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Pak CM, Gilmore MJ, Bulkley JE, Chakraborty P, Dagan-Rosenfeld O, Foreman AKM, Gollob MH, Jenkins CL, Katz AE, Lee K, Meeks N, O'Daniel JM, Posey JE, Rego SM, Shah N, Steiner RD, Stergachis AB, Subramanian SL, Trotter T, Wallace K, Williams MS, Goddard KAB, Buchanan AH, Manickam K, Powell B, Ezzell Hunter J. Implementing Evidence-Based Assertions of Clinical Actionability in the Context of Secondary Findings: Updates from the ClinGen Actionability Working Group. Genet Med 2024:101164. [PMID: 38757444 DOI: 10.1016/j.gim.2024.101164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 05/07/2024] [Accepted: 05/08/2024] [Indexed: 05/18/2024] Open
Abstract
PURPOSE The ClinGen Actionability Working Group (AWG) developed an evidence-based framework to generate actionability reports and scores of gene-condition pairs in the context of secondary findings from genome sequencing. Here we describe the expansion of the framework to include actionability assertions. METHODS Initial development of the actionability rubric was based on previously scored adult gene-condition pairs and individual expert evaluation. Rubric refinement was iterative and based on evaluation, feedback, and discussion. The final rubric was pragmatically evaluated via integration into actionability assessments for 27 gene-condition pairs. RESULTS The resulting rubric has a four-point scale (limited, moderate, strong, definitive) and uses the highest-scoring outcome-intervention pair of each gene-condition pair to generate a preliminary assertion. During AWG discussions, pre-defined criteria and factors guide discussion to produce a consensus assertion for a gene-condition pair, which may differ from the preliminary assertion. The AWG has retrospectively generated assertions for all previously scored gene-condition pairs and are prospectively asserting on gene-condition pairs under assessment, having completed over 170 adult and 188 pediatric gene-condition pairs. CONCLUSION The AWG expanded its framework to provide actionability assertions to enhance the clinical value of their resources and increase their utility as decision aids regarding return of secondary findings.
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Affiliation(s)
- Christine M Pak
- Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, Oregon.
| | - Marian J Gilmore
- Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, Oregon
| | - Joanna E Bulkley
- Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, Oregon
| | - Pranesh Chakraborty
- Newborn Screening Ontario, Children's Hospital of Eastern Ontario, and Division of Metabolics University of Ottawa, Ottawa, Ontario
| | - Orit Dagan-Rosenfeld
- Department of Genetics, Stanford University School of Medicine, Stanford, California
| | | | | | - Charisma L Jenkins
- Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, Oregon
| | - Alexander E Katz
- Division of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Kristy Lee
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Naomi Meeks
- Section of Genetics, Department of Pediatrics, University of Colorado, Aurora, Colorado
| | - Julianne M O'Daniel
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Jennifer E Posey
- Molecular and Human Genetics Department, Baylor College of Medicine, Houston, Texas
| | - Shannon M Rego
- Institute for Human Genetics, University of California, San Francisco, California
| | - Neethu Shah
- Molecular and Human Genetics Department, Baylor College of Medicine, Houston, Texas
| | - Robert D Steiner
- University of Wisconsin and Marshfield Clinic, Marshfield and Madison, Wisconsin
| | - Andrew B Stergachis
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington
| | - Sai Lakshmi Subramanian
- Molecular and Human Genetics Department, Baylor College of Medicine, Houston, Texas, and Roche Diagnostics, Santa Clara, California
| | - Tracy Trotter
- Department of Pediatrics, John Muir Health, Walnut Creek, California
| | - Kathleen Wallace
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Marc S Williams
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Katrina A B Goddard
- Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, Oregon
| | - Adam H Buchanan
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Kandamurugu Manickam
- Department of Pediatrics, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, Ohio
| | - Bradford Powell
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Jessica Ezzell Hunter
- Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, North Carolina
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Lennon AM, Buchanan AH, Rego SP, Choudhry OA, Elias PZ, Sadler JR, Roberta J, Zhang Y, Flake DD, Honushefsky A, Salvati ZM, Sheridan K, Wagner ES, Fishman EK, Papadopoulos N, Beer TM. Outcomes following a false positive multi-cancer early detection (MCED) test: Results from DETECT-A, the first large, prospective, interventional MCED study. Cancer Prev Res (Phila) 2024:745184. [PMID: 38705577 DOI: 10.1158/1940-6207.capr-23-0451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/23/2024] [Accepted: 05/01/2024] [Indexed: 05/07/2024]
Abstract
Guideline recommended standard of care (SoC) screening is available for four cancer types; most cancer-related deaths are caused by cancers without SoC screening. DETECT-A is the first prospective interventional trial evaluating an MCED blood test (CancerSEEK) in women without a history of cancer, providing the first opportunity to assess the long-term outcomes of individuals with false positive (FP) MCED results. This prospective analysis of DETECT-A participants with FP results evaluates the performance of an imaging-based diagnostic workflow and examines cancer risk following a FP result. This analysis included all DETECT-A participants with a positive CancerSEEK test and subsequent flourine-18 fluorodeoxyglucose positron emission tomography-IV contrast enhanced computed tomography (18-F-FDG PET-CT) imaging and clinical workup indicating no evidence of cancer within one year of enrollment (n=98). Medical records, study interactions, and study surveys were used to assess cancer incidence, treatments, and clinical outcomes through August 2023. Ninety-five of 98 participants with a FP result remained cancer-free with a median follow-up of 3.6 years (IQR: 2.5-4.1) from determination of FP status. Three incident cancers were observed over the follow-up period. One bilateral stage IIIC ovarian cancer was diagnosed 1.9 years after determination of FP status; two stage I breast cancers were diagnosed 0.1 and 1.6 years from determination of FP status. The annual incidence rate of cancer during follow-up from FP determination was 1.0% (95% CI: 0.2%-2.8%). Participants with a positive CancerSEEK test who underwent 18-F-FDG PET-CT and clinical workup without cancer findings had low risk for cancer over the following several years.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Tomasz M Beer
- Exact Sciences (United States), Madison, WI, United States
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Honushefsky A, Wagner ES, Sheridan K, Spickard KM, LeMasters WR, Walter CN, Beaver T, Lennon AM, Papadopoulos N, Rahm AK, Buchanan AH. Real-time evaluation and adaptation to facilitate rapid recruitment in a large, prospective cohort study. BMC Health Serv Res 2024; 24:336. [PMID: 38481315 PMCID: PMC10938733 DOI: 10.1186/s12913-024-10750-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/19/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Recruiting large cohorts efficiently can speed the translation of findings into care across a range of scientific disciplines and medical specialties. Recruitment can be hampered by factors such as financial barriers, logistical concerns, and lack of resources for patients and clinicians. These and other challenges can lead to underrepresentation in groups such as rural residents and racial and ethnic minorities. Here we discuss the implementation of various recruitment strategies for enrolling participants into a large, prospective cohort study, assessing the need for adaptations and making them in real-time, while maintaining high adherence to the protocol and high participant satisfaction. METHODS While conducting a large, prospective trial of a multi-cancer early detection blood test at Geisinger, an integrated health system in central Pennsylvania, we monitored recruitment progress, adherence to the protocol, and participants' satisfaction. Tracking mechanisms such as paper records, electronic health records, research databases, dashboards, and electronic files were utilized to measure each outcome. We then reviewed study procedures and timelines to list the implementation strategies that were used to address barriers to recruitment, protocol adherence and participant satisfaction. RESULTS Adaptations to methods that contributed to achieving the enrollment goal included offering multiple recruitment options, adopting group consenting, improving visit convenience, increasing the use of electronic capture and the tracking of data and source documents, staffing optimization via leveraging resources external to the study team when appropriate, and integrating the disclosure of study results into routine clinical care without adding unfunded work for clinicians. We maintained high protocol adherence and positive participant experience as exhibited by a very low rate of protocol deviations and participant complaints. CONCLUSION Recruiting rapidly for large studies - and thereby facilitating clinical translation - requires a nimble, creative approach that marshals available resources and changes course according to data. Planning a rigorous assessment of a study's implementation outcomes prior to study recruitment can further ground study adaptations and facilitate translation into practice. This can be accomplished by proactively and continuously assessing and revising implementation strategies.
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Affiliation(s)
| | - Eric S Wagner
- Geisinger, 549 Fair Street, Bloomsburg, PA, 17815, USA
| | | | | | | | | | - Taryn Beaver
- Geisinger, 549 Fair Street, Bloomsburg, PA, 17815, USA
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Schwartz MLB, McDonald WS, Hallquist MLG, Hu Y, McCormick CZ, Walters NL, Tsun J, Zimmerman K, Decker A, Gray C, Malinowski J, Sturm AC, Buchanan AH. Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results. JAMA Netw Open 2024; 7:e242388. [PMID: 38488794 PMCID: PMC10943406 DOI: 10.1001/jamanetworkopen.2024.2388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/23/2024] [Indexed: 03/18/2024] Open
Abstract
Importance Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. Objective To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. Design, Setting, and Participants This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Exposure Clinically confirmed P/LP result disclosed by phone or letter. Main Outcomes and Measures Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Results Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). Conclusions and Relevance This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.
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Affiliation(s)
- Marci L. B. Schwartz
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | | | | | - Jessica Tsun
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | | | - Amie Decker
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- University of Arkansas Medical Sciences, Little Rock
| | - Celia Gray
- Phenomics and Clinical Data Core, Geisinger, Danville, Pennsylvania
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- 23andMe, Sunnyvale, California
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Thompson CL, Buchanan AH, Myers R, Weinberg DS. Integrating primary care, shared decision making, and community engagement to facilitate equitable access to multi-cancer early detection clinical trials. Front Oncol 2024; 13:1307459. [PMID: 38486933 PMCID: PMC10937460 DOI: 10.3389/fonc.2023.1307459] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/06/2023] [Indexed: 03/17/2024] Open
Abstract
Effective implementation of cancer screening programs can reduce disease-specific incidence and mortality. Screening is currently recommended for breast, cervical, colorectal and lung cancer. However, initial and repeat adherence to screening tests in accordance with current guidelines is sub-optimal, with the lowest rates observed in historically underserved groups. If used in concert with recommended cancer screening tests, new biospecimen-based multi-cancer early detection (MCED) tests could help to identify more cancers that may be amendable to effective treatment. Clinical trials designed to assess the safety and efficacy of MCED tests to assess their potential for reducing cancer mortality are needed and many are underway. In the conduct of MCED test trials, it is crucial that participant recruitment efforts successfully engage participants from diverse populations experiencing cancer disparities. Strategic partnerships involving health systems, clinical practices, and communities can increase the reach of MCED trial recruitment efforts among populations experiencing disparities. This goal can be achieved by developing health system-based learning communities that build understanding of and trust in biomedical research; and by applying innovative methods for identifying eligible trial patients, educating potential participants about research trials, and engaging eligible individuals in shared decision making (SDM) about trial participation. This article describes how a developing consortium of health systems has used this approach to encourage the uptake of cancer screening in a wide range of populations and how such a strategy can facilitate the enrollment of persons from diverse patient and community populations in MCED trials.
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Affiliation(s)
- Cheryl L. Thompson
- Penn State Cancer Institute, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, United States
| | - Adam H. Buchanan
- Department of Genomic Health, Geisinger, Danville, PA, United States
| | - Ronald Myers
- Division of Population Science Department of Medical Oncology, Thomas Jefferson University, Philadelphia, PA, United States
| | - David S. Weinberg
- Department of Medicine, Fox Chase Cancer Center, Philadelphia, PA, United States
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Yu KD, Betts MN, Urban GM, Schwartz MLB, Robinson TO, Moyer RJ, Taddonio SW, Vasudevan A, Johns A, Sturm AC, Kelly MA, Williams MS, Poler SM, Buchanan AH. Evaluation of Malignant Hyperthermia Features in Patients with Pathogenic or Likely Pathogenic RYR1 Variants Disclosed through a Population Genomic Screening Program. Anesthesiology 2024; 140:52-61. [PMID: 37787745 DOI: 10.1097/aln.0000000000004786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
BACKGROUND Malignant hyperthermia (MH) susceptibility is a heritable musculoskeletal disorder that can present as a potentially fatal hypermetabolic response to triggering anesthesia agents. Genomic screening for variants in MH-associated genes RYR1 and CACNA1S provides an opportunity to prevent morbidity and mortality. There are limited outcomes data from disclosing variants in RYR1, the most common MH susceptibility gene, in unselected populations. The authors sought to identify the rate of MH features or fulminant episodes after triggering agent exposure in an unselected population undergoing genomic screening including actionable RYR1 variants. METHODS The MyCode Community Health Initiative by Geisinger (USA) is an electronic health record-linked biobank that discloses pathogenic and likely pathogenic variants in clinically actionable genes to patient-participants. Available electronic anesthesia and ambulatory records for participants with actionable RYR1 results returned through December 2020 were evaluated for pertinent findings via double-coded chart reviews and reconciliation. Descriptive statistics for observed phenotypes were calculated. RESULTS One hundred fifty-two participants had an actionable RYR1 variant disclosed during the study period. None had previous documented genetic testing for MH susceptibility; one had previous contracture testing diagnosing MH susceptibility. Sixty-eight participants (44.7%) had anesthesia records documenting triggering agent exposure during at least one procedure. None received dantrolene treatment or had documented muscle rigidity, myoglobinuria, hyperkalemia, elevated creatine kinase, severe myalgia, or tea-colored urine. Of 120 possibly MH-related findings (postoperative intensive care unit admissions, hyperthermia, arterial blood gas evaluation, hypercapnia, or tachycardia), 112 (93.3%) were deemed unlikely to be MH events; 8 (6.7%) had insufficient records to determine etiology. CONCLUSIONS Results demonstrate a low frequency of classic intraanesthetic hypermetabolic phenotypes in an unselected population with actionable RYR1 variants. Further research on the actionability of screening for MH susceptibility in unselected populations, including economic impact, predictors of MH episodes, and expanded clinical phenotypes, is necessary. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Kristen D Yu
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Megan N Betts
- Department of Genomic Health, Geisinger, Danville, Pennsylvania; WellSpan Health, York, Pennsylvania
| | | | - Marci L B Schwartz
- Department of Genomic Health, Geisinger, Danville, Pennsylvania; Division of Clinical and Metabolic Genetics, and Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, The Hospital for Sick Children, Toronto, Canada
| | | | - Robert J Moyer
- Department of Anesthesiology, Geisinger, Danville, Pennsylvania
| | - Scott W Taddonio
- Department of Anesthesiology, Geisinger, Danville, Pennsylvania; Department of Anesthesiology, Jefferson Health, Philadelphia, Pennsylvania
| | - Anasuya Vasudevan
- Department of Anesthesiology, Geisinger, Danville, Pennsylvania; Vigilant Anesthesia PC, New York, New York
| | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Amy C Sturm
- Department of Genomic Health, Geisinger, Danville, Pennsylvania; 23andMe, Sunnyvale, California
| | - Melissa A Kelly
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Marc S Williams
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - S Mark Poler
- Department of Anesthesiology, Geisinger, Danville, Pennsylvania
| | - Adam H Buchanan
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
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Schwiter R, Rocha H, Johns A, Savatt JM, Diehl DL, Kelly MA, Williams MS, Buchanan AH. Low adenoma burden in unselected patients with a pathogenic APC variant. Genet Med 2023; 25:100949. [PMID: 37542411 DOI: 10.1016/j.gim.2023.100949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 07/28/2023] [Accepted: 07/28/2023] [Indexed: 08/06/2023] Open
Abstract
PURPOSE Genomic screening can improve clinical outcomes, but presentation of individuals with risk for polyposis identified via genomic screening is unknown. To inform assessment of clinical utility of genomic screening for polyposis risk, clinical presentation of individuals in an unselected health care system cohort with an APC pathogenic or likely pathogenic (P/LP) variant causative of familial adenomatous polyposis are described. METHODS Electronic health records of individuals with an APC P/LP variant identified via the MyCode program (MyCode APC+) were reviewed to assess adenoma burden and compare it among individuals with a clinical diagnosis of familial adenomatous polyposis and matched variant-negative controls. RESULTS The prevalence of APC P/LP variants in this health care cohort is estimated to be 1 in 2800. Twenty-four MyCode APC+ individuals were identified during the study period. Median age at result disclosure was 53 years. Rate of clinical polyposis was 8%. Two of six participants with a classic region variant and none of those with an attenuated region variant had polyposis. MyCode APC+ participants did not differ from controls in cumulative adenoma count. CONCLUSION APC P/LP variant prevalence estimate in the MyCode cohort is higher than prior published prevalence rates. Individuals with APC P/LP variants identified via genomic screening had a low adenoma burden.
