North Carolina Genomic Evaluation by Next-generation Exome Sequencing, 2

NCT03548779 | Completed Results FDA Device

• 2 other identifiers: 17-0816U01HG006487
• Study Type: interventional
• Target: 548
• Locations: 1 country
• Sites: 3

Brief Summary

The "North Carolina Clinical Genomic Evaluation by Next-gen Exome Sequencing, 2 (NCGENES 2)" study is part of a larger consortium project investigating the clinical utility, or net benefit of an intervention on patient and family well-being as well as diagnostic efficacy, management planning, and medical outcomes. A clinical trial will be implemented to compare (1) first-line exome sequencing to usual care and (2) participant pre-visit preparation to no pre-visit preparation. The study will use a randomized controlled design, with 2x2 factorial design, coupled with patient-reported outcomes and comprehensive clinical data collection addressing key outcomes, to determine the net impact of diagnostic results and secondary findings.

Conditions

Epilepsy; Seizure; Neuromuscular Diseases; Brain Malformation; Intellectual Disability; Autism Spectrum Disorder; Hypotonia; Inborn Errors of Metabolism; Movement Disorders; Genetic Disease; Development Delay; Chromosome Abnormality; Hearing Loss; Dysmorphic Features; Skeletal Dysplasia; Congenital Abnormality; Microcephaly; Macrocephaly

Outcome Measures

Primary Outcomes (20)

• Initial Patient Pediatric Quality of Life (Peds QL) Score

  The Peds QL Measurement Model for the Pediatric Quality of Inventory measures the core dimensions of health as delineated by the World Health Organization as well as role (school) functioning. The 23-item PedsQL Core Scales (Physical Functioning, Emotional Functioning, Social Functioning, and School Functioning) are developmentally appropriate surveys (Ages 2-4, 5-7, 8-12, 13-18) designed for parent proxy report. The 23 items are grouped together on the questionnaire, and are answered on a scale of 0-4. Items are reversed scored and linearly transformed to a 0-100 scale (0=100, 1=75, 2=50, 3=25, 4=0), so that higher scores indicate better Health-Related Quality of Life (HRQOL). This questionnaire will be self-administered at home.

  4-6 weeks prior to clinic visit 1

• Final Patient Pediatric Quality of Life (Peds QL) Score

  The Peds QL Measurement Model for the Pediatric Quality of Inventory measures the core dimensions of health as delineated by the World Health Organization as well as role (school) functioning. The 23-item PedsQL Core Scales (Physical Functioning, Emotional Functioning, Social Functioning, and School Functioning) are developmentally appropriate surveys (Ages 2-4, 5-7, 8-12, 13-18) designed for parent proxy report. The 23 items are grouped together on the questionnaire, and are answered on a scale of 0-4. Items are reversed scored and linearly transformed to a 0-100 scale (0=100, 1=75, 2=50, 3=25, 4=0), so that higher scores indicate better HRQOL. This questionnaire will be interviewer administered by telephone.

  6 months after return of results

• Initial Caregiver QoL Score

  The Short-Form Health Survey (SF-12) questionnaire is a reliable measure of perceived health that describes the degree of general physical health status and mental health distress. It consists of 12 items, derived from the physical and mental domains. Scores have a range of 0 to 100 and were designed to have a mean score of 50 and a standard deviation of 10 in a representative sample of the US population, with higher scores indicating greater functioning. This questionnaire will be self-administered at home.

  4-6 weeks prior to clinic visit 1

• Intermediate Caregiver QoL Score

  The SF-12 questionnaire is a reliable measure of perceived health that describes the degree of general physical health status and mental health distress. It consists of 12 items, derived from the physical and mental domains. Scores have a range of 0 to 100 and were designed to have a mean score of 50 and a standard deviation of 10 in a representative sample of the US population, with higher scores indicating greater functioning. This questionnaire will be interviewer administered by telephone.

  2 weeks after return of results

• Final Caregiver QoL Score

  The SF-12 questionnaire is a reliable measure of perceived health that describes the degree of general physical health status and mental health distress. It consists of 12 items, derived from the physical and mental domains. Scores have a range of 0 to 100 and were designed to have a mean score of 50 and a standard deviation of 10 in a representative sample of the US population, with higher scores indicating greater functioning. This questionnaire will be interviewer administered by telephone.

  6 months after return of results

• Post-Clinic Visit 1 Mean Patient Centeredness Score

  Patient centeredness scale, which measures the caregiver's perception of the level of patient centeredness of their visit with their child's provider (developed by Little et al., 2001). Self-administered in the clinic, immediately after clinic visit 1. Item responses will be coded as: 1=Very strongly disagree; 2=Strongly disagree; 3=Moderately disagree; 4=Neither agree nor disagree; 5=Moderately agree; 6=Strongly agree; 7=Very strongly agree. Response values will be summed and divided by the total number of items (21) to obtain mean scores ranging from 0-7 where higher values indicate stronger perceptions of patient centeredness.

