260 resultados para value-estimate


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An antagonistic effect of voriconazole on the fungicidal activity of sequential doses of amphotericin B has previously been demonstrated in Candida albicans strains susceptible to voriconazole. Because treatment failure and the need to switch to other antifungals are expected to occur more often in infections that are caused by resistant strains, it was of interest to study whether the antagonistic effect was still seen in Candida strains with reduced susceptibility to voriconazole. With the hypothesis that antagonism will not occur in voriconazole-resistant strains, C. albicans strains with characterized mechanisms of resistance against voriconazole, as well as Candida glabrata and Candida krusei strains with differences in their degrees of susceptibility to voriconazole were exposed to voriconazole or amphotericin B alone, to both drugs simultaneously, or to voriconazole followed by amphotericin B in an in vitro kinetic model. Amphotericin B administered alone or simultaneously with voriconazole resulted in fungicidal activity. When amphotericin B was administered after voriconazole, its activity was reduced (median reduction, 61%; range, 9 to 94%). Levels of voriconazole-dependent inhibition of amphotericin B activity differed significantly among the strains but were not correlated with the MIC values (correlation coefficient, -0.19; P = 0.65). Inhibition was found in C. albicans strains with increases in CDR1 and CDR2 expression but not in the strain with an increase in MDR1 expression. In summary, decreased susceptibility to voriconazole does not abolish voriconazole-dependent inhibition of the fungicidal activity of amphotericin B in voriconazole-resistant Candida strains. The degree of interaction could not be predicted by the MIC value alone.

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BACKGROUND: Allogeneic stem cell transplantation is usually considered the only curative treatment option for patients with advanced or transformed myelodysplastic syndromes in complete remission, but post-remission chemotherapy and autologous stem cell transplantation are potential alternatives, especially in patients over 45 years old. DESIGN AND METHODS: We evaluated, after intensive anti-leukemic remission-induction chemotherapy, the impact of the availability of an HLA-identical sibling donor on an intention-to treat basis. Additionally, all patients without a sibling donor in complete remission after the first consolidation course were randomized to either autologous peripheral blood stem cell transplantation or a second consolidation course consisting of high-dose cytarabine. RESULTS: The 4-year survival of the 341 evaluable patients was 28%. After achieving complete remission, the 4-year survival rates of patients under 55 years old with or without a donor were 54% and 41%, respectively, with an adjusted hazard ratio of 0.81 (95% confidence interval [95% CI], 0.49-1.35) for survival and of 0.67 (95% CI, 0.42-1.06) for disease-free survival. In patients with intermediate/high risk cytogenetic abnormalities the hazard ratio in multivariate analysis was 0.58 (99% CI, 0.22-1.50) (P=0.14) for survival and 0.46 (99% CI, 0.22-1.50) for disease-free survival (P=0.03). In contrast, in patients with low risk cytogenetic characteristics the hazard ratio for survival was 1.17 (99% CI, 0.40-3.42) and that for disease-free survival was 1.02 (99% CI, 0.40-2.56). The 4-year survival of the 65 patients randomized to autologous peripheral blood stem cell transplantation or a second consolidation course of high-dose cytarabine was 37% and 27%, respectively. The hazard ratio in multivariate analysis was 1.22 (95% CI, 0.65-2.27) for survival and 1.02 (95% CI, 0.56-1.85) for disease-free survival. CONCLUSIONS: Patients with a donor and candidates for allogeneic stem cell transplantation in first complete remission may have a better disease-free survival than those without a donor in case of myelodysplastic syndromes with intermediate/high-risk cytogenetics. Autologous peripheral blood stem cell transplantation does not provide longer survival than intensive chemotherapy.

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BACKGROUND: VeriStrat(®) is a serum proteomic test used to determine whether patients with advanced non-small cell lung cancer (NSCLC) who have already received chemotherapy are likely to have good or poor outcomes from treatment with gefitinib or erlotinib. The main objective of our retrospective study was to evaluate the role of VS as a marker of overall survival (OS) in patients treated with erlotinib and bevacizumab in the first line. PATIENTS AND METHODS: Patients were pooled from two phase II trials (SAKK19/05 and NTR528). For survival analyses, a log-rank test was used to determine if there was a statistically significant difference between groups. The hazard ratio (HR) of any separation was assessed using Cox proportional hazards models. RESULTS: 117 patients were analyzed. VeriStrat classified patients into two groups which had a statistically significant difference in duration of OS (p=0.0027, HR=0.480, 95% confidence interval: 0.294-0.784). CONCLUSION: VeriStrat has a prognostic role in patients with advanced, nonsquamous NSCLC treated with erlotinib and bevacizumab in the first line. Further work is needed to study the predictive role of VeriStrat for erlotinib and bevacizumab in chemotherapy-untreated patients.