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Affiliation(s)
| | - Heather Rocha
- Department of Genomic Health, Geisinger, Danville, PA
| | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, PA
| | | | - David L Diehl
- Department of Medicine, Division of Gastroenterology and Hepatology, Geisinger, Danville, PA
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Savatt JM, Johns A, Schwartz MLB, McDonald WS, Salvati ZM, Oritz NM, Masnick M, Hatchell K, Hao J, Buchanan AH, Williams MS. Testing and Management of Iron Overload After Genetic Screening-Identified Hemochromatosis. JAMA Netw Open 2023; 6:e2338995. [PMID: 37870835 PMCID: PMC10594145 DOI: 10.1001/jamanetworkopen.2023.38995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 09/08/2023] [Indexed: 10/24/2023] Open
Abstract
Importance HFE gene-associated hereditary hemochromatosis type 1 (HH1) is underdiagnosed, resulting in missed opportunities for preventing morbidity and mortality. Objective To assess whether screening for p.Cys282Tyr homozygosity is associated with recognition and management of asymptomatic iron overload. Design, Setting, and Participants This cross-sectional study obtained data from the Geisinger MyCode Community Health Initiative, a biobank of biological samples and linked electronic health record data from a rural, integrated health care system. Participants included those who received a p.Cys282Tyr homozygous result via genomic screening (MyCode identified), had previously diagnosed HH1 (clinically identified), and those negative for p.Cys282Tyr homozygosity between 2017 and 2018. Data were analyzed from April 2020 to August 2023. Exposure Disclosure of a p.Cys282Tyr homozygous result. Main Outcomes and Measures Postdisclosure management and HFE-associated phenotypes in MyCode-identified participants were analyzed. Rates of HFE-associated phenotypes in MyCode-identified participants were compared with those of clinically identified participants. Relevant laboratory values and rates of laboratory iron overload among participants negative for p.Cys282Tyr homozygosity were compared with those of MyCode-identified participants. Results A total of 86 601 participants had available exome sequences at the time of analysis, of whom 52 994 (61.4%) were assigned female at birth, and the median (IQR) age was 62.0 (47.0-73.0) years. HFE p.Cys282Tyr homozygosity was disclosed to 201 participants, of whom 57 (28.4%) had a prior clinical HH1 diagnosis, leaving 144 participants who learned of their status through screening. There were 86 300 individuals negative for p.Cys282Tyr homozygosity. After result disclosure, among MyCode-identified participants, 99 (68.8%) had a recommended laboratory test and 36 (69.2%) with laboratory or liver biopsy evidence of iron overload began phlebotomy or chelation. Fifty-three (36.8%) had iron overload; rates of laboratory iron overload were higher in MyCode-identified participants than participants negative for p.Cys282Tyr homozygosity (females: 34.1% vs 2.1%, P < .001; males: 39.0% vs 2.9%, P < .001). Iron overload (females: 34.1% vs 79.3%, P < .001; males: 40.7% vs 67.9%, P = .02) and some liver-associated phenotypes were observed at lower frequencies in MyCode-identified participants compared with clinically identified individuals. Conclusions and Relevance Results of this cross-sectional study showed the ability of genomic screening to identify undiagnosed iron overload and encourage relevant management, suggesting the potential benefit of population screening for HFE p.Cys282Tyr homozygosity. Further studies are needed to examine the implications of genomic screening for health outcomes and cost-effectiveness.
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Affiliation(s)
| | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Marci L. B. Schwartz
- Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Nicole M. Oritz
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Max Masnick
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | | | - Jing Hao
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
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Hallquist MLG, Borensztein MJ, Coughlin CR, Buchanan AH, Andrew Faucett W, Peay HL, Smith ME, Tricou EP, Uhlmann WR, Wain KE, Ormond KE. Defining critical educational components of informed consent for genetic testing: views of US-based genetic counselors and medical geneticists. Eur J Hum Genet 2023; 31:1165-1174. [PMID: 37308598 PMCID: PMC10545703 DOI: 10.1038/s41431-023-01401-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 03/22/2023] [Accepted: 05/23/2023] [Indexed: 06/14/2023] Open
Abstract
The Clinical Genome Resource (ClinGen) Consent and Disclosure Recommendation (CADRe) framework proposes that key components of informed consent for genetic testing can be covered with a targeted discussion for many conditions rather than a time-intensive traditional genetic counseling approach. We surveyed US genetics professionals (medical geneticists and genetic counselors) on their response to scenarios that proposed core informed consent concepts for clinical genetic testing developed in a prior expert consensus process. The anonymous online survey included responses to 3 (of 6 possible) different clinical scenarios that summarized the application of the core concepts. There was a binary (yes/no) question asking respondents whether they agreed the scenarios included the minimum necessary and critical educational concepts to allow an informed decision. Respondents then provided open-ended feedback on what concepts were missing or could be removed. At least one scenario was completed by 238 respondents. For all but one scenario, over 65% of respondents agreed that the identified concepts portrayed were sufficient for an informed decision; the exome scenario had the lowest agreement (58%). Qualitative analysis of the open-ended comments showed no consistently mentioned concepts to add or remove. The level of agreement with the example scenarios suggests that the minimum critical educational components for pre-test informed consent proposed in our prior work is a reasonable starting place for targeted pre-test discussions. This may be helpful in providing consistency to the clinical practice of both genetics and non-genetics providers, meeting patients' informational needs, tailoring consent for psychosocial support, and in future guideline development.
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Affiliation(s)
| | - Maia J Borensztein
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Curtis R Coughlin
- Department of Pediatrics and Center for Bioethics and Humanities, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | | | - Holly L Peay
- RTI International, Genomics, Bioinformatics, and Translational Research Center, Raleigh, NC, USA
| | - Maureen E Smith
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Eric P Tricou
- Geisinger, Danville, PA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Wendy R Uhlmann
- Division of Genetic Medicine, Department of Internal Medicine; Department of Human Genetics; Center for Bioethics & Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, USA
| | | | - Kelly E Ormond
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, CA, USA
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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10
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Pichardo PFA, Hellums RN, Hao J, Savatt JM, Hassen D, Pellitteri PK, Alvi M, Buchanan AH, Purdy NC. Thyroidectomy Outcomes in Patients Identified With RET Pathogenic Variants Through a Population Genomic Screening Program. JAMA Otolaryngol Head Neck Surg 2023; 149:195-202. [PMID: 36602781 PMCID: PMC9857699 DOI: 10.1001/jamaoto.2022.4195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 10/24/2022] [Indexed: 01/06/2023]
Abstract
Importance Population-based genomic screening can facilitate early detection of medullary thyroid carcinoma (MTC) in patients with pathogenic/likely pathogenic (P/LP) RET variants. Objective To evaluate the clinical treatment and patient outcomes after identification of P/LP RET proto-oncogene variants associated with the risk of MTC via a population genomic screening program. Design, Setting, Participants This retrospective cross-sectional study was completed between June 1, 2016, and May 31, 2022, for a mean follow-up period of 22.4 months (range, 2-76 months). The study included patients who were identified as having P/LP RET variants through a population genomic screening program at a rural tertiary care center and who underwent thyroidectomy after results disclosure. Main Outcomes and Measures The outcomes of interest were preoperative evaluation and treatment-related outcomes. Measures included imaging and laboratory findings, extent of surgery, pathologic diagnosis, and staging. Results Seventy-five patients were identified as having P/LP RET variants exclusively through genomic screening. Twenty of these patients (27%; 11 women [55%] and 9 men [45%]; median age, 48 years [range, 22-73 years]) underwent total thyroidectomy; 13 of these patients (65%) also had a central neck dissection. No patients had clinically apparent disease at the time of surgery. Pathologic findings indicated MTC for 12 patients and papillary thyroid carcinoma in 2. Of patients with MTC, 10 had stage I disease, 1 had stage II disease, 1 had stage III disease, and none had stage IV disease. Based on postoperative surveillance imaging and laboratory results, no patient had evidence of recalcitrant disease. Conclusions and Relevance In this cross-sectional study, all malignant neoplasms identified on surgical pathology were clinically occult, with surgical intervention based solely on the identification of the P/LP RET variant via population genomic screening. This finding suggests that genomic screening may provide opportunities for early detection and treatment of MTC, with the potential for improved patient outcomes.
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Affiliation(s)
- Priscilla F. A. Pichardo
- Department of Otolaryngology–Head and Neck Surgery, Geisinger Medical Center, Danville, Pennsylvania
| | - Ryan N. Hellums
- Department of Otolaryngology–Head and Neck Surgery, Geisinger Medical Center, Danville, Pennsylvania
| | - Jing Hao
- Department of Population Health Sciences, Geisinger Medical Center, Danville, Pennsylvania
- Genomic Medicine Institute, Geisinger Medical Center, Danville, Pennsylvania
| | - Juliann M. Savatt
- Genomic Medicine Institute, Geisinger Medical Center, Danville, Pennsylvania
| | - Dina Hassen
- Department of Population Health Sciences, Geisinger Medical Center, Danville, Pennsylvania
| | - Phillip K. Pellitteri
- Department of Otolaryngology–Head and Neck Surgery, Geisinger Medical Center, Danville, Pennsylvania
| | - Madiha Alvi
- Department of Endocrinology, Geisinger Medical Center, Danville, Pennsylvania
| | - Adam H. Buchanan
- Genomic Medicine Institute, Geisinger Medical Center, Danville, Pennsylvania
| | - Nicholas C. Purdy
- Department of Otolaryngology–Head and Neck Surgery, Geisinger Medical Center, Danville, Pennsylvania
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11
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McCormick CZ, Yu KD, Johns A, Campbell-Salome G, Hallquist MLG, Sturm AC, Buchanan AH. Investigating Psychological Impact after Receiving Genetic Risk Results-A Survey of Participants in a Population Genomic Screening Program. J Pers Med 2022; 12:jpm12121943. [PMID: 36556164 PMCID: PMC9781266 DOI: 10.3390/jpm12121943] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/17/2022] [Accepted: 11/19/2022] [Indexed: 11/24/2022] Open
Abstract
Genomic screening programs have potential to benefit individuals who may not be clinically ascertained, but little is known about the psychological impact of receiving genetic results in this setting. The current study sought to further the understanding of individuals’ psychological response to receiving an actionable genetic test result from genomic screening. Telephone surveys were conducted with patient-participants at 6 weeks and 6 months post genetic result disclosure between September 2019 and May 2021 and assessed emotional response to receiving results via the FACToR, PANAS, and decision regret scales. Overall, 354 (29.4%) study participants completed both surveys. Participants reported moderate positive emotions and low levels of negative emotions, uncertainty, privacy concern, and decision regret over time. There were significant decreases in negative emotions (p = 0.0004) and uncertainty (p = 0.0126) between time points on the FACToR scale. “Interested” was the highest scoring discrete emotion (T1 3.6, T2 3.3, scale 0−5) but was significantly lower at 6 months (<0.0001). Coupled with other benefits of genomic screening, these results of modest psychological impact waning over time adds support to clinical utility of population genomic screening programs. However, questions remain regarding how to elicit an emotional response that motivates behavior change without causing psychological harm.
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Affiliation(s)
| | | | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | - Gemme Campbell-Salome
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
- 23andMe, Sunnyvale, CA 94086, USA
| | - Adam H. Buchanan
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
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12
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Baker A, Tolwinski K, Atondo J, Davis FD, Goehringer J, Jones LK, Pisieczko CJ, Sturm AC, Williams JL, Williams MS, Rahm AK, Buchanan AH. Understanding the Patient Experience of Receiving Clinically Actionable Genetic Results from the MyCode Community Health Initiative, a Population-Based Genomic Screening Initiative. J Pers Med 2022; 12:jpm12091511. [PMID: 36143296 PMCID: PMC9501087 DOI: 10.3390/jpm12091511] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 11/16/2022] Open
Abstract
Understanding unselected individuals’ experiences receiving genetic results through population genomic screening is critical to advancing clinical utility and improving population health. We conducted qualitative interviews with individuals who received clinically actionable genetic results via the MyCode© Genomic Screening and Counseling program. We purposively sampled cohorts to seek diversity in result-related disease risk (e.g., cancer or cardiovascular) and in personal or family history of related diseases. Transcripts were analyzed using a two-step inductive coding process of broad thematic analysis followed by in-depth coding of each theme. Four thematic domains identified across all cohorts were examined: process assessment, psychosocial response, behavioral change due to the genetic result, and family communication. Coding of 63 interviews among 60 participants revealed that participants were satisfied with the results disclosure process, initially experienced a range of positive, neutral, and negative psychological reactions to results, adjusted positively to results over time, undertook clinically indicated actions in response to results, and communicated results with relatives to whom they felt emotionally close. Our findings of generally favorable responses to receiving clinically actionable genetic results via a genomic screening program may assuage fear of patient distress in such programs and guide additional biobanks, genomic screening programs, and research studies.
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Affiliation(s)
- Anna Baker
- Department of Psychology, Bucknell University, Lewisburg, PA 17837, USA or
- Department of Psychology, Clemson University, Clemson, SC 29634, USA
| | - Kasia Tolwinski
- Biomedical Ethics Unit, McGill University, Montreal, QC H3A 0G4, Canada
| | - Jamie Atondo
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
| | | | | | - Laney K. Jones
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
- Heart and Vascular Institute, Geisinger, Danville, PA 17822, USA
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
- 23andMe, Sunnyvale, CA 94086, USA
| | | | - Marc S. Williams
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
| | | | - Adam H. Buchanan
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
- Correspondence:
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13
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Savatt JM, Ortiz NM, Thone GM, McDonald WS, Kelly MA, Berry ASF, Alvi MM, Hallquist MLG, Malinowski J, Purdy NC, Williams MS, Sturm AC, Buchanan AH. Observational study of population genomic screening for variants associated with endocrine tumor syndromes in a large, healthcare-based cohort. BMC Med 2022; 20:205. [PMID: 35668420 PMCID: PMC9172012 DOI: 10.1186/s12916-022-02375-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/12/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND In current care, patients' personal and self-reported family histories are primarily used to determine whether genetic testing for hereditary endocrine tumor syndromes (ETS) is indicated. Population genomic screening for other conditions has increased ascertainment of individuals with pathogenic/likely pathogenic (P/LP) variants, leading to improved management and earlier diagnoses. It is unknown whether such benefits occur when screening broader populations for P/LP ETS variants. This manuscript assesses clinical utility outcomes of a large, unselected, healthcare-based genomic screening program by describing personal and family history of syndrome-related features, risk management behaviors after result disclosure, and rates of relevant post-disclosure diagnoses in patient-participants with P/LP ETS variants. METHODS Observational study of individuals informed of a P/LP variant in MEN1, RET, SDHAF2, SDHB, SDHC, SDHD, or VHL through Geisinger's MyCode Community Health Initiative between June 2016 and October 2019. Electronic health records (EHRs) of participants were evaluated for a report of pre-disclosure personal and self-reported family histories and post-disclosure risk management and diagnoses. RESULTS P/LP variants in genes of interest were identified in 199 of 130,490 (1 in 656) adult Geisinger MyCode patient-participants, 80 of which were disclosed during the study period. Eighty-one percent (n = 65) did not have prior evidence of the result in their EHR and, because they were identified via MyCode, were included in further analyses. Five participants identified via MyCode (8%) had a personal history of syndrome-related features; 16 (25%) had a positive self-reported family history. Time from result disclosure to EHR review was a median of 0.7 years. Post-disclosure, 36 (55.4%) completed a recommended risk management behavior; 11 (17%) were diagnosed with a syndrome-related neoplasm after completing a risk management intervention. CONCLUSIONS Broader screening for pathogenic/likely pathogenic variants associated with endocrine tumor syndromes enables detection of at-risk individuals, leads to the uptake of risk management, and facilitates relevant diagnoses. Further research will be necessary to continue to determine the clinical utility of screening diverse, unselected populations for such variants.
