Health-related quality-of-life in patients with newly diagnosed multiple myeloma in the FIRST trial: lenalidomide plus low-dose dexamethasone versus melphalan, prednisone, thalidomide.

We compared the health-related quality-of-life of patients with newly diagnosed multiple myeloma aged over 65 years or transplant-ineligible in the pivotal, phase III FIRST trial. Patients received: i) continuous lenalidomide and low-dose dexamethasone until disease progression; ii) fixed cycles of lenalidomide and low-dose dexamethasone for 18 months; or iii) fixed cycles of melphalan, prednisone, thalidomide for 18 months. Data were collected using the validated questionnaires (QLQ-MY20, QLQ-C30, and EQ-5D). The analysis focused on the EQ-5D utility value and six domains pre-selected for their perceived clinical relevance. Lenalidomide and low-dose dexamethasone, and melphalan, prednisone, thalidomide improved patients' health-related quality-of-life from baseline over the duration of the study across all pre-selected domains of the QLQ-C30 and EQ-5D. In the QLQ-MY20, lenalidomide and low-dose dexamethasone demonstrated a significantly greater reduction in the Disease Symptoms domain compared with melphalan, prednisone, thalidomide at Month 3, and significantly lower scores for QLQ-MY20 Side Effects of Treatment at all post-baseline assessments except Month 18. Linear mixed-model repeated-measures analyses confirmed the results observed in the cross-sectional analysis. Continuous lenalidomide and low-dose dexamethasone delays disease progression versus melphalan, prednisone, thalidomide and has been associated with a clinically meaningful improvement in health-related quality-of-life. These results further establish continuous lenalidomide and low-dose dexamethasone as a new standard of care for initial therapy of myeloma by demonstrating superior health-related quality-of-life during treatment, compared with melphalan, prednisone, thalidomide.

A phase IIa randomized clinical study testing GNbAC1, a humanized monoclonal antibody against the envelope protein of multiple sclerosis associated endogenous retrovirus in multiple sclerosis patients - A twelve month follow-up.

GNbAC1 is a humanized monoclonal antibody targeting MSRV-Env, an endogenous retroviral protein, which is expressed in multiple sclerosis (MS) lesions, is pro-inflammatory and inhibits oligodendrocyte precursor cell differentiation. This paper describes the open-label extension up to 12months of a trial testing GNbAC1 in 10 MS patients at 2 and 6mg/kg. The primary objective was to assess GNbAC1 safety, and other objectives were pharmacokinetic and pharmacodynamic assessments. During the extended study, no safety issues occurred in the 8 remaining patients. No anti-GNbAC1 antibodies were detected. GNbAC1 appears well tolerated.

Multicontrast connectometry: A new tool to assess cerebellum alterations in early relapsing-remitting multiple sclerosis.

BACKGROUND: Cerebellar pathology occurs in late multiple sclerosis (MS) but little is known about cerebellar changes during early disease stages. In this study, we propose a new multicontrast "connectometry" approach to assess the structural and functional integrity of cerebellar networks and connectivity in early MS. METHODS: We used diffusion spectrum and resting-state functional MRI (rs-fMRI) to establish the structural and functional cerebellar connectomes in 28 early relapsing-remitting MS patients and 16 healthy controls (HC). We performed multicontrast "connectometry" by quantifying multiple MRI parameters along the structural tracts (generalized fractional anisotropy-GFA, T1/T2 relaxation times and magnetization transfer ratio) and functional connectivity measures. Subsequently, we assessed multivariate differences in local connections and network properties between MS and HC subjects; finally, we correlated detected alterations with lesion load, disease duration, and clinical scores. RESULTS: In MS patients, a subset of structural connections showed quantitative MRI changes suggesting loss of axonal microstructure and integrity (increased T1 and decreased GFA, P < 0.05). These alterations highly correlated with motor, memory and attention in patients, but were independent of cerebellar lesion load and disease duration. Neither network organization nor rs-fMRI abnormalities were observed at this early stage. CONCLUSION: Multicontrast cerebellar connectometry revealed subtle cerebellar alterations in MS patients, which were independent of conventional disease markers and highly correlated with patient function. Future work should assess the prognostic value of the observed damage. Hum Brain Mapp 36:1609-1619, 2015. © 2014 Wiley Periodicals, Inc.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

STRATEGIC-1: A multiple-lines, randomized, open-label GERCOR phase III study in patients with unresectable wild-type RAS metastatic colorectal cancer.