  Immediately after clinic 1 day of visit 1

• Post-Return of Results Mean Patient Centeredness Score

  Patient centeredness scale, which measures the caregiver's perception of the level of patient centeredness of their visit with their child's provider (developed by Little et al., 2001). Self-administered in the clinic, immediately after clinic visit 1. Item responses will be coded as: 1=Very strongly disagree; 2=Strongly disagree; 3=Moderately disagree; 4=Neither agree nor disagree; 5=Moderately agree; 6=Strongly agree; 7=Very strongly agree. Response values will be summed and divided by the total number of items (21) to obtain mean scores ranging from 0-7 where higher values indicate stronger perceptions of patient centeredness.

  2 weeks after return of results

• Number of Questions Caregiver Asks in Clinic Visit 1

  Count of number of questions caregiver asks provider in the audio recording of clinic visit 1. Coded by trained study staff.

  During clinic 1 day of visit 1

• Number of In-patient Hospital Admissions Among Child Participants 1 Year Prior to Return of Results

  Count of number of in-patient hospital admissions among child participants during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Admissions were summed across all participants.

  1 year prior to return of results

• Number of In-patient Hospital Admissions Among Child Participants 1 Year After Return of Results

  Count of number of in-patient hospital admissions among child participants during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Admissions were summed across all participants.

  1 year after return of results

• Number of In-patient Hospital Days Among Child Participants 1 Year Prior to Return of Results

  Count of number of in-patient hospital days among child participants during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Days were summed across all participants.

  1 year prior to return of results

• Number of In-patient Hospital Days Among Child Participants 1 Year After Return of Results

  Count of number of in-patient hospital days among child participants during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Days were summed across all participants.

  1 year after return of results

• Number of Long-term Care Admissions Among Child Participants 1 Year Prior to Return of Results

  Count of number of long-term care admissions among child participants during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Admissions were summed across all participants.

  1 year prior to return of results

• Number of Long-term Care Admissions Among Child Participants 1 Year After Return of Results

  Count of number of long-term care admissions among child participants during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Admissions were summed across all participants.

  1 year after return of results

• Number of Long-term Care Days Among Child Participants 1 Year Prior to Return of Results

  Count of number of long-term care days among child participants during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Days were summed across all participants.

  1 year prior to return of results

• Number of Long-term Care Days Among Child Participants 1 Year After Return of Results

  Count of number of long-term care days during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Days were summed across all participants.

  1 year after return of results

• Number of ER Visits Among Child Participants 1 Year Prior to Return of Results

  Count of number of ER visits during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Visits were summed across all participants.

  1 year prior to return of results

• Number of ER Visits Among Child Participants 1 Year After Return of Results

  Count of number of ER visits during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Visits were summed across all participants.

  1 year after return of results

• Number of Specialists Visits Among Child Participants 1 Year Prior to Return of Results

  Count of number of specialists visits during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Visits were summed across all participants.

  1 year prior to return of results

• Number of Specialists Visits Among Child Participants 1 Year After Return of Results

  Count of number of specialists visits during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. Visits were summed across all participants.

  1 year after return of results

Secondary Outcomes (15)

• Initial Average Peds QL Score for "Missing School for Not Feeling Well"

  4-6 weeks prior to clinic visit 1

• Final Average Peds QL Score for "Missing School for Not Feeling Well"

  6 months after return of results

• Initial Average Peds QL Score for "Missing School for Doctors Visit"

  4-6 weeks prior to clinic visit 1

• Final Average Peds QL Score for "Missing School for Doctors Visit"

  6 months after return of results

• Initial Amount of Work Missed Because of Child's Condition or Treatments Score

  4-6 weeks prior to clinic visit 1

Study Arms (4)

Pre-visit prep / usual care + exome seq

EXPERIMENTAL

Participants randomized to pre-visit prep will receive a study packet with educational materials and a question prompt list. These participants will be instructed to review the materials, discuss them with family members if desired, use the question prompt list to select questions they would like to ask at clinic visit 1, and bring the list to their clinic visit 1 appointment. Participants will receive usual care and will be offered research exome sequencing.

Behavioral: Pre-visit prep; Diagnostic Test: usual care + exome seq

Pre-visit prep / usual care

EXPERIMENTAL

Participants randomized to pre-visit prep will receive a study packet with educational materials and a question prompt list. These participants will be instructed to review the materials, discuss them with family members if desired, use the question prompt list to select questions they would like to ask at clinic visit 1, and bring the list to their clinic visit 1 appointment. Participants will receive usual care.

Behavioral: Pre-visit prep

No prep / usual care + exome seq

EXPERIMENTAL

Participants in the no pre-visit preparation arm will receive a mailed card reminding them about their upcoming clinic visit. Participants will receive usual care and will be offered research exome sequencing.

