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Association Data (association + data)

Distribution by Scientific Domains

Medical Sciences	50%
Life Sciences	50%

Selected Abstracts

The Impact of Private Insurance Coverage on Veterans' Use of VA Care: Insurance and Selection Effects

HEALTH SERVICES RESEARCH, Issue 1p1 2008
Yujing Shen
Objective. To examine private insurance coverage and its impact on use of Veterans Health Administration (VA) care among VA enrollees without Medicare coverage. Data Sources. The 1999 National Health Survey of Veteran Enrollees merged with VA administrative data, with other information drawn from American Hospital Association data and the Area Resource File. Study Design. We modeled VA enrollees' decision of having private insurance coverage and its impact on use of VA care controlling for sociodemographic information, patients' health status, VA priority status and access to VA and non-VA alternatives. We estimated the true impact of insurance on the use of VA care by teasing out potential selection bias. Bias came from two sources: a security selection effect (sicker enrollees purchase private insurance for extra security and use more VA and non-VA care) and a preference selection effect (VA enrollees who prefer non-VA care may purchase private insurance and use less VA care). Principal Findings. VA enrollees with private insurance coverage were less likely to use VA care. Security selection dominated preference selection and naïve models that did not control for selection effects consistently underestimated the insurance effect. Conclusions. Our results indicate that prior research, which has not controlled for insurance selection effects, may have underestimated the potential impact of any private insurance policy change, which may in turn affect VA enrollees' private insurance coverage and consequently their use of VA care. From the decline in private insurance coverage from 1999 to 2002, we projected an increase of 29,400 patients and 158 million dollars for VA health care services. [source]

Gene, region and pathway level analyses in whole-genome studies

GENETIC EPIDEMIOLOGY, Issue 3 2010
Omar De la Cruz
Abstract In the setting of genome-wide association studies, we propose a method for assigning a measure of significance to pre-defined sets of markers in the genome. The sets can be genes, conserved regions, or groups of genes such as pathways. Using the proposed methods and algorithms, evidence for association between a particular functional unit and a disease status can be obtained not just by the presence of a strong signal from a SNP within it, but also by the combination of several simultaneous weaker signals that are not strongly correlated. This approach has several advantages. First, moderately strong signals from different SNPs are combined to obtain a much stronger signal for the set, therefore increasing power. Second, in combination with methods that provide information on untyped markers, it leads to results that can be readily combined across studies and platforms that might use different SNPs. Third, the results are easy to interpret, since they refer to functional sets of markers that are likely to behave as a unit in their phenotypic effect. Finally, the availability of gene-level P -values for association is the first step in developing methods that integrate information from pathways and networks with genome-wide association data, and these can lead to a better understanding of the complex traits genetic architecture. The power of the approach is investigated in simulated and real datasets. Novel Crohn's disease associations are found using the WTCCC data. Genet. Epidemiol. 34: 222,231, 2010. © 2009 Wiley-Liss, Inc. [source]

GENOMIZER: an integrated analysis system for genome-wide association data,

HUMAN MUTATION, Issue 6 2006
Andre Franke
Abstract Genome-wide association analysis appears to be a promising way to identify heritable susceptibility factors for complex human disorders. However, the feasibility of large-scale genotyping experiments is currently limited by an incomplete marker coverage of the genome, a restricted understanding of the functional role of given genomic regions, and the small sample sizes used. Thus, genome-wide association analysis will be a screening tool to facilitate subsequent gene discovery rather than a means to completely resolve individual genetic risk profiles. The validation of association findings will continue to rely upon the replication of "leads" in independent samples from either the same or different populations. Even under such pragmatic conditions, the timely analysis of the large data sets in question poses serious technical challenges. We have therefore developed public-domain software, GENOMIZER, that implements the workflow of an association experiment, including data management, single-point and haplotype analysis, "lead" definition, and data visualization. GENOMIZER (www.ikmb.uni-kiel.de/genomizer) comes with a complete user manual, and is open-source software licensed under the GNU Lesser General Public License. We suggest that the use of this software will facilitate the handling and interpretation of the currently emerging genome-wide association data. Hum Mutat 27(6), 583,588, 2006. © 2006 Wiley-Liss, Inc. [source]

Review article: Patient-level outcomes: the missing link

NEPHROLOGY, Issue 4 2009
DENISE V O'SHAUGHNESSY
SUMMARY Treatment of chronic kidney disease (CKD) may be life-saving, but can disrupt every aspect of a patient's life and the lives of family members. Many patients with CKD are elderly with significant comorbidities and sometimes therapies to improve survival may be less important than those that improve or maintain quality of life. In this setting, patient-level benefits become particularly important goals of therapy. Randomized controlled trials (RCT) are also essential to justify expensive therapies, such as medications used in the treatment of CKD mineral and bone disorders. Surprisingly, data to support the efficacy of these drugs for patient-level outcomes remains limited. In fact, fewer RCT are conducted in renal medicine than in any other medical specialty and reliance is often placed on association data and the assessment of intermediate and biochemical end-points. While some of these may prove to be valid surrogates for clinically important outcomes, some may not. Inclusion of patient-level outcomes in clinical research provides a missing link that can inform a more comprehensive approach to clinical practice and patient care. Incorporating measures of health-related quality of life into clinical trials can make outcomes more relevant and may be relatively simple. This paper provides examples of reliable, validated instruments to measure health-related quality of life domains and functional status, together with practical instructions for their use. Most could be incorporated into RCT of CKD mineral and bone disorder treatments. Inclusion of outcomes that are perceived by patients to be significant should become standard practice in renal medicine and in clinical renal research. [source]

CTLA4/ICOS gene variants and haplotypes are associated with rheumatoid arthritis and primary biliary cirrhosis in the Canadian population

ARTHRITIS & RHEUMATISM, Issue 4 2009
Erin J. Walker
Objective The co-occurrence of different autoimmune diseases in patients and their families suggests the presence of shared genetic risk factors. Two compelling candidate autoimmune disease susceptibility genes are those that encode CTLA4 and inducible costimulator (ICOS), immunoregulatory proteins. Associations of CTLA4 polymorphisms with various autoimmune diseases have been reported, but for rheumatoid arthritis (RA) and primary biliary cirrhosis (PBC), the association data are inconsistent and have largely excluded analysis of polymorphisms in the ICOS gene adjacent to CTLA4. We undertook this study to examine whether CTLA4 and ICOS influence RA and PBC susceptibility by testing CTLA4/ICOS polymorphisms for association with these diseases in Canadian subjects. Methods Caucasian RA patients (n = 1,140), PBC patients (n = 481), and controls (n = 1,248) were typed for 21 biallelic polymorphisms across the CTLA4/ ICOS genes using a multiplex genotyping array, and the results were analyzed using a false discovery rate method to correct for multiple testing. Results Significant associations of multiple CTLA4 and ICOS gene polymorphisms with RA and PBC were observed, with the strongest association signals for both diseases coming from a CTLA4/ICOS intergenic single-nucleotide polymorphism, rs17268364 (corrected P [Pcorr] = 6.0 × 10,4 and Pcorr < 1.0 × 10,4, respectively). Significant associations, which were common to both diseases, were also observed with other alleles and haplotypes across 3 linkage disequilibrium blocks within the CTLA4 gene, the intergenic region, and the ICOS gene. Conclusion Our results provide evidence for RA and PBC association with the CTLA4/ICOS locus and suggest that the risk allele(s) within this region may be common to both diseases. [source]