Clinical Genetics Institute

Salt Lake City, UT, United States

Clinical Genetics Institute

Salt Lake City, UT, United States
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Khoury M.J.,Centers for Disease Control and Prevention | Khoury M.J.,U.S. National Cancer Institute | Coates R.J.,Centers for Disease Control and Prevention | Fennell M.L.,Brown University | And 5 more authors.
Journal of the National Cancer Institute - Monographs | Year: 2012

Advances in genomics and related fields promise a new era of personalized medicine in the cancer care continuum. Nevertheless, there are fundamental challenges in integrating genomic medicine into cancer practice. We explore how multilevel research can contribute to implementation of genomic medicine. We first review the rapidly developing scientific discoveries in this field and the paucity of current applications that are ready for implementation in clinical and public health programs. We then define a multidisciplinary translational research agenda for successful integration of genomic medicine into policy and practice and consider challenges for successful implementation. We illustrate the agenda using the example of Lynch syndrome testing in newly diagnosed cases of colorectal cancer and cascade testing in relatives. We synthesize existing information in a framework for future multilevel research for integrating genomic medicine into the cancer care continuum. © The Author 2012. Published by Oxford University Press. All rights reserved.

Coates R.,Centers for Disease Control and Prevention | Williams M.,Intermountain Healthcare Clinical Genetics Institute | Gudgeon J.,Clinical Genetics Institute
PLoS Currents | Year: 2011

Individuals with Lynch syndrome, sometimes referred to as hereditary non-polyposis colorectal cancer (HNPCC), have an increased risk of developing colorectal cancer (CRC) as well as other cancers. The increased risk is due to inherited mutations in mismatch repair (MMR) genes, which reduce the ability of cells to repair DNA damage. Screening for Lynch syndrome in individuals newly diagnosed with colorectal cancer has been proposed as part of a strategy that combines tests and interventions to reduce the risk of colorectal cancer in the relatives of the colorectal cancer patients with Lynch Syndrome.

Taylor D.P.,University of Utah | Stoddard G.J.,University of Utah | Burt R.W.,Huntsman Cancer Institute | Burt R.W.,University of Utah | And 6 more authors.
Genetics in Medicine | Year: 2011

PURPOSE: Using a large, retrospective cohort from the Utah Population Database, we assess how well family history predicts who will acquire colorectal cancer during a 20-year period. METHODS: Individuals were selected between ages 35 and 80 with no prior record of colorectal cancer diagnosis, as of the year 1985. Numbers of colorectal cancer-affected relatives and diagnosis ages were collected. Familial relative risk and absolute risk estimates were calculated. Colorectal cancer diagnoses in the cohort were counted between years 1986 and 2005. Cox regression and Harrell's C were used to measure the discriminatory power of resulting models. RESULTS: A total of 431,153 individuals were included with 5,334 colorectal cancer diagnoses. Familial relative risk ranged from 0.83 to 12.39 and 20-year absolute risk from 0.002 to 0.21. With familial relative risk as the only predictor, Harrell's C = 0.53 and with age only, Harrell's C = 0.66. Familial relative risk combined with age produced a Harrell's C = 0.67. CONCLUSION: Family history by itself is not a strong predictor of exactly who will acquire colorectal cancer within 20 years. However, stratification of risk using absolute risk probabilities may be more helpful in focusing screening on individuals who are more likely to develop the disease. © 2011 Lippincott Williams & Wilkins.

Manolio T.A.,Human Genome Research Institutes | Chisholm R.L.,Northwestern University | Ozenberger B.,Human Genome Research Institutes | Roden D.M.,Vanderbilt University | And 22 more authors.
Genetics in Medicine | Year: 2013

Although the potential for genomics to contribute to clinical care has long been anticipated, the pace of defining the risks and benefits of incorporating genomic findings into medical practice has been relatively slow. Several institutions have recently begun genomic medicine programs, encountering many of the same obstacles and developing the same solutions, often independently. Recognizing that successful early experiences can inform subsequent efforts, the National Human Genome Research Institute brought together a number of these groups to describe their ongoing projects and challenges, identify common infrastructure and research needs, and outline an implementation framework for investigating and introducing similar programs elsewhere. Chief among the challenges were limited evidence and consensus on which genomic variants were medically relevant; lack of reimbursement for genomically driven interventions; and burden to patients and clinicians of assaying, reporting, intervening, and following up genomic findings. Key infrastructure needs included an openly accessible knowledge base capturing sequence variants and their phenotypic associations and a framework for defining and cataloging clinically actionable variants. Multiple institutions are actively engaged in using genomic information in clinical care. Much of this work is being done in isolation and would benefit from more structured collaboration and sharing of best practices.

Taylor D.P.,University of Utah | Cannon-Albright L.A.,University of Utah | Cannon-Albright L.A.,Veterans Affairs Medical Center | Sweeney C.,University of Utah | And 6 more authors.
Genetics in Medicine | Year: 2011

Purpose: To compare colonoscopy screening/surveillance rates by level of risk for colorectal cancer based on age, personal history of adenomatous polyps or colorectal cancer, or family history of colorectal cancer. Methods: Participants were aged 30-90 years, were seen within 5 years at Intermountain Healthcare, and had family history in the Utah Population Database. Colonoscopy rates were measured for those with/without risk factors. Results: Among those aged 60-69 years, 48.4% had colonoscopy in the last 10 years, with rates declining after age 70 years. Percentages of those having had a colonoscopy in the last 10 years generally increased by risk level from 38.5% in those with a familial relative risk <1.0 to 47.6% in those with a familial relative risk >3.0. Compared with those with no family history, the odds ratio for being screened according to guidelines was higher for those with one first-degree relative diagnosed with colorectal cancer ≥ 60 years or two affected second-degree relatives (1.54, 95% confidence interval: 1.46-1.61) than those with one affected first-degree relative diagnosed <60 years or ≥2 affected first-degree relatives (1.25, 95% confidence interval: 1.14-1.37). Conclusions: Compliance with colonoscopy guidelines was higher for those with familial risk but did not correspond with the degree of risk. © 2011 Lippincott Williams & Wilkins.

Williams J.L.,Clinical Genetics Institute | Collingridge D.S.,Statistical Data Center | Williams M.S.,Clinical Genetics Institute
Genetics in Medicine | Year: 2011

Purpose: Family history can guide patient care but is underused. Physician experience with family history has been inadequately characterized. The study's purpose was to assess primary care physicians'experiences with family history. Methods: A qualitative study using an existential-phenomenological approach. Primary care physicians using an electronic health record to enter family history participated in semistructured interviews. Themes were developed relating to physicians'experiences with collection and documentation of family history. A summary describing each physician's experience was developed and analyzed. The themes and experiences from each primary care physician were synthesized across all participants. Results: Positive and negative experiences were identified. Positive experience was associated with the perceived usefulness of family history to guide patient care, confidence using family history, practice efficiency, and enhancing the physician-patient relationship. Negative experience was primarily associated with perception that family history had to be collected and process problems, although confusion about the use of family history, perceived inaccuracies and incompleteness of the information provided, time, and potential liability contributed to negative experience. Most primary care physicians had an overall positive experience with family history, although the balance of the positive and negative experiences did not seem related to the degree the electronic health record was used to enter family history. Conclusions: The primary care physicians'experience with family history represents the synthesis of tensions between positive and negative experiences relating to collection and use. Understanding the components of the experience could inform redesign of systems to enhance the positive and reduce the negative elements. © 2011 Lippincott Williams & Wilkins.

