The effect of interferon beta-1b treatment on MRI measures of cerebral atrophy in secondary progressive multiple sclerosis.

The recently completed European trial of interferon beta-1b (IFN beta -1b) in patients with secondary progressive multiple sclerosis (SP multiple sclerosis) has given an opportunity to assess the impact of treatment on cerebral atrophy using serial MRI. Unenhanced T-1-weighted brain imaging was acquired in a subgroup of 95 patients from five of the European centres; imaging was performed at 6-month intervals from month 0 to month 36. A blinded observer measured cerebral volume on four contiguous 5 mm cerebral hemisphere slices at each time point, using an algorithm with a high level of reproducibility and automation. There was a significant and progressive reduction in cerebral volume in both placebo and treated groups, with a mean reduction of 3.9 and 2.9%, respectively, by month 36 (P = 0.34 between groups). Exploratory subgroup analyses indicated that patients without gadolinium (Gd) enhancement at the baseline had a greater reduction of cerebral volume in the placebo group (mean reduction at month 36: placebo 5.1%, IFN beta -1b 1.8%, P < 0.05) whereas those with Gd-enhancing lesions showed a trend to greater reduction of cerebral volume if the patient was on IFN<beta>-1b (placebo 2.6%, IFN beta -1b, 3.7%; P > 0.05). These results are consistent with ongoing tissue loss in both arms of this study of secondary progressive multiple sclerosis. This finding is concordant with previous observations that disease progression, although delayed, is not halted by IFN beta. The different pattern seen in patients with and without baseline gadolinium enhancement suggests that part of the cerebral volume reduction observed in IFN beta -treated patients may be due to the anti-inflammatory/antioedematous effect of the drug. Longer periods of observation and larger groups of patients may be needed to detect the effects of treatment on cerebral atrophy in this population of patients with advanced disease

Research Priorities for Neglected Infectious Diseases in Latin America and the Caribbean Region

Dujardin, J. C. et al. 5 p.-1 tab.Global priorities for research in neglected infectious diseases (NIDs) can be assessed in different ways, but it is important to realize that regional priorities may significantly differ one from another. The region of Latin America and the Caribbean (LAC) is—along with Africa and Asia—more affected by NIDs than other regions of the world. Some of the Latin American NIDs are common to other continents, while others are very specific or disproportionately affect the Latin American region [1– 3] (Table 1). Because of its huge ecological diversity, ongoing environmental changes, and massive migrations, LAC is also a catalyst for the (re-)emergence and spreading of NIDs, both inside and outside the subcontinent. Following a colloquium on NIDs in LAC held in Lima, Peru, between 12 and 14 November 2009, a thematic workshop was organized with the support of the European Commission (EC). It involved 29 scientists (16 from the Americas, two from the Democratic Republic of Congo and India, respectively, and nine from Europe) working on different NIDs and representing several research areas from basic to applied. This report summarizes the consensus comments of the expert group after oral and written consultation. It is envisaged that this document should stimulate a debate within the scientific community and serve as a recommendation for future actions by international or regional funding agencies in the area of NIDs in LACThis work was supported by the Directorate-General for Development Cooperation of the Belgian Government (framework agreement 03, project 95502) and the European CommissionPeer reviewe

A refined molecular taxonomy of breast cancer

The current histoclinical breast cancer classification is simple but imprecise. Several molecular classifications of breast cancers based on expression profiling have been proposed as alternatives. However, their reliability and clinical utility have been repeatedly questioned, notably because most of them were derived from relatively small initial patient populations. We analyzed the transcriptomes of 537 breast tumors using three unsupervised classification methods. A core subset of 355 tumors was assigned to six clusters by all three methods. These six subgroups overlapped with previously defined molecular classes of breast cancer, but also showed important differences, notably the absence of an ERBB2 subgroup and the division of the large luminal ER+ group into four subgroups, two of them being highly proliferative. Of the six subgroups, four were ER+/PR+/AR+, one was ER−/PR−/AR+ and one was triple negative (AR−/ER−/PR−). ERBB2-amplified tumors were split between the ER−/PR−/AR+ subgroup and the highly proliferative ER+ LumC subgroup. Importantly, each of these six molecular subgroups showed specific copy-number alterations. Gene expression changes were correlated to specific signaling pathways. Each of these six subgroups showed very significant differences in tumor grade, metastatic sites, relapse-free survival or response to chemotherapy. All these findings were validated on large external datasets including more than 3000 tumors. Our data thus indicate that these six molecular subgroups represent well-defined clinico-biological entities of breast cancer. Their identification should facilitate the detection of novel prognostic factors or therapeutical targets in breast cancer

