Survival prediction from clinico-genomic models - a comparative study

<p>Abstract</p> <p>Background</p> <p>Survival prediction from high-dimensional genomic data is an active field in today's medical research. Most of the proposed prediction methods make use of genomic data alone without considering established clinical covariates that often are available and known to have predictive value. Recent studies suggest that combining clinical and genomic information may improve predictions, but there is a lack of systematic studies on the topic. Also, for the widely used Cox regression model, it is not obvious how to handle such combined models.</p> <p>Results</p> <p>We propose a way to combine classical clinical covariates with genomic data in a clinico-genomic prediction model based on the Cox regression model. The prediction model is obtained by a simultaneous use of both types of covariates, but applying dimension reduction only to the high-dimensional genomic variables. We describe how this can be done for seven well-known prediction methods: variable selection, unsupervised and supervised principal components regression and partial least squares regression, ridge regression, and the lasso. We further perform a systematic comparison of the performance of prediction models using clinical covariates only, genomic data only, or a combination of the two. The comparison is done using three survival data sets containing both clinical information and microarray gene expression data. Matlab code for the clinico-genomic prediction methods is available at <url>http://www.med.uio.no/imb/stat/bmms/software/clinico-genomic/</url>.</p> <p>Conclusions</p> <p>Based on our three data sets, the comparison shows that established clinical covariates will often lead to better predictions than what can be obtained from genomic data alone. In the cases where the genomic models are better than the clinical, ridge regression is used for dimension reduction. We also find that the clinico-genomic models tend to outperform the models based on only genomic data. Further, clinico-genomic models and the use of ridge regression gives for all three data sets better predictions than models based on the clinical covariates alone.</p

Efficacy of AZM therapy in patients with gingival overgrowth induced by Cyclosporine A: a systematic review

<p>Abstract</p> <p>Background</p> <p>In daily clinical practice of a dental department it's common to find gingival overgrowth (GO) in periodontal patients under treatment with Cyclosporine A (CsA). The pathogenesis of GO and the mechanism of action of Azithromycin (AZM) are unclear. A systematic review was conducted in order to evaluate the efficacy of Azithromycin in patients with gingival overgrowth induced by assumption of Cyclosporine A.</p> <p>Methods</p> <p>A bibliographic search was performed using the online databases MEDLINE, EMBASE and Cochrane Central of Register Controlled Trials (CENTRAL) in the time period between 1966 and September 2008.</p> <p>Results</p> <p>The literature search retrieved 24 articles; only 5 were Randomised Controlled Trials (RCTs), published in English, fulfilled the inclusion criteria. A great heterogeneity between proposed treatments and outcomes was found, and this did not allow to conduct a quantitative meta-analysis. The systematic review revealed that a 5-day course of Azithromycin with Scaling and Root Planing reduces the degree of gingival overgrowth, while a 7-day course of metronidazole is only effective on concomitant bacterial over-infection.</p> <p>Conclusion</p> <p>Few RCTs on the efficacy of systemic antibiotic therapy in case of GO were found in the literature review. A systemic antibiotic therapy without plaque and calculus removal is not able to reduce gingival overgrowth. The great heterogeneity of diagnostic data and outcomes is due to the lack of precise diagnostic methods and protocols about GO. Future studies need to improve both diagnostic methods and tools and adequate classification aimed to determine a correct prognosis and an appropriate therapy for gingival overgrowth.</p

Open-label study comparing the efficacy and tolerability of aripiprazole and haloperidol in the treatment of pediatric tic disorders

Due to its unique pharmacodynamic properties of dopamine partial agonist activity, and its association with few and mild side effects, aripiprazole is a candidate atypical antipsychotic for patients with tic disorders. This open-label study compared the efficacy and tolerability of aripiprazole with haloperidol, a typical antipsychotic widely used to treat patients with tic disorders. Forty-eight children and adolescents with tic disorders were recruited from the outpatient clinic at South Korea and treated with aripiprazole (initial dose, 5.0 mg/d; maximum dose 20 mg/d) or haloperidol (initial dose, 0.75 mg/d; maximum dose, 4.5 mg/d) for 8 weeks. Treatment efficacy was measured using the yale global tic severity scale (YGTSS), and tolerability was measured using the extrapyramidal symptom rating scale (ESRS) and an adverse effects checklist. Total tic scores as measured by the YGTSS decreased over time in both groups (p < 0.001) without any significant differences between groups. ESRS scores were significantly higher in the haloperidol group during the 4 weeks after commencement of medication (p < 0.05). These results indicate that aripiprazole may be a promising drug in the treatment of children and adolescents with tic disorders. Further controlled studies are needed to determine the efficacy and tolerability of aripiprazole in these patients

