A Pilot Project Exploring the Impact of Whole Genome Sequencing in Healthcare
The MedSeq Project Pilot Study: Integrating Whole Genome Sequencing Into the Practice of Clinical Medicine
Sponsor study identifier
Secondary identifiers
NIH
interventional
213
1 country
1
Study Start
December 2011
Actual (reported)Primary Completion
November 4, 2016
Actual (reported)Study Completion
January 2, 2021
Actual (reported)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.
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
January 2, 2021
Actual (reported)Click on a node to explore related trials.
Some registry-reported names shown below are not yet linked in this graph.
Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
December 2011
Actual (reported)August 17, 2012
Actual (reported)November 29, 2012
Actual (reported)November 4, 2016
Actual (reported)November 7, 2018
Actual (reported)January 2, 2021
Actual (reported)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
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)
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)
Psychological Impact
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)
Decisional 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)
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)
Expectations
Baseline
Doctors and their patients receive a Genome Report and an Annotated Family History Report.
Doctors and their patients receive an Annotated Family History Report only.
Doctors and their patients receive a Genome Report and a Family History report. There are two sections of the Genome Report: 1. The General Genome Report, which include highly penetrant disease mutations, carrier status for recessive disease, and pharmacogenetic associations. 2. 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.
Brigham and Women's Hospital
Boston, Massachusetts, 02115, United States
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.
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.
Robert C Green, MD, MPH
Brigham and Women's Hospital
213 participants (actual enrollment reported by the registry).
First Submitted
August 17, 2012
First Posted
November 29, 2012
Study Start
December 2011
Actual (reported)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)
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)
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)
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)
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)
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)
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)
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
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)
Doctors and their patients receive a Family History report.
Registry-reported names are shown in full. Names without a link have not yet been matched to a Syfrah profile.
Contact the study team to confirm eligibility.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Arndt AK, MacRae CA. Genetic testing in cardiovascular diseases. Curr Opin Cardiol. 2014 May;29(3):235-40. doi: 10.1097/HCO.0000000000000055.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Green RC, Rehm H, Kohane I. Clinical Genome Sequencing. Genomic and Personalized Medicine 2nd Edition: 102- 122, 2012.
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.
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.
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 Project: a randomized trial of integrating whole genome sequencing into clinical medicine. Trials. 2014 Mar 20;15:85. doi: 10.1186/1745-6215-15-85.
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: 10.1159/000370102. Epub 2015 Jan 21.
Cirino AL, Lakdawala NK, McDonough B, Conner L, Adler D, Weinfeld M, O'Gara P, Rehm HL, Machini K, Lebo M, Blout C, Green RC, MacRae CA, Seidman CE, Ho CY; MedSeq Project*. A Comparison of Whole Genome Sequencing to Multigene Panel Testing in Hypertrophic Cardiomyopathy Patients. Circ Cardiovasc Genet. 2017 Oct;10(5):e001768. doi: 10.1161/CIRCGENETICS.117.001768.
Vassy JL, Christensen KD, Schonman EF, Blout CL, Robinson JO, Krier JB, Diamond PM, Lebo M, Machini K, Azzariti DR, Dukhovny D, Bates DW, MacRae CA, Murray MF, Rehm HL, McGuire AL, Green RC; MedSeq Project. The Impact of Whole-Genome Sequencing on the Primary Care and Outcomes of Healthy Adult Patients: A Pilot Randomized Trial. Ann Intern Med. 2017 Jun 27;167(3):159-169. doi: 10.7326/M17-0188. Print 2017 Aug 1.
Primary Completion
November 4, 2016
Actual (reported)Study Completion
January 2, 2021
Actual (reported)Last Updated
August 27, 2024
Results First Posted
November 7, 2018
Record last verified: 2024-08
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