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Affiliation(s)
| | - Nicole M Ortiz
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | | | | | | | | | - Madiha M Alvi
- Endocrinology, Diabetes, and Metabolism, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA
| | | | | | - Nicholas C Purdy
- Geisinger Commonwealth School of Medicine, Scranton, PA, USA.,Otolaryngology, Geisinger, Danville, PA, USA
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA
| | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA.,Heart and Vascular Institute, Geisinger, Danville, PA, USA
| | - Adam H Buchanan
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA
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14
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Hunter JE, Jenkins CL, Bulkley JE, Gilmore MJ, Lee K, Pak CM, Wallace KE, Buchanan AH, Foreman AKM, Freed AS, Goehringer S, Manickam K, Meeks NJL, Ramos EM, Shah N, Steiner RD, Subramanian SL, Trotter T, Webber EM, Williams MS, Goddard KAB, Powell BC. ClinGen's Pediatric Actionability Working Group: Clinical actionability of secondary findings from genome-scale sequencing in children and adolescents. Genet Med 2022; 24:1328-1335. [PMID: 35341655 PMCID: PMC9156571 DOI: 10.1016/j.gim.2022.02.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 10/18/2022] Open
Abstract
PURPOSE Synthesis and curation of evidence regarding the clinical actionability of secondary findings (SFs) from genome-scale sequencing are needed to support decision-making on reporting of these findings. To assess actionability of SFs in children and adolescents, the Clinical Genome Resource established the Pediatric Actionability Working Group (AWG). METHODS The Pediatric AWG modified the framework of the existing Adult AWG, which included production of summary reports of actionability for genes and associated conditions and consensus actionability scores for specific outcome-intervention pairs. Modification of the adult framework for the pediatric setting included accounting for special considerations for reporting presymptomatic or predictive genetic findings in the pediatric context, such as maintaining future autonomy by not disclosing conditions not actionable until adulthood. The Pediatric AWG then applied this new framework to genes and associated conditions with putative actionability. RESULTS As of September 2021, the Pediatric AWG applied the new framework to 70 actionability topics representing 143 genes. Reports and scores are publicly available at www.clinicalgenome.org. CONCLUSION The Pediatric AWG continues to curate gene-condition topics and build an evidence-based resource, supporting clinical communities and decision-makers with policy development on the return of SFs in pediatric populations.
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Affiliation(s)
- Jessica Ezzell Hunter
- Genomics, Ethics, and Translational Research Program, RTI International, ResearchTriangle Park, NC.
| | - Charisma L Jenkins
- Department of Translational and Applied Genomics (TAG), Kaiser Permanente Center for Health Research, Portland, OR
| | - Joanna E Bulkley
- Department of Translational and Applied Genomics (TAG), Kaiser Permanente Center for Health Research, Portland, OR
| | - Marian J Gilmore
- Department of Translational and Applied Genomics (TAG), Kaiser Permanente Center for Health Research, Portland, OR
| | - Kristy Lee
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Christine M Pak
- Department of Translational and Applied Genomics (TAG), Kaiser Permanente Center for Health Research, Portland, OR
| | - Kathleen E Wallace
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Ann Katherine M Foreman
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Amanda S Freed
- Department of Clinical Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA
| | | | - Kandamurugu Manickam
- Division of Genetic and Genomic Medicine, Department of Pediatrics, Nationwide Children's Hospital, Columbus, OH; The Ohio State University College of Medicine, Columbus, OH
| | - Naomi J L Meeks
- Section of Genetics and Metabolism, Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Erin M Ramos
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Neethu Shah
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Robert D Steiner
- School of Medicine and Public Health, University of Wisconsin, Madison, WI
| | | | | | | | | | - Katrina A B Goddard
- Department of Translational and Applied Genomics (TAG), Kaiser Permanente Center for Health Research, Portland, OR
| | - Bradford C Powell
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
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15
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Jones LK, Strande NT, Calvo EM, Chen J, Rodriguez G, McCormick CZ, Hallquist MLG, Savatt JM, Rocha H, Williams MS, Sturm AC, Buchanan AH, Glasgow RE, Martin CL, Rahm AK. A RE-AIM Framework Analysis of DNA-Based Population Screening: Using Implementation Science to Translate Research Into Practice in a Healthcare System. Front Genet 2022; 13:883073. [PMID: 35692820 PMCID: PMC9174580 DOI: 10.3389/fgene.2022.883073] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction: DNA-based population screening has been proposed as a public health solution to identify individuals at risk for serious health conditions who otherwise may not present for medical care. The clinical utility and public health impact of DNA-based population screening is a subject of active investigation. Geisinger, an integrated healthcare delivery system, was one of the first healthcare systems to implement DNA screening programs (MyCode Community Health Initiative (MyCode) and clinical DNA screening pilot) that leverage exome data to identify individuals at risk for developing conditions with potential clinical actionability. Here, we demonstrate the use of an implementation science framework, RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance), to conduct a post-hoc evaluation and report outcomes from these two programs to inform the potential impact of DNA-based population screening. Methods: Reach and Effectiveness outcomes were determined from the MyCode research program, while Adoption and Implementation outcomes were measured using the clinical DNA screening pilot. Reach was defined as the number of patients who were offered and consented to participate in MyCode. Effectiveness of DNA screening was measured by reviewing MyCode program publications and synthesizing findings from themes. Adoption was measured by the total number of DNA screening tests ordered by clinicians at the clinical pilot sites. Implementation was assessed by interviewing a subset of clinical pilot clinicians about the deployment of and recommended adaptations to the pilot that could inform future program dissemination. Results:Reach: As of August 2020, 68% (215,078/316,612) of individuals approached to participate in the MyCode program consented. Effectiveness: Published evidence reported from MyCode demonstrates that DNA screening identifies at-risk individuals more comprehensively than clinical ascertainment based on phenotypes or personal/family history. Adoption: From July 2018 to June 2021, a total of 1,026 clinical DNA screening tests were ordered by 60 clinicians across the three pilot clinic sites. Implementation: Interviews with 14 clinicians practicing at the pilot clinic sites revealed motivation to provide patients with DNA screening results and yielded future implementation strategies. Conclusion: The RE-AIM framework offers a pragmatic solution to organize, analyze, and report outcomes across differently resourced and designed precision health programs that include genomic sequencing and return of clinically actionable genomic information.
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Affiliation(s)
- Laney K. Jones
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Heart and Vascular Institute, Geisinger, Danville, PA, United States
| | - Natasha T. Strande
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Evan M. Calvo
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Jingheng Chen
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | | | | | | | - Juliann M. Savatt
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Heather Rocha
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Marc S. Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Amy C. Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Heart and Vascular Institute, Geisinger, Danville, PA, United States
| | - Adam H. Buchanan
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Russell E. Glasgow
- University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Christa L. Martin
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Alanna Kulchak Rahm
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- *Correspondence: Alanna Kulchak Rahm,
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16
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Goddard KAB, Lee K, Buchanan AH, Powell BC, Hunter JE. Establishing the Medical Actionability of Genomic Variants. Annu Rev Genomics Hum Genet 2022; 23:173-192. [PMID: 35363504 PMCID: PMC10184682 DOI: 10.1146/annurev-genom-111021-032401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Actionability is an important concept in medicine that does not have a well-accepted standard definition, nor is there a general consensus on how to establish it. Medical actionability is often conflated with clinical utility, a related but distinct concept. This lack of clarity contributes to practice variation and inconsistent coverage decisions in genomic medicine, leading to the potential for systematic bias in the use of evidence-based interventions. We clarify how medical actionability and clinical utility are distinct and then discuss the spectrum of actionability, including benefits for the person, the family, and society. We also describe applications across the life course, including prediction, diagnosis, and treatment. Current challenges in assessing the medical actionability of identified genomic variants include gaps in the evidence, limited contexts with practice guidelines, and subjective aspects of medical actionability. A standardized and authoritative assessment of medical actionability is critical to implementing genomic medicine in a fashion that improves population health outcomes and reduces health disparities. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Katrina A B Goddard
- Department of Translational and Applied Genomics, Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA; .,Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA; , .,Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA; .,Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, North Carolina, USA;
| | - Kristy Lee
- Department of Translational and Applied Genomics, Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA; .,Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA; , .,Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA; .,Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, North Carolina, USA;
| | - Adam H Buchanan
- Department of Translational and Applied Genomics, Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA; .,Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA; , .,Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA; .,Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, North Carolina, USA;
| | - Bradford C Powell
- Department of Translational and Applied Genomics, Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA; .,Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA; , .,Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA; .,Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, North Carolina, USA;
| | - Jessica Ezzell Hunter
- Department of Translational and Applied Genomics, Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA; .,Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA; , .,Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA; .,Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, North Carolina, USA;
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17
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Buchanan AH, Manickam K, Meyer MN, Wagner JK, Hallquist MLG, Williams JL, Rahm AK, Williams MS, Chen ZME, Shah CK, Garg TK, Lazzeri AL, Schwartz MLB, Lindbuchler DAM, Fan AL, Leeming R, Servano PO, Smith AL, Vogel VG, Abul-Husn NS, Dewey FE, Lebo MS, Mason-Suares HM, Ritchie MD, Davis FD, Carey DJ, Feinberg DT, Faucett WA, Ledbetter DH, Murray MF. Correction to: Early cancer diagnoses through BRCA1/2 screening of unselected adult biobank participants. Genet Med 2021; 23:2470. [PMID: 34646007 PMCID: PMC9119243 DOI: 10.1038/s41436-021-01304-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Adam H Buchanan
- Geisinger Health System, Danville, PA, USA. .,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA.
| | - Kandamurugu Manickam
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Michelle N Meyer
- Geisinger Health System, Danville, PA, USA.,Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - Jennifer K Wagner
- Geisinger Health System, Danville, PA, USA.,Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - Miranda L G Hallquist
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Janet L Williams
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Alanna Kulchak Rahm
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Marc S Williams
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Zong-Ming E Chen
- Geisinger Health System, Danville, PA, USA.,Laboratory Medicine, Geisinger Health System, Danville, PA, USA
| | - Chaitali K Shah
- Geisinger Health System, Danville, PA, USA.,Radiology, Geisinger Health System, Danville, PA, USA
| | - Tullika K Garg
- Geisinger Health System, Danville, PA, USA.,Department of Urology, Geisinger Health System, Danville, PA, USA
| | - Amanda L Lazzeri
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Marci L B Schwartz
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - D' Andra M Lindbuchler
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Audrey L Fan
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Rosemary Leeming
- Geisinger Health System, Danville, PA, USA.,General Surgery, Geisinger Health System, Danville, PA, USA
| | - Pedro O Servano
- Geisinger Health System, Danville, PA, USA.,Family Medicine, Geisinger Health System, Danville, PA, USA
| | - Ashlee L Smith
- Geisinger Health System, Danville, PA, USA.,Women's Health, Geisinger Health System, Danville, PA, USA
| | - Victor G Vogel
- Geisinger Health System, Danville, PA, USA.,Hematology & Oncology, Geisinger Health System, Danville, PA, USA
| | | | | | - Matthew S Lebo
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA, USA
| | - Heather M Mason-Suares
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA, USA
| | - Marylyn D Ritchie
- Geisinger Health System, Danville, PA, USA.,Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, USA
| | - F Daniel Davis
- Geisinger Health System, Danville, PA, USA.,Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - David J Carey
- Geisinger Health System, Danville, PA, USA.,Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
| | - David T Feinberg
- Geisinger Health System, Danville, PA, USA.,Office of the Chief Executive Officer, Geisinger Health System, Danville, PA, USA
| | - W Andrew Faucett
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - David H Ledbetter
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Michael F Murray
- Geisinger Health System, Danville, PA, USA.,Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
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18
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Fan X, Wynn J, Shang N, Liu C, Fedotov A, Hallquist MLG, Buchanan AH, Williams MS, Smith ME, Hoell C, Rasmussen-Torvik LJ, Peterson JF, Wiesner GL, Murad AM, Jarvik GP, Gordon AS, Rosenthal EA, Stanaway IB, Crosslin DR, Larson EB, Leppig KA, Henrikson NB, Williams JL, Li R, Hebbring S, Weng C, Shen Y, Crew KD, Chung WK. Penetrance of Breast Cancer Susceptibility Genes From the eMERGE III Network. JNCI Cancer Spectr 2021; 5:pkab044. [PMID: 34377931 PMCID: PMC8346699 DOI: 10.1093/jncics/pkab044] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/08/2021] [Accepted: 04/22/2021] [Indexed: 01/03/2023] Open
Abstract
Background Unbiased estimates of penetrance are challenging but critically important to make informed choices about strategies for risk management through increased surveillance and risk-reducing interventions. Methods We studied the penetrance and clinical outcomes of 7 breast cancer susceptibility genes (BRCA1, BRCA2, TP53, CHEK2, ATM, PALB2, and PTEN) in almost 13 458 participants unselected for personal or family history of breast cancer. We identified 242 female participants with pathogenic or likely pathogenic variants in 1 of the 7 genes for penetrance analyses, and 147 women did not previously know their genetic results. Results Out of the 147 women, 32 women were diagnosed with breast cancer at an average age of 52.8 years. Estimated penetrance by age 60 years ranged from 17.8% to 43.8%, depending on the gene. In clinical-impact analysis, 42.3% (95% confidence interval = 31.3% to 53.3%) of women had taken actions related to their genetic results, and 2 new breast cancer cases were identified within the first 12 months after genetic results disclosure. Conclusions Our study provides population-based penetrance estimates for the understudied genes CHEK2, ATM, and PALB2 and highlights the importance of using unselected populations for penetrance studies. It also demonstrates the potential clinical impact of genetic testing to improve health care through early diagnosis and preventative screening.
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Affiliation(s)
- Xiao Fan
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Julia Wynn
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Ning Shang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Alexander Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, NY, USA
| | | | | | | | - Maureen E Smith
- Department of Medicine, Northwestern University, Chicago Feinberg School of Medicine, Chicago, IL, USA
| | - Christin Hoell
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Georgia L Wiesner
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrea M Murad
- Division of Genetic Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Gail P Jarvik
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - Adam S Gordon
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Elisabeth A Rosenthal
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - Ian B Stanaway
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - David R Crosslin
- Department of Biomedical Informatics and Medical Education, University of Washington Medical Center, Seattle, WA, USA
| | - Eric B Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Kathleen A Leppig
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Nora B Henrikson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | - Rongling Li
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic, Marshfield, WI, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Katherine D Crew
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
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19
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Savatt JM, Deckard NM, Thone G, McDonald WS, Alvi MM, Purdy NC, Lindemann TL, Sturm AC, Buchanan AH. Experience Completing Population Screening for Variants Associated With Endocrine Tumor Syndromes in a Large, Healthcare-Based Cohort. J Endocr Soc 2021. [PMCID: PMC8090758 DOI: 10.1210/jendso/bvab048.1026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Abstract
Hereditary endocrine tumor syndromes (ETS) including Multiple Endocrine Neoplasia Types 1 and 2 (MEN1 and MEN2), von Hippel-Lindau (VHL), and Hereditary Paraganglioma and Pheochromocytoma syndromes (PGL/PCC) have a collective prevalence of 1 in 8500. In current practice, patients’ personal and family histories are used to determine whether genetic testing for ETS is warranted. Population genetic screening for other actionable conditions implies that current practice can be enhanced to identify individuals with genetic variants and that identification of such individuals can lead to improvements in risk management and early-onset diagnoses. It is unknown whether such benefits occur when screening for ETS risk. We report on the rate of syndrome-related features and post-disclosure risk management in patients informed of a pathogenic/likely pathogenic (P/LP) variant in a gene associated with an ETS through the MyCode Community Health Initiative (MyCode).
MyCode is a biobank of individuals from a health system who consent to health-related research and return of clinically actionable results. Exome sequences are analyzed for P/LP variants in actionable genes, confirmed by a clinical laboratory, and disclosed to participants and their providers. All participants are offered follow-up with a genetics provider post-disclosure. Here, we focus on participants that received a P/LP variant in MEN1, RET, VHL, or an SDHx gene from June 2016-October 2019. From May-July 2020 we performed dual, manual review of participants’ electronic health records to assess personal and family histories, risk management behaviors, and post-disclosure diagnoses of endocrine neoplasms.
Of 87,493 participants with available exome data, P/LP variants in genes of interest were identified in and disclosed to 80 participants (65% female, 99% self-reported White race, 99% self-reported non-Hispanic ethnicity, median age 57 years at results disclosure, median time since disclosure 2 years). Eighty-one percent of participants (n=65) did not have a prior diagnosis of an ETS and were included in additional analyses. Five participants (8%) had a personal history of syndrome-related features; 16 (25%) had a positive family history. Only seven (11%) met existing clinical testing criteria pre-disclosure. Post-disclosure, 37 (57%) completed at least one recommended risk management behavior; 11 of these (17%) were diagnosed with a syndrome-related neoplasm (e.g., medullary thyroid cancer).
Results of population screening in a healthcare cohort suggest genetic variants associated with ETS risk are more common than previously reported (1 in 1094). Though additional studies on clinical utility are needed, these results suggest that screening healthcare populations for genetic risk can enable detection of individuals at risk for ETS, lead to uptake of risk management, and facilitate relevant clinical diagnoses.
