Incidental findings in genomic sequencing: a health economics perspective

When this blog began, I mentioned that I would be happy to publish posts by other researchers: different opinions and healthy debate are both welcome here. I’m therefore very pleased to introduce a colleague of mine at the University of Oxford, Jilles Fermont, who discusses some recently published articles on incidental findings in genomic sequencing from a health economics perspective.

Incidental findings (IFs) are a topic of considerable debate, not just in genomic medicine but also in other fields of medicine. To date, few health economists have undertaken any work in this area, but a recent burst of publications suggests that this is beginning to change. This post is primarily prompted by the publication of a paper in Genetics in Medicine earlier in November titled “The cost-effectiveness of returning incidental findings from next-generation genomic sequencing”, authored by Bennette and colleagues. The authors intended to evaluate the clinical and economic impact of IFs in genomic sequencing. The cost-effectiveness analysis (CEA) is restricted and has limitations (see below) but, as the authors already indicated, it is much more of an exploratory study providing policy recommendations on how to deal with IFs from genomic sequencing. Also, it is not a CEA of next-generation sequencing (NGS) but that of the return of IFs. Despite these caveats, it remains an interesting and relevant paper. Those involved or interested in this field are recommended to read it.

To provide some context to the discussion that follows, it should be noted that in the past year, Bennette et al conducted work related to this study: a discrete choice experiment to quantify patient preferences for the return of IFs in genomic medicine. Fairly recently the same research group published a study design to assess the cost-effectiveness of whole-exome (WES) and whole genome sequencing (WGS) in bowel cancer patients, and presented at the recent ISPOR meeting in Montreal (poster G9) about the economic value of NGS technologies to prevent bowel cancer. Professor David Veenstra, who co-authored the above-mentioned studies, is known for his longstanding interest in this field.

In the most recent study in Genetics in Medicine, a decision-analytic model including quality-adjusted life years (QALY) and lifetime costs was developed to evaluate the clinical and economic impact of returning clinically actionable IFs. The authors selected three hypothetical cohorts of patients: cardiomyopathy patients, bowel cancer patients, and healthy individuals. Model input parameters are based on secondary data; a limited number of studies, expert opinions, and assumptions. Multiple scenario analyses were conducted.

The American College of Medical Genetics and Genomics (ACMG) identified 56 genes to be clinically actionable. Instead of modelling these genes individually, the authors decided to assess multiple inheritable conditions that include most of these genes.

Results from their model indicates that returning IFs would increase QALYs by 20 at a cost of almost $900,000 for cardiomyopathy patients, 25 QALYs at a cost of $2.9 million for bowel cancer patients, and 67 QALYs at a cost of $3.9 million for healthy individuals. The respective incremental cost-effectiveness ratios are approximately $45,000, $115,000, and $59,000.

The main policy recommendation is that the return of IFs is likely to produce health benefits for various diseases and that responding to IFs resulting from genomic testing could be cost-effective for specific populations.

The paper has several strengths and limitations. Despite the sensitivity analysis, there is much uncertainty and the biggest limitation would be the use of secondary data and the assumptions that were made to construct the decision model. Considering their plan to assess the cost-effectiveness of genomic sequencing in bowel cancer patients included in a randomized controlled trial with a follow-up period of 12 months, the authors will be able to improve their decision model. This pioneering work serves as a great example and is useful to those who are planning to undertake similar work or are already doing so.

With only few researchers exploring the economics of genomics, and with the many developments in this field taking place at such a rapid pace, there is much work that needs to be done, particularly in the area of IFs. There are ample opportunities. I am already looking forward to seeing the results of the study by Veenstra and colleagues assessing cost-effectiveness using primary data. Together with other health economic researchers, including myself and colleagues at the Health Economics Research Centre in Oxford, we should be able to provide robust evidence on the true economic costs and consequences of returning IFs from next-generation genome sequencing in the near future.

Jilles Fermont (

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