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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT03548779
Other study ID # 17-0816
Secondary ID U01HG006487
Status Active, not recruiting
Phase N/A
First received
Last updated
Start date September 28, 2018
Est. completion date September 8, 2024

Study information

Verified date February 2024
Source University of North Carolina, Chapel Hill
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial 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.


Description:

The NCGENES 2 study is part of the "Clinical Sequencing Evidence-Generating Research (CSER2)" - Clinical Sites with Enhanced Diversity (U01), and brings together interdisciplinary experts from across North Carolina to address questions critical to the translation of genomic medicine to the care of patients with suspected genetic disorders. In this renewal of the initial NCGENES study, NCGENES 2 will carry out a clinical trial of exome sequencing as a diagnostic test to answer the next set of questions vital to making genome-scale sequencing a routine clinical tool. The study population will be drawn from a state-wide network of Clinical Genetics and Pediatric Neurology clinics -- clinical domains in which patients are enriched for phenotypes caused by heterogeneous genetic conditions. Exome sequencing and genome sequencing (ES/GS) are efficient means of establishing a molecular diagnosis in these populations, with yields of positive or possible diagnostic results in at least 30% of patients examined based on findings from NCGENES and other work. Evidence will be generated regarding the clinical utility of ES/GS using a prospective randomized controlled trial that compares usual care plus exome sequencing to usual care. Patient-reported data, electronic health records data, and administrative claims data will be used to evaluate defined health outcomes, in collaboration with experts in health economics and health services research, to address pressing questions about the utility of exome sequencing. Furthermore, an examination of communication between patients and physicians, and between physicians and laboratories, and how these critical interactions affect the utility of genomic sequencing will be conducted. A second, nested randomized trial (crossed with exome sequencing in a full-factorial design) will be incorporated to test the hypothesis that a theory-based, multi-component pre-clinic preparation intervention for patients will improve patient-centered outcomes. An "embedded Ethical, Legal, and Social Implications (ELSI)" component will provide feedback to providers regarding communication discrepancies to iteratively improve care. Finally, the challenges of integrating clinical data and genomic information across a state-wide network of sites and examining different models of interaction between genomic clinicians and molecular diagnostic laboratorians will be explored.


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 806
Est. completion date September 8, 2024
Est. primary completion date September 8, 2023
Accepts healthy volunteers No
Gender All
Age group 0 Years and older
Eligibility Both children and parents are participants: Inclusion Criteria: Parents meeting the following criteria: 1. Parent of a child who meets the criteria below 2. At least 18 years old. 3. Must be able to provide informed consent for child and self. 4. Must be fluent in English or Spanish. Children meeting the following criteria: 1. Infants and children 15 years old or less. 2. Referred for initial evaluation of a possible monogenic disorder OR 3. Seen for evaluation of an undiagnosed disorder in a study-associated clinic. Exclusion Criteria: Parents: 1. Younger than 18 years old. 2. Unwilling to complete study surveys and other procedures. 3. Have cognitive or other impairments precluding ability to provide giving informed consent. 4. Not fluent in English or Spanish. 5. Unable to attend all clinic visits Children: 1. Have a known genetic or non-genetic diagnosis (only referred for counseling or management). 2. Medically unstable.

Study Design


Related Conditions & MeSH terms

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

Intervention

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

Locations

Country Name City State
United States Mission Health Asheville North Carolina
United States University of North Carolina at Chapel Hill Chapel Hill North Carolina
United States East Carolina University Greenville North Carolina

Sponsors (4)

Lead Sponsor Collaborator
University of North Carolina, Chapel Hill East Carolina University, Mission Health System, Asheville, NC, National Human Genome Research Institute (NHGRI)

Country where clinical trial is conducted

United States, 

References & Publications (60)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — 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

