Prediction of hemodynamic severity of coarctation by magnetic resonance imaging.

A published formula containing minimal aortic cross-sectional area and the flow deceleration pattern in the descending aorta obtained by cardiovascular magnetic resonance predicts significant coarctation of the aorta (CoA). However, the existing formula is complicated to use in clinical practice and has not been externally validated. Consequently, its clinical utility has been limited. The aim of this study was to derive a simple and clinically practical algorithm to predict severe CoA from data obtained by cardiovascular magnetic resonance. Seventy-nine consecutive patients who underwent cardiovascular magnetic resonance and cardiac catheterization for the evaluation of native or recurrent CoA at Children's Hospital Boston (n = 30) and the University of California, San Francisco (n = 49), were retrospectively reviewed. The published formula derived from data obtained at Children's Hospital Boston was first validated from data obtained at the University of California, San Francisco. Next, pooled data from the 2 institutions were analyzed, and a refined model was created using logistic regression methods. Finally, recursive partitioning was used to develop a clinically practical prediction tree to predict transcatheter systolic pressure gradient ≥ 20 mm Hg. Severe CoA was present in 48 patients (61%). Indexed minimal aortic cross-sectional area and heart rate-corrected flow deceleration time in the descending aorta were independent predictors of CoA gradient ≥ 20 mm Hg (p <0.01 for both). A prediction tree combining these variables reached a sensitivity and specificity of 90% and 76%, respectively. In conclusion, the presented prediction tree on the basis of cutoff values is easy to use and may help guide the management of patients investigated for CoA.

The management of brain metastases

Brain metastases occur in 20-50% of NSCLC and 50-80% of SCLC. In this review, we will look at evidence-based medicine data and give some perspectives on the management of BM. We will address the problems of multiple BM, single BM and prophylactic cranial irradiation. Recursive Partitioning Analysis (RPA) is a powerful prognostic tool to facilitate treatment decisions. Dealing with multiple BM, the use of corticosteroids was established more than 40 years ago by a unique randomized trial (RCT). Palliative effect is high (_80%) as well as side-effects. Whole brain radiotherapy (WBRT) was evaluated in many RCTs with a high (60-90%) response rate; several RT regimes are equivalent, but very high dose per fraction should be avoided. In multiple BM from SCLC, the effect of WBRT is comparable to that in NSCLC but chemotherapy (CXT) although advocated is probably less effective than RT. Single BM from NSCLC occurs in 30% of all BM cases; several prognostic classifications including RPA are very useful. Several options are available in single BM: WBRT, surgery (SX), radiosurgery (RS) or any combination of these. All were studied in RCTs and will be reviewed: the addition of WBRT to SX or RS gives a better neurological tumour control, has little or no impact on survival, and may be more toxic. However omitting WBRT after SX alone gives a higher risk of cerebro-spinal fluid dissemination. Prophylactic cranial irradiation (PCI) has a major role in SCLC. In limited disease, meta-analyses have shown a positive impact of PCI in the decrease of brain relapse and in survival improvement, especially for patients in complete remission. Surprisingly, this has been recently confirmed also in extensive disease. Experience with PCI for NSCLC is still limited, but RCT suggest a reduction of BM with no impact on survival. Toxicity of PCI is a matter of debate, as neurological or neuro-cognitive impairment is already present prior to PCI in almost half of patients. However RT toxicity is probably related to total dose and dose per fraction. Perspectives : Future research should concentrate on : 1) combined modalities in multiple BM. 2) Exploration of treatments in oligo-metastases. 3) Further exploration of PCI in NSCLC. 4) Exploration of new, toxicity-sparing radiotherapy techniques (IMRT, Tomotherapy etc).

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Impact of Prophylactic Cranial Irradiation Timing on Brain Relapse Rates in Patients With Stage IIIB Non-Small-Cell Lung Carcinoma Treated With Two Different Chemoradiotherapy Regimens.

