Lenalidomide maintenance after stem-cell transplantation for multiple myeloma.

BACKGROUND: High-dose chemotherapy with autologous stem-cell transplantation is a standard treatment for young patients with multiple myeloma. Residual disease is almost always present after transplantation and is responsible for relapse. This phase 3, placebo-controlled trial investigated the efficacy of lenalidomide maintenance therapy after transplantation. METHODS: We randomly assigned 614 patients younger than 65 years of age who had nonprogressive disease after first-line transplantation to maintenance treatment with either lenalidomide (10 mg per day for the first 3 months, increased to 15 mg if tolerated) or placebo until relapse. The primary end point was progression-free survival. RESULTS: Lenalidomide maintenance therapy improved median progression-free survival (41 months, vs. 23 months with placebo; hazard ratio, 0.50; P<0.001). This benefit was observed across all patient subgroups, including those based on the β(2)-microglobulin level, cytogenetic profile, and response after transplantation. With a median follow-up period of 45 months, more than 70% of patients in both groups were alive at 4 years. The rates of grade 3 or 4 peripheral neuropathy were similar in the two groups. The incidence of second primary cancers was 3.1 per 100 patient-years in the lenalidomide group versus 1.2 per 100 patient-years in the placebo group (P=0.002). Median event-free survival (with events that included second primary cancers) was significantly improved with lenalidomide (40 months, vs. 23 months with placebo; P<0.001). CONCLUSIONS: Lenalidomide maintenance after transplantation significantly prolonged progression-free and event-free survival among patients with multiple myeloma. Four years after randomization, overall survival was similar in the two study groups. (Funded by the Programme Hospitalier de Recherche Clinique and others; ClinicalTrials.gov number, NCT00430365.).

Comparing connectomes across subjects and populations at different scales.

Brain connectivity can be represented by a network that enables the comparison of the different patterns of structural and functional connectivity among individuals. In the literature, two levels of statistical analysis have been considered in comparing brain connectivity across groups and subjects: 1) the global comparison where a single measure that summarizes the information of each brain is used in a statistical test; 2) the local analysis where a single test is performed either for each node/connection which implies a multiplicity correction, or for each group of nodes/connections where each subset is summarized by one single test in order to reduce the number of tests to avoid a penalizing multiplicity correction. We comment on the different levels of analysis and present some methods that have been proposed at each scale. We highlight as well the possible factors that could influence the statistical results and the questions that have to be addressed in such an analysis.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Minimal clinically meaningful differences for the EORTC QLQ-C30 and EORTC QLQ-BN20 scales in brain cancer patients.

BACKGROUND: We aimed to determine the smallest changes in health-related quality of life (HRQoL) scores in the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire core 30 and the Brain Cancer Module (QLQ-BN20), which could be considered as clinically meaningful in brain cancer patients. Materials and methods: World Health Organisation performance status (PS) and mini-mental state examination (MMSE) were used as clinical anchors appropriate to related subscales to determine the minimal clinically important differences (MCIDs) in HRQoL change scores (range 0-100) in the QLQ-C30 and QLQ-BN20. A threshold of 0.2 standard deviation (SD) (small effect) was used to exclude anchor-based MCID estimates considered too small to inform interpretation. RESULTS: Based on PS, our findings support the following integer estimates of the MCID for improvement and deterioration, respectively: physical (6, 9), role (14, 12), and cognitive functioning (8, 8); global health status (7, 4*), fatigue (12, 9), and motor dysfunction (4*, 5). Anchoring with MMSE, cognitive functioning MCID estimates for improvement and deterioration were (11, 2*) and for communication deficit were (9, 7). Estimates with asterisks were <0.2 SD and were excluded from our MCID range of 5-14. CONCLUSION: These estimates can help clinicians evaluate changes in HRQoL over time, assess the value of a health care intervention and can be useful in determining sample sizes in designing future clinical trials.

