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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT01736566
Other study ID # MedSeq™
Secondary ID U01HG006500
Status Completed
Phase N/A
First received
Last updated
Start date December 2011
Est. completion date January 2, 2021

Study information

Verified date April 2024
Source Brigham and Women's Hospital
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

The MedSeq™ Project seeks to explore the impact of incorporating information from a patient's whole genome sequence into the practice of clinical medicine. In the extension phase of MedSeq we are attempting increase our participant diversity by increasing targeted enrollment of African/African American patient participants.


Description:

Whole genome sequencing (WGS) and whole exome sequencing (WES) services are currently available to and are being utilized by physicians and their patients in both research and clinical settings. The widespread availability and use of WGS and WES in the practice of clinical medicine is imminent. In the very near future, sequencing of individual genomes will be inexpensive and ubiquitous, and patients will be looking to the medical establishment for interpretations, insight and advice to improve their health. Developing standards and procedures for the use of WGS information in clinical medicine is an urgent need, but there are numerous obstacles related to integrity and storage of WGS data, interpretation and responsible clinical integration. MedSeq™ seeks to develop a process to integrate WGS into clinical medicine and explore the impact of doing so. We believe that WGS will be used in many ways, including two distinct and complementary situations. In generally healthy patients, physicians will use the results of WGS to derive insight into future health risks and inform prevention and surveillance efforts, a category we refer to as General Genomic Medicine. In patients presenting with a family history or symptoms of a disease, physicians will use the results of WGS to interrogate particular sets of genes known to be associated with the disease in question, a category we refer to as Disease-Specific Genomic Medicine. Beginning in fall 2012, we will enroll 10 primary care physicians and 100 of their healthy middle-aged patients to evaluate the use of General Genomic Medicine, and 10 cardiologists and 100 of their patients presenting with hypertrophic cardiomyopathy (HCM) or dilated cardiomyopathy (DCM) to evaluate the use of Disease-Specific Genomic Medicine. We will randomize physicians and their patients within each of the above models to receive clinically meaningful information derived from WGS versus current standard of care without the use of WGS. MedSeq™ is comprised of three distinct but highly collaborative projects. Project 1 will enroll physicians and patients into the protocol, educate the physicians on basic genomic principles and safely monitor the use of genomic information in clinical practice. Project 2 will use a WGS analysis/interpretation pipeline to generate a genome report on each patient randomized to receive WGS in this protocol. Project 3 will examine preferences and motivations of physicians and patients enrolled, evaluate the flow and utilization of genomic information within the clinical interactions, and assess understanding, behavior, medical consequences and healthcare costs associated with the use of WGS in these models of medical practice. In an extension phase of the study, we will 1) recruit approximately 10-15 patient-participants who self-identify as African or African American, whose physicians deem to be healthy. All will be placed in the whole genome-sequencing arm of the study. They will undergo the same activities as traditional MedSeq participants except for randomization. 2) We will conduct a targeted phenotype assessment on MedSeq Project patient-participants who are identified to have a monogenic finding. We plan to perform additional analysis by reviewing their medical records and looking specifically with their variant in mind to see if features associated with the variants were known prior to the study or were identified by further testing or by their physical during the course of the study. This initiative will significantly accelerate the use of genomics in clinical medicine by creating and safely testing novel methods for integrating information from WGS into physicians' care of patients.


Recruitment information / eligibility

Status Completed
Enrollment 213
Est. completion date January 2, 2021
Est. primary completion date November 4, 2016
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years to 90 Years
Eligibility Note for Age Eligibility: - Cardiology patients 18 Years to 90 Years OR - Primary Care Patients 40 Years to 65 Years (Adult, Senior) Inclusion Criteria: Primary Care - Generally healthy (as defined by the primary care provider) adult patients at Brigham and Women's Hospital ages 40-65. All patients must be fluent in English. Cardiology - Patients in the Partners Healthcare System who are 18 years or older with a diagnosis of hypertrophic cardiomyopathy (HCM) or dilated cardiomyopathy (DCM) and a family history of HCM or DCM who previously had or who are candidates for targeted HCM or DCM genetic testing through routine clinical practice within Partners. All patients must be fluent in English. Exclusion Criteria: Primary Care - Patients who do not meet the above criteria. Patients with cardiac disease or a progressive debilitating illness. Patients who are pregnant or patients whose spouses/significant others are pregnant. Patients with untreated clinical anxiety or depression (as measured by a Hospital Anxiety and Depression Scale (HADS) score > 11 administered at the baseline study visit.) Cardiology - Patients who do not meet the above criteria. Patients with a progressive debilitating illness. Patients who are pregnant or patients whose spouses/significant others are pregnant. Patients with untreated clinical anxiety or depression (as measured by a Hospital Anxiety and Depression Scale (HADS) score > 11 administered at the baseline study visit.) Extension Phase - Additional Inclusion Criteria Part 1: - Above inclusion and exclusion criteria PLUS: - Inclusion: Self-identify as African or African American. Part 2: Inclusion Criteria - MedSeq participants determined to have a monogenic finding Exclusion Criteria - Participants not previously enrolled in MedSeq Project - Participants not identified to have a monogenic finding