PURPOSE: To retrospectively assess the influence of prophylactic cranial irradiation (PCI) timing on brain relapse rates in patients treated with two different chemoradiotherapy (CRT) regimens for Stage IIIB non-small-cell lung cancer (NSCLC). METHODS AND MATERIALS: A cohort of 134 patients, with Stage IIIB NSCLC in recursive partitioning analysis Group 1, was treated with PCI (30 Gy at 2 Gy/fr) following one of two CRT regimens. Regimen 1 (n = 58) consisted of three cycles of induction chemotherapy (ICT) followed by concurrent CRT (C-CRT). Regimen 2 (n = 76) consisted of immediate C-CRT during thoracic radiotherapy. RESULTS: At a median follow-up of 27.6 months (range, 7.2-40.4), 65 patients were alive. Median, progression-free, and brain metastasis-free survival (BMFS) times for the whole study cohort were 23.4, 15.4, and 23.0 months, respectively. Median survival time and the 3-year survival rate for regimens 1 and 2 were 19.3 vs. 26.1 months (p = 0.001) and 14.4% vs. 34.4% (p < .001), respectively. Median time from the initiation of primary treatment to PCI was 123.2 (range, 97-161) and 63.4 (range, 55-74) days for regimens 1 and 2, respectively (p < 0.001). Overall, 11 (8.2%) patients developed brain metastasis (BM) during the follow-up period: 8 (13.8%) in regimen 1 and 3 (3.9%) in regimen 2 (p = 0.03). Only 3 (2.2%) patients developed BM at the site of first failure, and for 2 of them, it was also the sole site of recurrence. Median BMFS for regimens 1 and 2 were 17.4 (13.5-21.3) vs. 26.0 (22.9-29.1 months), respectively (p < 0.001). CONCLUSION: These results suggest that in Stage IIIB NSCLC patients treated with PCI, lower BM incidence and longer survival rates result from immediate C-CRT rather than ITC-first regimens. This indicates the benefit of earlier PCI use without delay because of induction protocols.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.

A combined molecular clinical predictor of survival validated with the rtog-0525 cohort

For glioblastoma (GBM), survival classification has primarily relied on clinical criteria, exemplified by the Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA). We sought to improve tumor classification by combining tumor biomarkers with the clinical RPA data. To accomplish this, we first developed 4 molecular biomarkers derived from gene expression profiling, a glioma CpG island methylator phenotype, a novel MGMT promoter methylation assay, and IDH1 mutations. A molecular predictor (MP) model was created with these 4 biomarkers on a training set of 220 retrospectively collected archival GBMtumors. ThisMPwas further combined with RPA classification to develop a molecular-clinical predictor (MCP). The median survivals for the combined, 4-class MCP were 65 months, 31 months, 13 months, and 9 months, which was significantly improved when compared with the RPA alone. The MCP was then applied to 725 samples from the RTOG-0525 cohort, showing median survival for each risk group of NR, 26 months, 16 months, and 11 months. The MCP was significantly improved over the RPA at outcome prediction in the RTOG 0525 cohort with a 33%increase in explained variation with respect to survival, validating the result obtained in the training set. To illustrate the benefit of the MCP for patient stratification, we examined progression-free survival (PFS) for patients receiving standard-dose temozolomide (SD-TMZ) vs. dose-dense TMZ (DD-TMZ) in RPA and MCP risk groups. A significant difference between DD-TMZ and SD-TMZ was observed in the poorest surviving MCP risk group with a median PFS of 6 months vs. 3 months (p ¼ 0.048, log-rank test). This difference was not seen using the RPA classification alone. In summary, we have developed a combined molecular-clinical predictor that appears to improve outcome prediction when compared with clinical variables alone. This MCP may serve to better identify patients requiring intensive treatments beyond the standard of care.

BrainCheck - a very brief tool to detect incipient cognitive decline: optimized case-finding combining patient- and informant-based data.

