Utah family-based analysis: past, present and future.
ABSTRACT A unique genealogical resource linked to phenotype data was created in Utah over 30 years ago. Here we review the history and content of this resource. In addition, we review three current methodologies used in conjunction with this resource to define the heritable contribution to phenotypes and to identify predisposition genes responsible for these phenotypes. Example analyses and high-risk pedigrees are presented. Finally we briefly review ways this resource, or others like it, may expand in future.
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ABSTRACT: Background. Population-based studies are needed to estimate the prevalence of underweight or overweight/obese childhood cancer survivors. Procedure. Adult survivors (diagnosed ≤20 years) were identified from the linked Utah Cancer Registry and Utah Population Database. We included survivors currently aged ≥20 years and ≥5 years from diagnosis (N = 1060), and a comparison cohort selected on birth year and sex (N = 5410). BMI was calculated from driver license data available from 2000 to 2010. Multivariable generalized linear regression models were used to calculate prevalence relative risks (RR) and 95% confidence intervals (95% CI) of BMI outcomes for survivors and the comparison cohort. Results. Average time since diagnosis was 18.5 years (SD = 7.8), and mean age at BMI for both groups was 30.5 (survivors SD = 7.7, comparison SD = 8.0). Considering all diagnoses, survivors were not at higher risk for being underweight or overweight/obese than the comparison. Male central nervous system tumor survivors were overweight (RR = 1.12, 95% CI 1.01-1.23) more often than the comparison. Female survivors, who were diagnosed at age 10 and under, had a 10% higher risk of being obese than survivors diagnosed at ages 16-20 (P < 0.05). Conclusion. While certain groups of childhood cancer survivors are at risk for being overweight/obese, in general they do not differ from population estimates.Journal of Cancer Epidemiology 01/2014; 2014:531958. DOI:10.1155/2014/531958
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ABSTRACT: Probabilistic record linkage is a method commonly used to determine whether demographic records refer to the same person. The Fellegi-Sunter method is a probabilistic approach that uses field weights based on log likelihood ratios to determine record similarity. This paper introduces an extension of the Fellegi-Sunter method that incorporates approximate field comparators in the calculation of field weights. The data warehouse of a large academic medical center was used as a case study. The approximate comparator extension was compared with the Fellegi-Sunter method in its ability to find duplicate records previously identified in the data warehouse using different demographic fields and matching cutoffs. The approximate comparator extension misclassified 25% fewer pairs and had a larger Welch's T statistic than the Fellegi-Sunter method for all field sets and matching cutoffs. The accuracy gain provided by the approximate comparator extension grew as less information was provided and as the matching cutoff increased. Given the ubiquity of linkage in both clinical and research settings, the incremental improvement of the extension has the potential to make a considerable impact.Journal of Biomedical Informatics 09/2009; 43(1):24-30. DOI:10.1016/j.jbi.2009.08.004 · 2.48 Impact Factor
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ABSTRACT: The Federated Utah Research and Translational Health e-Repository (FURTHeR) is a Utah statewide informatics platform for the new Center for Clinical and Translational Science at the University of Utah. We have been working on one of FURTHeR's key components, a federated query engine for heterogeneous resources, that we believe has the potential to meet some of the fundamental needs of translational science to access and integrate diverse biomedical data and promote discovery of new knowledge. The architecture of the federated query engine for heterogeneous resources is described and demonstrated.AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 01/2009; 2009:70-4.