Diagnostic Test: usual care + exome seq

No prep / usual care

NO INTERVENTION

Participants in the no pre-visit preparation arm will receive a mailed card reminding them about their upcoming clinic visit. Participants will receive usual care.

Interventions

Pre-visit prep BEHAVIORAL

Patient and provider surveys will be used to measure the impact of pre-visit preparation on the primary outcomes of engagement of participants in the clinical interaction and their view of the interaction as patient-centered, in addition to secondary outcomes that may be affected by this intervention (described above). The study investigators will test the hypothesis that patients will benefit from pre-visit preparation by: (1) rating their clinical encounters as more patient-centered and (2) asking more questions during their clinical encounters.

Pre-visit prep / usual care; Pre-visit prep / usual care + exome seq

usual care + exome seq DIAGNOSTIC_TEST

Provider surveys will be used to assess impact of exome sequencing on diagnostic thinking and management planning. Health utilization and condition-specific general clinical outcomes will be assessed from health records data.

No prep / usual care + exome seq; Pre-visit prep / usual care + exome seq

Eligibility Criteria

• Age: 0 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Parents meeting the following criteria:
• Parent of a child who meets the criteria below
• At least 18 years old.
• Must be able to provide informed consent for child and self.
• Must be fluent in English or Spanish.
• Children meeting the following criteria:
• Infants and children 15 years old or less.
• Referred for initial evaluation of a possible monogenic disorder OR
• Seen for evaluation of an undiagnosed disorder in a study-associated clinic.

You may not qualify if:

• Parents:
• Younger than 18 years old.
• Unwilling to complete study surveys and other procedures.
• Have cognitive or other impairments precluding ability to provide giving informed consent.
• Not fluent in English or Spanish.
• Unable to attend all clinic visits
• Children:
• Have a known genetic or non-genetic diagnosis (only referred for counseling or management).
• Medically unstable.

Sponsors & Collaborators

• University of North Carolina, Chapel Hill: lead
• National Human Genome Research Institute (NHGRI): collaborator
• East Carolina University: collaborator
• Mission Health System, Asheville, NC: collaborator

Study Sites (3)

Mission Health

Asheville, North Carolina, 28801, United States

Location

University of North Carolina at Chapel Hill

Chapel Hill, North Carolina, 27599, United States

Location

East Carolina University

Greenville, North Carolina, 27858, United States

Location

Related Publications (61)

• Aboumatar HJ, Carson KA, Beach MC, Roter DL, Cooper LA. The impact of health literacy on desire for participation in healthcare, medical visit communication, and patient reported outcomes among patients with hypertension. J Gen Intern Med. 2013 Nov;28(11):1469-76. doi: 10.1007/s11606-013-2466-5. Epub 2013 May 21.

  PMID: 23690237 BACKGROUND

• ACMG Board of Directors. Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics. Genet Med. 2015 Jun;17(6):505-7. doi: 10.1038/gim.2015.41. Epub 2015 Mar 12.

  PMID: 25764213 BACKGROUND

• Amendola LM, Dorschner MO, Robertson PD, Salama JS, Hart R, Shirts BH, Murray ML, Tokita MJ, Gallego CJ, Kim DS, Bennett JT, Crosslin DR, Ranchalis J, Jones KL, Rosenthal EA, Jarvik ER, Itsara A, Turner EH, Herman DS, Schleit J, Burt A, Jamal SM, Abrudan JL, Johnson AD, Conlin LK, Dulik MC, Santani A, Metterville DR, Kelly M, Foreman AK, Lee K, Taylor KD, Guo X, Crooks K, Kiedrowski LA, Raffel LJ, Gordon O, Machini K, Desnick RJ, Biesecker LG, Lubitz SA, Mulchandani S, Cooper GM, Joffe S, Richards CS, Yang Y, Rotter JI, Rich SS, O'Donnell CJ, Berg JS, Spinner NB, Evans JP, Fullerton SM, Leppig KA, Bennett RL, Bird T, Sybert VP, Grady WM, Tabor HK, Kim JH, Bamshad MJ, Wilfond B, Motulsky AG, Scott CR, Pritchard CC, Walsh TD, Burke W, Raskind WH, Byers P, Hisama FM, Rehm H, Nickerson DA, Jarvik GP. Actionable exomic incidental findings in 6503 participants: challenges of variant classification. Genome Res. 2015 Mar;25(3):305-15. doi: 10.1101/gr.183483.114. Epub 2015 Jan 30.

  PMID: 25637381 BACKGROUND

• Barnett ML, Landon BE, O'Malley AJ, Keating NL, Christakis NA. Mapping physician networks with self-reported and administrative data. Health Serv Res. 2011 Oct;46(5):1592-609. doi: 10.1111/j.1475-6773.2011.01262.x. Epub 2011 Apr 26.

  PMID: 21521213 BACKGROUND

• Bates BR. Public culture and public understanding of genetics: a focus group study. Public Underst Sci. 2005 Jan;14(1):47-65. doi: 10.1177/0963662505048409.

  PMID: 15822248 BACKGROUND

• Berg JS, Adams M, Nassar N, Bizon C, Lee K, Schmitt CP, Wilhelmsen KC, Evans JP. An informatics approach to analyzing the incidentalome. Genet Med. 2013 Jan;15(1):36-44. doi: 10.1038/gim.2012.112. Epub 2012 Sep 20.

  PMID: 22995991 BACKGROUND

• Berg JS, Foreman AK, O'Daniel JM, Booker JK, Boshe L, Carey T, Crooks KR, Jensen BC, Juengst ET, Lee K, Nelson DK, Powell BC, Powell CM, Roche MI, Skrzynia C, Strande NT, Weck KE, Wilhelmsen KC, Evans JP. A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genome-scale sequencing. Genet Med. 2016 May;18(5):467-75. doi: 10.1038/gim.2015.104. Epub 2015 Aug 13.

  PMID: 26270767 BACKGROUND

• Black KZ, Hardy CY, De Marco M, Ammerman AS, Corbie-Smith G, Council B, Ellis D, Eng E, Harris B, Jackson M, Jean-Baptiste J, Kearney W, Legerton M, Parker D, Wynn M, Lightfoot A. Beyond incentives for involvement to compensation for consultants: increasing equity in CBPR approaches. Prog Community Health Partnersh. 2013 Fall;7(3):263-70. doi: 10.1353/cpr.2013.0040.

  PMID: 24056508 BACKGROUND

• Brandes K, Linn AJ, Butow PN, van Weert JC. The characteristics and effectiveness of Question Prompt List interventions in oncology: a systematic review of the literature. Psychooncology. 2015 Mar;24(3):245-52. doi: 10.1002/pon.3637. Epub 2014 Jul 31.

  PMID: 25082386 BACKGROUND

• Burkett K, Morris E, Manning-Courtney P, Anthony J, Shambley-Ebron D. African American families on autism diagnosis and treatment: the influence of culture. J Autism Dev Disord. 2015 Oct;45(10):3244-54. doi: 10.1007/s10803-015-2482-x.

  PMID: 26055985 BACKGROUND

• Bussey-Jones J, Garrett J, Henderson G, Moloney M, Blumenthal C, Corbie-Smith G. The role of race and trust in tissue/blood donation for genetic research. Genet Med. 2010 Feb;12(2):116-21. doi: 10.1097/GIM.0b013e3181cd6689.

  PMID: 20098329 BACKGROUND

• Catz DS, Green NS, Tobin JN, Lloyd-Puryear MA, Kyler P, Umemoto A, Cernoch J, Brown R, Wolman F. Attitudes about genetics in underserved, culturally diverse populations. Community Genet. 2005;8(3):161-72. doi: 10.1159/000086759.

  PMID: 16113533 BACKGROUND

• Clayton JM, Butow PN, Tattersall MH, Devine RJ, Simpson JM, Aggarwal G, Clark KJ, Currow DC, Elliott LM, Lacey J, Lee PG, Noel MA. Randomized controlled trial of a prompt list to help advanced cancer patients and their caregivers to ask questions about prognosis and end-of-life care. J Clin Oncol. 2007 Feb 20;25(6):715-23. doi: 10.1200/JCO.2006.06.7827.

  PMID: 17308275 BACKGROUND

• Corbie-Smith G, Thomas SB, St George DM. Distrust, race, and research. Arch Intern Med. 2002 Nov 25;162(21):2458-63. doi: 10.1001/archinte.162.21.2458.

  PMID: 12437405 BACKGROUND

• Cunningham-Burley S. Public knowledge and public trust. Community Genet. 2006;9(3):204-10. doi: 10.1159/000092658.

  PMID: 16741351 BACKGROUND

• DeWalt DA, Schillinger D, Ruo B, Bibbins-Domingo K, Baker DW, Holmes GM, Weinberger M, Macabasco-O'Connell A, Broucksou K, Hawk V, Grady KL, Erman B, Sueta CA, Chang PP, Cene CW, Wu JR, Jones CD, Pignone M. Multisite randomized trial of a single-session versus multisession literacy-sensitive self-care intervention for patients with heart failure. Circulation. 2012 Jun 12;125(23):2854-62. doi: 10.1161/CIRCULATIONAHA.111.081745. Epub 2012 May 9.