INTRODUCTION: Optimal identification of subtle cognitive impairment in the primary care setting requires a very brief tool combining (a) patients' subjective impairments, (b) cognitive testing, and (c) information from informants. The present study developed a new, very quick and easily administered case-finding tool combining these assessments ('BrainCheck') and tested the feasibility and validity of this instrument in two independent studies. METHODS: We developed a case-finding tool comprised of patient-directed (a) questions about memory and depression and (b) clock drawing, and (c) the informant-directed 7-item version of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). Feasibility study: 52 general practitioners rated the feasibility and acceptance of the patient-directed tool. Validation study: An independent group of 288 Memory Clinic patients (mean ± SD age = 76.6 ± 7.9, education = 12.0 ± 2.6; 53.8% female) with diagnoses of mild cognitive impairment (n = 80), probable Alzheimer's disease (n = 185), or major depression (n = 23) and 126 demographically matched, cognitively healthy volunteer participants (age = 75.2 ± 8.8, education = 12.5 ± 2.7; 40% female) partook. All patient and healthy control participants were administered the patient-directed tool, and informants of 113 patient and 70 healthy control participants completed the very short IQCODE. RESULTS: Feasibility study: General practitioners rated the patient-directed tool as highly feasible and acceptable. Validation study: A Classification and Regression Tree analysis generated an algorithm to categorize patient-directed data which resulted in a correct classification rate (CCR) of 81.2% (sensitivity = 83.0%, specificity = 79.4%). Critically, the CCR of the combined patient- and informant-directed instruments (BrainCheck) reached nearly 90% (that is 89.4%; sensitivity = 97.4%, specificity = 81.6%). CONCLUSION: A new and very brief instrument for general practitioners, 'BrainCheck', combined three sources of information deemed critical for effective case-finding (that is, patients' subject impairments, cognitive testing, informant information) and resulted in a nearly 90% CCR. Thus, it provides a very efficient and valid tool to aid general practitioners in deciding whether patients with suspected cognitive impairments should be further evaluated or not ('watchful waiting').

Phylogenetic structures of the Holarctic Sorex araneus group and its relationships with S-samniticus, as inferred from mtDNA sequences

The shrews of the Sorex araneus group, characterized by the sexual chromosome complex XY1, Y2 have been intensively studied by morphological, karyotypical, and biochemical analyses. Nevertheless, the phylogenetic relationships among the species belonging to the araneus complex are still under debate, as different approaches gave often contradictory results. In this paper, partial nucleotide sequences of the mitochondrial DNA cytochrome b gene (1011 bp) were determined for 6 species of the araneus group from Eurasia and North America. We also included in the data set the sequences of Sorex samniticus, whose relationships with the araneus group remain controversial. Three other species representing two major karyological groups were also examined. Both parsimony and distance trees strongly support the monophyly of the araneus group. Sorex sumniticus is significantly more closely related to the araneus complex than to the other species included in the analysis. Based on the branching pattern within the araneus group, an attempt has been made to reconstruct the colonization history of the Holarctic region.

Development and evaluation of antibody-MHC/peptide conjugates as a new form of cancer immunotherapy