Study Design


Related Conditions & MeSH terms


Intervention

Other:
Family History + Whole Genome Sequencing
Doctors and their patients receive a Genome Report and a Family History report. There are two sections of the Genome Report: The General Genome Report, which include highly penetrant disease mutations, carrier status for recessive disease, and pharmacogenetic associations. The Cardiac Risk Supplement, which contain genetic information found in the genome regarding cardiac diseases or a risk of cardiovascular diseases that can help with the care of the patient. Extension Phase: Experimental: Family History + Whole Genome Sequencing *In the main study participants are randomized to either the Experimental or Other Arm, in the Extension phase of the study all participants are in the Experimental Arm.
Family History Only
Doctors and their patients receive a Family History report.

Locations

Country Name City State
United States Brigham and Women's Hospital Boston Massachusetts

Sponsors (4)

Lead Sponsor Collaborator
Brigham and Women's Hospital Baylor College of Medicine, Duke University, National Human Genome Research Institute (NHGRI)

Country where clinical trial is conducted

United States, 

References & Publications (33)

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Berg JS, Amendola LM, Eng C, Van Allen E, Gray SW, Wagle N, Rehm HL, DeChene ET, Dulik MC, Hisama FM, Burke W, Spinner NB, Garraway L, Green RC, Plon S, Evans JP, Jarvik GP; Members of the CSER Actionability and Return of Results Working Group. Processes and preliminary outputs for identification of actionable genes as incidental findings in genomic sequence data in the Clinical Sequencing Exploratory Research Consortium. Genet Med. 2013 Nov;15(11):860-7. doi: 10.1038/gim.2013.133. Epub 2013 Oct 24. Erratum In: Genet Med. 2014 Feb;16(2):203. — View Citation

Biesecker LG, Green RC. Diagnostic clinical genome and exome sequencing. N Engl J Med. 2014 Jun 19;370(25):2418-25. doi: 10.1056/NEJMra1312543. No abstract available. — View Citation

Biesecker LG. Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: lessons from the ClinSeq project. Genet Med. 2012 Apr;14(4):393-8. doi: 10.1038/gim.2011.78. Epub 2012 Feb 16. — View Citation

Blumenthal-Barby JS, McGuire AL, Green RC, Ubel PA. How behavioral economics can help to avoid 'The last mile problem' in whole genome sequencing. Genome Med. 2015 Jan 22;7(1):3. doi: 10.1186/s13073-015-0132-8. eCollection 2015. — View Citation

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Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy without a math test: development of the Subjective Numeracy Scale. Med Decis Making. 2007 Sep-Oct;27(5):672-80. doi: 10.1177/0272989X07304449. Epub 2007 Jul 19. — View Citation

Green ED, Guyer MS; National Human Genome Research Institute. Charting a course for genomic medicine from base pairs to bedside. Nature. 2011 Feb 10;470(7333):204-13. doi: 10.1038/nature09764. — View Citation

Green RC, Berg JS, Berry GT, Biesecker LG, Dimmock DP, Evans JP, Grody WW, Hegde MR, Kalia S, Korf BR, Krantz I, McGuire AL, Miller DT, Murray MF, Nussbaum RL, Plon SE, Rehm HL, Jacob HJ. Exploring concordance and discordance for return of incidental findings from clinical sequencing. Genet Med. 2012 Apr;14(4):405-10. doi: 10.1038/gim.2012.21. Epub 2012 Mar 15. — View Citation

Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, McGuire AL, Nussbaum RL, O'Daniel JM, Ormond KE, Rehm HL, Watson MS, Williams MS, Biesecker LG; American College of Medical Genetics and Genomics. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013 Jul;15(7):565-74. doi: 10.1038/gim.2013.73. Epub 2013 Jun 20. Erratum In: Genet Med. 2017 May;19(5):606. — View Citation

Green RC, Lautenbach D, McGuire AL. GINA, genetic discrimination, and genomic medicine. N Engl J Med. 2015 Jan 29;372(5):397-9. doi: 10.1056/NEJMp1404776. No abstract available. — View Citation

Green RC, Rehm H, Kohane I. Clinical Genome Sequencing. Genomic and Personalized Medicine 2nd Edition: 102- 122, 2012.

Hall MA, Camacho F, Lawlor JS, Depuy V, Sugarman J, Weinfurt K. Measuring trust in medical researchers. Med Care. 2006 Nov;44(11):1048-53. doi: 10.1097/01.mlr.0000228023.37087.cb. — View Citation

Hwang KB, Lee IH, Park JH, Hambuch T, Choe Y, Kim M, Lee K, Song T, Neu MB, Gupta N, Kohane IS, Green RC, Kong SW. Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods. Hum Mutat. 2014 Aug;35(8):936-44. doi: 10.1002/humu.22587. Epub 2014 Jun 24. — View Citation

Jarvik GP, Amendola LM, Berg JS, Brothers K, Clayton EW, Chung W, Evans BJ, Evans JP, Fullerton SM, Gallego CJ, Garrison NA, Gray SW, Holm IA, Kullo IJ, Lehmann LS, McCarty C, Prows CA, Rehm HL, Sharp RR, Salama J, Sanderson S, Van Driest SL, Williams MS, Wolf SM, Wolf WA; eMERGE Act-ROR Committee and CERC Committee; CSER Act-ROR Working Group; Burke W. Return of genomic results to research participants: the floor, the ceiling, and the choices in between. Am J Hum Genet. 2014 Jun 5;94(6):818-26. doi: 10.1016/j.ajhg.2014.04.009. Epub 2014 May 8. — View Citation

Kaphingst KA, Facio FM, Cheng MR, Brooks S, Eidem H, Linn A, Biesecker BB, Biesecker LG. Effects of informed consent for individual genome sequencing on relevant knowledge. Clin Genet. 2012 Nov;82(5):408-15. doi: 10.1111/j.1399-0004.2012.01909.x. Epub 2012 Aug 7. — View Citation

Khoury MJ, Berg A, Coates R, Evans J, Teutsch SM, Bradley LA. The evidence dilemma in genomic medicine. Health Aff (Millwood). 2008 Nov-Dec;27(6):1600-11. doi: 10.1377/hlthaff.27.6.1600. — View Citation

Kohane IS, Masys DR, Altman RB. The incidentalome: a threat to genomic medicine. JAMA. 2006 Jul 12;296(2):212-5. doi: 10.1001/jama.296.2.212. No abstract available. Erratum In: JAMA. 2006 Sep 27;296(12):1466. — View Citation

Krier JB, Green RC. Management of incidental findings in clinical genomic sequencing. Curr Protoc Hum Genet. 2013;Chapter 9:Unit9.23. doi: 10.1002/0471142905.hg0923s77. — View Citation

Lee IH, Lee K, Hsing M, Choe Y, Park JH, Kim SH, Bohn JM, Neu MB, Hwang KB, Green RC, Kohane IS, Kong SW. Prioritizing disease-linked variants, genes, and pathways with an interactive whole-genome analysis pipeline. Hum Mutat. 2014 May;35(5):537-47. doi: 10.1002/humu.22520. Epub 2014 Mar 6. — View Citation

Lipkus IM. Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations. Med Decis Making. 2007 Sep-Oct;27(5):696-713. doi: 10.1177/0272989X07307271. Epub 2007 Sep 14. — View Citation

MacRae CA. Action and the actionability in exome variation. Circ Cardiovasc Genet. 2012 Dec;5(6):597-8. doi: 10.1161/CIRCGENETICS.112.965152. No abstract available. — View Citation

McGuire AL, Joffe S, Koenig BA, Biesecker BB, McCullough LB, Blumenthal-Barby JS, Caulfield T, Terry SF, Green RC. Point-counterpoint. Ethics and genomic incidental findings. Science. 2013 May 31;340(6136):1047-8. doi: 10.1126/science.1240156. Epub 2013 May 16. No abstract available. — View Citation

McGuire AL, McCullough LB, Evans JP. The indispensable role of professional judgment in genomic medicine. JAMA. 2013 Apr 10;309(14):1465-6. doi: 10.1001/jama.2013.1438. No abstract available. — View Citation