  PMID: 22572916 BACKGROUND

• Dobransky-Fasiska D, Brown C, Pincus HA, Nowalk MP, Wieland M, Parker LS, Cruz M, McMurray ML, Mulsant B, Reynolds CF 3rd; RNDC-Community Partners. Developing a community-academic partnership to improve recognition and treatment of depression in underserved African American and white elders. Am J Geriatr Psychiatry. 2009 Nov;17(11):953-64. doi: 10.1097/JGP.0b013e31818f3a7e.

  PMID: 20104053 BACKGROUND

• Durand MA, Carpenter L, Dolan H, Bravo P, Mann M, Bunn F, Elwyn G. Do interventions designed to support shared decision-making reduce health inequalities? A systematic review and meta-analysis. PLoS One. 2014 Apr 15;9(4):e94670. doi: 10.1371/journal.pone.0094670. eCollection 2014.

  PMID: 24736389 BACKGROUND

• Eggly S, Harper FW, Penner LA, Gleason MJ, Foster T, Albrecht TL. Variation in question asking during cancer clinical interactions: a potential source of disparities in access to information. Patient Educ Couns. 2011 Jan;82(1):63-8. doi: 10.1016/j.pec.2010.04.008. Epub 2010 Apr 28.

  PMID: 20430566 BACKGROUND

• Elder JH, Brasher S, Alexander B. Identifying the Barriers to Early Diagnosis and Treatment in Underserved Individuals with Autism Spectrum Disorders (ASD) and Their Families: A Qualitative Study. Issues Ment Health Nurs. 2016 Jun;37(6):412-20. doi: 10.3109/01612840.2016.1153174. Epub 2016 Apr 12.

  PMID: 27070190 BACKGROUND

• Epstein RM, Street RL Jr. The values and value of patient-centered care. Ann Fam Med. 2011 Mar-Apr;9(2):100-3. doi: 10.1370/afm.1239. No abstract available.

  PMID: 21403134 BACKGROUND

• Evans JP, Wilhelmsen KC, Berg J, Schmitt CP, Krishnamurthy A, Fecho K, Ahalt SC. A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine. EGEMS (Wash DC). 2016 Apr 19;4(1):1198. doi: 10.13063/2327-9214.1198. eCollection 2016.

  PMID: 27195307 BACKGROUND

• Evans JP. Return of results to the families of children in genomic sequencing: tallying risks and benefits. Genet Med. 2013 Jun;15(6):435-6. doi: 10.1038/gim.2013.54. No abstract available.

  PMID: 23739673 BACKGROUND

• Evans JP. When is a medical finding "incidental"? Genet Med. 2013 Jul;15(7):515-6. doi: 10.1038/gim.2013.74. Epub 2013 May 30. No abstract available.

  PMID: 23722872 BACKGROUND

• Facio FM, Lee K, O'Daniel JM. A genetic counselor's guide to using next-generation sequencing in clinical practice. J Genet Couns. 2014 Aug;23(4):455-62. doi: 10.1007/s10897-013-9662-7. Epub 2013 Oct 24.

  PMID: 24151055 BACKGROUND

• Fan Z, Greenwood R, Felix AC, Shiloh-Malawsky Y, Tennison M, Roche M, Crooks K, Weck K, Wilhelmsen K, Berg J, Evans J. GCH1 heterozygous mutation identified by whole-exome sequencing as a treatable condition in a patient presenting with progressive spastic paraplegia. J Neurol. 2014 Mar;261(3):622-4. doi: 10.1007/s00415-014-7265-3. Epub 2014 Feb 8. No abstract available.

  PMID: 24509643 BACKGROUND

• Foreman AK, Lee K, Evans JP. The NCGENES project: exploring the new world of genome sequencing. N C Med J. 2013 Nov-Dec;74(6):500-4.

  PMID: 24316776 BACKGROUND

• Frey LJ, Lenert L, Lopez-Campos G. EHR Big Data Deep Phenotyping. Contribution of the IMIA Genomic Medicine Working Group. Yearb Med Inform. 2014 Aug 15;9(1):206-11. doi: 10.15265/IY-2014-0006.

  PMID: 25123744 BACKGROUND

• Girdea M, Dumitriu S, Fiume M, Bowdin S, Boycott KM, Chenier S, Chitayat D, Faghfoury H, Meyn MS, Ray PN, So J, Stavropoulos DJ, Brudno M. PhenoTips: patient phenotyping software for clinical and research use. Hum Mutat. 2013 Aug;34(8):1057-65. doi: 10.1002/humu.22347. Epub 2013 May 24.

  PMID: 23636887 BACKGROUND

• Gordon HS, Street RL Jr, Sharf BF, Souchek J. Racial differences in doctors' information-giving and patients' participation. Cancer. 2006 Sep 15;107(6):1313-20. doi: 10.1002/cncr.22122.

