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

ABSTRACT: 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.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.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.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.

SUBMITTER: Bennette CS

PROVIDER: S-EPMC4430464 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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

Bennette Caroline S CS Gallego Carlos J CJ Burke Wylie W Jarvik Gail P GP Veenstra David L DL

Genetics in medicine : official journal of the American College of Medical Genetics 20141113 7

<h4>Purpose</h4>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.<h4>Methods</h4>We developed a decision-analytic policy model to project the quality-adjusted life-years and lifetime costs associated with returning ACMG-reco ...[more]

PMID: 25394171

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Project description:BackgroundIn recent years more than 20 assemblers have been proposed to tackle the hard task of assembling NGS data. A common heuristic when assembling a genome is to use several assemblers and then select the best assembly according to some criteria. However, recent results clearly show that some assemblers lead to better statistics than others on specific regions but are outperformed on other regions or on different evaluation measures. To limit these problems we developed GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weighted graph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.ResultsGAM-NGS has been tested on six different datasets and compared to other assembly reconciliation tools. The availability of a reference sequence for three of them allowed us to show how GAM-NGS is a tool able to output an improved reliable set of sequences. GAM-NGS is also a very efficient tool able to merge assemblies using substantially less computational resources than comparable tools. In order to achieve such goals, GAM-NGS avoids global alignment between contigs, making its strategy unique among other assembly reconciliation tools.ConclusionsThe difficulty to obtain correct and reliable assemblies using a single assembler is forcing the introduction of new algorithms able to enhance de novo assemblies. GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct.

Dataset Information

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

Publications

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

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