One of the new publications that appeared in my searches this week was this paper on “Next-Generation Sequencing vs Culture-Based Methods for Diagnosing Periprosthetic Joint Infection After Total Knee Arthroplasty: A Cost-Effectiveness Analysis”, published in The Journal of Arthroplasty. I wrote about it on this Twitter thread, but I just wanted to expand on a couple of points here.
I’ve been sharing weekly updates of new publications in health economics and genomics on social media for a few weeks, but thought it would be useful if I also presented these updates in weekly blog posts.
There are 2 new publications this week:
- Estimating the Costs of Genomic Sequencing in Cancer Control | pubmed.ncbi.nlm.nih.gov/32493298/
- Next-Generation Sequencing vs Culture-Based Methods for Diagnosing Periprosthetic Joint Infection After Total Knee Arthroplasty: A Cost-Effectiveness Analysis | pubmed.ncbi.nlm.nih.gov/31005439/
As I’m putting these in a blog post for the first time, here are the latest publications from the past four weeks too: Continue reading
In 2018, I contributed to the publication of a special theme section in Value in Health on assessing the value of clinical genomic testing. You can read a blog post about this publication here, and access the special issue here. My contribution to this was as a member of the Global Economics and Evaluation of Clinical Genomics Sequencing Working Group (GEECS), formerly known as the Population Genomics Health Economists Working Group.
I’m pleased to say that we have just published a second theme section in the same journal, this time focused on evaluation methods for moving precision medicine into practice and policy. This theme section features five papers from the GEECS team and one paper by the ISPOR Special Interest Group on Precision Medicine and Advanced Therapies. As before, the work was chaired by Kathryn A. Phillips, PhD.
Four years ago I blogged on how “The $1000 genome is a myth”. I think the first paragraph from that blog post is as relevant today as it was in 2015:
Barely a day goes by without a news story or social media post proclaiming that the $1000 genome now exists, and is ushering in a healthcare revolution. Every day, somebody, somewhere in the world, posts these graphs on Twitter. There’s even a Wikipedia page devoted to this topic. It’s a persistent news headline and, frustratingly, it’s currently wrong.
Since 2015, the health economic evidence base for genome sequencing has gradually expanded, and several cost estimates are now available, but overall I think we still lack the sort of rigorously conducted microcosting studies that can usefully inform resource allocation decisions regarding genomic testing.
Hopefully this paper that we published in Genetics in Medicine a couple of weeks’ ago can make such a contribution.
When I started this blog in 2014 I wanted to provide a forum for the discussion of issues surrounding the health economic analysis of genomic technologies. I knew that I would start off by writing most of the blog posts, but my plan in the medium-term was to invite researchers from all backgrounds to contribute posts. However, this was not something I ever really got around to publicising. Consequently there has only been one guest post since this blog began.
I have less time to write for the blog now, so this seems like a good opportunity to put the call out for more guest posts. If you would like to contribute a post on any topic related to health economics and genomics, please get in touch. You can do this via the contact form, or via a DM on Twitter, or via my email address. There are no restrictions on the topic of posts: these could be paper reviews, comments on current issues in the field, editorial type posts, methods discussions or even debate-type posts. If you have something to say on health economics and genomics that requires more space than the 280 characters offered by Twitter, but isn’t quite right for a formal peer-reviewed paper, then this could be the format for you. I do not intend/want to edit any posts other than to do some light touch editing to fix typos etc.: there is no blog ‘voice’, and all opinions are welcome.
If you are interested in contributing, please get in touch!
Apologies for the lack of activity on this blog. The amount of time I have for writing blog posts has reduced considerably over the past few months! I do hope to begin writing more general blog posts again soon, but I’m checking in today to highlight a paper that we published this week in the European Journal of Human Genetics.
I’ve written about evaluating the outcomes of genomic sequencing a few times in this blog, in the context of several different publications. A key issue here is that we still lack evidence on the health outcomes associated with sequencing, and a commonly cited reason for this is that health economists are unsure as to whether the QALY can fully quantify the outcomes that are important to patients when they undergo genomic testing. There isn’t a great deal of consensus on this matter, or on the issue of whether information on personal utility should feed into resource allocation decisions in this context. This methodological uncertainty may partially explain why existing economic evaluations of genomic sequencing have not gone beyond ‘narrow’ outcome measures such as diagnostic yield.
However, before abandoning QALYs in this clinical context (if this is even possible), I think there are several steps that can and should be taken to improve the evidence base on the clinical and non-clinical utility of genomic sequencing. With this in mind, I recently published an editorial in PharmacoEconomics – Open with Sarah Wordsworth titled “Evaluating the Outcomes Associated with Genomic Sequencing: A Roadmap for Future Research”, in which we expand on what these steps might be. I think this topic should be debated more widely, so if anybody has alternative views on this I’d be happy to hear them!
Around 12 months ago I joined an exciting new venture: the Population Genomics Health Economists Working Group. This group is made up of health economists and policy researchers from major institutions across the globe who have been at the forefront of the incorporation of genomics into clinical care. The group is chaired by Kathryn A. Phillips, PhD, Director of the Center for Translational and Policy Research on Personalized Medicine (TRANSPERS) at the University of California. You can find out more about the group members here.
The first key output from this working group has been published today: a themed section in the September issue of Value in Health which addresses the challenges and solutions for assessment of the value of clinical genomic testing.
An increasing number of qualitative and quantitative research papers in health economics and genomics have been published in recent years. To keep track of these publications, and to have a useful summary of available publications at hand, researchers at HERC have set up a database of health economics and genomics studies. I have helped to set up this database, as has Sarah Wordsworth, but a first-year PhD student, Patrick Fahr, has undertaken most of the hard work and should receive the lion’s share of the credit!
Yesterday, we published an article in Genomics in Medicine titled: “Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature”. The lead author for this work was Katharina Schwarze, who spent several months at HERC working on a project related to the costs of whole genome sequencing.
The aim of this particular piece of work was to summarise the current health economic evidence for whole-exome sequencing (WES) and whole-genome sequencing (WGS). The key finding was that the current health economic evidence base to support the more widespread use of WES and WGS in clinical practice is very limited. Other important findings include the following:
- Cost estimates for a single test ranged from $555 to $5,169 for WES and from $1,906 to $24,810 for WGS.
- There was no evidence that the cost of WES was falling over time, and only limited evidence that the cost of WGS was decreasing.
- Few studies used outcome measures recommended for use in economic evaluations, such as survival or quality of life.
- Only eight publications were full economic evaluations, of which only five produced evidence that WES or WGS may represent a cost-effective use of limited health-care resources.
We conclude by making four practical recommendations:
- Future studies should report costs by stage of testing for WES and WGS and highlight particularly notable costs, as it is currently difficult to identify key cost drivers.
- Future studies should report resource use and unit costs in a disaggregated manner to aid interpretation.
- Future studies evaluating the cost-effectiveness of WES or WGS should use calculated costs instead of prices, to better capture the economic value associated with WES and WGS, and to avoid incorrect and inefficient adoption decisions.
- Future studies of the cost-effectiveness of WES and WGS should include trained health economists as coinvestigators to improve study quality.
This paper challenges a number of assumptions in the literature and in the wider conversation regarding the cost and potential value of next generation sequencing technologies. I hope you’ll read, share, and debate these findings!