  PMID: 16909424 BACKGROUND

• Gozu A, Beach MC, Price EG, Gary TL, Robinson K, Palacio A, Smarth C, Jenckes M, Feuerstein C, Bass EB, Powe NR, Cooper LA. Self-administered instruments to measure cultural competence of health professionals: a systematic review. Teach Learn Med. 2007 Spring;19(2):180-90. doi: 10.1080/10401330701333654.

  PMID: 17564547 BACKGROUND

• 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.

  PMID: 23788249 BACKGROUND

• Haase R, Michie M, Skinner D. Flexible positions, managed hopes: the promissory bioeconomy of a whole genome sequencing cancer study. Soc Sci Med. 2015 Apr;130:146-53. doi: 10.1016/j.socscimed.2015.02.016. Epub 2015 Feb 13.

  PMID: 25697637 BACKGROUND

• Haga SB, Rosanbalm KD, Boles L, Tindall GM, Livingston TM, O'Daniel JM. Promoting public awareness and engagement in genome sciences. J Genet Couns. 2013 Aug;22(4):508-16. doi: 10.1007/s10897-013-9577-3. Epub 2013 Feb 23.

  PMID: 23435715 BACKGROUND

• Hartz SM, Quan T, Ibiebele A, Fisher SL, Olfson E, Salyer P, Bierut LJ. The significant impact of education, poverty, and race on Internet-based research participant engagement. Genet Med. 2017 Feb;19(2):240-243. doi: 10.1038/gim.2016.91. Epub 2016 Jul 28.

  PMID: 27467456 BACKGROUND

• Henderson GE. With great (participant) rights comes great (researcher) responsibility. Genet Med. 2016 Feb;18(2):124-5. doi: 10.1038/gim.2015.67. Epub 2015 May 7. No abstract available.

  PMID: 25950735 BACKGROUND

• Hudon C, Fortin M, Haggerty JL, Lambert M, Poitras ME. Measuring patients' perceptions of patient-centered care: a systematic review of tools for family medicine. Ann Fam Med. 2011 Mar-Apr;9(2):155-64. doi: 10.1370/afm.1226.

  PMID: 21403143 BACKGROUND

• Isaacson M. Clarifying concepts: cultural humility or competency. J Prof Nurs. 2014 May-Jun;30(3):251-8. doi: 10.1016/j.profnurs.2013.09.011.

  PMID: 24939335 BACKGROUND

• Joseph-Williams N, Elwyn G, Edwards A. Knowledge is not power for patients: a systematic review and thematic synthesis of patient-reported barriers and facilitators to shared decision making. Patient Educ Couns. 2014 Mar;94(3):291-309. doi: 10.1016/j.pec.2013.10.031. Epub 2013 Nov 9.

  PMID: 24305642 BACKGROUND

• Kaphingst KA, Blanchard M, Milam L, Pokharel M, Elrick A, Goodman MS. Relationships Between Health Literacy and Genomics-Related Knowledge, Self-Efficacy, Perceived Importance, and Communication in a Medically Underserved Population. J Health Commun. 2016;21 Suppl 1(Suppl 1):58-68. doi: 10.1080/10810730.2016.1144661.

  PMID: 27043759 BACKGROUND

• Katz MG, Jacobson TA, Veledar E, Kripalani S. Patient literacy and question-asking behavior during the medical encounter: a mixed-methods analysis. J Gen Intern Med. 2007 Jun;22(6):782-6. doi: 10.1007/s11606-007-0184-6. Epub 2007 Apr 12.

  PMID: 17431697 BACKGROUND

• Kinnersley P, Edwards A, Hood K, Ryan R, Prout H, Cadbury N, MacBeth F, Butow P, Butler C. Interventions before consultations to help patients address their information needs by encouraging question asking: systematic review. BMJ. 2008 Jul 16;337:a485. doi: 10.1136/bmj.a485.

  PMID: 18632672 BACKGROUND

• Lea DH, Kaphingst KA, Bowen D, Lipkus I, Hadley DW. Communicating genetic and genomic information: health literacy and numeracy considerations. Public Health Genomics. 2011;14(4-5):279-89. doi: 10.1159/000294191. Epub 2010 Apr 20.

  PMID: 20407217 BACKGROUND

• Lee K, Berg JS, Milko L, Crooks K, Lu M, Bizon C, Owen P, Wilhelmsen KC, Weck KE, Evans JP, Garg S. High Diagnostic Yield of Whole Exome Sequencing in Participants With Retinal Dystrophies in a Clinical Ophthalmology Setting. Am J Ophthalmol. 2015 Aug;160(2):354-363.e9. doi: 10.1016/j.ajo.2015.04.026. Epub 2015 Apr 22.

  PMID: 25910913 BACKGROUND

• Leos C, Khan CM, Rini C. Understanding self-management behaviors in symptomatic adults with uncertain etiology using an illness perceptions framework. J Behav Med. 2016 Apr;39(2):310-9. doi: 10.1007/s10865-015-9698-2. Epub 2015 Dec 8.