BACKGROUND: The management of unresectable metastatic colorectal cancer (mCRC) is a comprehensive treatment strategy involving several lines of therapy, maintenance, salvage surgery, and treatment-free intervals. Besides chemotherapy (fluoropyrimidine, oxaliplatin, irinotecan), molecular-targeted agents such as anti-angiogenic agents (bevacizumab, aflibercept, regorafenib) and anti-epidermal growth factor receptor agents (cetuximab, panitumumab) have become available. Ultimately, given the increasing cost of new active compounds, new strategy trials are needed to define the optimal use and the best sequencing of these agents. Such new clinical trials require alternative endpoints that can capture the effect of several treatment lines and be measured earlier than overall survival to help shorten the duration and reduce the size and cost of trials. METHODS/DESIGN: STRATEGIC-1 is an international, open-label, randomized, multicenter phase III trial designed to determine an optimally personalized treatment sequence of the available treatment modalities in patients with unresectable RAS wild-type mCRC. Two standard treatment strategies are compared: first-line FOLFIRI-cetuximab, followed by oxaliplatin-based second-line chemotherapy with bevacizumab (Arm A) vs. first-line OPTIMOX-bevacizumab, followed by irinotecan-based second-line chemotherapy with bevacizumab, and by an anti-epidermal growth factor receptor monoclonal antibody with or without irinotecan as third-line treatment (Arm B). The primary endpoint is duration of disease control. A total of 500 patients will be randomized in a 1:1 ratio to one of the two treatment strategies. DISCUSSION: The STRATEGIC-1 trial is designed to give global information on the therapeutic sequences in patients with unresectable RAS wild-type mCRC that in turn is likely to have a significant impact on the management of this patient population. The trial is open for inclusion since August 2013. TRIAL REGISTRATION: STRATEGIC-1 is registered at Clinicaltrials.gov: NCT01910610, 23 July, 2013. STRATEGIC-1 is registered at EudraCT-No.: 2013-001928-19, 25 April, 2013.

Interleukin-22 is increased in multiple sclerosis patients and targets astrocytes.

BACKGROUND: Increasing evidences link T helper 17 (Th17) cells with multiple sclerosis (MS). In this context, interleukin-22 (IL-22), a Th17-linked cytokine, has been implicated in blood brain barrier breakdown and lymphocyte infiltration. Furthermore, polymorphism between MS patients and controls has been recently described in the gene coding for IL-22 binding protein (IL-22BP). Here, we aimed to better characterize IL-22 in the context of MS. METHODS: IL-22 and IL-22BP expressions were assessed by ELISA and qPCR in the following compartments of MS patients and control subjects: (1) the serum, (2) the cerebrospinal fluid, and (3) immune cells of peripheral blood. Identification of the IL-22 receptor subunit, IL-22R1, was performed by immunohistochemistry and immunofluorescence in human brain tissues and human primary astrocytes. The role of IL-22 on human primary astrocytes was evaluated using 7-AAD and annexin V, markers of cell viability and apoptosis, respectively. RESULTS: In a cohort of 141 MS patients and healthy control (HC) subjects, we found that serum levels of IL-22 were significantly higher in relapsing MS patients than in HC but also remitting and progressive MS patients. Monocytes and monocyte-derived dendritic cells contained an enhanced expression of mRNA coding for IL-22BP as compared to HC. Using immunohistochemistry and confocal microscopy, we found that IL-22 and its receptor were detected on astrocytes of brain tissues from both control subjects and MS patients, although in the latter, the expression was higher around blood vessels and in MS plaques. Cytometry-based functional assays revealed that addition of IL-22 improved the survival of human primary astrocytes. Furthermore, tumor necrosis factor α-treated astrocytes had a better long-term survival capacity upon IL-22 co-treatment. This protective effect of IL-22 seemed to be conferred, at least partially, by a decreased apoptosis. CONCLUSIONS: We show that (1) there is a dysregulation in the expression of IL-22 and its antagonist, IL-22BP, in MS patients, (2) IL-22 targets specifically astrocytes in the human brain, and (3) this cytokine confers an increased survival of the latter cells.

