEASURES: Incidence of type 2 diabetes and contribution of risk factors to its association with socioeconomic status. RESULTS: Over a mean follow-up of 14.2 years, 818 incident cases of diabetes were identified. Participants in the lowest occupational category had a 1.86-fold (hazard ratio 1.86, 95% confidence interval 1.48 to 2.32) greater risk of developing diabetes relative to those in the highest occupational category. Health behaviours and body mass index explained 33% (-1% to 78%) of this socioeconomic differential when risk factors were assessed at study baseline (attenuation of hazard ratio from 1.86 to 1.51), 36% (22% to 66%) when they were assessed repeatedly over the follow-up (attenuated hazard ratio 1.48), and 45% (28% to 75%) when long term exposure over the follow-up was accounted for (attenuated hazard ratio 1.41). With additional adjustment for biological risk markers, a total of 53% (29% to 88%) of the socioeconomic differential was explained (attenuated hazard ratio 1.35, 1.05 to 1.72). CONCLUSIONS: Modifiable risk factors such as health behaviours and obesity, when measured repeatedly over time, explain almost half of the social inequalities in incidence of type 2 diabetes. This is more than was seen in previous studies based on single measurement of risk factors.

Risk factor profile and management of cerebrovascular patients in the REACH Registry.

BACKGROUND: Cerebrovascular disease (CVD) is a global public health problem. CVD patients are at high risk of recurrent stroke and other atherothrombotic events. Prevalence of risk factors, comorbidities, utilization of secondary prevention therapies and adherence to guidelines all influence the recurrent event rate. We assessed these factors in 18,992 CVD patients within a worldwide registry of stable outpatients. METHODS: The Reduction of Atherothrombosis for Continued Health Registry recruited >68,000 outpatients (44 countries). The subjects were mainly recruited by general practitioners (44%) and internists (29%) if they had symptomatic CVD, coronary artery disease, peripheral arterial disease (PAD) and/or >or=3 atherothrombotic risk factors. RESULTS: The 18,992 CVD patients suffered a stroke (53.7%), transient ischemic attack (TIA) (27.7%) or both (18.5%); 40% had symptomatic atherothrombotic disease in >or=1 additional vascular beds: 36% coronary artery disease; 10% PAD and 6% both. The prevalence of risk factors at baseline was higher in the TIA subgroup than in the stroke group: treated hypertension (83.5/82.0%; p = 0.02), body mass index >or=30 (26.7/20.8%; p < 0.0001), hypercholesterolemia (65.1/52.1%; p < 0.0001), atrial fibrillation (14.7/11.9%; p < 0.0001) and carotid artery disease (42.3/29.7%; p < 0.0001). CVD patients received antiplatelet agents (81.7%), oral anticoagulants (17.3%), lipid-lowering agents (61.2%) and antihypertensives (87.9%), but guideline treatment targets were frequently not achieved (54.5% had elevated blood pressure at baseline, while 4.5% had untreated diabetes). CONCLUSIONS: A high percentage of CVD patients have additional atherothrombotic disease manifestations. The risk profile puts CVD patients, especially the TIA subgroup, at high risk for future atherothrombotic events. Undertreatment is common worldwide and adherence to guidelines needs to be enforced.

A critical evaluation of secondary cancer risk models applied to Monte Carlo dose distributions of 2-dimensional, 3-dimensional conformal and hybrid intensity-modulated radiation therapy for breast cancer.

The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.

Population specific and up to date cardiovascular risk charts can be efficiently obtained with record linkage of routine and observational data.

BACKGROUND: Only few countries have cohorts enabling specific and up-to-date cardiovascular disease (CVD) risk estimation. Individual risk assessment based on study samples that differ too much from the target population could jeopardize the benefit of risk charts in general practice. Our aim was to provide up-to-date and valid CVD risk estimation for a Swiss population using a novel record linkage approach. METHODS: Anonymous record linkage was used to follow-up (for mortality, until 2008) 9,853 men and women aged 25-74 years who participated in the Swiss MONICA (MONItoring of trends and determinants in CVD) study of 1983-92. The linkage success was 97.8%, loss to follow-up 1990-2000 was 4.7%. Based on the ESC SCORE methodology (Weibull regression), we used age, sex, blood pressure, smoking, and cholesterol to generate three models. We compared the 1) original SCORE model with a 2) recalibrated and a 3) new model using the Brier score (BS) and cross-validation. RESULTS: Based on the cross-validated BS, the new model (BS = 14107×10(-6)) was somewhat more appropriate for risk estimation than the original (BS = 14190×10(-6)) and the recalibrated (BS = 14172×10(-6)) model. Particularly at younger age, derived absolute risks were consistently lower than those from the original and the recalibrated model which was mainly due to a smaller impact of total cholesterol. CONCLUSION: Using record linkage of observational and routine data is an efficient procedure to obtain valid and up-to-date CVD risk estimates for a specific population.

Assessment of the 10-year probability of osteoporotic hip fracture combining clinical risk factors and heel bone ultrasound: the EPISEM prospective cohort of 12,958 elderly women.

This study aimed to develop a hip screening tool that combines relevant clinical risk factors (CRFs) and quantitative ultrasound (QUS) at the heel to determine the 10-yr probability of hip fractures in elderly women. The EPISEM database, comprised of approximately 13,000 women 70 yr of age, was derived from two population-based white European cohorts in France and Switzerland. All women had baseline data on CRFs and a baseline measurement of the stiffness index (SI) derived from QUS at the heel. Women were followed prospectively to identify incident fractures. Multivariate analysis was performed to determine the CRFs that contributed significantly to hip fracture risk, and these were used to generate a CRF score. Gradients of risk (GR; RR/SD change) and areas under receiver operating characteristic curves (AUC) were calculated for the CRF score, SI, and a score combining both. The 10-yr probability of hip fracture was computed for the combined model. Three hundred seven hip fractures were observed over a mean follow-up of 3.2 yr. In addition to SI, significant CRFs for hip fracture were body mass index (BMI), history of fracture, an impaired chair test, history of a recent fall, current cigarette smoking, and diabetes mellitus. The average GR for hip fracture was 2.10 per SD with the combined SI + CRF score compared with a GR of 1.77 with SI alone and of 1.52 with the CRF score alone. Thus, the use of CRFs enhanced the predictive value of SI alone. For example, in a woman 80 yr of age, the presence of two to four CRFs increased the probability of hip fracture from 16.9% to 26.6% and from 52.6% to 70.5% for SI Z-scores of +2 and -3, respectively. The combined use of CRFs and QUS SI is a promising tool to assess hip fracture probability in elderly women, especially when access to DXA is limited.

Complications of systemic juvenile idiopathic arthritis: risk factors and management recommendations.

Systemic juvenile idiopathic arthritis (SJIA) is an inflammatory condition characterized by fever, lymphadenopathy, arthritis, rash and serositis. Systemic inflammation has been associated with dysregulation of the innate immune system, suggesting that SJIA is an autoinflammatory disorder. IL-1 and IL-6 play a major role in the pathogenesis of SJIA, and treatment with IL-1 and IL-6 inhibitors has shown to be highly effective. However, complications of SJIA, including macrophage activation syndrome, limitations in functional outcome by arthritis and long-term damage from chronic inflammation, continue to be a major issue in SJIA patients' care. Translational research leading to a profound understanding of the cytokine crosstalk in SJIA and the identification of risk factors for SJIA complications will help to improve long-term outcome.

Impact of common risk factors of fibrosis progression in chronic hepatitis C.

OBJECTIVE: The natural course of chronic hepatitis C varies widely. To improve the profiling of patients at risk of developing advanced liver disease, we assessed the relative contribution of factors for liver fibrosis progression in hepatitis C. DESIGN: We analysed 1461 patients with chronic hepatitis C with an estimated date of infection and at least one liver biopsy. Risk factors for accelerated fibrosis progression rate (FPR), defined as ≥0.13 Metavir fibrosis units per year, were identified by logistic regression. Examined factors included age at infection, sex, route of infection, HCV genotype, body mass index (BMI), significant alcohol drinking (≥20 g/day for ≥5 years), HIV coinfection and diabetes. In a subgroup of 575 patients, we assessed the impact of single nucleotide polymorphisms previously associated with fibrosis progression in genome-wide association studies. Results were expressed as attributable fraction (AF) of risk for accelerated FPR. RESULTS: Age at infection (AF 28.7%), sex (AF 8.2%), route of infection (AF 16.5%) and HCV genotype (AF 7.9%) contributed to accelerated FPR in the Swiss Hepatitis C Cohort Study, whereas significant alcohol drinking, anti-HIV, diabetes and BMI did not. In genotyped patients, variants at rs9380516 (TULP1), rs738409 (PNPLA3), rs4374383 (MERTK) (AF 19.2%) and rs910049 (major histocompatibility complex region) significantly added to the risk of accelerated FPR. Results were replicated in three additional independent cohorts, and a meta-analysis confirmed the role of age at infection, sex, route of infection, HCV genotype, rs738409, rs4374383 and rs910049 in accelerating FPR. CONCLUSIONS: Most factors accelerating liver fibrosis progression in chronic hepatitis C are unmodifiable.

The Swiss cohort study on substance use risk factors : findings of two waves

Aim: To summarize published findings in peer-reviewed journals of the first two waves of the Swiss Cohort Study on Substance Use Risk Factors (C-SURF), a longitudinal study assessing risk and protective factors of 5,987 young men during the phase of emerging adulthood (20 years at baseline, followed-up 15 months later). Methods: Included were 33 studies published until November 2014 focusing on substance use. Results: Substance use in early adulthood is a prevalent and stable behavior. The 12-month prevalence of nonmedical use of prescription drugs (10.6%) lies between that of cannabis (36.4%) and other illicit drugs such as ecstasy (3.7%) and cocaine (3.2%). Although peer pressure in the form of misconduct is associated with increased substance use, other aspects such as peer involvement in social activities may have beneficial effects. Regular sport activities are associated with reduced substance use, with the exception of alcohol use. Young men are susceptible to structural conditions such as the price of alcohol beverages or the density of on-premise alcohol outlets. Particularly alcohol use in public settings such as bars, discos or in parks (compared with private settings such as the home) is associated with alcohol-related harm, including injuries or violence. Being a single parent versus nuclear family has no effect on alcohol use, but active parenting does. Besides parenting, religiousness is an important protective factor for both legal and illegal substance use. Merely informing young men about the risks of substance use may not be an effective preventive measure. At-risk users of licit and illicit substances are more health literate, e. g., for example, they seek out more information on the internet than non-at-risk-users or abstainers. Discussion: There are a number of risk and protective substance use factors, but their associations with substance use do not necessarily agree with those found outside Europe. In the United States, for example, heavy alcohol use in this age group commonly takes place in private settings, whereas in Switzerland it more often takes place in public settings. Other behaviors, such as the nonmedical use of prescription drugs, appear to be similar to those found overseas, which may show the need for targeted preventive actions. C-SURF findings point to the necessity of establishing European studies to identify factors for designing specific preventive actions.

A Meta-Analysis of Trabecular Bone Score in Fracture Risk Prediction and Its Relationship to FRAX.

Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this meta-analysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR = 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines. © 2015 American Society for Bone and Mineral Research.

Long-Term Trends of HIV Type 1 Drug Resistance Prevalence among Antiretroviral Treatment-Experienced Patients in Switzerland.

