Perceived Health in Lung Cancer Patients: The Role of Positive and Negative Affect

Purpose: To examine the association of affective experience and health-related quality of life in lung cancer patients, we hypothesized that negative affect would be positively, and positive affect would be negatively, associated with perceived health. Methods: A sample of 133 English-speaking lung cancer patients (33% female; mean age = 63.68 years old, SD = 9.37) completed a battery of self-report surveys. Results: Results of our secondary analysis indicate that trait negative affect was significantly associated with poor physical and social functioning, greater role limitations due to emotional problems, greater bodily pain, and poor general health. Positive affect was significantly associated with adaptive social functioning, fewer emotion-based role limitations, and less severe bodily pain. In a full model, positive affect was significantly associated with greater levels of social functioning and general health, over and above the effects of negative affect. Conclusions: Reduction of negative affect is an important therapeutic goal, but the ability to maintain positive affect may result in greater perceived health. Indeed, engagement in behaviors that result in greater state positive affect may, over time, result in dispositional changes and enhancement of quality of life

Perceived health in lung cancer patients: the role of positive and negative affect

Abstract Purpose To examine the association of affective experience and health-related quality of life in lung cancer patients, we hypothesized that negative affect would be positively, and positive affect would be negatively, associated with perceived health. Methods A sample of 133 English-speaking lung cancer patients (33% female; mean age = 63.68 years old, SD = 9.37) completed a battery of self-report surveys. Results Results of our secondary analysis indicate that trait negative affect was significantly associated with poor physical and social functioning, greater role limitations due to emotional problems, greater bodily pain, and poor general health. Positive affect was significantly associated with adaptive social functioning, fewer emotion-based role limitations, and less severe bodily pain. In a full model, positive affect was significantly associated with greater levels of social functioning and general health, over and above the effects of negative affect. Conclusions Reduction of negative affect is an important therapeutic goal, but the ability to maintain positive affect may result in greater perceived health. Indeed, engagement in behaviors that result in greater state positive affect may, over time, result in dispositional changes and enhancement of quality of life

Genomewide Association Study of Statin-Induced Myopathy in Patients Recruited Using the UK Clinical Practice Research Datalink.

Statins can be associated with myopathy. We have undertaken a genomewide association study (GWAS) to discover and validate genetic risk factors for statin-induced myopathy in a "real-world" setting. One hundred thirty-five patients with statin myopathy recruited via the UK Clinical Practice Research Datalink were genotyped using the Illumina OmniExpress Exome version 1.0 Bead Chip and compared with the Wellcome Trust Case-Control Consortium (n = 2,501). Nominally statistically significant single nucleotide polymorphism (SNP) signals in the GWAS (P T in the SLCO1B1 gene) SNP was genomewide significant in the severe myopathy (creatine kinase > 10 × upper limit of normal or rhabdomyolysis) group (P = 2.55 × 10-9 ; odds ratio 5.15; 95% confidence interval 3.13-8.45). The association with SLCO1B1 was present for several statins and replicated in the independent validation cohorts. The data highlight the role of SLCO1B1 c.521C>T SNP as a replicable genetic risk factor for statin myopathy. No other novel genetic risk factors with a similar effect size were identified

Use of Endocrine Therapy for Breast Cancer Risk Reduction: ASCO Clinical Practice Guideline Update

To update the ASCO guideline on pharmacologic interventions for breast cancer risk reduction and provide guidance on clinical issues that arise when deciding to use endocrine therapy for breast cancer risk reduction.; An Expert Panel conducted targeted systematic literature reviews to identify new studies.; A randomized clinical trial that evaluated the use of anastrozole for reduction of estrogen receptor-positive breast cancers in postmenopausal women at increased risk of developing breast cancer provided the predominant basis for the update.; In postmenopausal women at increased risk, the choice of endocrine therapy now includes anastrozole (1 mg/day) in addition to exemestane (25 mg/day), raloxifene (60 mg/day), or tamoxifen (20 mg/day). The decision regarding choice of endocrine therapy should take into consideration age, baseline comorbidities, and adverse effect profiles. Clinicians should not prescribe anastrozole, exemestane, or raloxifene for breast cancer risk reduction to premenopausal women. Tamoxifen 20 mg/day for 5 years is still considered standard of care for risk reduction in premenopausal women who are at least 35 years old and have completed childbearing. Data on low-dose tamoxifen as an alternative to the standard dose for both pre- and postmenopausal women with intraepithelial neoplasia are discussed in the Clinical Considerations section of this article. Additional information is available at www.asco.org/breast-cancer-guidelines

A Synthesis of Current Surveillance Planning Methods for the Sequential Monitoring of Drug and Vaccine Adverse Effects Using Electronic Health Care Data