Summary One of the major goals of cancer immunotherapy is the induction of a specific and effective antitumor cytotoxic T lymphocyte (CTL) response. However, the downregulation of Class I Major Histocompatibility Complexes (MHC) expression and the low level of tumor peptide presentation on tumor cell surface, ás well as the low immunogenicity of tumor specific antigens, limit the effectiveness of anti-tumor CTL responses. On the other hand, monoclonal antibodies, which bind with high affinity to tumor cell surface markers, are powerful tumor targeting tools. However, their capacity to .kill cancer cells is limited and mAb cancer treatments usually require the addition of different form of chemotherapy. The new cancer immunotherapy strategy described herein combines the advantage of the high tumor targeting capacity of monoclonal antibodies (mAb) with the powerful cytotoxicity of CD8 T lymphocytes directed against highly antigenic peptide-MHC complexes. Monoclonal antibody Fab fragments directed against a cell surface tumor associated antigen (TAA) are chemically coupled to soluble MHC class I complexes carrying a highly antigenic peptide. Antibody guided targeting and oligomerization of numerous antigenic class IMHC/peptide complexes on tumor cell surfaces can redirect the cytotoxicity of peptide-specific CD8 T cells towards target cancer cells. After the description of the production of murine anti-tumor xMHC/peptide conjugates in the first part of this thesis, the therapeutic potential of such conjugates were sequentially investigated in different syngeneic tumor mouse models. As a first proof of principle, transgenic OT-1 mice and later CEA transgenic C57BL/6 (B6) mice, adoptively transferred with OT-1 spleen cells and immunized with ovalbumin, were used as a model of high frequency of ova peptide specific T cells. In these mice, growth inhibition and regression of palpable colon carcinoma expressing CEA, were obtained by systemic injection of anti-CEA Fab/H-2Kb/ova peptide conjugates. Next, LCMV virus and influenza virus infection of B6 mice were used as viral models to redirect natural antiviral CTL responses to tumors via conjugates loaded with viral peptides. We showed that in mice infected with the LCMV virus, subcutaneous CEA-expressing tumor cells were inhibited by the H2Db/GP33 restricted anti-viral CTL response when preincubated before grafting with anti-CEA Fab-H-2Db/GP33 peptide conjugates. In mice infected with the influenza virus, lung metastases expressing the HER2 antigen were inhibited by the H-2Db/NP366 restricted CTLs response when preincubated before injection with anti-Her2 Fab-H-2Db/NP366 peptide conjugates. In the last chapter, the stability of the peptide in the anti-CEA Fab-H-2Db/GP33 conjugates was improved by the covalent photocross-link of the GP33 peptide in the H-2Db MHC groove. Thus, LCMV immune mice could reject CEA expressing tumors when treated with systemic injections of anti-CEA FabH-2Db/GP33 cross-linked conjugates. These results are encouraging for the potential application of this strategy in clinic. Such conjugates could be used alone in patients boosted by the relevant virus, or used in combination with existing T cell based ìmmunotherapy. Résumé Une des principales approches utilisées dans l'immunothérapie contre le cancer consiste en l'induction d'une réponse T cytotoxique (CTL) spécifiquement dirigée contre la tumeur. Cependant, le faible niveau d'expression des complexes majeurs d'histocompatibilité de classe I (CMH I) et de présentation des peptides tumoraux à la surface des cellules cancéreuses ainsi que la faible immunogenicité des antigens tumoraux, limitent l'efficacité de la réponse CTL. D'autre part,. l'injection d'anticorps monoclonaux (mAb), se liant avec une haute affinité aux marqueurs de surface des cellules tumorales, a fourni des résultats cliniques encourageant. Cependant l'efficacité de ces mAbs contre des tumeur solides reste limitée et necessite souvent l'addition de chimiotherapie. La nouvelle stratégie thérapeutique décrite dans ce travail associe le fort pouvoir de localisation des anticorps monoclonaux et le fort pouvoir cytotoxique des lymphocytes T CD8+. Des fragments Fab d'anticorps monoclonaux, dirigés contre des antigènes surexprimés à la surface de cellules tumorales, ont été chimiquement couplés à des CMH I solubles, portant un peptide fortement antigénique. Le ciblage et l'oligomérisation à la surface des cellules tumorales de nombreux CMH I présentant un peptide antigénique, va réorienter la cytotoxicité des cellules T CD8+ spécifiques du peptide présenté, vers les cellules tumorales cibles. Après une description de la production de conjugé anti-tumeur x CMH Upeptide dans la première partie de cette thèse, le potentiel thérapeutique de tels conjugés a été successivement étudiés in vivo dans différents modèles de tumeur syngénéiques. Tout d'abord, des souris OT-1 transgéniques, puis des souris C57BL/6 (B6) transférées avec des cellules de rate OT-1 puis immunisées avec l'ovalbumine, ont été employées comme modèle de haute fréquence de cellules T CD8+ spécifiques du peptide ova. Chez ces souris, l'inhibition de la croissance et la régression de nodules palpables de carcinomes exprimant l'antigène caccino embryonaire (ACE), ont été obtenues par l'injection systémique de conjugés anti-ACE Fab/H-2Kb/ova. Par la suite, l'infection de souris B6 par le virus LCMV et par le virus de la grippe, ont été utilisés comme modèles viraux pour redirigées des