Radiosurgery for brain metastases: specific indications for Gamma Knife in lieu of Linac in a single center using both methods

INTRODUCTION: Radiosurgery (RS) is gaining increasing acceptance in the upfront management of brain metastases (BM). It was initially used in so-called radioresistant metastases (melanoma, renal cell, sarcoma) because it allowed delivering higher dose to the tumor. Now, RS is also used for BM of other cancers. The risk of high incidence of new BM questions the need for associated whole-brain radiotherapy (WBRT). Recent evidence suggests that RS alone allows avoiding cognitive impairment related to WBRT, and the latter should be upheld for salvage therapy. Thus the increase use of RS for single and multiple BM raises new technical challenges for treatment delivery and dosimetry. We present our single institution experience focusing on the criteria that led to patients' selection for RS treatment with Gamma Knife (GK) in lieu of Linac. METHODS: Leksell Gamma Knife Perfexion (Elekta, Sweden) was installed in July 2010. Currently, the Swiss federal health care supports the costs of RS for BM with Linac but not with GK. Therefore, in our center, we always consider first the possibility to use Linac for this indication, and only select patients for GK in specific situations. All cases of BM treated with GK were retrospectively reviewed for criteria yielding to GK indication, clinical information, and treatment data. Further work in progress includes a posteriori dosimetry comparison with our Linac planning system (Brainscan V.5.3, Brainlab, Germany). RESULTS: From July 2010 to March 2012, 20 patients had RS for BM with GK (7 patients with single BM, and 13 with multiple BM). During the same period, 31 had Linac-based RS. Primary tumor was melanoma in 9, lung in 7, renal in 2, and gastrointestinal tract in 2 patients. In single BM, the reason for choosing of GK was the anatomical location close to, or in highly functional areas (1 motor cortex, 1 thalamic, 1 ventricular, 1 mesio-temporal, 3 deep cerebellar close to the brainstem), especially since most of these tumors were intended to be treated with high-dose RS (24 Gy at margin) because of their histology (3 melanomas, 1 renal cell). In multiple BM, the reason for choosing GK in relation with the anatomical location of the lesions was either technical (limitations of Linac movements, especially in lower posterior fossa locations) or closeness of multiple lesions to highly functional areas (typically, multiple posterior fossa BM close to the brainstem), precluding optimal dosimetry with Linac. Again, this was made more critical for multiple BM needing high-dose RS (6 melanoma, 2 hypernephroma). CONCLUSION: Radiosurgery for BM may represent some technical challenge in relation with the anatomical location and multiplicity of the lesions. These considerations may be accentuated for so-called radioresistant BM, when higher dose RS in needed. In our experience, Leksell Gamma Knife Perfexion proves to be useful in addressing these challenges for the treatment of BM.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Multiple processes regulate long-term population dynamics of sea urchins on Mediterranean rocky reefs

We annually monitored the abundance and size structure of herbivorous sea urchin populations (Paracentrotus lividus and Arbacia lixula) inside and outside a marine reserve in the Northwestern Mediterranean on two distinct habitats (boulders and vertical walls) over a period of 20 years, with the aim of analyzing changes at different temporal scales in relation to biotic and abiotic drivers. P. lividus exhibited significant variability in density over time on boulder bottoms but not on vertical walls, and temporal trends were not significantly different between the protection levels. Differences in densities were caused primarily by variance in recruitment, which was less pronounced inside the MPA and was correlated with adult density, indicating density-dependent recruitment under high predation pressure, as well as some positive feedback mechanisms that may facilitate higher urchin abundances despite higher predator abundance. Populations within the reserve were less variable in abundance and did not exhibit the hyper-abundances observed outside the reserve, suggesting that predation effects maybe more subtle than simply lowering the numbers of urchins in reserves. A. lixula densities were an order of magnitude lower than P. lividus densities and varied within sites and over time on boulder bottoms but did not differ between protection levels. In December 2008, an exceptionally violent storm reduced sea urchin densities drastically (by 50% to 80%) on boulder substrates, resulting in the lowest values observed over the entire study period, which remained at that level for at least two years (up to the present). Our results also showed great variability in the biological and physical processes acting at different temporal scales. This study highlights the need for appropriate temporal scales for studies to fully understand ecosystem functioning, the concepts of which are fundamental to successful conservation and management.

Reproducibility of species lists, visual cover estimates and frequency methods for recording high mountain vegetation

Question: When multiple observers record the same spatial units of alpine vegetation, how much variation is there in the records and what are the consequences of this variation for monitoring schemes to detect change? Location: One test summit in Switzerland (Alps) and one test summit in Scotland (Cairngorm Mountains). Method: Eight observers used the GLORIA protocols for species composition and visual cover estimates in percent on large summit sections (>100 m2) and species composition and frequency in nested quadrats (1 m2). Results: The multiple records from the same spatial unit for species composition and species cover showed considerable variation in the two countries. Estimates of pseudoturnover of composition and coefficients of variation of cover estimates for vascular plant species in 1m x 1m quadrats showed less variation than in previously published reports whereas our results in larger sections were broadly in line with previous reports. In Scotland, estimates for bryophytes and lichens were more variable than for vascular plants. Conclusions: Statistical power calculations indicated that, unless large numbers of plots were used, changes in cover or frequency were only likely to be detected for abundant species (exceeding 10% cover) or if relative changes were large (50% or more). Lower variation could be reached with the point methods and with larger numbers of small plots. However, as summits often strongly differ from each other, supplementary summits cannot be considered as a way of increasing statistical power without introducing a supplementary component of variance into the analysis and hence the power calculations.

Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Improved multiple-locus variable-number tandem-repeat assay for Staphylococcus aureus genotyping, providing a highly informative technique together with strong phylogenetic value.

We describe an improved multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for genotyping Staphylococcus aureus. We compare its performance to those of multilocus sequence typing (MLST) and spa typing in a survey of 309 strains. This collection includes 87 epidemic methicillin-resistant S. aureus (MRSA) strains of the Harmony collection, 75 clinical strains representing the major MLST clonal complexes (CCs) (50 methicillin-sensitive S. aureus [MSSA] and 25 MRSA), 135 nasal carriage strains (133 MSSA and 2 MRSA), and 13 published S. aureus genome sequences. The results show excellent concordance between the techniques' results and demonstrate that the discriminatory power of MLVA is higher than those of both MLST and spa typing. Two hundred forty-two genotypes are discriminated with 14 VNTR loci (diversity index, 0.9965; 95% confidence interval, 0.9947 to 0.9984). Using a cutoff value of 45%, 21 clusters are observed, corresponding to the CCs previously defined by MLST. The variability of the different tandem repeats allows epidemiological studies, as well as follow-up of the evolution of CCs and the identification of potential ancestors. The 14 loci can conveniently be analyzed in two steps, based upon a first-line simplified assay comprising a subset of 10 loci (panel 1) and a second subset of 4 loci (panel 2) that provides higher resolution when needed. In conclusion, the MLVA scheme proposed here, in combination with available on-line genotyping databases (including http://mlva.u-psud.fr/), multiplexing, and automatic sizing, can provide a basis for almost-real-time large-scale population monitoring of S. aureus.

Evaluation of Appropriate Maintenance, Repair and Rehabilitation Methods for Iowa Bridges, TR-429, 2003

Most states, including Iowa, have a significant number of substandard bridges. This number will increase significantly unless some type of preventative maintenance is employed. Both the Iowa Department of Transportation and Iowa counties have successfully employed numerous maintenance, repair and rehabilitation (MR&R) strategies for correcting various types of deficiencies. However, successfully employed MR&R procedures are often not systematically documented or defined for those involved in bridge maintenance. This study addressed the need for a standard bridge MR&R manual for Iowa with emphasis for secondary road applications. As part of the study, bridge MR&R activities that are relevant to the state of Iowa have been systematically categorized into a manual, in a standardized format. Where pertinent, design guidelines have been presented. Material presented in this manual is divided into two major categories: 1) Repair and Rehabilitation of Bridge Superstructure Components, and 2) Repair and Rehabilitation of Bridge Substructure Components. There are multiple subcategories within both major categories that provide detailed information. Some of the detailed information includes step-by-step procedures for accomplishing MR&R activities, material specifications and detailed drawings where available. The source of information contained in the manual is public domain technical literature and information provided by Iowa County Engineers. A questionnaire was sent to all 99 counties in Iowa to solicit information and the research team personally solicited input from many Iowa counties as a follow-up to the questionnaire.

Retrofit Methods for Distortion Cracking Problems in Plate Girder Bridges, TR-436, 2003

