Treatment response and remission in a double-blind, randomized, head-to-head study of lisdexamfetamine dimesylate and atomoxetine in children and adolescents with attention-deficit hyperactivity disorder

The Author(s) 2014. This article is published with open access at Springerlink.com Objectives A secondary objective of this head-to-head study of lisdexamfetamine dimesylate (LDX) and ato-moxetine (ATX) was to assess treatment response rates in children and adolescents with attention-deficit hyperactiv-ity disorder (ADHD) and an inadequate response to methylphenidate (MPH). The primary efficacy and safety outcomes of the study, SPD489-317 (ClinicalTrials.gov NCT01106430), have been published previously. Methods In this 9-week, double-blind, active-controlled study, patients aged 6–17 years with a previous inadequate response to MPH were randomized (1:1) to dose-optimized LDX (30, 50 or 70 mg/day) or ATX (patients \70 kg: 0.5–1.2 mg/kg/day, not to exceed 1.4 mg/kg/day; patients C70 kg: 40, 80 or 100 mg/day). Treatment response was a secondary efficacy outcome and was predefined as a reduction from baseline in ADHD Rating Scale IV (ADHD-RS-IV) total score of at least 25, 30 or 50 %. Sustained response was predefined as a reduction from baseline in ADHD-RS-IV total score (C25, C30 or C50 %) or a Clinical Global Impressions (CGI)–Improvement (CGI–I) score of 1 or 2 throughout weeks 4–9. CGI– Severity (CGI–S) scores were also assessed, as an indicator of remission. Results A total of 267 patients were enrolled (LDX, n = 133; ATX, n = 134) and 200 completed the study (LDX, n = 99; ATX, n = 101). By week 9, significantly (p \ 0.01) greater proportions of patients receiving LDX than ATX met the response criteria of a reduction from baseline in ADHD-RS-IV total score of at least 25 % (90.5 vs. 76.7 %), 30 % (88.1 vs. 73.7 %) or 50 % (73.0 vs. 50.4 %). Sustained response rates were also signifi-cantly (p \ 0.05) higher among LDX-treated patient

Benign Orbital Tumors with Bone Destruction in Children

Purpose: To present rare benign orbital tumors with bone destruction in children who could not be diagnosed presurgically and may simulate malignant ones. Methods: A retrospective review of cases. Clinical, operative and pathological records in all children with a diagnosis of benign orbital tumors who showed remarkable bone destruction at a tertiary Ophthalmic Center in China between Jan 1, 2000 and Dec 31, 2009 were reviewed. All patients had definitive histopathologic diagnosis. Results: Eight patients with benign orbital tumors showed obvious bone destruction, including six cases of eosinophilic granuloma, one case of leiomyoma and one case of primary orbital intraosseous hemangioma. Among them, three patients were females and five patients were males. Tumors were unilateral in all cases, with both the right and left side affected equally. Age ranged from 3 to 7 years (mean 4.1 years). Symptom duration ranged from 1 to 5 weeks (mean 4.8 weeks). Eyelid swelling and palpable mass were the most common complaint. There was no evidence for multifocal involvement in cases with eosinophilic granuloma. Among six patients with eosinophilic granuloma, two were treated with low dose radiation (10 Gy), three received systemic corticosteroid and one was periodically observed only after incisional biopsy or subtotal curettage. There was no postoperative therapeutic intervention in the two patients with leiomyoma and intraosseous hemangioma. All eight patients regained normal vision without local recurrence after a mean follow-up time o

Very Important Pool (VIP) genes – an application for microarray-based molecular signatures

