Healthy Adults (Full Study and Extension Phase) Clinical Trial
Official title:
The MedSeq Project Pilot Study: Integrating Whole Genome Sequencing Into the Practice of Clinical Medicine
Verified date | April 2024 |
Source | Brigham and Women's Hospital |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
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.
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 |
Country | Name | City | State |
---|---|---|---|
United States | Brigham and Women's Hospital | Boston | Massachusetts |
Lead Sponsor | Collaborator |
---|---|
Brigham and Women's Hospital | Baylor College of Medicine, Duke University, National Human Genome Research Institute (NHGRI) |
United States,
Arndt AK, MacRae CA. Genetic testing in cardiovascular diseases. Curr Opin Cardiol. 2014 May;29(3):235-40. doi: 10.1097/HCO.0000000000000055. — View Citation
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
Brehaut JC, O'Connor AM, Wood TJ, Hack TF, Siminoff L, Gordon E, Feldman-Stewart D. Validation of a decision regret scale. Med Decis Making. 2003 Jul-Aug;23(4):281-92. doi: 10.1177/0272989X03256005. — View Citation
Carleton RN, Norton MA, Asmundson GJ. Fearing the unknown: a short version of the Intolerance of Uncertainty Scale. J Anxiety Disord. 2007;21(1):105-17. doi: 10.1016/j.janxdis.2006.03.014. Epub 2006 May 2. — View Citation
Evans JP, Meslin EM, Marteau TM, Caulfield T. Genomics. Deflating the genomic bubble. Science. 2011 Feb 18;331(6019):861-2. doi: 10.1126/science.1198039. No abstract available. — View Citation
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 all — Click here to view all references
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 |