Sequencing and Comparative Genome Analysis of Two Pathogenic Streptococcus gallolyticus Subspecies: Genome Plasticity, Adaptation and Virulence

Streptococcus gallolyticus infections in humans are often associated with bacteremia, infective endocarditis and colon cancers. The disease manifestations are different depending on the subspecies of S. gallolyticus causing the infection. Here, we present the complete genomes of S. gallolyticus ATCC 43143 (biotype I) and S. pasteurianus ATCC 43144 (biotype II.2). The genomic differences between the two biotypes were characterized with comparative genomic analyses. The chromosome of ATCC 43143 and ATCC 43144 are 2,36 and 2,10 Mb in length and encode 2246 and 1869 CDS respectively. The organization and genomic contents of both genomes were most similar to the recently published S. gallolyticus UCN34, where 2073 (92%) and 1607 (86%) of the ATCC 43143 and ATCC 43144 CDS were conserved in UCN34 respectively. There are around 600 CDS conserved in all Streptococcus genomes, indicating the Streptococcus genus has a small core-genome (constitute around 30% of total CDS) and substantial evolutionary plasticity. We identified eight and five regions of genome plasticity in ATCC 43143 and ATCC 43144 respectively. Within these regions, several proteins were recognized to contribute to the fitness and virulence of each of the two subspecies. We have also predicted putative cell-surface associated proteins that could play a role in adherence to host tissues, leading to persistent infections causing sub-acute and chronic diseases in humans. This study showed evidence that the S. gallolyticus still possesses genes making it suitable in a rumen environment, whereas the ability for S. pasteurianus to live in rumen is reduced. The genome heterogeneity and genetic diversity among the two biotypes, especially membrane and lipoproteins, most likely contribute to the differences in the pathogenesis of the two S. gallolyticus biotypes and the type of disease an infected patient eventually develops

Toll-like receptor 4 signaling in liver injury and hepatic fibrogenesis

Toll-like receptors (TLRs) are a family of transmembrane pattern recognition receptors (PRR) that play a key role in innate and adaptive immunity by recognizing structural components unique to bacteria, fungi and viruses. TLR4 is the most studied of the TLRs, and its primary exogenous ligand is lipopolysaccharide, a component of Gram-negative bacterial walls. In the absence of exogenous microbes, endogenous ligands including damage-associated molecular pattern molecules from damaged matrix and injured cells can also activate TLR4 signaling. In humans, single nucleotide polymorphisms of the TLR4 gene have an effect on its signal transduction and on associated risks of specific diseases, including cirrhosis. In liver, TLR4 is expressed by all parenchymal and non-parenchymal cell types, and contributes to tissue damage caused by a variety of etiologies. Intact TLR4 signaling was identified in hepatic stellate cells (HSCs), the major fibrogenic cell type in injured liver, and mediates key responses including an inflammatory phenotype, fibrogenesis and anti-apoptotic properties. Further clarification of the function and endogenous ligands of TLR4 signaling in HSCs and other liver cells could uncover novel mechanisms of fibrogenesis and facilitate the development of therapeutic strategies

The role of tenascin-C in tissue injury and tumorigenesis

The extracellular matrix molecule tenascin-C is highly expressed during embryonic development, tissue repair and in pathological situations such as chronic inflammation and cancer. Tenascin-C interacts with several other extracellular matrix molecules and cell-surface receptors, thus affecting tissue architecture, tissue resilience and cell responses. Tenascin-C modulates cell migration, proliferation and cellular signaling through induction of pro-inflammatory cytokines and oncogenic signaling molecules amongst other mechanisms. Given the causal role of inflammation in cancer progression, common mechanisms might be controlled by tenascin-C during both events. Drugs targeting the expression or function of tenascin-C or the tenascin-C protein itself are currently being developed and some drugs have already reached advanced clinical trials. This generates hope that increased knowledge about tenascin-C will further improve management of diseases with high tenascin-C expression such as chronic inflammation, heart failure, artheriosclerosis and cancer

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment