Xin Niu1, Laura M Amendola2, Ragan Hart2, Caroline S Bennette3, Patrick Heagerty4, Martha Horike-Pyne2, Susan B Trinidad5, Elisabeth A Rosenthal2, Bryan Comstock4, Chris Nefcy4, Fuki M Hisama2, Robin L Bennett2, William M Grady6, Carlos J Gallego7, Peter Tarczy-Hornoch8, Stephanie M Fullerton5, Wylie Burke5, Dean A Regier9, Michael O Dorschner10, Brian H Shirts11, Peggy D Robertson12, Deborah A Nickerson12, Donald L Patrick13, Gail P Jarvik14, David L Veenstra15. 1. Department of Epidemiology, University of Washington, Seattle, WA 98195, USA. 2. Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA. 3. Flatiron Health, New York, NY 10010, USA. 4. Department of Biostatistics, University of Washington, Seattle, WA 98195, USA. 5. Department of Bioethics and Humanities, University of Washington, Seattle, WA 98195, USA. 6. Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98101, USA. 7. Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA; Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH 44106, USA; Comparative Health Outcomes, Economics and Policy Institute (CHOICE), University of Washington, Seattle, WA 98195, USA. 8. Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA. 9. Canadian Centre for Applied Research in Cancer Control, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada. 10. Department of Pathology, University of Washington, Seattle, WA 98195, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. 11. Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA. 12. Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. 13. Department of Health Services, University of Washington, Seattle, WA 98195, USA. 14. Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. 15. Comparative Health Outcomes, Economics and Policy Institute (CHOICE), University of Washington, Seattle, WA 98195, USA. Electronic address: veenstra@uw.edu.
Abstract
BACKGROUND:Clinical exome sequencing (CES) provides the advantage of assessing genetic variation across the human exome compared to a traditional stepwise diagnostic approach or multi-gene panels. Comparative effectiveness research methods offer an approach to better understand the patient-centered and economic outcomes of CES. PURPOSE: To evaluate CES compared to usual care (UC) in the diagnostic work-up of inherited colorectal cancer/polyposis (CRCP) in a randomized controlled trial (RCT). METHODS: The primary outcome was clinical sensitivity for the diagnosis of inherited CRCP; secondary outcomes included psychosocial outcomes, family communication, and healthcare resource utilization. Participants were surveyed 2 and 4 weeks after results return and at 3-month intervals up to 1 year. RESULTS: Evolving outcome measures and standard of care presented critical challenges. The majority of participants in the UC arm received multi-gene panels [94.73%]. Rates of genetic findings supporting the diagnosis of hereditary CRCP were 7.5% [7/93] vs. 5.4% [5/93] in the CES and UC arms, respectively (P = 0.28). Differences in privacy concerns after receiving CRCP results were identified (0.88 in UC vs 0.38 in CES, P = 0.05); however, healthcare resource utilization, family communication and psychosocial outcomes were similar between the two arms. More participants with positive results (17.7%) intended to change their life insurance 1 month after the first return visit compared to participants returned a variant of uncertain significance (9.1%) or negative result (4.8%) (P = 0.09). CONCLUSION: Our results suggest that CES provides similar clinical benefits to multi-gene panels in the diagnosis of hereditary CRCP.
RCT Entities:
BACKGROUND: Clinical exome sequencing (CES) provides the advantage of assessing genetic variation across the human exome compared to a traditional stepwise diagnostic approach or multi-gene panels. Comparative effectiveness research methods offer an approach to better understand the patient-centered and economic outcomes of CES. PURPOSE: To evaluate CES compared to usual care (UC) in the diagnostic work-up of inherited colorectal cancer/polyposis (CRCP) in a randomized controlled trial (RCT). METHODS: The primary outcome was clinical sensitivity for the diagnosis of inherited CRCP; secondary outcomes included psychosocial outcomes, family communication, and healthcare resource utilization. Participants were surveyed 2 and 4 weeks after results return and at 3-month intervals up to 1 year. RESULTS: Evolving outcome measures and standard of care presented critical challenges. The majority of participants in the UC arm received multi-gene panels [94.73%]. Rates of genetic findings supporting the diagnosis of hereditary CRCP were 7.5% [7/93] vs. 5.4% [5/93] in the CES and UC arms, respectively (P = 0.28). Differences in privacy concerns after receiving CRCP results were identified (0.88 in UC vs 0.38 in CES, P = 0.05); however, healthcare resource utilization, family communication and psychosocial outcomes were similar between the two arms. More participants with positive results (17.7%) intended to change their life insurance 1 month after the first return visit compared to participants returned a variant of uncertain significance (9.1%) or negative result (4.8%) (P = 0.09). CONCLUSION: Our results suggest that CES provides similar clinical benefits to multi-gene panels in the diagnosis of hereditary CRCP.
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