Rehm HL. Disease-targeted sequencing: a cornerstone in the clinic. Nat Rev Genet. 2013 Apr;14(4):295-300. doi: 10.1038/nrg3463. Epub 2013 Mar 12. — View Citation

Roter D, Larson S. The Roter interaction analysis system (RIAS): utility and flexibility for analysis of medical interactions. Patient Educ Couns. 2002 Apr;46(4):243-51. doi: 10.1016/s0738-3991(02)00012-5. — View Citation

Song T, Hwang KB, Hsing M, Lee K, Bohn J, Kong SW. gSearch: a fast and flexible general search tool for whole-genome sequencing. Bioinformatics. 2012 Aug 15;28(16):2176-7. doi: 10.1093/bioinformatics/bts358. Epub 2012 Jun 23. — View Citation

Varmus H. Ten years on--the human genome and medicine. N Engl J Med. 2010 May 27;362(21):2028-9. doi: 10.1056/NEJMe0911933. No abstract available. — View Citation

Vassy JL, Green RC, Lehmann LS. Genomic medicine in primary care: barriers and assets. Postgrad Med J. 2013 Nov;89(1057):615-6. doi: 10.1136/postgradmedj-2013-132093. No abstract available. — View Citation

Vassy JL, Lautenbach DM, McLaughlin HM, Kong SW, Christensen KD, Krier J, Kohane IS, Feuerman LZ, Blumenthal-Barby J, Roberts JS, Lehmann LS, Ho CY, Ubel PA, MacRae CA, Seidman CE, Murray MF, McGuire AL, Rehm HL, Green RC; MedSeq Project. The MedSeq Proje — View Citation

Vassy JL, McLaughlin HM, MacRae CA, Seidman CE, Lautenbach D, Krier JB, Lane WJ, Kohane IS, Murray MF, McGuire AL, Rehm HL, Green RC. A one-page summary report of genome sequencing for the healthy adult. Public Health Genomics. 2015;18(2):123-9. doi: 10.1 — View Citation