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20
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Hallquist MLG, Tricou EP, Ormond KE, Savatt JM, Coughlin CR, Faucett WA, Hercher L, Levy HP, O'Daniel JM, Peay HL, Stosic M, Smith M, Uhlmann WR, Wand H, Wain KE, Buchanan AH. Application of a framework to guide genetic testing communication across clinical indications. Genome Med 2021; 13:71. [PMID: 33926532 PMCID: PMC8086064 DOI: 10.1186/s13073-021-00887-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 04/14/2021] [Indexed: 12/20/2022] Open
Abstract
Background Genetic information is increasingly relevant across healthcare. Traditional genetic counseling (GC) may limit access to genetic information and may be more information and support than some individuals need. We report on the application and clinical implications of a framework to consistently integrate genetics expertise where it is most useful to patients. Methods The Clinical Genome Resource’s (ClinGen) Consent and Disclosure Recommendations (CADRe) workgroup designed rubrics to guide pre- and post-genetic test communication. Using a standard set of testing indications, pre- and post-test rubrics were applied to 40 genetic conditions or testing modalities with diverse features, including variability in levels of penetrance, clinical actionability, and evidence supporting a gene-disease relationship. Final communication recommendations were reached by group consensus. Results Communication recommendations were determined for 478 unique condition-indication or testing-indication pairs. For half of the conditions and indications (238/478), targeted discussions (moderate communication depth) were the recommended starting communication level for pre- and post-test conversations. Traditional GC was recommended pre-test for adult-onset neurodegenerative conditions for individuals with no personal history and post-test for most conditions when genetic testing revealed a molecular diagnosis as these situations are likely higher in complexity and uncertainty. A brief communication approach was recommended for more straightforward conditions and indications (e.g., familial hypercholesterolemia; familial variant testing). Conclusions The CADRe recommendations provide guidance for clinicians in determining the depth of pre- and post-test communication, strategically aligning the anticipated needs of patients with the starting communication approach. Shorter targeted discussions or brief communications are suggested for many tests and indications. Longer traditional GC consultations would be reserved for patients with more complex and uncertain situations where detailed information, education, and psychological support can be most beneficial. Future studies of the CADRe communication framework will be essential for determining if CADRe-informed care supports quality patient experience while improving access to genetic information across healthcare. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00887-x.
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Affiliation(s)
| | - Eric P Tricou
- Geisinger, 100 N Academy Blvd, Danville, PA, 17822, USA.,Department of Genetics and Stanford Center for Biomedical Ethics, Center for Academic Medicine, Stanford University School of Medicine, 453 Quarry Road, Stanford, CA, 94304, USA
| | - Kelly E Ormond
- Department of Genetics and Stanford Center for Biomedical Ethics, Center for Academic Medicine, Stanford University School of Medicine, 453 Quarry Road, Stanford, CA, 94304, USA
| | | | - Curtis R Coughlin
- University of Colorado Department of Pediatrics and Center for Bioethics and Humanities, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | | | - Laura Hercher
- Sarah Lawrence College Joan H. Marks Graduate Program in Human Genetics, 1 Mead Way, Bronxville, NY, 10708, USA
| | - Howard P Levy
- Johns Hopkins University Division of General Internal Medicine and McKusick-Nathans Institute of Genetic Medicine, 0753 Falls Rd, Suite 325, Lutherville, MD, USA
| | - Julianne M O'Daniel
- Department of Genetics Genetic Medicine Building, University of North Carolina at Chapel Hill, 120 Mason Farm Rd, CB # 7264, Chapel Hill, NC, 27514, USA
| | - Holly L Peay
- RTI International, 3040 E Cornwallis Rd, Research Triangle Park, NC, 27709, USA
| | - Melissa Stosic
- DotLab, 780 E Main St, Suite 1, Branford, CT, 06405, USA
| | - Maureen Smith
- Northwestern University Feinberg School of Medicine, 310 E. Superior St., Chicago, IL, 60611-3008, USA
| | - Wendy R Uhlmann
- Department of Internal Medicine, Division of Genetic Medicine, University of Michigan Medicine, 300 North Ingalls, NI3 A03, SPC 5419, Ann Arbor, MI, 48109-5419, USA
| | - Hannah Wand
- Department of Genetics and Stanford Center for Biomedical Ethics, Center for Academic Medicine, Stanford University School of Medicine, 453 Quarry Road, Stanford, CA, 94304, USA
| | - Karen E Wain
- Geisinger, 100 N Academy Blvd, Danville, PA, 17822, USA
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21
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Schwartz MLB, Buchanan AH, Hallquist MLG, Haggerty CM, Sturm AC. Genetic counseling for patients with positive genomic screening results: Considerations for when the genetic test comes first. J Genet Couns 2021; 30:634-644. [PMID: 33786929 DOI: 10.1002/jgc4.1386] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/18/2020] [Accepted: 12/31/2020] [Indexed: 01/06/2023]
Abstract
Emerging genetic testing delivery models have enabled individuals to receive testing without a medical indication. This article will highlight key considerations for patient care in the setting of adult patients with positive results for monogenic disease identified through genomic screening. Suggestions for how to adapt genetic counseling to a genomic screening population will encompass topics such as phenotyping, risk assessments, and the use of existing guidelines and resources. Case examples will demonstrate principles of genotype-first patient care.
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Affiliation(s)
| | | | | | - Christopher M Haggerty
- The Heart Institute, Geisinger, Danville, PA, USA.,Department of Translational Data Science and Informatics, Geisinger, Danville, PA, USA
| | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
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22
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Carruth ED, Beer D, Alsaid A, Schwartz MLB, McMinn M, Kelly MA, Buchanan AH, Nevius CD, Calkins H, James CA, Murray B, Tichnell C, Matsumura ME, Kirchner HL, Fornwalt BK, Sturm AC, Haggerty CM. Clinical Findings and Diagnostic Yield of Arrhythmogenic Cardiomyopathy Through Genomic Screening of Pathogenic or Likely Pathogenic Desmosome Gene Variants. Circ Genom Precis Med 2021; 14:e003302. [PMID: 33684294 DOI: 10.1161/circgen.120.003302] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Genomic screening holds great promise for presymptomatic identification of hidden disease, and prevention of dramatic events, including sudden cardiac death associated with arrhythmogenic cardiomyopathy (ACM). Herein, we present findings from clinical follow-up of carriers of ACM-associated pathogenic/likely pathogenic desmosome variants ascertained through genomic screening. METHODS Of 64 548 eligible participants in Geisinger MyCode Genomic Screening and Counseling program (2015-present), 92 individuals (0.14%) identified with pathogenic/likely pathogenic desmosome variants by clinical laboratory testing were referred for evaluation. We reviewed preresult medical history, patient-reported family history, and diagnostic testing results to assess both arrhythmogenic right ventricular cardiomyopathy and left-dominant ACM. RESULTS One carrier had a prior diagnosis of dilated cardiomyopathy with arrhythmia; no other related diagnoses or diagnostic family history criteria were reported. Fifty-nine carriers (64%) had diagnostic testing in follow-up. Excluding the variant, 21/59 carriers satisfied at least one arrhythmogenic right ventricular cardiomyopathy task force criterion, 11 (52%) of whom harbored DSP variants, but only 5 exhibited multiple criteria. Six (10%) carriers demonstrated evidence of left-dominant ACM, including high rates of atypical late gadolinium enhancement by magnetic resonance imaging and nonsustained ventricular tachycardia. Two individuals received new cardiomyopathy diagnoses and received defibrillators for primary prevention. CONCLUSIONS Genomic screening for pathogenic/likely pathogenic variants in desmosome genes can uncover both left- and right-dominant ACM. Findings of overt cardiomyopathy were limited but were most common in DSP-variant carriers and notably absent in PKP2-variant carriers. Consideration of the pathogenic/likely pathogenic variant as a major criterion for diagnosis is inappropriate in the setting of genomic screening.
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Affiliation(s)
- Eric D Carruth
- Department of Translational Data Science and Informatics (E.D.C., C.D.N., B.K.F., C.M.H.), Geisinger, Danville, PA
| | - Dominik Beer
- The Heart Institute (D.B., A.A., M.E.M., B.K.F., A.C.S., C.M.H.), Geisinger, Danville, PA
| | - Amro Alsaid
- The Heart Institute (D.B., A.A., M.E.M., B.K.F., A.C.S., C.M.H.), Geisinger, Danville, PA
| | - Marci L B Schwartz
- Genomic Medicine Institute (M.L.B.S., M.M., M.A.K., A.H.B., A.C.S.), Geisinger, Danville, PA
| | - Megan McMinn
- Genomic Medicine Institute (M.L.B.S., M.M., M.A.K., A.H.B., A.C.S.), Geisinger, Danville, PA
| | - Melissa A Kelly
- Genomic Medicine Institute (M.L.B.S., M.M., M.A.K., A.H.B., A.C.S.), Geisinger, Danville, PA
| | - Adam H Buchanan
- Genomic Medicine Institute (M.L.B.S., M.M., M.A.K., A.H.B., A.C.S.), Geisinger, Danville, PA
| | - Christopher D Nevius
- Department of Translational Data Science and Informatics (E.D.C., C.D.N., B.K.F., C.M.H.), Geisinger, Danville, PA
| | - Hugh Calkins
- Division of Cardiology, Department of Medicine, Johns Hopkins Medical Center, Baltimore, MD (H.C., C.A.J., B.M., C.T.)
| | - Cynthia A James
- Division of Cardiology, Department of Medicine, Johns Hopkins Medical Center, Baltimore, MD (H.C., C.A.J., B.M., C.T.)
| | - Brittney Murray
- Division of Cardiology, Department of Medicine, Johns Hopkins Medical Center, Baltimore, MD (H.C., C.A.J., B.M., C.T.)
| | - Crystal Tichnell
- Division of Cardiology, Department of Medicine, Johns Hopkins Medical Center, Baltimore, MD (H.C., C.A.J., B.M., C.T.)
| | - Martin E Matsumura
- The Heart Institute (D.B., A.A., M.E.M., B.K.F., A.C.S., C.M.H.), Geisinger, Danville, PA
| | - H Lester Kirchner
- Department of Population Health Sciences (H.L.K.), Geisinger, Danville, PA
| | - Brandon K Fornwalt
- Department of Translational Data Science and Informatics (E.D.C., C.D.N., B.K.F., C.M.H.), Geisinger, Danville, PA.,The Heart Institute (D.B., A.A., M.E.M., B.K.F., A.C.S., C.M.H.), Geisinger, Danville, PA.,Department of Radiology (B.K.F.), Geisinger, Danville, PA
| | - Amy C Sturm
- The Heart Institute (D.B., A.A., M.E.M., B.K.F., A.C.S., C.M.H.), Geisinger, Danville, PA.,Genomic Medicine Institute (M.L.B.S., M.M., M.A.K., A.H.B., A.C.S.), Geisinger, Danville, PA
| | - Christopher M Haggerty
- Department of Translational Data Science and Informatics (E.D.C., C.D.N., B.K.F., C.M.H.), Geisinger, Danville, PA.,The Heart Institute (D.B., A.A., M.E.M., B.K.F., A.C.S., C.M.H.), Geisinger, Danville, PA
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23
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Campbell-Salome G, Buchanan AH, Hallquist MLG, Rahm AK, Rocha H, Sturm AC. Uncertainty management for individuals with Lynch Syndrome: Identifying and responding to healthcare barriers. Patient Educ Couns 2021; 104:403-412. [PMID: 32782180 DOI: 10.1016/j.pec.2020.07.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 04/24/2020] [Accepted: 07/21/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVE Examine the uncertainty management process of individuals with Lynch syndrome (LS). METHODS 19 phone interviews were conducted with individuals with LS. The interview guide included questions on family communication, risk perceptions, and uncertainty management. Data were analyzed using the constant comparison method to code for emergent themes. RESULTS Qualitative analysis found individuals with LS tried to manage their uncertainty through preventive care, but were often confounded by healthcare barriers. Healthcare barriers included cost and insurance issues, absence of coordinated care, insufficient provider knowledge, and lack of patient-centered communication. Participants reported increased uncertainty and anxiety due to these barriers and used alternative uncertainty management strategies such as advocating for themselves with providers, seeking information online, and communicating with family for emotional support. CONCLUSION Healthcare barriers identified in this study exacerbated uncertainty and anxiety for individuals with LS and challenged their ability to engage in preventive care. In response, participants used alternative uncertainty management strategies to reduce their uncertainty, which may have unintended negative consequences. PRACTICE IMPLICATIONS Findings support the need for providers to partner with specialists in genetics and/or LS to better care for individuals with LS. Findings highlight opportunities for interventions in healthcare to better support individuals with LS.
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Affiliation(s)
| | | | | | - Alanna K Rahm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | - Heather Rocha
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
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24
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Campbell-Salome G, Jones LK, Masnick MF, Walton NA, Ahmed CD, Buchanan AH, Brangan A, Esplin ED, Kann DG, Ladd IG, Kelly MA, Kindt I, Kirchner HL, McGowan MP, McMinn MN, Morales A, Myers KD, Oetjens MT, Rahm AK, Schmidlen TJ, Sheldon A, Simmons E, Snir M, Strande NT, Walters NL, Wilemon K, Williams MS, Gidding SS, Sturm AC. Developing and Optimizing Innovative Tools to Address Familial Hypercholesterolemia Underdiagnosis: Identification Methods, Patient Activation, and Cascade Testing for Familial Hypercholesterolemia. Circ Genom Precis Med 2021; 14:e003120. [PMID: 33480803 PMCID: PMC7892261 DOI: 10.1161/circgen.120.003120] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. Methods and Results: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. Conclusions: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.
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Affiliation(s)
- Gemme Campbell-Salome
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Laney K Jones
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Max F Masnick
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Nephi A Walton
- Intermountain Precision Genomics, Intermountain Healthcare, St. George, UT (N.A.W.)
| | - Catherine D Ahmed
- The Familial Hypercholesterolemia Foundation, Pasadena, CA (C.D.A., M.P.M., K.D.M., A.S., K.W.)
| | - Adam H Buchanan
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Andrew Brangan
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | | | - David G Kann
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Ilene G Ladd
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Melissa A Kelly
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | | | - H Lester Kirchner
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Mary P McGowan
- The Familial Hypercholesterolemia Foundation, Pasadena, CA (C.D.A., M.P.M., K.D.M., A.S., K.W.).,Geisel School of Medicine at Dartmouth, Dartmouth Hitchcock Medical Center, Lebanon, NH (M.P.M.)
| | - Megan N McMinn
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Ana Morales
- Invitae, San Francisco, CA (E.D.E., A.M., E.S., M.S.)
| | - Kelly D Myers
- The Familial Hypercholesterolemia Foundation, Pasadena, CA (C.D.A., M.P.M., K.D.M., A.S., K.W.)
| | - Matthew T Oetjens
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Alanna Kulchak Rahm
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Tara J Schmidlen
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Amanda Sheldon
- The Familial Hypercholesterolemia Foundation, Pasadena, CA (C.D.A., M.P.M., K.D.M., A.S., K.W.)
| | | | - Moran Snir
- Invitae, San Francisco, CA (E.D.E., A.M., E.S., M.S.)
| | - Natasha T Strande
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Nicole L Walters
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Katherine Wilemon
- The Familial Hypercholesterolemia Foundation, Pasadena, CA (C.D.A., M.P.M., K.D.M., A.S., K.W.)
| | - Marc S Williams
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Samuel S Gidding
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
| | - Amy C Sturm
- Geisinger, Danville, PA (G.C.-S., L.K.J., M.F.M., A.H.B., A.B., D.G.K., I.G.L., M.A.K., H.L.K., M.N.M., M.T.O., A.K.R., T.J.S., N.T.S., N.L.W., M.S.W., S.S.G., A.C.S.)
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Lennon AM, Buchanan AH, Kinde I, Warren A, Honushefsky A, Cohain AT, Ledbetter DH, Sanfilippo F, Sheridan K, Rosica D, Adonizio CS, Hwang HJ, Lahouel K, Cohen JD, Douville C, Patel AA, Hagmann LN, Rolston DD, Malani N, Zhou S, Bettegowda C, Diehl DL, Urban B, Still CD, Kann L, Woods JI, Salvati ZM, Vadakara J, Leeming R, Bhattacharya P, Walter C, Parker A, Lengauer C, Klein A, Tomasetti C, Fishman EK, Hruban RH, Kinzler KW, Vogelstein B, Papadopoulos N. Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention. Science 2020; 369:eabb9601. [PMID: 32345712 PMCID: PMC7509949 DOI: 10.1126/science.abb9601] [Citation(s) in RCA: 288] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 04/23/2020] [Indexed: 12/12/2022]
Abstract
Cancer treatments are often more successful when the disease is detected early. We evaluated the feasibility and safety of multicancer blood testing coupled with positron emission tomography-computed tomography (PET-CT) imaging to detect cancer in a prospective, interventional study of 10,006 women not previously known to have cancer. Positive blood tests were independently confirmed by a diagnostic PET-CT, which also localized the cancer. Twenty-six cancers were detected by blood testing. Of these, 15 underwent PET-CT imaging and nine (60%) were surgically excised. Twenty-four additional cancers were detected by standard-of-care screening and 46 by neither approach. One percent of participants underwent PET-CT imaging based on false-positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multicancer blood testing combined with PET-CT can be safely incorporated into routine clinical care, in some cases leading to surgery with intent to cure.