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The aims of this study were twofold. The first was to investigate the diagnostic performance of two biochemical markers, procalcitonin (PCT) and lipopolysaccharide-binding protein (LBP), considering each individually and then combined, for the postmortem diagnosis of sepsis. We also tested the usefulness of pericardial fluid for postmortem LBP determination. Two study groups were formed, a sepsis-related fatalities group of 12 cases and a control group of 30 cases. Postmortem native CT scans, autopsy, histology, neuropathology, and toxicology as well as other postmortem biochemical investigations were performed in all cases. Microbiological investigations were also carried out in the septic group. Postmortem serum PCT and LBP levels differed between the two groups. Both biomarkers, individually considered, allowed septic states to be diagnosed, whereas increases in both postmortem serum PCT and LBP levels were only observed in cases of sepsis. Similarly, normal PCT and LBP values in postmortem serum were identified only in non-septic cases. Pericardial fluid LBP levels do not correlate with the presence of underlying septic states. No relationship was observed between postmortem serum and pericardial fluid LBP levels in either septic or non-septic groups, or between pericardial fluid PCT and LBP levels.

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PURPOSE: To identify cancer-linked genes, Sjöblom et al. and Wood et al. performed a genome-wide mutation screening in human breast and colorectal cancers. 140 CAN-genes were found in breast cancer, which in turn contained overall 334 mutations. These mutations could prove useful for diagnostic and therapeutic purposes. METHODS: We used a MALDI-TOF MS 40-plex assay for testing 40 loci within 21 high-ranking breast cancer CAN-genes. To confirm mutations, we performed single-plex assays and sequencing. RESULTS: In general, the mutation rate of the analyzed loci in our sample cohort was very low. No mutation from the 40 loci analyzed could be found in the 6 cell lines. In tissue samples, a single breast cancer tissue sample showed heterozygosity at locus c.5834G>A within the ZFYVE26 gene (Zinc finger FYVE domain-containing gene 26). CONCLUSIONS: Sjöblom et al./Wood et al. already showed that the vast majority of CAN-genes are mutated at very low frequency. Due to the fact that we only found one mutation in our cohort, we therefore assume that at the selected loci, mutations might be low-frequency events and therefore, more rarely detectable. However, further evaluation of the CAN-gene mutations in larger cohorts should be the aim of further studies.

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Tumor necrosis factor (TNF) alpha, interleukins (IL) 2, 4, 6, and 10, and IgG oligoclonal bands (IgG OB) in vitro production was assessed, after whole-blood stimulation with lipopolysaccharide or concanavalin A, in 61 patients presenting with relapsing-remitting, relapsing-progressive, or chronic progressive multiple sclerosis. Multiple sclerosis patients were receiving no treatment or azathioprine (AZA), cyclosporin, cyclophosphamide, subcutaneous interferon (IFN) beta 1 a, or corticosteroids (CST). Statistical correlations significantly showed that: (a) AZA lowers TNF-alpha (P = 0.002) and increases IL-4 production (P = 0.0024), and IFN-beta 1 a increases TNF-alpha and decreases IL-4 levels; (b) CST has a negative effect on TNF-alpha, IL-6, and IL-4 synthesis; and (c) AZA, IFN-beta 1 a, and CST diminish IgG OB synthesis (P = 0.001). Although our study of the dynamics of TNF-alpha, IL-2, IL-4, IL-6, and IL-10 in vitro production generally found no statistically significant correlations (partly explained by the limited number of values in the various groups), IL-6 was shown to drop during the periods surrounding relapse (P = 0.05) in the absence of treatment, while TNF-alpha (P = 0.04) and IL-6 (P < 0.05) dropped before exacerbation in the presence of AZA. In vitro production of TNF-alpha was closely and positively correlated with that of IL-6, independently of clinical features. The enhanced production of IL-10 detected before or at relapse with AZA and IFN-beta 1 a (trends) may interfere with initiation of the immune reaction and with the development of new CNS lesions. Some discrepancies with previously published results stress the difficulties in studying the state of stimulation of different populations of leukocytes by using a variety of in vitro stimuli and in establishing a correlation between mRNA studies and the amount of final or active protein produced.