réponses anti-virales naturelles vers les tumeurs, en utilisant des conjugés chargés avec des peptides viraux. Nous avons montré que .chez les souris infectées par le LCMV, la croissance de carcinome sous-cutané est empêchée par la réponse anti-virale, spécifique du complexe H2Db/GP33, lorsque les cellules tumorales greffées sont pré-incubées avec des conjugés anti-CEA Fab-H-2Db/GP33. Dans le cas de souris infectées par le virus de la grippe, la métastatisation de mélanomes pulmonaires exprimant l'antigène HER-2 est inhibée par la réponse anti-virale spécifique du complexe H-2Db/NP366, après pré-incubation des cellules tumorales avec des conjugés anti-Her2 FabxH-2Db/NP366. Dans le dernier chapitre, la liaison covalente du peptide GP33 dans le complexe H-2Db a amélioré la stabilité des conjugés correspondants et a permis le traitement systémique de souris greffées avec des tumeurs exprimant l'ACE et infectées par le LCMV. L'ensemble de ces résultats sont encourageant pour l'application de cette strategie en clinique. De tels conjugués pourraient être employés seuls ou en combinaison avec des protocols d'immunisation peptidique anti-tumoral. Résumé pour un large public Dans les pays industrialisés, le cancer se situe au deuxième rang des causes de mortalité après les maladies cardiovasculaires. Les principaux traitement de nombreux cancers sont la chirurgie, en association avec la radiothérapie et la chimiothérapie. L'immunothérapie est l'une des nouvelles approches mises en oeuvre pour la lutte contre le cancer. Elle peut être humorale, et s'appuyer alors sur la perfusion d'anticorps monoclonaux dirigés contre des antigènes tumoraux, par exemple les anticorps dirigés contre les protéines oncogéniques Her-2/neu dans le cancer du sein. Ces anticorps ont le grand avantage de spécifiquement se localiser à la tumeur et d'induire la lyse ou d'inhiber la proliferation des cellules tumorales exprimant l'antigène. Certains sont utilisés en clinique pour le traitement de lymphomes, de carcinomes de l'ovaire et du sein ou encore de carcinomes metastatiques du côlon. Cependant l'efficacité de ces anticorps contre des tumeurs solides reste limitée et les traitements exigent souvent d'être combiner avec de la chimiothérapie. L'immunothérapie spécifique peut également être cellulaire et reposer sur une démarche de type vaccinal, consistant à générer des lymphocytes T cytotoxiques (cytotoxic T lymphocytes :CTL) capables de détruire spécifiquement les cellules malignes. Pour obtenir une réponse lymphocytaire T cytotoxique antitumorale, la cellule T doit reconnaître un antigène associé à la tumeur, présenté sous forme de peptide dans un complexe majeur d'histocompatibilité de classe I. Or les cellules tumorales ne presentent pas efficacement les peptides antigèniques, car elles se caractérisent par une diminution ou une absence d'expression des antigènes d'histocompatibilité de classe I, des molécules d'adhésion et des cytokines costimulatrices, et par une faible expression des antigènes associés aux tumeurs. C'est en partie pourquoi, malgré l'induction de fortes réponses CTL specifiquement dirigés contre des antigens tumoraux, les régressions tumorales obtenus grace à ces vaccinations sont relativement rares. Alors que chez les personnes atteintes du cancer on observe l'instauration d'une tolérance immunitaire vis-à-vis de la tumeur, à l'inverse, notre systeme immunitaire reste parfaitement capable de combattre des infection virales classiques, tels que la grippe, qui font aussi appel à une réponse T cytotoxique. Notre groupe de recherche a donc eu l'idee de développer une nouvelle approche thérapeutique où une réponse immunitaire anti-virale très efficace serait redirigée vers les tumeurs par des anticorps monoclonaux. Concrètement, nous avons chimiquement couplés des fragments d'anticorps monoclonaux dirigés contre des antigènes surexprimés à la surface de cellules tumorales, à des CMH I portant un peptide viral antigénique. Les cellules tumorales, ciblées par le fragment anticorps et couvertes d' antigènes viraux présentés par des molécules de CMH I, peuvent ainsi tromper les lymphocytes cytotoxiques anti-viraux qui vont détruire les cellules tumorales comme si elles étaient infectées par le virus. Suite à des résultats prometteurs obtenus in vitro avec différents conjugués anticorps-CMH humain de type HLA.A2/peptide Flu, le but du projet était de tester in vivo des conjugués anticorps-CMH I murins sur des modèles expérimentaux de souris. Tout d'abord, des souris transgéniques pour un recepteur T specifique du peptide ova, puis des transferts adoptifs de ces cellules T specifiques dans des souris immunocompétentes, ont été choisi comme modèle de haute fréquence des cellules T spécifiques, et ont permi de valider le principe de la strategie in vivo. Puis, deux modèles viraux ont été elaboré avec le virus LCMV et le virus Influenza, pour réorienter des réponses antivirales naturelles vers les tumeurs grâce à des conjugés chargés avec des peptides viraux. Nous avons montré la grande capacité de nos conjugués à rediriger des réponses cytotoxiques vers les tumeurs et inhiber la croissance de tumeurs syngénéiques sous cutanés et pulmonaires. Ces résultats d'inhibition tumorales obtenus dans des souris immunocompétentes, grâce à l'injection de conjugués anticorps xCMH/peptide et réorientant deux réponses antivirales différentes vers deux modèles tumoraux syngeneiques, sont encourageant pour l'application de cette nouvelle stratégie en clinique.