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Affiliation(s)
- Anne Marie Lennon
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Medicine Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | | | - Isaac Kinde
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | - Andrew Warren
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
- Third Rock Ventures, LLC, 29 Newbury Street Boston, MA 02116, USA
| | | | - Ariella T Cohain
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | | | - Fred Sanfilippo
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, 100 Woodruff Circle Atlanta, GA 30322, USA
| | | | | | - Christian S Adonizio
- Geisinger, 100 N. Academy Avenue Danville, PA 17822, USA
- Geisinger Cancer Institute, 100 N. Academy Avenue Danville, PA 17822, USA
| | - Hee Jung Hwang
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | - Kamel Lahouel
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Joshua D Cohen
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Christopher Douville
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Aalpen A Patel
- Geisinger, 100 N. Academy Avenue Danville, PA 17822, USA
| | - Leonardo N Hagmann
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | | | - Nirav Malani
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | - Shibin Zhou
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Chetan Bettegowda
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Neurosurgery, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - David L Diehl
- Geisinger, 100 N. Academy Avenue Danville, PA 17822, USA
| | - Bobbi Urban
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | | | - Lisa Kann
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | - Julie I Woods
- Geisinger, 100 N. Academy Avenue Danville, PA 17822, USA
| | | | | | | | | | - Carroll Walter
- Geisinger, 100 N. Academy Avenue Danville, PA 17822, USA
| | - Alex Parker
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
| | - Christoph Lengauer
- Thrive Earlier Detection Corp., 38 Sidney Street Cambridge, MA 02139, USA
- Third Rock Ventures, LLC, 29 Newbury Street Boston, MA 02116, USA
| | - Alison Klein
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Epidemiology, the Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street Baltimore, MD 21205, USA
| | - Cristian Tomasetti
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Biostatistics, the Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street Baltimore, MD 21205, USA
| | - Elliot K Fishman
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Radiology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA
| | - Ralph H Hruban
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Pathology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Kenneth W Kinzler
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Bert Vogelstein
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
| | - Nickolas Papadopoulos
- Department of Oncology, the Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.
- The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- The Ludwig Center, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
- Department of Pathology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA
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26
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Buchanan AH, Lester Kirchner H, Schwartz MLB, Kelly MA, Schmidlen T, Jones LK, Hallquist MLG, Rocha H, Betts M, Schwiter R, Butry L, Lazzeri AL, Frisbie LR, Rahm AK, Hao J, Willard HF, Martin CL, Ledbetter DH, Williams MS, Sturm AC. Clinical outcomes of a genomic screening program for actionable genetic conditions. Genet Med 2020; 22:1874-1882. [PMID: 32601386 PMCID: PMC7605431 DOI: 10.1038/s41436-020-0876-4] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 06/12/2020] [Accepted: 06/12/2020] [Indexed: 01/07/2023] Open
Abstract
Purpose Three genetic conditions—hereditary breast and ovarian cancer syndrome, Lynch syndrome, and familial hypercholesterolemia—have tier 1 evidence for interventions that reduce morbidity and mortality, prompting proposals to screen unselected populations for these conditions. We examined the impact of genomic screening on risk management and early detection in an unselected population. Methods Observational study of electronic health records (EHR) among individuals in whom a pathogenic/likely pathogenic variant in a tier 1 gene was discovered through Geisinger’s MyCode project. EHR of all eligible participants was evaluated for a prior genetic diagnosis and, among participants without such a diagnosis, relevant personal/family history, postdisclosure clinical diagnoses, and postdisclosure risk management. Results Eighty-seven percent of participants (305/351) did not have a prior genetic diagnosis of their tier 1 result. Of these, 65% had EHR evidence of relevant personal and/or family history of disease. Of 255 individuals eligible to have risk management, 70% (n = 179) had a recommended risk management procedure after results disclosure. Thirteen percent of participants (41/305) received a relevant clinical diagnosis after results disclosure. Conclusion Genomic screening programs can identify previously unrecognized individuals at increased risk of cancer and heart disease and facilitate risk management and early cancer detection.
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Affiliation(s)
| | - H Lester Kirchner
- Department of Population Health Sciences, Geisinger, Danville, PA, USA
| | | | | | - Tara Schmidlen
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | - Laney K Jones
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | | | - Heather Rocha
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | - Megan Betts
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | | | - Loren Butry
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | | | | | | | - Jing Hao
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Department of Population Health Sciences, Geisinger, Danville, PA, USA
| | - Huntington F Willard
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Genome Medical, Durham, NC, USA
| | - Christa L Martin
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Autism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
| | - David H Ledbetter
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Autism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
| | | | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
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Hooker G, Allain DC, Buchanan AH, Care M, Conway L, Cumming A, Dixon S, Paulyson-Nuñez K, Riordan S, Williams J. An analysis of growth in the genetic counseling profession 2009 to 2019. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.e13526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e13526 Background: Genetic counselors (GCs) are health care professionals who provide support to patients and physicians navigating the rapidly changing landscape of genetic testing and the genetic underpinnings of disease. Increased demand for genetic counseling services prompted an analysis of changes in the workforce over the last decade. Methods: To quantify the growth in the GC profession in the U.S and Canada in the last decade, we acquired data from the American Board of Genetic Counseling, National Society of Genetic Counselors, Canadian Association of Genetic Counselors, Accreditation Council for Genetic Counseling and Association of Genetic Counseling Program Directors. Results: Between 2009 and 2019, the workforce more than doubled, growing from 2,205 ABGC-certified GCs to 5,172. In Canada, the number of CAGC-certified GCs has grown from 211 in 2009 to 327 in 2019. Growth is striking in cancer genetic counseling; the proportion of GCs providing direct patient care in North America who report cancer as a primary specialty has increased from 25% in 2008 to 50% in 2019. Similar growth has been seen in training opportunities for GCs. The number of accredited graduate programs has increased from 33 in 2009 to 51 in 2019, with several more in development. Combined, these programs had 464 training slots in 2019, up from 223 in 2009. In 2019, 1569 applicants registered for the applicant match for training. Training opportunities and clinical genetic counselors are concentrated in large metropolitan areas, with over half of GCs working in 28 metro regions. GC services in rural areas are increasingly provided remotely via telemedicine, with 59% of GCs in direct patient care in 2018 reporting providing services by phone and 19% using web or video services to deliver care. In cancer genetics, about 50% of GCs nationwide reported in 2018 their 3rd next available appointment for new patients was within 14 days. Conclusions: The past decade has seen significant growth in the numbers of GCs and more patients have access to GCs than a decade ago. Reimbursement for services remains a significant barrier to access. Further research is warranted to understand additional political, administrative and logistical facilitators and barriers to providing care to all who need genetics services.
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Jones C, Parker A, Warren A, Vanenkevort EA, Gupta M, Lagerman B, Honushefsky AM, Cohain A, Leeming R, O'Broin-Lennon AM, Buchanan AH. Mammography utilization among women with a negative circulating tumor DNA-based early cancer detection test. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.1563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
1563 Background: Blood-based tests may enable minimally invasive detection of multiple cancer types. One such test, CancerSEEK, employs ctDNA and protein biomarkers for this purpose. Test performance has been evaluated in women without a history of cancer in an ongoing prospective study called DETECT-A. The introduction of such blood tests holds promise, and their future utility lies in augmenting, not displacing, standard-of-care (SOC) cancer screening. One important safety concern is that a negative test result could provide false reassurance that discourages adherence to SOC cancer screening. To investigate this possibility, we studied delivery of mammography to DETECT-A participants before and after receipt of a negative CancerSEEK result. Methods: DETECT-A screened 10,000 women aged 65-75 using CancerSEEK. Participants completed a survey about cancer screening at enrollment and at one-year post-enrollment. We analyzed only those participants who had received a negative CancerSEEK result, were insured by Geisinger Health Plan (GHP), and had completed both surveys. GHP claims data were used to identify mammograms performed within one year prior-to and post-enrollment. Overall utilization was determined by combining claims and survey data at enrollment and one-year post-enrollment. In addition to comparing SOC screening rates pre- versus post-testing, we evaluated the impact of primary care physician (PCP) type (Geisinger versus any other institution), as screening reminder mechanisms differ between institutions. Results: Of the 2,241 participants who met analysis criteria, 73.6% (n = 1,650) had a mammogram in the year before enrollment while a significantly great number (79.3%, n = 1,777) did so during the one-year follow-up (χ2(1) = 59.05, p < 0.001). At enrollment, there were 591 participants who had not had a mammogram completed in the previous year, but 404 (68.4%) of them did have a mammogram during the one-year follow-up. The rate of change in mammography utilization did not differ between those who had a Geisinger versus a non-Geisinger PCP (χ2(2) = 1.83, p = 0.40). Conclusions: Participants in a study using a novel blood test for earlier cancer detection had a significantly higher rate of annual mammography after study enrollment and testing. These results indicate that introduction of a minimally invasive ctDNA and protein biomarker-based cancer screening test may engender greater, not lesser, utilization of SOC cancer screening. Further study is required to understand the root causes of increased utilization in this context.
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Affiliation(s)
| | - Alex Parker
- Thrive Earlier Detection Corp., Cambridge, MA
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29
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Savatt JM, Wagner JK, Joffe S, Rahm AK, Williams MS, Bradbury AR, Davis FD, Hergenrather J, Hu Y, Kelly MA, Kirchner HL, Meyer MN, Mozersky J, O'Dell SM, Pervola J, Seeley A, Sturm AC, Buchanan AH. Pediatric reporting of genomic results study (PROGRESS): a mixed-methods, longitudinal, observational cohort study protocol to explore disclosure of actionable adult- and pediatric-onset genomic variants to minors and their parents. BMC Pediatr 2020; 20:222. [PMID: 32414353 PMCID: PMC7227212 DOI: 10.1186/s12887-020-02070-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/06/2020] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Exome and genome sequencing are routinely used in clinical care and research. These technologies allow for the detection of pathogenic/likely pathogenic variants in clinically actionable genes. However, fueled in part by a lack of empirical evidence, controversy surrounds the provision of genetic results for adult-onset conditions to minors and their parents. We have designed a mixed-methods, longitudinal cohort study to collect empirical evidence to advance this debate. METHODS Pediatric participants in the Geisinger MyCode® Community Health Initiative with available exome sequence data will have their variant files assessed for pathogenic/likely pathogenic variants in 60 genes designated as actionable by MyCode. Eight of these genes are associated with adult-onset conditions (Hereditary Breast and Ovarian Cancer Syndrome (HBOC), Lynch syndrome, MUTYH-associated polyposis, HFE-Associated Hereditary Hemochromatosis), while the remaining genes have pediatric onset. Prior to clinical confirmation of results, pediatric MyCode participants and their parents/legal guardians will be categorized into three study groups: 1) those with an apparent pathogenic/likely pathogenic variant in a gene associated with adult-onset disease, 2) those with an apparent pathogenic/likely pathogenic variant in a gene associated with pediatric-onset disease or with risk reduction interventions that begin in childhood, and 3) those with no apparent genomic result who are sex- and age-matched to Groups 1 and 2. Validated and published quantitative measures, semi-structured interviews, and a review of electronic health record data conducted over a 12-month period following disclosure of results will allow for comparison of psychosocial and behavioral outcomes among parents of minors (ages 0-17) and adolescents (ages 11-17) in each group. DISCUSSION These data will provide guidance about the risks and benefits of informing minors and their family members about clinically actionable, adult-onset genetic conditions and, in turn, help to ensure these patients receive care that promotes physical and psychosocial health. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03832985. Registered 6 February 2019.
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Affiliation(s)
| | - Jennifer K Wagner
- Center for Translational Bioethics and Health Care Policy, Geisinger, Danville, PA, USA
| | - Steven Joffe
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | | | - Angela R Bradbury
- Department of Medicine, Division of Hematology-Oncology, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA, USA
| | - F Daniel Davis
- Center for Translational Bioethics and Health Care Policy, Geisinger, Danville, PA, USA
| | - Julie Hergenrather
- Department of Psychiatry and Behavioral Health, Geisinger, Danville, PA, USA
| | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville, PA, USA
| | | | - H Lester Kirchner
- Department of Population Health Sciences, Geisinger, Danville, PA, USA
| | - Michelle N Meyer
- Center for Translational Bioethics and Health Care Policy, Geisinger, Danville, PA, USA
| | - Jessica Mozersky
- Bioethics Research Center, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Sean M O'Dell
- Department of Psychiatry and Behavioral Health, Geisinger, Danville, PA, USA
- Department of Population Health Sciences, Geisinger, Danville, PA, USA
| | - Josie Pervola
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | - Andrea Seeley
- Department of Pediatrics, Geisinger, Danville, PA, USA
| | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
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Lynch JA, Sharp RR, Aufox SA, Bland ST, Blout C, Bowen DJ, Buchanan AH, Halverson C, Harr M, Hebbring SJ, Henrikson N, Hoell C, Holm IA, Jarvik G, Kullo IJ, Kochan DC, Larson EB, Lazzeri A, Leppig KA, Madden J, Marasa M, Myers MF, Peterson J, Prows CA, Kulchak Rahm A, Ralston J, Milo Rasouly H, Scrol A, Smith ME, Sturm A, Stuttgen K, Wiesner G, Williams MS, Wynn J, Williams JL. Understanding the Return of Genomic Sequencing Results Process: Content Review of Participant Summary Letters in the eMERGE Research Network. J Pers Med 2020; 10:jpm10020038. [PMID: 32413979 PMCID: PMC7354464 DOI: 10.3390/jpm10020038] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/06/2020] [Accepted: 05/09/2020] [Indexed: 01/26/2023] Open
Abstract
A challenge in returning genomic test results to research participants is how best to communicate complex and clinically nuanced findings to participants in a manner that is scalable to the large numbers of participants enrolled. The purpose of this study was to examine the features of genetic results letters produced at each Electronic Medical Records and Genomics (eMERGE3) Network site to assess their readability and content. Letters were collected from each site, and a qualitative analysis of letter content and a quantitative analysis of readability statistics were performed. Because letters were produced independently at each eMERGE site, significant heterogeneity in readability and content was found. The content of letters varied widely from a baseline of notifying participants that results existed to more detailed information about positive or negative results, as well as materials for sharing with family members. Most letters were significantly above the Centers for Disease Control-suggested reading level for health communication. While continued effort should be applied to make letters easier to understand, the ongoing challenge of explaining complex genomic information, the implications of negative test results, and the uncertainty that comes with some types of test and result makes simplifying letter text challenging.
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Affiliation(s)
- John A. Lynch
- Department of Communication, University of Cincinnati, Cincinnati, OH 45220, USA
- Correspondence:
| | | | - Sharon A. Aufox
- Center for Genomic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; (S.A.A.); (C.H.)
| | - Sarah T. Bland
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.T.B.); (J.P.)
| | - Carrie Blout
- Harvard Pilgrim Health Care Institute, Boston, MA 02115, USA;
| | - Deborah J. Bowen
- Department of Bioethics and Humanities, School of Medicine, University of Washington, Seattle, WA 98195, USA;
| | - Adam H. Buchanan
- Genomic Medicine Institute, Geisinger, Danville, PA 17822, USA; (A.H.B.); (A.L.); (A.K.R.); (A.S.); (M.S.W.); (J.L.W.)
| | - Colin Halverson
- School of Medicine, Indiana University-Purdue University, Indianapolis, IN 46202, USA;
| | - Margaret Harr
- Center for Applied Genomics, Children’s Hospital of Pennsylvania, Philadelphia, PA 19104, USA;
| | | | - Nora Henrikson
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente of Washington, Seattle, WA 98101, USA; (N.H.); (E.B.L.); (J.R.); (A.S.)
- Department of Health Services, School of Public Health, University of Washington, Seattle, WA 98195, USA
| | - Christin Hoell
- Center for Genomic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; (S.A.A.); (C.H.)
| | - Ingrid A. Holm
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA;
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, USA;
| | - Gail Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA 98195, USA;
| | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55902, USA; (I.J.K.); (D.C.K.); (K.S.)
| | - David C. Kochan
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55902, USA; (I.J.K.); (D.C.K.); (K.S.)
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente of Washington, Seattle, WA 98101, USA; (N.H.); (E.B.L.); (J.R.); (A.S.)
- Division of General Internal Medicine, University of Washington, Seattle, WA 98195, USA
| | - Amanda Lazzeri
- Genomic Medicine Institute, Geisinger, Danville, PA 17822, USA; (A.H.B.); (A.L.); (A.K.R.); (A.S.); (M.S.W.); (J.L.W.)
| | - Kathleen A. Leppig
- Genetic Services, Kaiser Permanente of Washington, Seattle, WA 98101, USA;
- University of Washington Biomedical and Health Informatics, Seattle, WA 98195, USA
| | - Jill Madden
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, USA;
| | - Maddalena Marasa
- Department of Medicine, Division of Nephrology, Columbia University Irving Medical Center, New York, NY 10032, USA; (M.M.); (H.M.R.)
| | - Melanie F. Myers
- College of Medicine, University of Cincinnati, Cincinnati, OH 45220, USA;
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati, Cincinnati, OH 45229, USA;
| | - Josh Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.T.B.); (J.P.)