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 60 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Number of in-patient hospital admissions 1 year prior to return of results Count of number of in-patient hospital admissions during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year prior to return of results
Primary Number of in-patient hospital admissions 1 year after return of results Count of number of in-patient hospital admissions during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year after return of results
Primary Number of in-patient hospital days 1 year prior to return of results Count of number of in-patient hospital days during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year prior to return of results
Primary Number of in-patient hospital days 1 year after return of results Count of number of in-patient hospital days during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year after return of results
Primary Number of long-term care admissions 1 year prior to return of results Count of number of long-term care admissions during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year prior to return of results
Primary Number of long-term care admissions 1 year after return of results Count of number of long-term care admissions during 1 year after return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year after return of results
Primary Number of long-term care days 1 year prior to return of results Count of number of long-term care days during 1 year prior to return of results using data obtained from the Electronic Medical Record. Coded by trained study staff. 1 year prior to return of results
Primary Number of long-term care days 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. 1 year after return of results
Primary Number of ER visits 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. 1 year prior to return of results
Primary Number of ER visits 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. 1 year after return of results
Primary Number of specialists visits 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. 1 year prior to return of results
Primary Number of specialists visits 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. 1 year after return of results
Primary 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
Primary 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
Primary 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
Primary 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
Primary 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
Primary 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. Mean scores will be calculated by summing the response values and dividing by the total number of items (21). Higher scores indicate stronger perceptions of patient centeredness. Immediately after clinic 1 day of visit 1
Primary 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). Interviewer administered by telephone. 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. Mean scores will be calculated by summing the response values and dividing by the total number of items (21). Higher scores indicate stronger perceptions of patient centeredness. 2 weeks after return of results
Primary 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
Secondary Initial Average Peds QL score for "missing school for not feeling well" This is a single item measure from the Peds QL that will be 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 for this single measure. This questionnaire will be self-administered at home. 4-6 weeks prior to clinic visit 1
Secondary Final Average Peds QL score for "missing school for not feeling well" This is a single item measure from the Peds QL that will be 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 for this single measure. This questionnaire will be interviewer-administered by telephone. 6 months after return of results
Secondary Initial Average Peds QL score for "missing school for doctors visit" This is a single item measure from the Peds QL that will be 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 for this single measure. This measure will be included in the questionnaire that will be self-administered at home. 4-6 weeks prior to clinic visit 1
Secondary Final Average Peds QL score for "missing school for doctors visit" This is a single item measure from the Peds QL that will be 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 for this single measure. This measure will be interviewer administered by telephone. 6 months after return of results
Secondary Initial Amount of work missed because of child's condition or treatments score This is a single item measure that will be answered on a scale of 1-6 where 1=None, 2=Less than a week, 3=Between 1 and 4 weeks, 4= Between 4 and 8 weeks, 5=Between 8 and 12 weeks, 6=I stopped working altogether. Higher scores indicate greater amounts of work missed because of the child's condition or treatments. This measure will be included in the questionnaire that will be self-administered at home. 4-6 weeks prior to clinic visit 1
Secondary Final Amount of work missed because of child's condition or treatments score This is a single item measure that will be answered on a scale of 1-6 where 1=None, 2=Less than a week, 3=Between 1 and 4 weeks, 4= Between 4 and 8 weeks, 5=Between 8 and 12 weeks, 6=I stopped working altogether. Higher scores indicate greater amounts of work missed because of the child's condition or treatments. This measure will be interviewer-administered by telephone. 6 months after return of results
Secondary Initial Difficulty with finishing normal work (including both work outside of the home and housework) because of child's condition or treatments score This is a single item measure that will be answered on a scale of 1-5, where 1=Not at all, 2=A little bit, 3=Somewhat, 4=Quite a bit, 5=Very much. Higher scores indicate greater difficulty finishing normal work (including both work outside of the home and housework) because of child's condition or treatments. This measure will be included in the questionnaire that will be self-administered at home. 4-6 weeks prior to clinic visit 1
Secondary Intermediate Difficulty with finishing normal work (including both work outside of the home and housework) because of child's condition or treatments score This is a single item measure that will be answered on a scale of 1-5, where 1=Not at all, 2=A little bit, 3=Somewhat, 4=Quite a bit, 5=Very much. Higher scores indicate greater difficulty finishing normal work (including both work outside of the home and housework) because of child's condition or treatments. This measure will be interviewer-administered by telephone. 2 weeks after return of results
Secondary Final Difficulty with finishing normal work (including both work outside of the home and housework) because of child's condition or treatments score This is a single item measure that will be answered on a scale of 1-5, where 1=Not at all, 2=A little bit, 3=Somewhat, 4=Quite a bit, 5=Very much. Higher scores indicate greater difficulty finishing normal work (including both work outside of the home and housework) because of child's condition or treatments. This measure will be interviewer-administered by telephone. 6 months after return of results
Secondary Vital status at final f/u Based on NC Vital Statistics, the child's vital status will be reported as living or deceased. final follow-up, up to approximately three years after clinic visit 1
Secondary Child causes of death related to the primary condition Based on NC Vital Statistics, child causes of death will be reported as related to the disorder of the child or not related to the disorder of the child. final follow-up up to approximately three years after clinic visit 1
Secondary Percent concordance of caregiver and provider reports of genetic or genomic test results Concordance between caregiver and provider reports of whether patients' diagnostic results were positive, negative, or uncertain. Coded as a dichotomous variable: 0=discordant diagnostic reports; 1=concordant diagnostic reports. 2 weeks after return of results
Secondary Mean Baseline Self Efficacy Score Self-efficacy scale, which measures caregivers' confidence in communicating with their child's provider. Self-administered as part of the intake questionnaire. Measured with adapted Decision Self Efficacy Scale (developed by O'Connor, 1995). Adapted wording from the original scale so items refer to general communication, as opposed to a specific decision. Shorted scale to 7 items from 11 since not all items were applicable to this study. Item responses will be coded as: 1=Not at all confident; 5=Very confident. Mean scores will be calculated by summing the response values and dividing by the total number of items (7). Higher scores indicate higher confidence in communicating with their child's provider. 4-6 weeks prior to clinic visit 1
Secondary Mean Pre-Clinic Visit 1 Self Efficacy Score Self-efficacy scale, which measures caregivers' confidence in communicating with their child's provider. Self-administered as part of the intake questionnaire. Measured with adapted Decision Self Efficacy Scale (developed by O'Connor, 1995). Adapted wording from the original scale so items refer to general communication, as opposed to a specific decision. Shorted scale to 7 items from 11 since not all items were applicable to this study. Item responses will be coded as: 1=Not at all confident; 5=Very confident. Mean scores will be calculated by summing the response values and dividing by the total number of items (7). Higher scores indicate higher confidence in communicating with their child's provider. Immediately before Clinic Visit 1
Secondary Post-Return of Results Mean FACToR Uncertainty Subscale Score Subscale of the Feeling About genomiC Testing Results measure assesses caregivers' level of uncertainty about their child's genetic test results (developed by Gallego et al., 2014). Interviewer administered by telephone. Item responses will be coded as: 1=Not at all; 2=A little; 3=Somewhat; 4=A good deal; 5=A great deal. Mean scores will be calculated by summing the response values and dividing by the total number of items (3). Higher scores indicate greater uncertainty about their child's genetic test results. 2 weeks after return of results
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