<p>Abstract</p> <p>Background</p> <p>Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicine. Derivation of biomarkers is a large step beyond hypothesis generation and imposes considerably more stringency for accuracy in identifying informative gene subsets to differentiate phenotypes. The inherent nature of microarray data, with fewer samples and replicates compared to the large number of genes, requires identifying informative genes prior to classifier construction. However, improving the ability to identify differentiating genes remains a challenge in bioinformatics.</p> <p>Results</p> <p>A new hybrid gene selection approach was investigated and tested with nine publicly available microarray datasets. The new method identifies a Very Important Pool (VIP) of genes from the broad patterns of gene expression data. The method uses a bagging sampling principle, where the re-sampled arrays are used to identify the most informative genes. Frequency of selection is used in a repetitive process to identify the VIP genes. The putative informative genes are selected using two methods, t-statistic and discriminatory analysis. In the t-statistic, the informative genes are identified based on p-values. In the discriminatory analysis, disjoint Principal Component Analyses (PCAs) are conducted for each class of samples, and genes with high discrimination power (DP) are identified. The VIP gene selection approach was compared with the p-value ranking approach. The genes identified by the VIP method but not by the p-value ranking approach are also related to the disease investigated. More importantly, these genes are part of the pathways derived from the common genes shared by both the VIP and p-ranking methods. Moreover, the binary classifiers built from these genes are statistically equivalent to those built from the top 50 p-value ranked genes in distinguishing different types of samples.</p> <p>Conclusion</p> <p>The VIP gene selection approach could identify additional subsets of informative genes that would not always be selected by the p-value ranking method. These genes are likely to be additional true positives since they are a part of pathways identified by the p-value ranking method and expected to be related to the relevant biology. Therefore, these additional genes derived from the VIP method potentially provide valuable biological insights.</p

Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables.

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.This is the accepted manuscript version. The final published version is available from Wiley at http://onlinelibrary.wiley.com/doi/10.1002/sim.3843/abstract;jsessionid=D83E836311AE8220A26CB4E7BFBF3DF1.f01t01

A deletion and a duplication in distal 22q11.2 deletion syndrome region. Clinical implications and review

<p>Abstract</p> <p>Background</p> <p>Individuals affected with DiGeorge and Velocardiofacial syndromes present with both phenotypic diversity and variable expressivity. The most frequent clinical features include conotruncal congenital heart defects, velopharyngeal insufficiency, hypocalcemia and a characteristic craniofacial dysmorphism. The etiology in most patients is a 3 Mb recurrent deletion in region 22q11.2. However, cases of infrequent deletions and duplications with different sizes and locations have also been reported, generally with a milder, slightly different phenotype for duplications but with no clear genotype-phenotype correlation to date.</p> <p>Methods</p> <p>We present a 7 month-old male patient with surgically corrected ASD and multiple VSDs, and dysmorphic facial features not clearly suggestive of 22q11.2 deletion syndrome, and a newborn male infant with cleft lip and palate and upslanting palpebral fissures. Karyotype, FISH, MLPA, microsatellite markers segregation studies and SNP genotyping by array-CGH were performed in both patients and parents.</p> <p>Results</p> <p>Karyotype and FISH with probe N25 were normal for both patients. MLPA analysis detected a partial <it>de novo </it>1.1 Mb deletion in one patient and a novel partial familial 0.4 Mb duplication in the other. Both of these alterations were located at a distal position within the commonly deleted region in 22q11.2. These rearrangements were confirmed and accurately characterized by microsatellite marker segregation studies and SNP array genotyping.</p> <p>Conclusion</p> <p>The phenotypic diversity found for deletions and duplications supports a lack of genotype-phenotype correlation in the vicinity of the LCRC-LCRD interval of the 22q11.2 chromosomal region, whereas the high presence of duplications in normal individuals supports their role as polymorphisms. We suggest that any hypothetical correlation between the clinical phenotype and the size and location of these alterations may be masked by other genetic and/or epigenetic modifying factors.</p

A Survey of Bayesian Statistical Approaches for Big Data

The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those that were available prior to the advent of Big Data. We present a review of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data

Pattern recognition receptors in immune disorders affecting the skin.

Contains fulltext : 109004.pdf (publisher's version ) (Open Access)Pattern recognition receptors (PRRs) evolved to protect organisms against pathogens, but excessive signaling can induce immune responses that are harmful to the host. Putative PRR dysfunction is associated with numerous immune disorders that affect the skin, such as systemic lupus erythematosus, cryopyrin-associated periodic syndrome, and primary inflammatory skin diseases including psoriasis and atopic dermatitis. As yet, the evidence is often confined to genetic association studies without additional proof of a causal relationship. However, insight into the role of PRRs in the pathophysiology of some disorders has already resulted in new therapeutic approaches based on immunomodulation of PRRs