Introduction: The large-scale assembly of electronic health care data combined with the use of sequential monitoring has made proactive postmarket drug- and vaccine-safety surveillance possible. Although sequential designs have been used extensively in randomized trials, less attention has been given to methods for applying them in observational electronic health care database settings. Existing Methods: We review current sequential-surveillance planning methods from randomized trials, and the Vaccine Safety Datalink (VSD) and Mini-Sentinel Pilot projects—two national observational electronic health care database safety monitoring programs. Future Surveillance Planning: Based on this examination, we suggest three steps for future surveillance planning in health care databases: (1) prespecify the sequential design and analysis plan, using available feasibility data to reduce assumptions and minimize later changes to initial plans; (2) assess existing drug or vaccine uptake, to determine if there is adequate information to proceed with surveillance, before conducting more resource-intensive planning; and (3) statistically evaluate and clearly communicate the sequential design with all those designing and interpreting the safety-surveillance results prior to implementation. Plans should also be flexible enough to accommodate dynamic and often unpredictable changes to the database information made by the health plans for administrative purposes. Conclusions: This paper is intended to encourage dialogue about establishing a more systematic, scalable, and transparent sequential design-planning process for medical-product safety-surveillance systems utilizing observational electronic health care databases. Creating such a framework could yield improvements over existing practices, such as designs with increased power to assess serious adverse events

Fermi Large Area Telescope Constraints on the Gamma-ray Opacity of the Universe

The Extragalactic Background Light (EBL) includes photons with wavelengths from ultraviolet to infrared, which are effective at attenuating gamma rays with energy above ~10 GeV during propagation from sources at cosmological distances. This results in a redshift- and energy-dependent attenuation of the gamma-ray flux of extragalactic sources such as blazars and Gamma-Ray Bursts (GRBs). The Large Area Telescope onboard Fermi detects a sample of gamma-ray blazars with redshift up to z~3, and GRBs with redshift up to z~4.3. Using photons above 10 GeV collected by Fermi over more than one year of observations for these sources, we investigate the effect of gamma-ray flux attenuation by the EBL. We place upper limits on the gamma-ray opacity of the Universe at various energies and redshifts, and compare this with predictions from well-known EBL models. We find that an EBL intensity in the optical-ultraviolet wavelengths as great as predicted by the "baseline" model of Stecker et al. (2006) can be ruled out with high confidence.Comment: 42 pages, 12 figures, accepted version (24 Aug.2010) for publication in ApJ; Contact authors: A. Bouvier, A. Chen, S. Raino, S. Razzaque, A. Reimer, L.C. Reye

Introduction of Genetically Engineered Organisms - Draft Programmatic Environmental Impact Statement—July 2007

The U.S. Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) regulates the environmental introduction of genetically engineered (GE) organisms, including crop and noncrop plants, vertebrate and invertebrate animals, and micro-organisms. APHIS regulations are grounded in the most up-to-date science and are designed to provide a level of oversight appropriate for the safe introduction of GE organisms. APHIS is considering whether revisions to its regulations are necessary. One purpose of such revisions would be to address current and future technological trends resulting in GE plants with which the agency is less familiar, such as plants with environmental stress tolerance or enhanced nutrition, and plants engineered for new purposes such as biofuels or for production of pharmaceutical or industrial compounds. Additionally, the regulations would be revised to ensure a high level of environmental protection, to create regulatory processes that are transparent to stakeholders and the public, to consider the efficient use of agency resources, to ensure that the level of oversight is commensurate with the risk, and to ensure conformity with obligations under international treaties and agreements, such as World Trade Organization (WTO) agreements. To this end, this draft environmental impact statement (DEIS) was prepared to provide agency decisionmakers with a full range of regulatory alternatives and assist them in selecting a preferred alternative

Unfolding Kernel embeddings of graphs: Enhancing class separation through manifold learning

In this paper, we investigate the use of manifold learning techniques to enhance the separation properties of standard graph kernels. The idea stems from the observation that when we perform multidimensional scaling on the distance matrices extracted from the kernels, the resulting data tends to be clustered along a curve that wraps around the embedding space, a behavior that suggests that long range distances are not estimated accurately, resulting in an increased curvature of the embedding space. Hence, we propose to use a number of manifold learning techniques to compute a low-dimensional embedding of the graphs in an attempt to unfold the embedding manifold, and increase the class separation. We perform an extensive experimental evaluation on a number of standard graph datasets using the shortest-path (Borgwardt and Kriegel, 2005), graphlet (Shervashidze et al., 2009), random walk (Kashima et al., 2003) and Weisfeiler-Lehman (Shervashidze et al., 2011) kernels. We observe the most significant improvement in the case of the graphlet kernel, which fits with the observation that neglecting the locational information of the substructures leads to a stronger curvature of the embedding manifold. On the other hand, the Weisfeiler-Lehman kernel partially mitigates the locality problem by using the node labels information, and thus does not clearly benefit from the manifold learning. Interestingly, our experiments also show that the unfolding of the space seems to reduce the performance gap between the examined kernels. (C) 2015 Elsevier Ltd. All rights reserved

Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus

Elevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E–7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits