Original Research Article

The cost-effectiveness of returning incidental findings from next-generation genomic sequencing

  • Genetics in Medicine 17, 587595 (02 July 2015)
  • doi:10.1038/gim.2014.156
  • Download Citation
Received:
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Published online:

Abstract

Purpose:

The American College of Medical Genetics and Genomics (ACMG) recommended that clinical laboratories performing next-generation sequencing analyze and return pathogenic variants for 56 specific genes it considered medically actionable. Our objective was to evaluate the clinical and economic impact of returning these results.

Methods:

We developed a decision-analytic policy model to project the quality-adjusted life-years and lifetime costs associated with returning ACMG-recommended incidental findings in three hypothetical cohorts of 10,000 patients.

Results:

Returning incidental findings to cardiomyopathy patients, colorectal cancer patients, or healthy individuals would increase costs by $896,000, $2.9 million, and $3.9 million, respectively, and would increase quality-adjusted life-years by 20, 25.4, and 67 years, respectively, for incremental cost-effectiveness ratios of $44,800, $115,020, and $58,600, respectively. In probabilistic analyses, returning incidental findings cost less than $100,000/quality-adjusted life-year gained in 85, 28, and 91%, respectively, of simulations. Assuming next-generation sequencing costs $500, the incremental cost-effectiveness ratio for primary screening of healthy individuals was $133,400 (<$100,000/quality-adjusted life-year gained in 10% of simulations). Results were sensitive to the cohort age and assumptions about gene penetrance.

Conclusion:

Returning incidental findings is likely cost-effective for certain patient populations. Screening of generally healthy individuals is likely not cost-effective based on current data, unless next-generation sequencing costs less than $500.

Genet Med 17 7, 587–595.

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Acknowledgements

This work was supported by grant U01 HG0006507-01 from the National Human Genome Research Institute, by an R36 Award (1R36HS023340-01) from the Agency for Healthcare Research and Quality, a doctoral dissertation grant from the National Science Foundation (award 1424250), and by a grant from the University of Washington Northwest Institute of Genetic Medicine awarded by the Washington State Life Sciences Discovery Funds (grant 265508). The funding sources had no role in the design, conduct, or interpretation of the study or the preparation, review, or approval of the manuscript.

Author information

Affiliations

  1. Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, Washington, USA

    • Caroline S. Bennette
    • , Carlos J. Gallego
    •  & David L. Veenstra
  2. Department of Medicine and Genome Sciences, Division of Medical Genetics, University of Washington, Seattle, Washington, USA

    • Carlos J. Gallego
    •  & Gail P. Jarvik
  3. Department of Bioethics and Humanities, University of Washington, Seattle, Washington, USA

    • Wylie Burke
  4. Institute for Public Health Genetics, University of Washington, Seattle, Washington, USA

    • David L. Veenstra

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Corresponding author

Correspondence to David L. Veenstra.

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