This report is formatted to independently present four individual investigations related to similar web gap fatigue problems. Multiple steel girder bridges commonly exhibit fatigue cracking due to out-of-plane displacement of the web near the diaphragm connections. This fatigue-prone web gap area is typically located in negative moment regions of the girders where the diaphragm stiffener is not attached to the top flange. In the past, the Iowa Department of Transportation has attempted to stop fatigue crack propagation in these steel girder bridges by drilling holes at the crack tips. Other nondestructive retrofits have been tried; in a particular case on a two-girder bridge with floor beams, angles were bolted between the stiffener and top flange. The bolted angle retrofit has failed in the past and may not be a viable solution for diaphragm bridges. The drilled hole retrofit is often only a temporary solution, so a more permanent and effective retrofit is required. A new field retrofit has been developed that involves loosening the bolts in the connection between the diaphragm and the girders. Research on the retrofit has been initiated; however, no long-term studies of the effects of bolt loosening have been performed. The intent of this research is to study the short-term effects of the bolt loosening retrofit on I-beam and channel diaphragm bridges. The research also addressed the development of a continuous remote monitoring system to investigate the bolt loosening retrofit on an X-type diaphragm bridge over a number of months, ensuring that the measured strain and displacement reductions are not affected by time and continuous traffic loading on the bridge. The testing for the first three investigations is based on instrumentation of web gaps in a negative moment region on Iowa Department of Transportation bridges with I-beam, channel, and X-type diaphragms. One bridge of each type was instrumented with strain gages and deflection transducers. Field tests, using loaded trucks of known weight and configuration, were conducted on the bridges with the bolts in the tight condition and after implementing the bolt loosening retrofit to measure the effects of loosening the diaphragm bolts. Long-term data were also collected on the X-diaphragm bridge by a data acquisition system that collected the data continuously under ambient truck loading. The collected data were retrievable by an off-site modem connection to the remote data acquisition system. The data collection features and ruggedness of this system for remote bridge monitoring make it viable as a pilot system for future monitoring projects in Iowa. Results indicate that loosening the diaphragm bolts reduces strain and out-of-plane displacement in the web gap, and that the reduction is not affected over time by traffic or environmental loading on the bridge. Reducing the strain in the web gap allows the bridge to support more cycles of loading before experiencing fatigue, thus increase the service life of the bridge. Two-girder floor beam bridges may also exhibit fatigue cracking in girder webs.

Advanced MRI unravels the nature of tissue alterations in early multiple sclerosis.

INTRODUCTION: In patients with multiple sclerosis (MS), conventional magnetic resonance imaging (MRI) provides only limited insights into the nature of brain damage with modest clinic-radiological correlation. In this study, we applied recent advances in MRI techniques to study brain microstructural alterations in early relapsing-remitting MS (RRMS) patients with minor deficits. Further, we investigated the potential use of advanced MRI to predict functional performances in these patients. METHODS: Brain relaxometry (T1, T2, T2*) and magnetization transfer MRI were performed at 3T in 36 RRMS patients and 18 healthy controls (HC). Multicontrast analysis was used to assess for microstructural alterations in normal-appearing (NA) tissue and lesions. A generalized linear model was computed to predict clinical performance in patients using multicontrast MRI data, conventional MRI measures as well as demographic and behavioral data as covariates. RESULTS: Quantitative T2 and T2* relaxometry were significantly increased in temporal normal-appearing white matter (NAWM) of patients compared to HC, indicating subtle microedema (P = 0.03 and 0.004). Furthermore, significant T1 and magnetization transfer ratio (MTR) variations in lesions (mean T1 z-score: 4.42 and mean MTR z-score: -4.09) suggested substantial tissue loss. Combinations of multicontrast and conventional MRI data significantly predicted cognitive fatigue (P = 0.01, Adj-R (2) = 0.4), attention (P = 0.0005, Adj-R (2) = 0.6), and disability (P = 0.03, Adj-R (2) = 0.4). CONCLUSION: Advanced MRI techniques at 3T, unraveled the nature of brain tissue damage in early MS and substantially improved clinical-radiological correlations in patients with minor deficits, as compared to conventional measures of disease.

The 2005 Pakistan earthquake revisited: Methods for integrated landslide assessment

Five years after the 2005 Pakistan earthquake that triggered multiple mass movements, landslides continue to pose a threat to the population of Azad Kashmir, especially during heavy monsoon rains. The thousands of landslides that were triggered by the 7.6 magnitude earthquake in 2005 were not just due to a natural phenomenon but largely induced by human activities, namely, road building, grazing, and deforestation. The damage caused by the landslides in the study area (381 km2) is estimated at 3.6 times the annual public works budget of Azad Kashmir for 2005 of US$ 1 million. In addition to human suffering, this cost constitutes a significant economic setback to the region that could have been reduced through improved land use and risk management. This article describes interdisciplinary research conducted 18 months after the earthquake to provide a more systemic approach to understanding risks posed by landslides, including the physical, environmental, and human contexts. The goal of this research is twofold: to present empirical data on the social, geological, and environmental contexts in which widespread landslides occurred following the 2005 earthquake; and, second, to describe straightforward methods that can be used for integrated landslide risk assessments in data-poor environments. The article analyzes limitations of the methodologies and challenges for conducting interdisciplinary research that integrates both social and physical data. This research concludes that reducing landslide risk is ultimately a management issue, based in land use decisions and governance.