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Cynthia A. Prows
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati, Cincinnati, OH 45229, USA;
| | - Alanna Kulchak Rahm
- Genomic Medicine Institute, Geisinger, Danville, PA 17822, USA; (A.H.B.); (A.L.); (A.K.R.); (A.S.); (M.S.W.); (J.L.W.)
| | - James Ralston
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente of Washington, Seattle, WA 98101, USA; (N.H.); (E.B.L.); (J.R.); (A.S.)
- University of Washington Biomedical and Health Informatics, Seattle, WA 98195, USA
| | - Hila Milo Rasouly
- Department of Medicine, Division of Nephrology, Columbia University Irving Medical Center, New York, NY 10032, USA; (M.M.); (H.M.R.)
| | - Aaron Scrol
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente of Washington, Seattle, WA 98101, USA; (N.H.); (E.B.L.); (J.R.); (A.S.)
| | - Maureen E. Smith
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA;
| | - Amy Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA 17822, USA; (A.H.B.); (A.L.); (A.K.R.); (A.S.); (M.S.W.); (J.L.W.)
| | - Kelsey Stuttgen
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55902, USA; (I.J.K.); (D.C.K.); (K.S.)
| | - Georgia Wiesner
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
- Vanderbilt Clinical and Translational Hereditary Cancer Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Marc S. Williams
- Genomic Medicine Institute, Geisinger, Danville, PA 17822, USA; (A.H.B.); (A.L.); (A.K.R.); (A.S.); (M.S.W.); (J.L.W.)
| | - Julia Wynn
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10027, USA;
| | - Janet L. Williams
- Genomic Medicine Institute, Geisinger, Danville, PA 17822, USA; (A.H.B.); (A.L.); (A.K.R.); (A.S.); (M.S.W.); (J.L.W.)
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Hallquist MLG, Tricou EP, Hallquist MN, Savatt JM, Rocha H, Evans AE, Deckard N, Hu Y, Kirchner HL, Pervola J, Rahm AK, Rashkin M, Schmidlen TJ, Schwartz MLB, Williams JL, Williams MS, Buchanan AH. Positive impact of genetic counseling assistants on genetic counseling efficiency, patient volume, and cost in a cancer genetics clinic. Genet Med 2020; 22:1348-1354. [DOI: 10.1038/s41436-020-0797-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 03/25/2020] [Accepted: 03/27/2020] [Indexed: 12/29/2022] Open
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Webber EM, Hunter JE, Biesecker LG, Buchanan AH, Clarke EV, Currey E, Dagan-Rosenfeld O, Lee K, Lindor NM, Martin CL, Milosavljevic A, Mittendorf KF, Muessig KR, O'Daniel JM, Patel RY, Ramos EM, Rego S, Slavotinek AM, Sobriera NLM, Weaver MA, Williams MS, Evans JP, Goddard KAB. Evidence-based assessments of clinical actionability in the context of secondary findings: Updates from ClinGen's Actionability Working Group. Hum Mutat 2019; 39:1677-1685. [PMID: 30311382 PMCID: PMC6211797 DOI: 10.1002/humu.23631] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 07/19/2018] [Accepted: 08/23/2018] [Indexed: 12/31/2022]
Abstract
The use of genome-scale sequencing allows for identification of genetic findings beyond the original indication for testing (secondary findings). The ClinGen Actionability Working Group's (AWG) protocol for evidence synthesis and semi-quantitative metric scoring evaluates four domains of clinical actionability for potential secondary findings: severity and likelihood of the outcome, and effectiveness and nature of the intervention. As of February 2018, the AWG has scored 127 genes associated with 78 disorders (up-to-date topics/scores are available at www.clinicalgenome.org). Scores across these disorders were assessed to compare genes/disorders recommended for return as secondary findings by the American College of Medical Genetics and Genomics (ACMG) with those not currently recommended. Disorders recommended by the ACMG scored higher on outcome-related domains (severity and likelihood), but not on intervention-related domains (effectiveness and nature of the intervention). Current practices indicate that return of secondary findings will expand beyond those currently recommended by the ACMG. The ClinGen AWG evidence reports and summary scores are not intended as classifications of actionability, rather they provide a resource to aid decision makers as they determine best practices regarding secondary findings. The ClinGen AWG is working with the ACMG Secondary Findings Committee to update future iterations of their secondary findings list.
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Affiliation(s)
- Elizabeth M Webber
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
| | | | - Leslie G Biesecker
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Adam H Buchanan
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Elizabeth V Clarke
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
| | - Erin Currey
- Division of Genomics and Society, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | | | - Kristy Lee
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Noralane M Lindor
- Department of Health Science Research, Mayo Clinic Arizona, Scottsdale, Arizona
| | - Christa Lese Martin
- Autism & Developmental Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | | | - Kristin R Muessig
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
| | - Julianne M O'Daniel
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Ronak Y Patel
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Erin M Ramos
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Shannon Rego
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California
| | - Anne M Slavotinek
- Department of Pediatrics, University of California, San Francisco, San Francisco, California
| | - Nara Lygia M Sobriera
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Meredith A Weaver
- American College of Medical Genetics and Genomics, Bethesda, Maryland
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - James P Evans
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
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Wu RR, Myers RA, Buchanan AH, Dimmock D, Fulda KG, Haller IV, Haga SB, Harry ML, McCarty C, Neuner J, Rakhra-Burris T, Sperber N, Voils CI, Ginsburg GS, Orlando LA. Effect of Sociodemographic Factors on Uptake of a Patient-Facing Information Technology Family Health History Risk Assessment Platform. Appl Clin Inform 2019; 10:180-188. [PMID: 30866001 PMCID: PMC6415985 DOI: 10.1055/s-0039-1679926] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Accepted: 01/18/2019] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE Investigate sociodemographic differences in the use of a patient-facing family health history (FHH)-based risk assessment platform. METHODS In this large multisite trial with a diverse patient population, we evaluated the relationship between sociodemographic factors and FHH health risk assessment uptake using an information technology (IT) platform. The entire study was administered online, including consent, baseline survey, and risk assessment completion. We used multivariate logistic regression to model effect of sociodemographic factors on study progression. Quality of FHH data entered as defined as relatives: (1) with age of onset reported on relevant conditions; (2) if deceased, with cause of death and (3) age of death reported; and (4) percentage of relatives with medical history marked as unknown was analyzed using grouped logistic fixed effect regression. RESULTS A total of 2,514 participants consented with a mean age of 57 and 10.4% minority. Multivariate modeling showed that progression through study stages was more likely for younger (p-value = 0.005), more educated (p-value = 0.004), non-Asian (p-value = 0.009), and female (p-value = 0.005) participants. Those with lower health literacy or information-seeking confidence were also less likely to complete the study. Most significant drop-out occurred during the risk assessment completion phase. Overall, quality of FHH data entered was high with condition's age of onset reported 87.85%, relative's cause of death 85.55% and age of death 93.76%, and relative's medical history marked as unknown 19.75% of the time. CONCLUSION A demographically diverse population was able to complete an IT-based risk assessment but there were differences in attrition by sociodemographic factors. More attention should be given to ensure end-user functionality of health IT and leverage electronic medical records to lessen patient burden.
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Affiliation(s)
- R. Ryanne Wu
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
- Durham VA Cooperative Studies Program Epidemiology Center, Durham, North Carolina, United States
| | - Rachel A. Myers
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
| | - Adam H. Buchanan
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
| | - David Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, California, United States
| | - Kimberly G. Fulda
- The North Texas Primary Care Practice-Based Research Network and Family Medicine, University of North Texas Health Science Center, Fort Worth, Texas, United States
| | - Irina V. Haller
- Essentia Institute of Rural Health, Essentia, Duluth, Minnesota, United States
| | - Susanne B. Haga
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
| | - Melissa L. Harry
- Essentia Institute of Rural Health, Essentia, Duluth, Minnesota, United States
| | - Catherine McCarty
- University of Minnesota Medical School, Duluth Campus, Duluth, Minnesota, United States
| | - Joan Neuner
- Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
- Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
| | - Teji Rakhra-Burris
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
| | - Nina Sperber
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, United States
- Durham VA Health Services & Development Service, Durham, North Carolina, United States
| | - Corrine I. Voils
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, United States
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States
| | - Geoffrey S. Ginsburg
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
| | - Lori A. Orlando
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
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Williams MS, Buchanan AH, Davis FD, Faucett WA, Hallquist MLG, Leader JB, Martin CL, McCormick CZ, Meyer MN, Murray MF, Rahm AK, Schwartz MLB, Sturm AC, Wagner JK, Williams JL, Willard HF, Ledbetter DH. Patient-Centered Precision Health In A Learning Health Care System: Geisinger's Genomic Medicine Experience. Health Aff (Millwood) 2019; 37:757-764. [PMID: 29733722 DOI: 10.1377/hlthaff.2017.1557] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Health care delivery is increasingly influenced by the emerging concepts of precision health and the learning health care system. Although not synonymous with precision health, genomics is a key enabler of individualized care. Delivering patient-centered, genomics-informed care based on individual-level data in the current national landscape of health care delivery is a daunting challenge. Problems to overcome include data generation, analysis, storage, and transfer; knowledge management and representation for patients and providers at the point of care; process management; and outcomes definition, collection, and analysis. Development, testing, and implementation of a genomics-informed program requires multidisciplinary collaboration and building the concepts of precision health into a multilevel implementation framework. Using the principles of a learning health care system provides a promising solution. This article describes the implementation of population-based genomic medicine in an integrated learning health care system-a working example of a precision health program.
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Affiliation(s)
- Marc S Williams
- Marc S. Williams ( ) is director of the Genomic Medicine Institute, Geisinger, in Danville, Pennsylvania
| | - Adam H Buchanan
- Adam H. Buchanan is an assistant professor at the Genomic Medicine Institute, Geisinger
| | - F Daniel Davis
- F. Daniel Davis is director of the Center for Bioethics and Healthcare Policy, Geisinger
| | - W Andrew Faucett
- W. Andrew Faucett is a professor at the Genomic Medicine Institute, Geisinger
| | - Miranda L G Hallquist
- Miranda L. G. Hallquist is a genetic counselor at the Genomic Medicine Institute, Geisinger
| | - Joseph B Leader
- Joseph B. Leader is director of the Phenomic Analytics and Clinical Data Core, Geisinger
| | - Christa L Martin
- Christa L. Martin is director of the Autism and Developmental Medicine Institute, Geisinger
| | - Cara Z McCormick
- Cara Z. McCormick is a senior assistant at the Genomic Medicine Institute, Geisinger
| | - Michelle N Meyer
- Michelle N. Meyer is associate director for research ethics at the Center for Translational Bioethics and Health Care Policy, Geisinger
| | - Michael F Murray
- Michael F. Murray was a physician in the Genomic Medicine Institute, Geisinger, at the time this work was completed. He is now at the Yale School of Medicine
| | - Alanna K Rahm
- Alanna K. Rahm is an assistant professor at the Genomic Medicine Institute, Geisinger
| | - Marci L B Schwartz
- Marci L. B. Schwartz is a genetic counselor at the Genomic Medicine Institute, Geisinger
| | - Amy C Sturm
- Amy C. Sturm is a professor at the Genomic Medicine Institute, Geisinger
| | - Jennifer K Wagner
- Jennifer K. Wagner is associate director of bioethics research, Center for Translational Bioethics and Health Care Policy, Geisinger
| | - Janet L Williams
- Janet L. Williams is director of research genetic counselors, Genomic Medicine Institute, Geisinger
| | - Huntington F Willard
- Huntington F. Willard is director of the National Precision Health Institute, Geisinger
| | - David H Ledbetter
- David H. Ledbetter is executive vice president and chief scientific officer, Geisinger
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Manickam K, Buchanan AH, Schwartz MLB, Hallquist MLG, Williams JL, Rahm AK, Rocha H, Savatt JM, Evans AE, Butry LM, Lazzeri AL, Lindbuchler DM, Flansburg CN, Leeming R, Vogel VG, Lebo MS, Mason-Suares HM, Hoskinson DC, Abul-Husn NS, Dewey FE, Overton JD, Reid JG, Baras A, Willard HF, McCormick CZ, Krishnamurthy SB, Hartzel DN, Kost KA, Lavage DR, Sturm AC, Frisbie LR, Person TN, Metpally RP, Giovanni MA, Lowry LE, Leader JB, Ritchie MD, Carey DJ, Justice AE, Kirchner HL, Faucett WA, Williams MS, Ledbetter DH, Murray MF. Exome Sequencing-Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants. JAMA Netw Open 2018; 1:e182140. [PMID: 30646163 PMCID: PMC6324494 DOI: 10.1001/jamanetworkopen.2018.2140] [Citation(s) in RCA: 140] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
IMPORTANCE Detection of disease-associated variants in the BRCA1 and BRCA2 (BRCA1/2) genes allows for cancer prevention and early diagnosis in high-risk individuals. OBJECTIVES To identify pathogenic and likely pathogenic (P/LP) BRCA1/2 variants in an unselected research cohort, and to characterize the features associated with P/LP variants. DESIGN, SETTING, AND PARTICIPANTS This is a cross-sectional study of adult volunteers (n = 50 726) who underwent exome sequencing at a single health care system (Geisinger Health System, Danville, Pennsylvania) from January 1, 2014, to March 1, 2016. Participants are part of the DiscovEHR cohort and were identified through the Geisinger MyCode Community Health Initiative. They consented to a research protocol that included sequencing and return of actionable test results. Clinical data from electronic health records and clinical visits were correlated with variants. Comparisons were made between those with (cases) and those without (controls) P/LP variants in BRCA1/2. MAIN OUTCOMES Prevalence of P/LP BRCA1/2 variants in cohort, proportion of variant carriers not previously ascertained through clinical testing, and personal and family history of relevant cancers among BRCA1/2 variant carriers and noncarriers. RESULTS Of the 50 726 health system patients who underwent exome sequencing, 50 459 (99.5%) had no expected pathogenic BRCA1/2 variants and 267 (0.5%) were BRCA1/2 carriers. Of the 267 cases (148 [55.4%] were women and 119 [44.6%] were men with a mean [range] age of 58.9 [23-90] years), 183 (68.5%) received clinically confirmed results in their electronic health record. Among the 267 participants with P/LP BRCA1/2 variants, 219 (82.0%) had no prior clinical testing, 95 (35.6%) had BRCA1 variants, and 172 (64.4%) had BRCA2 variants. Syndromic cancer diagnoses were present in 11 (47.8%) of the 23 deceased BRCA1/2 carriers and in 56 (20.9%) of all 267 BRCA1/2 carriers. Among women, 31 (20.9%) of 148 variant carriers had a personal history of breast cancer, compared with 1554 (5.2%) of 29 880 noncarriers (odds ratio [OR], 5.95; 95% CI, 3.88-9.13; P < .001). Ovarian cancer history was present in 15 (10.1%) of 148 variant carriers and in 195 (0.6%) of 29 880 variant noncarriers (OR, 18.30; 95% CI, 10.48-31.4; P < .001). Among 89 BRCA1/2 carriers without prior testing but with comprehensive personal and family history data, 44 (49.4%) did not meet published guidelines for clinical testing. CONCLUSIONS AND RELEVANCE This study found that compared with previous clinical care, exome sequencing-based screening identified 5 times as many individuals with P/LP BRCA1/2 variants. These findings suggest that genomic screening may identify BRCA1/2-associated cancer risk that might otherwise remain undetected within health care systems and may provide opportunities to reduce morbidity and mortality in patients.