Patients' satisfaction with community treatment: a pilot cross-sectional survey adopting multiple perspectives.

ACCESSIBLE SUMMARY: Patients' satisfaction is scarcely studied within the context of community treatment for adolescents. Thus, this study adopts a multiple perspective on patients' satisfaction (including service users as well as staff members). The results highlighted that all informants (patients, foster carers in foster homes and professional caregivers from community treatment teams) perceived the patients to be satisfied, with foster carers reporting the highest patient satisfaction rate. Considering the patient satisfaction rate from multiple perspectives provides complementary understandings. Clinical outcomes and, specifically, a reduction in emotional difficulties were related to patient's satisfaction, but only from the patients' perspective. ABSTRACT: Community treatment (CT) teams in Switzerland provide care to patients who are unable to use regular child and adolescent mental health services (i.e. inpatient and outpatients facilities). No study has considered patients' self-rated satisfaction alongside with staff members' perspectives on patient satisfaction. Thus, adopting a cross-sectional survey design, we collected patients' satisfaction using the Client Satisfaction Questionnaire (CSQ-8), rated by multiple informants (patients, foster carers in foster homes and professional caregivers from CT teams). Professional caregivers assessed clinical outcomes using the Health of the Nation Outcome Scale for Children and Adolescents. The results indicated that all informants were satisfied with the community treatment teams. The satisfaction scores were not correlated across informants; however, the alleviation of emotional symptoms was correlated with patients' satisfaction. This study indicated that the use of a combined approach including the views of service users and professionals gives important complementary information. Finally, in our sample, lower emotional symptoms were linked to enhanced patient satisfaction. This study demonstrated the importance of considering multiple perspectives to obtain the most accurate picture of patients' satisfaction. Second, focusing on the reduction of emotional symptoms might lead to a higher degree of patients' satisfaction.

Patients' satisfaction with community treatment: a pilot cross-sectional survey adopting multiple perspectives.

ACCESSIBLE SUMMARY: Patients' satisfaction is scarcely studied within the context of community treatment for adolescents. Thus, this study adopts a multiple perspective on patients' satisfaction (including service users as well as staff members). The results highlighted that all informants (patients, foster carers in foster homes and professional caregivers from community treatment teams) perceived the patients to be satisfied, with foster carers reporting the highest patient satisfaction rate. Considering the patient satisfaction rate from multiple perspectives provides complementary understandings. Clinical outcomes and, specifically, a reduction in emotional difficulties were related to patient's satisfaction, but only from the patients' perspective. ABSTRACT: Community treatment (CT) teams in Switzerland provide care to patients who are unable to use regular child and adolescent mental health services (i.e. inpatient and outpatients facilities). No study has considered patients' self-rated satisfaction alongside with staff members' perspectives on patient satisfaction. Thus, adopting a cross-sectional survey design, we collected patients' satisfaction using the Client Satisfaction Questionnaire (CSQ-8), rated by multiple informants (patients, foster carers in foster homes and professional caregivers from CT teams). Professional caregivers assessed clinical outcomes using the Health of the Nation Outcome Scale for Children and Adolescents. The results indicated that all informants were satisfied with the community treatment teams. The satisfaction scores were not correlated across informants; however, the alleviation of emotional symptoms was correlated with patients' satisfaction. This study indicated that the use of a combined approach including the views of service users and professionals gives important complementary information. Finally, in our sample, lower emotional symptoms were linked to enhanced patient satisfaction. This study demonstrated the importance of considering multiple perspectives to obtain the most accurate picture of patients' satisfaction. Second, focusing on the reduction of emotional symptoms might lead to a higher degree of patients' satisfaction.