Whole brain radiotherapy with a conformational external beam radiation boost for lung cancer patients with 1-3 brain metastasis: a multi institutional study.

BACKGROUND: To determine the outcome of patients with brain metastasis (BM) from lung cancer treated with an external beam radiotherapy boost (RTB) after whole brain radiotherapy (WBRT). METHODS: A total of 53 BM patients with lung cancer were treated sequentially with WBRT and RTB between 1996 and 2008 according to our institutional protocol. Mean age was 58.8 years. The median KPS was 90. Median recursive partitioning analysis (RPA) and graded prognostic assessment (GPA) grouping were 2 and 2.5, respectively. Surgery was performed on 38 (71%) patients. The median number of BM was 1 (range, 1-3). Median WBRT and RTB combined dose was 39 Gy (range, 37.5-54). Median follow-up was 12.0 months. RESULTS: During the period of follow-up, 37 (70%) patients died. The median overall survival (OS) was 14.5 months. Only 13 patients failed in the brain. The majority of patients (n = 29) failed distantly. The 1-year OS, -local control, extracranial failure rates were 61.2%, 75.2% and 60.8%, respectively. On univariate analysis, improved OS was found to be significantly associated with total dose (< or = 39 Gy vs. > 39 Gy; p < 0.01), age < 65 (p < 0.01), absence of extracranial metastasis (p < 0.01), GPA > or = 2.5 (p = 0.01), KPS > or = 90 (p = 0.01), and RPA < 2 (p = 0.04). On multivariate analysis, total dose (p < 0.01) and the absence of extracranial metastasis (p = 0.03) retained statistical significance. CONCLUSIONS: The majority of lung cancer patients treated with WBRT and RTB progressed extracranially. There might be a subgroup of younger patients with good performance status and no extracranial disease who may benefit from dose escalation after WBRT to the metastatic site.

Pretherapeutic gamma-glutamyltransferase is an independent prognostic factor for patients with renal cell carcinoma.