Background. Accurate quantification of the prevalence of human immunodeficiency virus type 1 (HIV-1) drug resistance in patients who are receiving antiretroviral therapy (ART) is difficult, and results from previous studies vary. We attempted to assess the prevalence and dynamics of resistance in a highly representative patient cohort from Switzerland. Methods. On the basis of genotypic resistance test results and clinical data, we grouped patients according to their risk of harboring resistant viruses. Estimates of resistance prevalence were calculated on the basis of either the proportion of individuals with a virologic failure or confirmed drug resistance (lower estimate) or the frequency-weighted average of risk group-specific probabilities for the presence of drug resistance mutations (upper estimate). Results. Lower and upper estimates of drug resistance prevalence in 8064 ART-exposed patients were 50% and 57% in 1999 and 37% and 45% in 2007, respectively. This decrease was driven by 2 mechanisms: loss to follow-up or death of high-risk patients exposed to mono- or dual-nucleoside reverse-transcriptase inhibitor therapy (lower estimates range from 72% to 75%) and continued enrollment of low-risk patients who were taking combination ART containing boosted protease inhibitors or nonnucleoside reverse-transcriptase inhibitors as first-line therapy (lower estimates range from 7% to 12%). A subset of 4184 participants (52%) had 1 study visit per year during 2002-2007. In this subset, lower and upper estimates increased from 45% to 49% and from 52% to 55%, respectively. Yearly increases in prevalence were becoming smaller in later years. Conclusions. Contrary to earlier predictions, in situations of free access to drugs, close monitoring, and rapid introduction of new potent therapies, the emergence of drug-resistant viruses can be minimized at the population level. Moreover, this study demonstrates the necessity of interpreting time trends in the context of evolving cohort populations.

Comparing impact and cost-effectiveness of primary prevention strategies for lipid-lowering.

BACKGROUND: Lipid-lowering therapy is costly but effective at reducing coronary heart disease (CHD) risk. OBJECTIVE: To assess the cost-effectiveness and public health impact of Adult Treatment Panel III (ATP III) guidelines and compare with a range of risk- and age-based alternative strategies. DESIGN: The CHD Policy Model, a Markov-type cost-effectiveness model. DATA SOURCES: National surveys (1999 to 2004), vital statistics (2000), the Framingham Heart Study (1948 to 2000), other published data, and a direct survey of statin costs (2008). TARGET POPULATION: U.S. population age 35 to 85 years. Time Horizon: 2010 to 2040. PERSPECTIVE: Health care system. INTERVENTION: Lowering of low-density lipoprotein cholesterol with HMG-CoA reductase inhibitors (statins). OUTCOME MEASURE: Incremental cost-effectiveness. RESULTS OF BASE-CASE ANALYSIS: Full adherence to ATP III primary prevention guidelines would require starting (9.7 million) or intensifying (1.4 million) statin therapy for 11.1 million adults and would prevent 20,000 myocardial infarctions and 10,000 CHD deaths per year at an annual net cost of $3.6 billion ($42,000/QALY) if low-intensity statins cost $2.11 per pill. The ATP III guidelines would be preferred over alternative strategies if society is willing to pay $50,000/QALY and statins cost $1.54 to $2.21 per pill. At higher statin costs, ATP III is not cost-effective; at lower costs, more liberal statin-prescribing strategies would be preferred; and at costs less than $0.10 per pill, treating all persons with low-density lipoprotein cholesterol levels greater than 3.4 mmol/L (>130 mg/dL) would yield net cost savings. RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to the assumptions that LDL cholesterol becomes less important as a risk factor with increasing age and that little disutility results from taking a pill every day. LIMITATION: Randomized trial evidence for statin effectiveness is not available for all subgroups. CONCLUSION: The ATP III guidelines are relatively cost-effective and would have a large public health impact if implemented fully in the United States. Alternate strategies may be preferred, however, depending on the cost of statins and how much society is willing to pay for better health outcomes. FUNDING: Flight Attendants' Medical Research Institute and the Swanson Family Fund. The Framingham Heart Study and Framingham Offspring Study are conducted and supported by the National Heart, Lung, and Blood Institute.

Quantification of clenbuterol at trace level in human urine by ultra-high pressure liquid chromatography-tandem mass spectrometry.

Clenbuterol is a β2 agonist agent with anabolic properties given by the increase in the muscular mass in parallel to the decrease of the body fat. For this reason, the use of clenbuterol is forbidden by the World Anti-Doping Agency (WADA) in the practice of sport. This compound is of particular interest for anti-doping authorities and WADA-accredited laboratories due to the recent reporting of risk of unintentional doping following the eating of meat contaminated with traces of clenbuterol in some countries. In this work, the development and the validation of an ultra-high pressure liquid chromatography coupled to electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) method for the quantification of clenbuterol in human urine is described. The analyte was extracted from urine samples by liquid-liquid extraction (LLE) in basic conditions using tert butyl-methyl ether (TBME) and analyzed by UHPLC-MS/MS with a linear gradient of acetonitrile in 9min only. The simple and rapid method presented here was validated in compliance with authority guidelines and showed a limit of quantification at 5pg/mL and a linearity range from 5pg/mL to 300pg/mL. Good trueness (85.8-105%), repeatability (5.7-10.6% RSD) and intermediate precision (5.9-14.9% RSD) results were obtained. The method was then applied to real samples from eighteen volunteers collecting urines after single oral doses administration (1, 5 and 10μg) of clenbuterol-enriched yogurts.