Assessing treatment outcomes in multiple sclerosis trials and in the clinical setting

Increasing numbers of drugs are being developed for the treatment of multiple sclerosis (MS). Measurement of relevant outcomes is key for assessing the efficacy of new drugs in clinical trials and for monitoring responses to disease-modifying drugs in individual patients. Most outcomes used in trial and clinical settings reflect either clinical or neuroimaging aspects of MS (such as relapse and accrual of disability or the presence of visible inflammation and brain tissue loss, respectively). However, most measures employed in clinical trials to assess treatment effects are not used in routine practice. In clinical trials, the appropriate choice of outcome measures is crucial because the results determine whether a drug is considered effective and therefore worthy of further development; in the clinic, outcome measures can guide treatment decisions, such as choosing a first-line disease-modifying drug or escalating to second-line treatment. This Review discusses clinical, neuroimaging and composite outcome measures for MS, including patient-reported outcome measures, used in both trials and the clinical setting. Its aim is to help clinicians and researchers navigate through the multiple options encountered when choosing an outcome measure. Barriers and limitations that need to be overcome to translate trial outcome measures into the clinical setting are also discussed

The developing role of magnetic resonance imaging in Phase III multiple sclerosis treatment trials: Technical considerations and results of a large multicentre study

Magnetic resonance imaging (MRI) provides a powerful tool for both monitoring disease evolution in multiple sclerosis (MS) and assessing the efficacy of therapeutic intervention. A monthly MRI protocol is now routinely used to screen potential MS therapies, with the effect of treatment on MR activity providing the primary outcome measure. Phase III definitive MS treatment trials also generally incorporate an MR protocol. However, in view of the uncertain relationship between MR measures and clinical outcome, the primary endpoints of phase III studies are currently based on clinical indices. The first chapter of this thesis provides a critical review of the available MRI tools for monitoring disease progression. The limited extent of the relationship between clinical outcome and standard MR measures is stressed, and potential factors contributing to this dissociation are reviewed. The thesis is then presented in three parts, the first of which looks at recent developments in MRI acquisition and analysis methodology. In particular, the utility of three established techniques for measuring brain lesion volume (global thresholding, manual outlining and contouring) is examined. Work is presented that suggests a limited role for global thresholding-based lesion segmentation in serial MS studies. A comparison of a semi-automated local thresholding algorithm (contouring) with the currently recognised gold standard segmentation method (manual outlining) is presented, highlighting the advantages in terms of precision and reliability with the contour technique. The effect of slice thickness on MS lesion detection and brain lesion volume is examined, in order to define an optimal slice thickness for MS treatment trials. The second part examines the relationship between different MRI parameters and assesses the strength of clinical/MRI correlations in a substantial cohort of patients. The extent to which change in annual T2 lesion volume is dictated by ongoing inflammatory activity (assessed with monthly gadolinium enhanced imaging) is investigated using this cohort. Furthermore, the relationship between standard clinical indices of disease activity and progression on the one hand, and MR activity on monthly and annual imaging on the other, is defined. Using an extension of this database, power calculations are presented based on an annual imaging protocol where the change in T2 lesion volume provides the outcome measure. The aim is to guide efficient trial design by providing sample sizes for a typical multicentre parallel group placebo-controlled design. The results suggest that annual T2 lesion volume quantification provides a powerful and robust tool for monitoring the effect of treatment, and demonstrate that the current practice of including several hundred patients in an MR protocol produces substantial overpowering. Part Three describes the MRI results of a phase III trial using interferon beta-1b in patients with secondary progressive MS. The relationships between clinical and MR indices are also presented, and their implications for future trial design are discussed