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Affiliation(s)
- Kandamurugu Manickam
- Molecular and Human Genetics Department, Nationwide Children’s Hospital, Columbus, Ohio
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | | | | | | | | | - Heather Rocha
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - Alyson E. Evans
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Loren M. Butry
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | | | | | | | - Victor G. Vogel
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Matthew S. Lebo
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts
| | | | - Derick C. Hoskinson
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts
| | | | | | | | | | - Aris Baras
- Regeneron Genetics Center, Tarrytown, New York
| | | | | | | | | | - Korey A. Kost
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - Amy C. Sturm
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - T. Nate Person
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | | | - Lacy E. Lowry
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - Marylyn D. Ritchie
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
- Center for Translational Bioinformatics, University of Pennsylvania, Philadelphia
| | - David J. Carey
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Anne E. Justice
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | | | | | | | - Michael F. Murray
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
- Department of Genetics, Yale School of Medicine, New Haven, Connecticut
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Schwartz MLB, McCormick CZ, Lazzeri AL, Lindbuchler DM, Hallquist MLG, Manickam K, Buchanan AH, Rahm AK, Giovanni MA, Frisbie L, Flansburg CN, Davis FD, Sturm AC, Nicastro C, Lebo MS, Mason-Suares H, Mahanta LM, Carey DJ, Williams JL, Williams MS, Ledbetter DH, Faucett WA, Murray MF. A Model for Genome-First Care: Returning Secondary Genomic Findings to Participants and Their Healthcare Providers in a Large Research Cohort. Am J Hum Genet 2018; 103:328-337. [PMID: 30100086 PMCID: PMC6128218 DOI: 10.1016/j.ajhg.2018.07.009] [Citation(s) in RCA: 104] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 07/15/2018] [Indexed: 10/28/2022] Open
Abstract
There is growing interest in communicating clinically relevant DNA sequence findings to research participants who join projects with a primary research goal other than the clinical return of such results. Since Geisinger's MyCode Community Health Initiative (MyCode) was launched in 2007, more than 200,000 participants have been broadly consented for discovery research. In 2013 the MyCode consent was amended to include a secondary analysis of research genomic sequences that allows for delivery of clinical results. Since May 2015, pathogenic and likely pathogenic variants from a set list of genes associated with monogenic conditions have prompted "genome-first" clinical encounters. The encounters are described as genome-first because they are identified independent of any clinical parameters. This article (1) details our process for generating clinical results from research data, delivering results to participants and providers, facilitating condition-specific clinical evaluations, and promoting cascade testing of relatives, and (2) summarizes early results and participant uptake. We report on 542 participants who had results uploaded to the electronic health record as of February 1, 2018 and 291 unique clinical providers notified with one or more participant results. Of these 542 participants, 515 (95.0%) were reached to disclose their results and 27 (5.0%) were lost to follow-up. We describe an exportable model for delivery of clinical care through secondary use of research data. In addition, subject and provider participation data from the initial phase of these efforts can inform other institutions planning similar programs.
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Affiliation(s)
| | | | | | - D'Andra M Lindbuchler
- Geisinger, Danville, PA 17822, USA; Wilkes-Barre Area Career and Technical Center, Plains Township, PA 18705, USA
| | | | - Kandamurugu Manickam
- Geisinger, Danville, PA 17822, USA; Nationwide Children's Hospital, Columbus, OH 43205, USA
| | | | | | | | | | | | | | | | | | - Matthew S Lebo
- Laboratory for Molecular Medicine, Cambridge, MA 02139, USA
| | | | | | | | | | | | | | | | - Michael F Murray
- Geisinger, Danville, PA 17822, USA; Yale School of Medicine, New Haven, CT 06510, USA.
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Strande NT, Riggs ER, Buchanan AH, Ceyhan-Birsoy O, DiStefano M, Dwight SS, Goldstein J, Ghosh R, Seifert BA, Sneddon TP, Wright MW, Milko LV, Cherry JM, Giovanni MA, Murray MF, O’Daniel JM, Ramos EM, Santani AB, Scott AF, Plon SE, Rehm HL, Martin CL, Berg JS. Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource. Am J Hum Genet 2017; 100:895-906. [PMID: 28552198 DOI: 10.1016/j.ajhg.2017.04.015] [Citation(s) in RCA: 325] [Impact Index Per Article: 46.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Accepted: 04/26/2017] [Indexed: 10/19/2022] Open
Abstract
With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: "Definitive," "Strong," "Moderate," "Limited," "No Reported Evidence," or "Conflicting Evidence." Within the ClinGen structure, classifications derived with this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings.
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Hooker GW, Clemens KR, Quillin J, Vogel Postula KJ, Summerour P, Nagy R, Buchanan AH. Cancer Genetic Counseling and Testing in an Era of Rapid Change. J Genet Couns 2017; 26:1244-1253. [PMID: 28434142 DOI: 10.1007/s10897-017-0099-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 04/10/2017] [Indexed: 01/19/2023]
Abstract
The impacts of the Association for Molecular Pathology vs. Myriad Supreme Court decision regarding patenting DNA segments and multi-gene testing on cancer genetic counseling practice have not been well described. We aimed to assess genetic counselors' perceptions of how their genetic testing-related practices for hereditary breast and/or ovarian cancer (HBOC) changed after these events. One-hundred fifty-two genetic counselors from the National Society of Genetic Counselors Cancer Special Interest Group completed an anonymous, online, mixed-methods survey in November 2013. The survey presented four hypothetical patients and asked about changes in testing practice. Across the vignettes, a majority of participants reported specific changes in testing decisions following Association for Molecular Pathology vs. Myriad and availability of multi-gene testing. Ninety-three percent of participants reported changing the types of first- and second-line tests they order for HBOC; the degree of change varied geographically. Qualitative analysis indicated that some counselors have altered the counseling session content, trading depth of information for breadth and spending more time counseling about uncertainty. This study shows that cancer genetic counselors are adapting quickly to genetic testing changes, but with wide variability. Findings suggest future research to elucidate clinicians' and patients' preferences for guidance on the clinical implementation of next-generation sequencing.
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Affiliation(s)
| | | | - John Quillin
- Virginia Commonwealth University, Richmond, VA, USA
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Chambers D, Simpson L, Neta G, Schwarz UVT, Percy-Laurry A, Aarons GA, Neta G, Brownson R, Vogel A, Stirman SW, Sherr K, Sturke R, Norton WE, Varley A, Chambers D, Vinson C, Klesges L, Heurtin-Roberts S, Massoud MR, Kimble L, Beck A, Neely C, Boggs J, Nichols C, Wan W, Staab E, Laiteerapong N, Moise N, Shah R, Essock S, Handley M, Jones A, Carruthers J, Davidson K, Peccoralo L, Sederer L, Molfenter T, Scudder A, Taber-Thomas S, Schaffner K, Herschell A, Woodward E, Pitcock J, Ritchie M, Kirchner J, Moore JE, Khan S, Rashid S, Park J, Courvoisier M, Straus S, Blonigen D, Rodriguez A, Manfredi L, Nevedal A, Rosenthal J, Smelson D, Timko C, Stadnick N, Regan J, Barnett M, Lau A, Brookman-Frazee L, Guerrero E, Fenwick K, Kong Y, Aarons G, Lengnick-Hall R, Fenwick K, Henwood B, Sayer N, Rosen C, Orazem R, Smith B, Rosen C, Zimmerman L, Lounsbury D, Rosen C, Kimerling R, Trafton JA, Lindley S, Bhargava R, Roberts H, Gibson L, Escobar GJ, Liu V, Turk B, Ragins A, Kipnis P, Gruszkowski AK, Kennedy MW, Drobek ER, Turgeman L, Milicevic AS, Hubert TL, Myaskovsky L, Tjader YC, Monte RJ, Sapnas KG, Ramly E, Lauver DR, Bartels CM, Elnahal S, Ippolito A, Peabody H, Clancy C, Cebul R, Love T, Einstadter D, Bolen S, Watts B, Yakovchenko V, Park A, Lukesh W, Miller DR, Thornton D, Drainoni ML, Gifford AL, Smith S, Kyle J, Bauer MS, Eisenberg D, Liebrecht C, Barbaresso M, Kilbourne A, Park E, Perez G, Ostroff J, Greene S, Parchman M, Austin B, Larson E, Ferreri S, Shea C, Smith M, Turner K, Bacci J, Bigham K, Curran G, Ferreri S, Frail C, Hamata C, Jankowski T, Lantaff W, McGivney MS, Snyder M, McCullough M, Gillespie C, Petrakis BA, Jones E, Park A, Lukas CV, Rose A, Shoemaker SJ, Curran G, Thomas J, Teeter B, Swan H, Teeter B, Thomas J, Curran G, Balamurugan A, Lane-Fall M, Beidas R, Di Taranti L, Buddai S, Hernandez ET, Watts J, Fleisher L, Barg F, Miake-Lye I, Olmos T, Chuang E, Rodriguez H, Kominski G, Yano B, Shortell S, Hook M, Fleisher L, Fiks A, Halkyard K, Gruver R, Sykes E, Vesco K, Beadle K, Bulkley J, Stoneburner A, Leo M, Clark A, Smith J, Smyser C, Wolf M, Trivedi S, Hackett B, Rao R, Cole FS, McGonigle R, Donze A, Proctor E, Mathur A, Sherr K, Gakidou E, Gloyd S, Audet C, Salato J, Vermund S, Amico R, Smith S, Nyirandagijimana B, Mukasakindi H, Rusangwa C, Franke M, Raviola G, Cummings M, Goldberg E, Mwaka S, Kabajaasi O, Cattamanchi A, Katamba A, Jacob S, Kenya-Mugisha N, Davis JL, Reed J, Ramaswamy R, Parry G, Sax S, Kaplan H, Huang KY, Cheng S, Yee S, Hoagwood K, McKay M, Shelley D, Ogedegbe G, Brotman LM, Kislov R, Humphreys J, Harvey G, Wilson P, Lieberthal R, Payton C, Sarfaty M, Valko G, Bolton R, Lukas CV, Hartmann C, Mueller N, Holmes SK, Bokhour B, Ono S, Crabtree B, Gordon L, Miller W, Balasubramanian B, Solberg L, Cohen D, McGraw K, Blatt A, Pittman D, McCullough M, Hartmann C, Kales H, Berlowitz D, Hudson T, Gillespie C, Helfrich C, Finley E, Garcia A, Rosen K, Tami C, McGeary D, Pugh MJ, Potter JS, Helfrich C, Stryczek K, Au D, Zeliadt S, Sayre G, Gillespie C, Leeman J, Myers A, Grant J, Wangen M, Queen T, Morshed A, Dodson E, Tabak R, Brownson RC, Sheldrick RC, Mackie T, Hyde J, Leslie L, Yanovitzky I, Weber M, Gesualdo N, Kristensen T, Stanick C, Halko H, Dorsey C, Powell B, Weiner B, Lewis C, Powell B, Weiner B, Stanick C, Halko H, Dorsey C, Lewis C, Weiner B, Dorsey C, Stanick C, Halko H, Powell B, Lewis C, Stirman SW, Carreno P, Mallard K, Masina T, Monson C, Swindle T, Curran G, Patterson Z, Whiteside-Mansell L, Hanson R, Saunders B, Schoenwald S, Moreland A, Birken S, Powell B, Presseau J, Miake-Lye I, Ganz D, Mittman B, Delevan D, Finley E, Hill JN, Locatelli S, Bokhour B, Fix G, Solomon J, Mueller N, Lavela SL, Scott V, Scaccia J, Alia K, Skiles B, Wandersman A, Wilson P, Sales A, Roberts M, Kennedy A, Chambers D, Khoury MJ, Sperber N, Orlando L, Carpenter J, Cavallari L, Denny J, Elsey A, Fitzhenry F, Guan Y, Horowitz C, Johnson J, Madden E, Pollin T, Pratt V, Rakhra-Burris T, Rosenman M, Voils C, Weitzel K, Wu R, Damschroder L, Lu C, Ceccarelli R, Mazor KM, Wu A, Rahm AK, Buchanan AH, Schwartz M, McCormick C, Manickam K, Williams MS, Murray MF, Escoffery NC, Lebow-Skelley E, Udelson H, Böing E, Fernandez ME, Wood RJ, Mullen PD, Parekh J, Caldas V, Stuart EA, Howard S, Thomas G, Jennings JM, Torres J, Markham C, Shegog R, Peskin M, Rushing SC, Gaston A, Gorman G, Jessen C, Williamson J, Ward D, Vaughn A, Morris E, Mazzucca S, Burney R, Ramanadhan S, Minsky S, Martinez-Dominguez V, Viswanath K, Barker M, Fahim M, Ebnahmady A, Dragonetti R, Selby P, Farrell M, Tompkins J, Norton W, Rapport K, Hargreaves M, Lee R, Ramanadhan S, Kruse G, Deutsch C, Lanier E, Gray A, Leppin A, Christiansen L, Schaepe K, Egginton J, Branda M, Gaw C, Dick S, Montori V, Shah N, Korn A, Hovmand P, Fullerton K, Zoellner N, Hennessy E, Tovar A, Hammond R, Economos C, Kay C, Gazmararian J, Vall E, Cheung P, Franks P, Barrett-Williams S, Weiss P, Kay C, Gazmararian J, Hamilton E, Cheung P, Kay C, Vall E, Gazmararian J, Marques L, Dixon L, Ahles E, Valentine S, Monson C, Shtasel D, Stirman SW, Parra-Cardona R, Northridge M, Kavathe R, Zanowiak J, Wyatt L, Singh H, Islam N, Monteban M, Freedman D, Bess K, Walsh C, Matlack K, Flocke S, Baily H, Harden S, Ramalingam N, Alia K, Scaccia J, Scott V, Ramaswamy R, Wandersman A, Gold R, Cottrell E, Hollombe C, Dambrun K, Bunce A, Middendorf M, Dearing M, Cowburn S, Mossman N, Melgar G, Hopfer S, Hecht M, Ray A, Miller-Day M, BeLue R, Zimet G, Nelson EL, Kuhlman S, Doolittle G, Krebill H, Spaulding A, Levin T, Sanchez M, Landau M, Escobar P, Minian N, Selby P, Noormohamed A, Zawertailo L, Baliunas D, Giesbrecht N, Le Foll B, Samokhvalov A, Meisel Z, Polsky D, Schackman B, Mitchell J, Sevarino K, Gimbel S, Mwanza M, Nisingizwe MP, Michel C, Hirschhorn L, Lane-Fall M, Beidas R, Di Taranti L, Choudhary M, Thonduparambil D, Fleisher L, Barg F, Meissner P, Pinnock H, Barwick M, Carpenter C, Eldridge S, Grandes-Odriozola G, Griffiths C, Rycroft-Malone J, Murray E, Patel A, Sheikh A, Taylor SJC, Mittman B, Guilliford M, Pearce G, Korngiebel D, West K, Burke W, Hannon P, Harris J, Hammerback K, Kohn M, Chan GKC, Mafune R, Parrish A, Helfrich C, Beresford S, Pike KJ, Shelton R, Jandorf L, Erwin D, Charles TA, Parchman M, Baldwin LM, Ike B, Fickel J, Lind J, Cowper D, Fleming M, Sadler A, Dye M, Katzburg J, Ong M, Tubbesing S, McCullough M, Simmons M, Yakovchenko V, Harnish A, Gabrielian S, McInnes K, Smith J, Smelson D, Ferrand J, Torres E, Green A, Aarons G, Bradbury AR, Patrick-Miller LJ, Egleston BL, Domchek SM, Olopade OI, Hall MJ, Daly MB, Fleisher L, Grana G, Ganschow P, Fetzer D, Brandt A, Chambers R, Clark DF, Forman A, Gaber RS, Gulden C, Horte J, Long J, Lucas T, Madaan S, Mattie K, McKenna D, Montgomery S, Nielsen S, Powers J, Rainey K, Rybak C, Seelaus C, Stoll J, Stopfer J, Yao XS, Savage M, Miech E, Damush T, Rattray N, Myers J, Homoya B, Winseck K, Klabunde C, Langer D, Aggarwal A, Neilson E, Gunderson L, Escobar GJ, Gardner M, O’Sulleabhain L, Kroenke C, Liu V, Kipnis P. Proceedings from the 9th annual conference on the science of dissemination and implementation. Implement Sci 2017. [PMCID: PMC5414666 DOI: 10.1186/s13012-017-0575-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Foote JR, Lopez-Acevedo M, Buchanan AH, Secord AA, Lee PS, Fountain C, Myers ER, Cohn DE, Reed SD, Havrilesky LJ. Cost Comparison of Genetic Testing Strategies in Women With Epithelial Ovarian Cancer. J Oncol Pract 2017; 13:e120-e129. [DOI: 10.1200/jop.2016.011866] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Purpose: The advent of multigene panels has increased genetic testing options for women with epithelial ovarian cancer (EOC). We designed a decision model to compare costs and probabilities of identifying a deleterious mutation or variant of uncertain significance (VUS) using different genetic testing strategies. Methods: A decision model was developed to compare costs and outcomes of two testing strategies for women with EOC: multigene testing (MGT) versus single-gene testing for BRCA1/2. Outcomes were mean cost and number of deleterious mutations and VUSs identified. Model inputs were obtained from published genetic testing data in EOC. One-way sensitivity analyses and Monte Carlo probabilistic sensitivity analyses were performed. Results: No family history model: MGT cost $1,160 more on average than BRCA1/2 testing and identified an additional 3.8 deleterious mutations for every 100 women tested. For each additional deleterious mutation identified, MGT cost $30,812 and identified 5.4 additional VUSs. Family history model: MGT cost $654 more on average and identified an additional 7.0 deleterious mutations for every 100 women tested. For each additional deleterious mutation identified, MGT cost $9,909 and identified 2.6 additional VUSs. Conclusion: MGT was associated with a higher additional cost per deleterious mutation identified and a higher ratio of VUS burden to actionable information in women with no family history as compared with women with a family history. Family history should be considered when determining an initial genetic testing platform in women with EOC.