  PMID: 26646840 BACKGROUND

• Nutter RL, Bullas LR, Schultz RL. Some properties of five new Salmonella bacteriophages. J Virol. 1970 Jun;5(6):754-64. doi: 10.1128/JVI.5.6.754-764.1970.

  PMID: 4193833 BACKGROUND

• O'Daniel JM, Lee K. Whole-genome and whole-exome sequencing in hereditary cancer: impact on genetic testing and counseling. Cancer J. 2012 Jul-Aug;18(4):287-92. doi: 10.1097/PPO.0b013e318262467e.

  PMID: 22846728 BACKGROUND

• O'Daniel JM, Rosanbalm KD, Boles L, Tindall GM, Livingston TM, Haga SB. Enhancing geneticists' perspectives of the public through community engagement. Genet Med. 2012 Feb;14(2):243-9. doi: 10.1038/gim.2011.29. Epub 2012 Jan 19.

  PMID: 22241095 BACKGROUND

• Pickard KE, Kilgore AN, Ingersoll BR. Using Community Partnerships to Better Understand the Barriers to Using an Evidence-Based, Parent-Mediated Intervention for Autism Spectrum Disorder in a Medicaid System. Am J Community Psychol. 2016 Jun;57(3-4):391-403. doi: 10.1002/ajcp.12050. Epub 2016 May 19.

  PMID: 27216766 BACKGROUND

• Roche MI, Berg JS. Incidental Findings with Genomic Testing: Implications for Genetic Counseling Practice. Curr Genet Med Rep. 2015;3(4):166-176. doi: 10.1007/s40142-015-0075-9. Epub 2015 Aug 25.

  PMID: 26566463 BACKGROUND

• Rodriguez V, Andrade AD, Garcia-Retamero R, Anam R, Rodriguez R, Lisigurski M, Sharit J, Ruiz JG. Health literacy, numeracy, and graphical literacy among veterans in primary care and their effect on shared decision making and trust in physicians. J Health Commun. 2013;18 Suppl 1(Suppl 1):273-89. doi: 10.1080/10810730.2013.829137.

  PMID: 24093361 BACKGROUND

• Sansoni JE, Grootemaat P, Duncan C. Question Prompt Lists in health consultations: A review. Patient Educ Couns. 2015 Jun 3:S0738-3991(15)00258-X. doi: 10.1016/j.pec.2015.05.015. Online ahead of print.

  PMID: 26104993 BACKGROUND

• Sawaya GF, Guirguis-Blake J, LeFevre M, Harris R, Petitti D; U.S. Preventive Services Task Force. Update on the methods of the U.S. Preventive Services Task Force: estimating certainty and magnitude of net benefit. Ann Intern Med. 2007 Dec 18;147(12):871-5. doi: 10.7326/0003-4819-147-12-200712180-00007.

  PMID: 18087058 BACKGROUND

• Say R, Murtagh M, Thomson R. Patients' preference for involvement in medical decision making: a narrative review. Patient Educ Couns. 2006 Feb;60(2):102-14. doi: 10.1016/j.pec.2005.02.003.

  PMID: 16442453 BACKGROUND

• Seifert BA, O'Daniel JM, Amin K, Marchuk DS, Patel NM, Parker JS, Hoyle AP, Mose LE, Marron A, Hayward MC, Bizon C, Wilhelmsen KC, Evans JP, Earp HS 3rd, Sharpless NE, Hayes DN, Berg JS. Germline Analysis from Tumor-Germline Sequencing Dyads to Identify Clinically Actionable Secondary Findings. Clin Cancer Res. 2016 Aug 15;22(16):4087-4094. doi: 10.1158/1078-0432.CCR-16-0015. Epub 2016 Apr 15.

  PMID: 27083775 BACKGROUND

• Skrzynia C, Berg JS, Willis MS, Jensen BC. Genetics and heart failure: a concise guide for the clinician. Curr Cardiol Rev. 2015;11(1):10-7. doi: 10.2174/1573403x09666131117170446.

  PMID: 24251456 BACKGROUND

• Strande NT, Berg JS. Defining the Clinical Value of a Genomic Diagnosis in the Era of Next-Generation Sequencing. Annu Rev Genomics Hum Genet. 2016 Aug 31;17:303-32. doi: 10.1146/annurev-genom-083115-022348. Epub 2016 May 26.

  PMID: 27362341 BACKGROUND

• van Nimwegen KJ, Schieving JH, Willemsen MA, Veltman JA, van der Burg S, van der Wilt GJ, Grutters JP. The diagnostic pathway in complex paediatric neurology: a cost analysis. Eur J Paediatr Neurol. 2015 Mar;19(2):233-9. doi: 10.1016/j.ejpn.2014.12.014. Epub 2014 Dec 29.