BACKGROUND: Gamma-glutamyltransferase (GGT) regulates apoptotic balance and promotes cancer progression and invasion. Higher pretherapeutic GGT serum levels have been associated with worse outcomes in various malignancies, but there are no data for renal cell carcinoma (RCC). METHODS: Pretherapeutic GGT serum levels and clinicopathological parameters were retrospectively evaluated in 921 consecutive RCC patients treated with nephrectomy at a single institution between 1998 and 2013. Gamma-glutamyltransferase was analysed as continuous and categorical variable. Associations with RCC-specific survival were assessed with Cox proportional hazards models. Discrimination was measured with the C-index. Decision-curve analysis was used to evaluate the clinical net benefit. The median postoperative follow-up was 45 months. RESULTS: Median pretherapeutic serum GGT level was 25 U l(-1). Gamma-glutamyltransferase levels increased with advancing T (P<0.001), N (P=0.006) and M stages (P<0.001), higher grades (P<0.001), and presence of tumour necrosis (P<0.001). An increase of GGT by 10 U l(-1) was associated with an increase in the risk of death from RCC by 4% (HR 1.04, P<0.001). Based on recursive partitioning-based survival tree analysis, we defined four prognostic categories of GGT: normal low (<17.5 U l(-1)), normal high (17.5 to <34.5 U l(-1)), elevated (34.5 to <181.5 U l(-1)), and highly elevated (⩾181.5 U l(-1)). In multivariable analyses that adjusted for the effect of standard features, both continuously and categorically coded GGT were independent prognostic factors. Adding GGT to a model that included standard features increased the discrimination by 0.9% to 1.8% and improved the clinical net benefit. CONCLUSIONS: Pretherapeutic serum GGT is a novel and independent prognostic factor for patients with RCC. Stratifying patients into prognostic subgroups according to GGT may be used for patient counselling, tailoring surveillance, individualised treatment planning, and clinical trial design.

Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071-22072 study): a multicentre, randomised, open-label, phase 3 trial.

BACKGROUND: Cilengitide is a selective αvβ3 and αvβ5 integrin inhibitor. Data from phase 2 trials suggest that it has antitumour activity as a single agent in recurrent glioblastoma and in combination with standard temozolomide chemoradiotherapy in newly diagnosed glioblastoma (particularly in tumours with methylated MGMT promoter). We aimed to assess cilengitide combined with temozolomide chemoradiotherapy in patients with newly diagnosed glioblastoma with methylated MGMT promoter. METHODS: In this multicentre, open-label, phase 3 study, we investigated the efficacy of cilengitide in patients from 146 study sites in 25 countries. Eligible patients (newly diagnosed, histologically proven supratentorial glioblastoma, methylated MGMT promoter, and age ≥18 years) were stratified for prognostic Radiation Therapy Oncology Group recursive partitioning analysis class and geographic region and centrally randomised in a 1:1 ratio with interactive voice response system to receive temozolomide chemoradiotherapy with cilengitide 2000 mg intravenously twice weekly (cilengitide group) or temozolomide chemoradiotherapy alone (control group). Patients and investigators were unmasked to treatment allocation. Maintenance temozolomide was given for up to six cycles, and cilengitide was given for up to 18 months or until disease progression or unacceptable toxic effects. The primary endpoint was overall survival. We analysed survival outcomes by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00689221. FINDINGS: Overall, 3471 patients were screened. Of these patients, 3060 had tumour MGMT status tested; 926 patients had a methylated MGMT promoter, and 545 were randomly assigned to the cilengitide (n=272) or control groups (n=273) between Oct 31, 2008, and May 12, 2011. Median overall survival was 26·3 months (95% CI 23·8-28·8) in the cilengitide group and 26·3 months (23·9-34·7) in the control group (hazard ratio 1·02, 95% CI 0·81-1·29, p=0·86). None of the predefined clinical subgroups showed a benefit from cilengitide. We noted no overall additional toxic effects with cilengitide treatment. The most commonly reported adverse events of grade 3 or worse in the safety population were lymphopenia (31 [12%] in the cilengitide group vs 26 [10%] in the control group), thrombocytopenia (28 [11%] vs 46 [18%]), neutropenia (19 [7%] vs 24 [9%]), leucopenia (18 [7%] vs 20 [8%]), and convulsion (14 [5%] vs 15 [6%]). INTERPRETATION: The addition of cilengitide to temozolomide chemoradiotherapy did not improve outcomes; cilengitide will not be further developed as an anticancer drug. Nevertheless, integrins remain a potential treatment target for glioblastoma. FUNDING: Merck KGaA, Darmstadt, Germany.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.