* Note: There are 33 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Change in Attitudes and Trust Adapted measures (Hall, MA, et al. 2006) assessed participants' attitudes toward genetic information, trust of their physicians and the medical system regarding interpretation and use of genetic information. Higher scores on a 12-60 scale represent more positive attitudes and greater trust. Change at 6-weeks post-results disclosure relative to baseline, administered approx.12.5 months after baseline
Primary Change in Self Efficacy Assessed through a scale developed for the Multiplex Initiative (Kaphingst, K.A., et al. 2012). Higher scores on a 0-24 scale indicate greater confidence in participants' abilities to understand genetic information. Baseline and 6-months post-results disclosure (6 mos. follow-up administered approx. 17 months after baseline)
Primary Change in Preferences for WGS Information Through nine novel survey items, participants were asked about their preferences for the types of genetic testing results they would like to receive from their whole genome sequence. Scores on an 0-9 scale represent the change in the number of categories of types of genetic testing results out of 9 that participants wanted to learn about from Baseline to 6-weeks follow-up. Baseline and 6-weeks post-disclosure (6 wks follow-up administered approx. 12.5 mos. after baseline)
Primary Change in Perceived Health A single-item measure assessed how participants perceived their own health on a 1-5 scale. Adapted from the SF-12 (DeSalvo KB, Qual Life Res, 2006). Higher scores indicate more positive perceptions of health at follow-up Baseline, at the disclosure visit (about 1 hour after results disclosure, avg. 11 mos. after baseline) and 6-months post-disclosure (6 mos. follow-up follow-up administered approx. 17 months after baseline)
Primary Change in Shared Decision Making Changes in shared decision making were assessed through a single item adapted from the Control Preferences Scale, a measure designed to ascertain the degree of control an individual wants to assume when decisions are being made about medical treatment. Higher scores on a scale of 1-3 indicate preferences towards more equally shared decision making (Heisler et al 2003). Higher mean changes over time indicate a change in preference towards more equally shared decision making at follow-up. Baseline and 6-weeks post-disclosure (6 wks follow-up administered approx. 12.5 mos. after baseline)
Primary Change in Intolerance of Uncertainty Changes in participants' tolerance for uncertainty were assessed through a short 12-item version of the Intolerance of Uncertainty Scale (Carleton, 2007). Total summed scale range is 12-60, with higher scores indicating increased negative feelings about uncertainty from baseline to follow-up. Baseline and 6-months post-disclosure (6 mos. follow-up administered approx. 17 mos. after baseline)
Primary Change in General Anxiety and Depression The Hospital Anxiety and Depression Scale (HADS) scale was administered through a survey. This is a validated scale designed to assess the participants' level of depression and anxiety through Likert-type questions. Total ranges for each summed subscale, anxiety and depression, is 0-21. Any participant scoring >14 on the anxiety subscale or >16 on the depression subscale were contacted by study staff for evaluation. Higher scores indicate increased anxiety or depression from baseline to follow-up. Baseline, at the disclosure visit (about 1 hour after results disclosure, avg. 11 mos. after baseline), 6-weeks post-disclosure and 6-months post-disclosure (6 wks. follow-up administered approx. 12.5 mos and 6 mos follow-up approx 17 mos. after baseline)
Primary Change in Health Behaviors Novel items that asked whether participants changed vitamin use, supplement use, medication use, diet, exercise, or "other" health behaviors. Counts and percentages represent participants who reported any health behavior changes. 6-weeks post-disclosure and 6-months post-disclosure (6 wks. follow-up administered approx. 12.5 mos. and 6 mos. follow-up approx. 17 mos. after baseline)
Primary Information Sharing Sharing of information was assessed by asking patients if they intended to share results with others (at the end of the disclosure visit) and if they had shared their results with others (6 months after disclosure) adapted from the Health Information National Trends Survey (HINTS). At the disclosure visit (about 1 hour after results disclosure, avg. 11 mos. after baseline) and 6-months post-disclosure (approx. 17 mos. after baseline)
Primary Changes in Genomic Literacy Changes in participants' genomic literacy were measured with an 11-item measure adapted from the ClinSeq Study (Kaphingst K.A. et al. 2012) administered at baseline and 6 months post-disclosure. Items are marked as correct (1) or incorrect (0) and summed for a total scale range of 0 to 11, with higher scores indicating higher genomic literacy. Assessing Genomic Literacy at baseline and 6-months post-disclosure (approx. 17 mos. after baseline)
Primary Changes in Health Care Utilization Participants' health care utilization was assessed through a combination of medical record reviews and novel and adapted measures from the Behavioral Risk Factor Surveillance System (BRFSS). Changes are assessed by comparing the number of services and procedures received in 6 months following disclosure against the number of services and procedures received in the 6 months prior to disclosure. 6 months prior to disclosure and 6-months post-disclosure (approx. 17 mos. after baseline) and 5-years post-disclosure
Primary Change in Perceived Utility A novel survey item asked participants to rate the usefulness of whole genome sequencing results for managing health on a 1-10 scale. Scores at 6 months were compared to scores at baseline. At baseline and 6-months post-disclosure (approx. 17 mos. after baseline)
Secondary Psychological Impact Psychological impact was assessed by a modified version of the Multidimensional Impact of Cancer Risk Assessment (MICRA) questionnaire. Higher scores indicated more distress related to study results. 6-weeks post-disclosure and 6-months post-disclosure (6wks. follow-up administered approx. 12.5 mos. and 6 mos. follow-up approx. 17 mos. after baseline)
Secondary Decisional Regret Participants' satisfaction with their decision to participate in the MedSeq Project through a 5-item validated scale (Brehaut 2003). Average score computed after reversing scores of 2 negatively phrased items and converting score to range from 0-100 by subtracting 1 and multiplying by 25. Higher scores indicate greater regret. At post-disclosure visit (about 1 hour after results disclosure, avg. 11 mos. after baseline), at 6-weeks post-disclosure, and at 6-months post-disclosure (6 wks follow-up approx. 12.5 mos. and 6 mos. follow-up approx. 17 mos. after baseline)
Secondary Understanding A novel item assessed participants' subjective understanding of their study results on a 1-5 scale, where higher scores indicate greater subjective understanding. At post-disclosure visit (about 1 hour after results disclosure, avg. 11 mos. after baseline), at 6-weeks post-disclosure, and at 6-months post-disclosure (6 wks follow-up approx. 12.5 mos. and 6 mos. follow-up approx. 17 mos. after baseline)
Secondary Expectations Novel survey items asked participants about whether or not their genetic test results would be useful for specific reasons. Response options were "no," "probably not", "probably yes," and "yes." Responses of "probably yes" and "yes" were combined to simplify presentation of data. Baseline

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