Chute C.G.,Mayo Medical School | Ullman-Cullere M.,Dana-Farber Cancer Institute | Wood G.M.,Clinical Genetics Institute | Lin S.M.,Biomedical Informatics Research Center | And 2 more authors.
Genetics in Medicine | Year: 2013

Health care has become increasingly information intensive. The advent of genomic data, integrated into patient care, significantly accelerates the complexity and amount of clinical data. Translational research in the present day increasingly embraces new biomedical discovery in this data-intensive world, thus entering the domain of "big data." The Electronic Medical Records and Genomics consortium has taught us many lessons, while simultaneously advances in commodity computing methods enable the academic community to affordably manage and process big data. Although great promise can emerge from the adoption of big data methods and philosophy, the heterogeneity and complexity of clinical data, in particular, pose additional challenges for big data inferencing and clinical application. However, the ultimate comparability and consistency of heterogeneous clinical information sources can be enhanced by existing and emerging data standards, which promise to bring order to clinical data chaos. Meaningful Use data standards in particular have already simplified the task of identifying clinical phenotyping patterns in electronic health records. © American College of Medical Genetics and Genomics.

Arrington C.B.,University of Utah | Bleyl S.B.,University of Utah | Bleyl S.B.,Clinical Genetics Institute | Brunelli L.,University of Utah | Bowles N.E.,University of Utah
Future Cardiology | Year: 2013

Congenital heart defects (CHDs) are the most common congenital abnormalities. Analysis of large multigenerational families has led to the identification of a number of genes for CHDs. However, identifiable variations in these genes are the cause of a small proportion of cases of CHDs, suggesting significant genetic heterogeneity. In addition, large families with CHDs are rare, making the identification of additional genes difficult. Next-generation sequencing technologies will provide an opportunity to identify more genes in the future. However, the significant genetic variation between individuals will present a challenge to distinguish between 'pathogenic' and 'benign' variants. We have demonstrated that the analysis of multiple individuals in small families using combinations of algorithms can reduce the number of candidate variants to a small, manageable number. Thus, the analysis of small nuclear families or even distantly related 'sporadic' cases may begin to uncover the 'dark matter' of CHD genetics. © 2013 Future Medicine Ltd.

Gudgeon J.M.,Clinical Genetics Institute | Belnap T.W.,Geisinger Health System | Williams J.L.,Geisinger Health System | Williams M.S.,Geisinger Health System
Journal of Oncology Practice | Year: 2013

Purpose: To determine the impact of applying an age cutoff to tumor-based Lynch syndrome (LS) screening, specifically focusing on changes in relative effectiveness, efficiency, and cost. The project was undertaken to answer questions about implementation of the LS screening program in an integrated health care delivery system. Patients and Methods: Clinical data extracted from an internal cancer registry, previous modeling efforts, published literature, and gray data were used to populate decision models designed to answer questions about the impact of age cutoffs in LS screening. Patients with colorectal cancer (CRC) were stratified at 10-year intervals from ages 50 to 80 years and compared with no age cutoff. Outcomes are reported for a cohort of 325 patients screened and includes total cost to screen, LS cases present in the cutoff category, number of LS cases expected to be identified by screening, cost per LS case detected, and total number and percentage of LS cases missed. Conclusion: Applying an age cutoff to an LS screening program has considerable potential for decreasing total screening costs and increasing efficiency, but at a loss of effectiveness. Imposing an age cutoff of 50 years reduces the cost of the screening program to 16% of a program with no age cutoff, but at the expense of missing more than half of the cases. Failure to identify LS cases is magnified by a cascade effect in family members. The results of this analysis influenced the final policy in our system. Copyright © 2012 by American Society of Clinical Oncology.

Hoffman M.A.,Cerner Corporation | Williams M.S.,Clinical Genetics Institute
Human Genetics | Year: 2011

If the dream of personalized medicine is to be realized, tremendous amounts of data specific to each individual must be captured, synthesized and presented to clinicians at the time this information is needed to make care decisions for the patient. This can only be accomplished through the use of sophisticated electronic medical record (EMR) systems that are designed to support this function. This article will define two important aspects of a fully functional EMR the ability to: present patients or clinicians with high quality context specific information at the point of care (so-called "just-in time" education) and to combine clinically relevant information from disparate sources in order to guide the clinician to the optimized intervention for a given patient (clinical decision support). Personalized medicine examples are used to illustrate these concepts. As implemented most EMR systems are not being used to assimilate the information needed to provide personalized medicine. A description of necessary enhancements to currently available systems that will be needed to create a "personalized medicine enabled" EMR is provided. © 2011 Springer-Verlag.

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