Efficacy of vitamin D3 as add-on therapy in patients with relapsing-remitting multiple sclerosis receiving subcutaneous interferon β-1a: a Phase II, multicenter, double-blind, randomized, placebo-controlled trial.

Recent studies have demonstrated the immunomodulatory properties of vitamin D, and vitamin D deficiency may be a risk factor for the development of MS. The risk of developing MS has, in fact, been associated with rising latitudes, past exposure to sun and serum vitamin D status. Serum 25-hydroxyvitamin D [25(OH)D] levels have also been associated with relapses and disability progression. The identification of risk factors, such as vitamin D deficiency, in MS may provide an opportunity to improve current treatment strategies, through combination therapy with established MS treatments. Accordingly, vitamin D may play a role in MS therapy. Small clinical studies of vitamin D supplementation in patients with MS have reported positive immunomodulatory effects, reduced relapse rates and a reduction in the number of gadolinium-enhancing lesions. However, large randomized clinical trials of vitamin D supplementation in patients with MS are lacking. SOLAR (Supplementation of VigantOL(®) oil versus placebo as Add-on in patients with relapsing-remitting multiple sclerosis receiving Rebif(®) treatment) is a 96-week, three-arm, multicenter, double-blind, randomized, placebo-controlled, Phase II trial (NCT01285401). SOLAR will evaluate the efficacy of vitamin D(3) as add-on therapy to subcutaneous interferon beta-1a in patients with RRMS. Recruitment began in February 2011 and is aimed to take place over 1 calendar year due to the potential influence of seasonal differences in 25(OH)D levels.

Effects of anxiety on visuospatial pattern discrimination and decision-making processes: what can we learn from brain dynamics ?

Detection and discrimination of visuospatial input involve at least extracting, selecting and encoding relevant information and decision-making processes allowing selecting a response. These two operations are altered, respectively, by attentional mechanisms that change discrimination capacities, and by beliefs concerning the likelihood of uncertain events. Information processing is tuned by the attentional level that acts like a filter on perception, while decision-making processes are weighed by subjective probability of risk. In addition, it has been shown that anxiety could affect the detection of unexpected events through the modification of the level of arousal. Consequently, purpose of this study concerns whether and how decision-making and brain dynamics are affected by anxiety. To investigate these questions, the performance of women with either a high (12) or a low (12) STAI-T (State-Trait Anxiety Inventory, Spielberger, 1983) was examined in a decision-making visuospatial task where subjects have to recognize a target visual pattern from non-target patterns. The target pattern was a schematic image of furniture arranged in such a way as to give the impression of a living room. Non-target patterns were created by either the compression or the dilatation of the distances between objects. Target and non-target patterns were always presented in the same configuration. Preliminary behavioral results show no group difference in reaction time. In addition, visuo-spatial abilities were analyzed trough the signal detection theory for quantifying perceptual decisions in the presence of uncertainty (Green and Swets, 1966). This theory treats detection of a stimulus as a decision-making process determined by the nature of the stimulus and cognitive factors. Astonishingly, no difference in d' (corresponding to the distance between means of the distributions) and c (corresponds to the likelihood ratio) indexes was observed. Comparison of Event-related potentials (ERP) reveals that brain dynamics differ according to anxiety. It shows differences in component latencies, particularly a delay in anxious subjects over posterior electrode sites. However, these differences are compensated during later components by shorter latencies in anxious subjects compared to non-anxious one. These inverted effects seem indicate that the absence of difference in reaction time rely on a compensation of attentional level that tunes cortical activation in anxious subjects, but they have to hammer away to maintain performance.