Nick Dragojlovic1, Alison M Elliott2,3, Shelin Adam2,3, Clara van Karnebeek4,5, Anna Lehman2,3, Jill C Mwenifumbo3,6, Tanya N Nelson2,3,7,8, Christèle du Souich2,3, Jan M Friedman2,3, Larry D Lynd9,10. 1. Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada. 2. Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. 3. BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada. 4. Department of Pediatrics, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada. 5. Emma Children's Hospital, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands. 6. Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada. 7. Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. 8. Department of Pathology and Laboratory Medicine, BC Children's Hospital, Vancouver, British Columbia, Canada. 9. Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada. larry.lynd@ubc.ca. 10. Centre for Health Evaluation and Outcomes Sciences, Providence Health Research Institute, Vancouver, British Columbia, Canada. larry.lynd@ubc.ca.
Abstract
PURPOSE: This study aimed to generate benchmark estimates for the cost, diagnostic yield, and cost per positive diagnosis of diagnostic exome sequencing (ES) in heterogeneous pediatric patient populations and to illustrate how the design of an ES service can influence its cost and yield. METHODS: A literature review and Monte Carlo simulations were used to generate benchmark estimates for singleton and trio ES. A cost model for the Clinical Assessment of the Utility of Sequencing and Evaluation as a Service (CAUSES) study, which is testing a proposed delivery model for diagnostic ES in British Columbia, is used to illustrate the potential effects of changing the service design. RESULTS: The benchmark diagnostic yield was 34.3% (95% confidence interval (CI): 23.2-46.5) for trio ES and 26.5% (95% CI: 12.9-42.9) for singleton ES. The benchmark cost of delivery was C$6,437 (95% CI: $5,305-$7,704) in 2016 Canadian dollars (US$4,859; 4,391€) for trio ES and C$2,576 (95% CI: $1,993-$3,270) (US$1,944; 1,757€) for singleton ES. Scenario models for CAUSES suggest that alternative service designs could reduce costs but might lead to a higher cost per diagnosis due to lower yields. CONCLUSION: Broad conclusions about the cost-effectiveness of ES should be drawn with caution when relying on studies that use cost or yield assumptions that lie at the extremes of the benchmark ranges.
PURPOSE: This study aimed to generate benchmark estimates for the cost, diagnostic yield, and cost per positive diagnosis of diagnostic exome sequencing (ES) in heterogeneous pediatric patient populations and to illustrate how the design of an ES service can influence its cost and yield. METHODS: A literature review and Monte Carlo simulations were used to generate benchmark estimates for singleton and trio ES. A cost model for the Clinical Assessment of the Utility of Sequencing and Evaluation as a Service (CAUSES) study, which is testing a proposed delivery model for diagnostic ES in British Columbia, is used to illustrate the potential effects of changing the service design. RESULTS: The benchmark diagnostic yield was 34.3% (95% confidence interval (CI): 23.2-46.5) for trio ES and 26.5% (95% CI: 12.9-42.9) for singleton ES. The benchmark cost of delivery was C$6,437 (95% CI: $5,305-$7,704) in 2016 Canadian dollars (US$4,859; 4,391€) for trio ES and C$2,576 (95% CI: $1,993-$3,270) (US$1,944; 1,757€) for singleton ES. Scenario models for CAUSES suggest that alternative service designs could reduce costs but might lead to a higher cost per diagnosis due to lower yields. CONCLUSION: Broad conclusions about the cost-effectiveness of ES should be drawn with caution when relying on studies that use cost or yield assumptions that lie at the extremes of the benchmark ranges.
Authors: Bo Yuan; Lei Wang; Pengfei Liu; Chad Shaw; Hongzheng Dai; Lance Cooper; Wenmiao Zhu; Stephanie A Anderson; Linyan Meng; Xia Wang; Yue Wang; Fan Xia; Rui Xiao; Alicia Braxton; Sandra Peacock; Eric Schmitt; Patricia A Ward; Francesco Vetrini; Weimin He; Theodore Chiang; Donna Muzny; Richard A Gibbs; Arthur L Beaudet; Amy M Breman; Janice Smith; Sau Wai Cheung; Carlos A Bacino; Christine M Eng; Yaping Yang; James R Lupski; Weimin Bi Journal: Genet Med Date: 2020-06-24 Impact factor: 8.822
Authors: Peter N Robinson; Vida Ravanmehr; Julius O B Jacobsen; Daniel Danis; Xingmin Aaron Zhang; Leigh C Carmody; Michael A Gargano; Courtney L Thaxton; Guy Karlebach; Justin Reese; Manuel Holtgrewe; Sebastian Köhler; Julie A McMurry; Melissa A Haendel; Damian Smedley Journal: Am J Hum Genet Date: 2020-08-04 Impact factor: 11.025