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Affiliation(s)
- Jonathan R. Foote
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Micael Lopez-Acevedo
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Adam H. Buchanan
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Angeles Alvarez Secord
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Paula S. Lee
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Cynthia Fountain
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Evan R. Myers
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - David E. Cohn
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Shelby D. Reed
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
| | - Laura J. Havrilesky
- Duke University Medical Center, Durham, NC; and Ohio State University Medical Center, Columbus, OH
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Buchanan AH, Voils CI, Schildkraut JM, Fine C, Horick NK, Marcom PK, Wiggins K, Skinner CS. Adherence to Recommended Risk Management among Unaffected Women with a BRCA Mutation. J Genet Couns 2016; 26:79-92. [PMID: 27265406 DOI: 10.1007/s10897-016-9981-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 05/24/2016] [Indexed: 01/01/2023]
Abstract
Identifying unaffected women with a BRCA mutation can have a significant individual and population health impact on morbidity and mortality if these women adhere to guidelines for managing cancer risk. But, little is known about whether such women are adherent to current guidelines. We conducted telephone surveys of 97 unaffected BRCA mutation carriers who had genetic counseling at least one year prior to the survey to assess adherence to current guidelines, factors associated with adherence, and common reasons for performing and not performing recommended risk management. More than half of participants reported being adherent with current risk management recommendations for breast cancer (69 %, n = 67), ovarian cancer (82 %, n = 74) and both cancers (66 %, n = 64). Older age (OR = 10.53, p = 0.001), white race (OR = 8.93, p = 0.019), higher breast cancer genetics knowledge (OR = 1.67, p = 0.030), higher cancer-specific distress (OR = 1.07, p = 0.002) and higher physical functioning (OR = 1.09, p = 0.009) were significantly associated with adherence to recommended risk management for both cancers. Responses to open-ended questions about reasons for performing and not performing risk management behaviors indicated that participants recognized the clinical utility of these behaviors. Younger individuals and those with lower physical functioning may require targeted interventions to improve adherence, perhaps in the setting of long-term follow-up at a multi-disciplinary hereditary cancer clinic.
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Affiliation(s)
- Adam H Buchanan
- Geisinger Health System, Genomic Medicine Institute, M.C. 26-20, 100 N. Academy Ave, Danville, PA, 17822, USA.
| | - Corrine I Voils
- Center for Health Services Research in Primary Care, Durham VA Medical Center, Durham, NC, USA.,Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | | | - Catherine Fine
- Department of Genetics, UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA
| | - Nora K Horick
- Massachusetts General Hospital Biostatistics Center, Boston, MA, USA
| | - P Kelly Marcom
- Department of Medicine, Duke University Medical Center, Durham, NC, USA.,Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA
| | - Kristi Wiggins
- Division of Cellular Therapy, Duke University Medical Center, Durham, NC, USA
| | - Celette Sugg Skinner
- Department of Clinical Sciences and Harold C Simmons Cancer Center, University of Texas - Southwestern, Dallas, TX, USA
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Orlando LA, Wu RR, Myers RA, Buchanan AH, Henrich VC, Hauser ER, Ginsburg GS. Clinical utility of a Web-enabled risk-assessment and clinical decision support program. Genet Med 2016; 18:1020-8. [DOI: 10.1038/gim.2015.210] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Accepted: 12/09/2015] [Indexed: 12/13/2022] Open
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Champion VL, Rawl SM, Bourff SA, Champion KM, Smith LG, Buchanan AH, Fish LJ, Monahan PO, Stump TE, Springston JK, Gathirua-Mwangi WG, Skinner CS. Randomized trial of DVD, telephone, and usual care for increasing mammography adherence. J Health Psychol 2014; 21:916-26. [PMID: 25070967 DOI: 10.1177/1359105314542817] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
The purpose of this study was to test an intervention to increase mammography screening in women 51-75 years of age who had not received a mammogram in the last 15 months. A total of 1681 women were randomized to (1) a mailed tailored interactive DVD, (2) a computer-tailored telephone counseling, or (3) usual care. Women with income below US$75,000 who were in the interactive DVD group had significantly more mammograms than women in usual care. Women with income above US$75,000 had significantly fewer mammograms than women with income less than US$75,000 regardless of group. Further investigation is needed to understand why women with income above US$75,000 did not show the same benefit of the intervention.
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Affiliation(s)
- Victoria L Champion
- Indiana University School of Nursing, USA Indiana University Simon Cancer Center, USA
| | - Susan M Rawl
- Indiana University School of Nursing, USA Indiana University Simon Cancer Center, USA
| | | | | | | | | | | | | | | | | | | | - Celette Sugg Skinner
- The University of Texas Southwestern Medical Center, Harold C Simmons Cancer Center, USA
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Daniels MS, Babb SA, King RH, Urbauer DL, Batte BAL, Brandt AC, Amos CI, Buchanan AH, Mutch DG, Lu KH. Underestimation of risk of a BRCA1 or BRCA2 mutation in women with high-grade serous ovarian cancer by BRCAPRO: a multi-institution study. J Clin Oncol 2014; 32:1249-55. [PMID: 24638001 DOI: 10.1200/jco.2013.50.6055] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
PURPOSE Identification of the 10% to 15% of patients with ovarian cancer who have germline BRCA1 or BRCA2 mutations is important for management of both patients and relatives. The BRCAPRO model, which estimates mutation likelihood based on personal and family cancer history, can inform genetic testing decisions. This study's purpose was to assess the accuracy of BRCAPRO in women with ovarian cancer. METHODS BRCAPRO scores were calculated for 589 patients with ovarian cancer referred for genetic counseling at three institutions. Observed mutations were compared with those predicted by BRCAPRO. Analysis of variance was used to assess factors impacting BRCAPRO accuracy. RESULTS One hundred eighty (31%) of 589 patients with ovarian cancer tested positive. At BRCAPRO scores less than 40%, more mutations were observed than expected (93 mutations observed v 34.1 mutations expected; P < .001). If patients with BRCAPRO scores less than 10% had not been tested, 51 (28%) of 180 mutations would have been missed. BRCAPRO underestimated the risk for high-grade serous ovarian cancers but overestimated the risk for other histologies (P < .001), underestimation increased as age at diagnosis decreased (P = .02), and model performance varied by institution (P = .02). CONCLUSION Patients with ovarian cancer classified as low risk by BRCAPRO are more likely to test positive than predicted. The risk of a mutation in patients with low BRCAPRO scores is high enough to warrant genetic testing. This study demonstrates that assessment of family history by a validated model cannot effectively target testing to a high-risk ovarian cancer patient population, which strongly supports the recommendation to offer BRCA1/BRCA2 genetic testing to all patients with high-grade serous ovarian cancer regardless of family history.
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Affiliation(s)
- Molly S Daniels
- Molly S. Daniels, Diana L. Urbauer, Brittany A.L. Batte, Amanda C. Brandt, Christopher I. Amos, and Karen H. Lu, The University of Texas MD Anderson Cancer Center, Houston, TX; Sheri A. Babb and David G. Mutch, Washington University School of Medicine, St Louis, MO; Robin H. King and Adam H. Buchanan, Duke University, Durham, NC
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Orlando LA, Wu RR, Beadles C, Himmel T, Buchanan AH, Powell KP, Hauser ER, Henrich VC, Ginsburg GS. Implementing family health history risk stratification in primary care: Impact of guideline criteria on populations and resource demand. Am J Med Genet 2014; 166C:24-33. [DOI: 10.1002/ajmg.c.31388] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Wu RR, Himmel TL, Buchanan AH, Powell KP, Hauser ER, Ginsburg GS, Henrich VC, Orlando LA. Quality of family history collection with use of a patient facing family history assessment tool. BMC Fam Pract 2014; 15:31. [PMID: 24520818 PMCID: PMC3937044 DOI: 10.1186/1471-2296-15-31] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2013] [Accepted: 02/05/2014] [Indexed: 12/11/2022]
Abstract
Background Studies have shown that the quality of family health history (FHH) collection in primary care is inadequate to assess disease risk. To use FHH for risk assessment, collected data must have adequate detail. To address this issue, we developed a patient facing FHH assessment tool, MeTree. In this paper we report the content and quality of the FHH collected using MeTree. Methods Design: A hybrid implementation-effectiveness study. Patients were recruited from 2009 to 2012. Setting: Two community primary care clinics in Greensboro, NC. Participants: All non-adopted adult English speaking patients with upcoming appointments were invited to participate. Intervention: Education about and collection of FHH with entry into MeTree. Measures: We report the proportion of pedigrees that were high-quality. High-quality pedigrees are defined as having all the following criteria: (1) three generations of relatives, (2) relatives’ lineage, (3) relatives’ gender, (4) an up-to-date FHH, (5) pertinent negatives noted, (6) age of disease onset in affected relatives, and for deceased relatives, (7) the age and (8) cause of death (Prim Care31:479–495, 2004.). Results Enrollment: 1,184. Participant demographics: age range 18-92 (mean 58.8, SD 11.79), 56% male, and 75% white. The median pedigree size was 21 (range 8-71) and the FHH entered into MeTree resulted in a database of 27,406 individuals. FHHs collected by MeTree were found to be high quality in 99.8% (N = 1,182/1,184) as compared to <4% at baseline. An average of 1.9 relatives per pedigree (range 0-50, SD 4.14) had no data reported. For pedigrees where at least one relative has no data (N = 497/1,184), 4.97 relatives per pedigree (range 1-50, SD 5.44) had no data. Talking with family members before using MeTree significantly decreased the proportion of relatives with no data reported (4.98% if you talked to your relative vs. 10.85% if you did not, p-value < 0.001.). Conclusion Using MeTree improves the quantity and quality of the FHH data that is collected and talking with relatives prior to the collection of FHH significantly improves the quantity and quality of the data provided. This allows more patients to be accurately risk stratified and offered appropriate preventive care guided by their risk level. Trial number NCT01372553
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Affiliation(s)
- R Ryanne Wu
- Health Services Research and Development, Department of Veteran Affairs Medical Center, 411 W, Chapel Hill St,, Ste 600, Durham, NC 27701, USA.
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Beadles CA, Ryanne Wu R, Himmel T, Buchanan AH, Powell KP, Hauser E, Henrich VC, Ginsburg GS, Orlando LA. Providing patient education: impact on quantity and quality of family health history collection. Fam Cancer 2014; 13:325-32. [DOI: 10.1007/s10689-014-9701-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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Wu RR, Orlando LA, Himmel TL, Buchanan AH, Powell KP, Hauser ER, Agbaje AB, Henrich VC, Ginsburg GS. Patient and primary care provider experience using a family health history collection, risk stratification, and clinical decision support tool: a type 2 hybrid controlled implementation-effectiveness trial. BMC Fam Pract 2013; 14:111. [PMID: 23915256 PMCID: PMC3765729 DOI: 10.1186/1471-2296-14-111] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2013] [Accepted: 06/28/2013] [Indexed: 02/07/2023]
Abstract
BACKGROUND Family health history (FHH) is the single strongest predictor of disease risk and yet is significantly underutilized in primary care. We developed a patient facing FHH collection tool, MeTree, that uses risk stratification to generate clinical decision support for breast cancer, colorectal cancer, ovarian cancer, hereditary cancer syndromes, and thrombosis. Here we present data on the experience of patients and providers after integration of MeTree into 2 primary care practices. METHODS This was a Type 2 hybrid controlled implementation-effectiveness study in 3 community-based primary care clinics in Greensboro, NC. All non-adopted adult English speaking patients with upcoming routine appointments were invited. Patients were recruited from December 2009 to the present and followed for one year. Ease of integration of MeTree into clinical practice at the two intervention clinics was evaluated through patient surveys after their appointment and at 3 months post-visit, and physician surveys 3 months after tool integration. RESULTS Total enrollment =1,184. Average time to complete MeTree = 27 minutes. Patients found MeTree: easy to use (93%), easy to understand (97%), useful (98%), raised awareness of disease risk (85%), and changed how they think about their health (86%). Of the 26% (N = 311) asking for assistance to complete the tool, age (65 sd 9.4 vs. 57 sd 11.8, p-value < 0.00) and large pedigree size (24.4 sd 9.81 vs. 22.2 sd 8.30, p-value < 0.00) were the only significant factors; 77% of those requiring assistance were over the age of 60. Providers (N = 14) found MeTree: improved their practice (86%), improved their understanding of FHH (64%), made practice easier (79%), and worthy of recommending to their peers (93%). CONCLUSIONS Our study shows that MeTree has broad acceptance and support from both patients and providers and can be implemented without disruption to workflow.
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Affiliation(s)
- R Ryanne Wu
- Health Services Research and Development, VA Health System, Durham, NC, USA
- Duke Center for Personalized Medicine, Duke University, Durham, NC, USA
- Duke Department of Internal Medicine, Duke University Health System, Durham, NC, USA
| | - Lori A Orlando
- Duke Center for Personalized Medicine, Duke University, Durham, NC, USA
- Institute of Genome Science & Policy, Duke University, Durham, NC, USA
- Duke Department of Internal Medicine, Duke University Health System, Durham, NC, USA
| | - Tiffany L Himmel
- Institute of Genome Science & Policy, Duke University, Durham, NC, USA
| | - Adam H Buchanan
- Duke Cancer Institute, Duke University Health System, Durham, NC, USA
| | - Karen P Powell
- Center for Biotechnology, Genomics and Health Research, UNC-Greensboro, Greensboro, NC, USA
| | - Elizabeth R Hauser
- Center for Human Genetics, Duke University, Durham, NC, USA
- Durham Epidemiologic Research and Information Center, VA Health System, Durham, NC, USA
| | | | - Vincent C Henrich
- Center for Biotechnology, Genomics and Health Research, UNC-Greensboro, Greensboro, NC, USA
| | - Geoffrey S Ginsburg
- Duke Center for Personalized Medicine, Duke University, Durham, NC, USA
- Institute of Genome Science & Policy, Duke University, Durham, NC, USA
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Orlando LA, Buchanan AH, Hahn SE, Christianson CA, Powell KP, Skinner CS, Chesnut B, Blach C, Due B, Ginsburg GS, Henrich VC. Development and validation of a primary care-based family health history and decision support program (MeTree). N C Med J 2013; 74:287-296. [PMID: 24044145 PMCID: PMC5215064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree's interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree's strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers' needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines.
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Affiliation(s)
- Lori A Orlando
- Department of Medicine, Duke University, Durham, North Carolina 27705, USA.
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Orlando LA, Hauser ER, Christianson C, Powell KP, Buchanan AH, Chesnut B, Agbaje AB, Henrich VC, Ginsburg G. Protocol for implementation of family health history collection and decision support into primary care using a computerized family health history system. BMC Health Serv Res 2011; 11:264. [PMID: 21989281 PMCID: PMC3200182 DOI: 10.1186/1472-6963-11-264] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2011] [Accepted: 10/11/2011] [Indexed: 12/12/2022] Open
Abstract
Background The CDC's Family History Public Health Initiative encourages adoption and increase awareness of family health history. To meet these goals and develop a personalized medicine implementation science research agenda, the Genomedical Connection is using an implementation research (T3 research) framework to develop and integrate a self-administered computerized family history system with built-in decision support into 2 primary care clinics in North Carolina. Methods/Design The family health history system collects a three generation family history on 48 conditions and provides decision support (pedigree and tabular family history, provider recommendation report and patient summary report) for 4 pilot conditions: breast cancer, ovarian cancer, colon cancer, and thrombosis. All adult English-speaking, non-adopted, patients scheduled for well-visits are invited to complete the family health system prior to their appointment. Decision support documents are entered into the medical record and available to provider's prior to the appointment. In order to optimize integration, components were piloted by stakeholders prior to and during implementation. Primary outcomes are change in appropriate testing for hereditary thrombophilia and screening for breast cancer, colon cancer, and ovarian cancer one year after study enrollment. Secondary outcomes include implementation measures related to the benefits and burdens of the family health system and its impact on clinic workflow, patients' risk perception, and intention to change health related behaviors. Outcomes are assessed through chart review, patient surveys at baseline and follow-up, and provider surveys. Clinical validity of the decision support is calculated by comparing its recommendations to those made by a genetic counselor reviewing the same pedigree; and clinical utility is demonstrated through reclassification rates and changes in appropriate screening (the primary outcome). Discussion This study integrates a computerized family health history system within the context of a routine well-visit appointment to overcome many of the existing barriers to collection and use of family history information by primary care providers. Results of the implementation process, its acceptability to patients and providers, modifications necessary to optimize the system, and impact on clinical care can serve to guide future implementation projects for both family history and other tools of personalized medicine, such as health risk assessments.
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Affiliation(s)
- Lori A Orlando
- Department of Medicine, Duke University, 3475 Erwin Rd, Durham, NC 27705, USA.
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