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This thesis focuses on theoretical asset pricing models and their empirical applications. I aim to investigate the following noteworthy problems: i) if the relationship between asset prices and investors' propensities to gamble and to fear disaster is time varying, ii) if the conflicting evidence for the firm and market level skewness can be explained by downside risk, Hi) if costly learning drives liquidity risk. Moreover, empirical tests support the above assumptions and provide novel findings in asset pricing, investment decisions, and firms' funding liquidity. The first chapter considers a partial equilibrium model where investors have heterogeneous propensities to gamble and fear disaster. Skewness preference represents the desire to gamble, while kurtosis aversion represents fear of extreme returns. Using US data from 1988 to 2012, my model demonstrates that in bad times, risk aversion is higher, more people fear disaster, and fewer people gamble, in contrast to good times. This leads to a new empirical finding: gambling preference has a greater impact on asset prices during market downturns than during booms. The second chapter consists of two essays. The first essay introduces a foramula based on conditional CAPM for decomposing the market skewness. We find that the major market upward and downward movements can be well preadicted by the asymmetric comovement of betas, which is characterized by an indicator called "Systematic Downside Risk" (SDR). We find that SDR can efafectively forecast future stock market movements and we obtain out-of-sample R-squares (compared with a strategy using historical mean) of more than 2.27% with monthly data. The second essay reconciles a well-known empirical fact: aggregating positively skewed firm returns leads to negatively skewed market return. We reconcile this fact through firms' greater response to negative maraket news than positive market news. We also propose several market return predictors, such as downside idiosyncratic skewness. The third chapter studies the funding liquidity risk based on a general equialibrium model which features two agents: one entrepreneur and one external investor. Only the investor needs to acquire information to estimate the unobservable fundamentals driving the economic outputs. The novelty is that information acquisition is more costly in bad times than in good times, i.e. counter-cyclical information cost, as supported by previous empirical evidence. Later we show that liquidity risks are principally driven by costly learning. Résumé Cette thèse présente des modèles théoriques dévaluation des actifs et leurs applications empiriques. Mon objectif est d'étudier les problèmes suivants: la relation entre l'évaluation des actifs et les tendances des investisseurs à parier et à crainadre le désastre varie selon le temps ; les indications contraires pour l'entreprise et l'asymétrie des niveaux de marché peuvent être expliquées par les risques de perte en cas de baisse; l'apprentissage coûteux augmente le risque de liquidité. En outre, des tests empiriques confirment les suppositions ci-dessus et fournissent de nouvelles découvertes en ce qui concerne l'évaluation des actifs, les décisions relatives aux investissements et la liquidité de financement des entreprises. Le premier chapitre examine un modèle d'équilibre où les investisseurs ont des tendances hétérogènes à parier et à craindre le désastre. La préférence asymétrique représente le désir de parier, alors que le kurtosis d'aversion représente la crainte du désastre. En utilisant les données des Etats-Unis de 1988 à 2012, mon modèle démontre que dans les mauvaises périodes, l'aversion du risque est plus grande, plus de gens craignent le désastre et moins de gens parient, conatrairement aux bonnes périodes. Ceci mène à une nouvelle découverte empirique: la préférence relative au pari a un plus grand impact sur les évaluations des actifs durant les ralentissements de marché que durant les booms économiques. Exploitant uniquement cette relation générera un revenu excédentaire annuel de 7,74% qui n'est pas expliqué par les modèles factoriels populaires. Le second chapitre comprend deux essais. Le premier essai introduit une foramule base sur le CAPM conditionnel pour décomposer l'asymétrie du marché. Nous avons découvert que les mouvements de hausses et de baisses majeures du marché peuvent être prédits par les mouvements communs des bêtas. Un inadicateur appelé Systematic Downside Risk, SDR (risque de ralentissement systématique) est créé pour caractériser cette asymétrie dans les mouvements communs des bêtas. Nous avons découvert que le risque de ralentissement systématique peut prévoir les prochains mouvements des marchés boursiers de manière efficace, et nous obtenons des carrés R hors échantillon (comparés avec une stratégie utilisant des moyens historiques) de plus de 2,272% avec des données mensuelles. Un investisseur qui évalue le marché en utilisant le risque de ralentissement systématique aurait obtenu une forte hausse du ratio de 0,206. Le second essai fait cadrer un fait empirique bien connu dans l'asymétrie des niveaux de march et d'entreprise, le total des revenus des entreprises positiveament asymétriques conduit à un revenu de marché négativement asymétrique. Nous décomposons l'asymétrie des revenus du marché au niveau de l'entreprise et faisons cadrer ce fait par une plus grande réaction des entreprises aux nouvelles négatives du marché qu'aux nouvelles positives du marché. Cette décomposition révélé plusieurs variables de revenus de marché efficaces tels que l'asymétrie caractéristique pondérée par la volatilité ainsi que l'asymétrie caractéristique de ralentissement. Le troisième chapitre fournit une nouvelle base théorique pour les problèmes de liquidité qui varient selon le temps au sein d'un environnement de marché incomplet. Nous proposons un modèle d'équilibre général avec deux agents: un entrepreneur et un investisseur externe. Seul l'investisseur a besoin de connaitre le véritable état de l'entreprise, par conséquent, les informations de paiement coutent de l'argent. La nouveauté est que l'acquisition de l'information coute plus cher durant les mauvaises périodes que durant les bonnes périodes, comme cela a été confirmé par de précédentes expériences. Lorsque la récession comamence, l'apprentissage coûteux fait augmenter les primes de liquidité causant un problème d'évaporation de liquidité, comme cela a été aussi confirmé par de précédentes expériences.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

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Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

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Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003-2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, "real" observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered. Copyright (C) 2011 John Wiley & Sons, Ltd.