  PMID: 25604808 BACKGROUND

• Willems S, De Maesschalck S, Deveugele M, Derese A, De Maeseneer J. Socio-economic status of the patient and doctor-patient communication: does it make a difference? Patient Educ Couns. 2005 Feb;56(2):139-46. doi: 10.1016/j.pec.2004.02.011.

  PMID: 15653242 BACKGROUND

• Zamora I, Williams ME, Higareda M, Wheeler BY, Levitt P. Brief Report: Recruitment and Retention of Minority Children for Autism Research. J Autism Dev Disord. 2016 Feb;46(2):698-703. doi: 10.1007/s10803-015-2603-6.

  PMID: 26404703 BACKGROUND

• Staley BS, Milko LV, Waltz M, Griesemer I, Mollison L, Grant TL, Farnan L, Roche M, Navas A, Lightfoot A, Foreman AKM, O'Daniel JM, O'Neill SC, Lin FC, Roman TS, Brandt A, Powell BC, Rini C, Berg JS, Bensen JT. Evaluating the clinical utility of early exome sequencing in diverse pediatric outpatient populations in the North Carolina Clinical Genomic Evaluation of Next-generation Exome Sequencing (NCGENES) 2 study: a randomized controlled trial. Trials. 2021 Jun 14;22(1):395. doi: 10.1186/s13063-021-05341-2.

  PMID: 34127041 DERIVED

Related Links

• Ales M, Luca L, Marija V, Gorazd R, Karin W, Ana B, Alenka H, Peterlin B. Phenotype-driven gene target definition in clinical genome-wide sequencing data interpretation. Genet Med \[Internet\]. 2016 Mar 31 \[cited 2016 Aug 3\]

MeSH Terms

Conditions

Epilepsy; Neuromuscular Diseases; Intellectual Disability; Autism Spectrum Disorder; Muscle Hypotonia; Metabolism, Inborn Errors; Movement Disorders; Genetic Diseases, Inborn; Learning Disabilities; Chromosome Aberrations; Hearing Loss; Mucopolysaccharidosis IV; Congenital Abnormalities; Microcephaly; Megalencephaly

Condition Hierarchy (Ancestors)

Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neurobehavioral Manifestations; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Neurodevelopmental Disorders; Mental Disorders; Child Development Disorders, Pervasive; Neuromuscular Manifestations; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Metabolic Diseases; Nutritional and Metabolic Diseases; Communication Disorders; Pathologic Processes; Hearing Disorders; Ear Diseases; Otorhinolaryngologic Diseases; Sensation Disorders; Mucopolysaccharidoses; Carbohydrate Metabolism, Inborn Errors; Lysosomal Storage Diseases; Mucinoses; Connective Tissue Diseases; Skin and Connective Tissue Diseases; Craniofacial Abnormalities; Musculoskeletal Abnormalities; Musculoskeletal Diseases; Malformations of Cortical Development, Group I; Malformations of Cortical Development; Nervous System Malformations

Limitations and Caveats

Disruption of enrollment due to COVID-19 pandemic; required temporary pause in enrollment followed by adjusted study procedures. Instability of study personnel at one enrollment site led to fewer participants enrolled than initially anticipated.

Results Point of Contact

• Title: Jonathan Berg, MD, PhD
• Organization: University of North Carolina at Chapel Hill

jonathan_berg@med.unc.edu

919-966-7043

Study Officials

• Jeannette T Bensen, Ph.D

  University of North Carolina, Chapel Hill

  STUDY DIRECTOR

• Jonathan S Berg, MD, PhD

  University of North Carolina, Chapel Hill

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: CARE PROVIDER, OUTCOMES ASSESSOR
• Masking Details: The study coordinator will assign the first randomization to pre-visit preparation arm and care providers will not be told of the patient's pre-visit preparatory randomization arm prior to the first usual care visit. Randomization to exome sequencing will be performed after the first usual care visit by the study coordinator. Investigators will receive de-identified coded data and thus will not be able to link a patient name to an intervention arm. Some analyses will require individual-level randomization arm status to allow for comparison of parent questionnaire responses or health outcomes by arm - a major focus of this study. All interviewers and medical records staff conducting telephone surveys and/or medical records abstraction for clinical data will be blinded to the participants randomization status. Access to this information will be blocked in the electronic patient tracking status by study role.
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 24, 2018
• First Posted: June 7, 2018
• Study Start: September 28, 2018
• Primary Completion: September 8, 2023
• Study Completion: September 8, 2024
• Last Updated: May 13, 2025
• Results First Posted: May 13, 2025

Record last verified: 2024-02

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF
• Time Frame: Data will be shared following study completion and publication of primary study results.
• Access Criteria: Described above. Access will be by study leadership permission and under an inter-institutional data sharing agreement where relevant

Locations

US (3)