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Work in Progress: Classifying Evidence-based Genomic Applications for Practice and Prevention | | Blogs | CDC

Work in Progress: Classifying Evidence-based Genomic Applications for Practice and Prevention | | Blogs | CDC

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Work in Progress: Classifying Evidence-based Genomic Applications for Practice and Prevention

Posted on  by W. David Dotson and Muin J. Khoury, Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia



applications by evidence tiers with 68 tier 1, 107 tier 2 and 7 tier 3



In our 2015 paper,“Prioritizing genomic applications for action by level of evidence: A horizon-scanning method,” we proposed a systematic scanning method that assigns genomic applications to “tiers” defined by availability of synthesized evidence. Because of the amassed evidence on the validity and utility of genomic tests and related technologies, we suggested that researchers, policy makers, clinical and public health programs, and patients might benefit from knowing more about classifying evidence-based genomic applications for healthcare and public health. This classification process is a “work in progress.”

Simple, but challenging 

The essence of the horizon scanning method is relatively simple even though its applications may be challenging.
  • Tier 1 genomic applications have synthesized evidence adequate to suggest that implementation in practice may be appropriate at the present time.
  • Tier 2 genomic applications have insufficient evidence to clearly support implementation in everyday practice, but adequate to inform selective use such as in shared decision making.
  • Tier 3 genomic applications either have no synthesized evidence available, or have evidence suggesting that routine use is not appropriate.
In the past few years, we applied this method to dozens of genomic tests and added this information to our Public Health Genomics Knowledge Base (PHGKB) Tier Table. Of 181 applications examined to date, we found adequate evidence to classify 68 as Tier 1.

A closer look at the PHGKB Tier Table Database

The numbers don’t tell the whole story.

The numbers in the table above don’t tell the whole story. First, where are all the Tier 3 applications? Looking at the contents of the database, we can see that Tier 3 contains some aggregated entries. For example, there is a single entry covering available panel tests for risk assessment and prevention of common diseases. Another reason for the lack of Tier 3 applications is that we have chosen to focus on examples where evidence has led to recommendations discouraging use, rather than those where there is simply no synthesized evidence available.
The numbers are also tricky to interpret because entries are defined by how tests are used. It doesn’t make sense to ask, for example, whether BRCAgenetic counseling and/or testing is Tier 1. There are certainly numerous Tier 1 applications pertaining to BRCA counseling and testing, supported by recommendations from the U.S. Preventive Services Task Force (USPSTF) and National Comprehensive Cancer Network (NCCN). However, there is also a USPSTF-based Tier 3 application for routine BRCA genetic counseling and routine BRCA testing when the intended use is population screening (in women whose family health history is not associated with an increased risk of BRCA mutations).
Screen shot of the tier table from the PHGKB
Screen shot of PHGB (v2.1); Source: CDC
Because individual rows in the table do not always correspond with a single gene, variant, test, or evidence source, it is impossible to get a complete picture by looking at the table alone. Individual guidelines often contain many specific recommendations that must be separated into different rows in the Tier Table. Different guidelines might have recommendations that are more or less similar, and we must often make decisions on whether to attempt to reconcile any minor differences and present a summary using fewer rows, or to separate into more rows to avoid the risk of losing important context. This is an ongoing challenge. But from the project’s start we have maintained that there is no substitute for actually reading the guidelines and other evidence sources. As explained in “Prioritizing genomic applications for action by level of evidence: A horizon-scanning method,” we envision the primary use of the table as a means to find relevant evidence when it exists.
The overall number of entries reflects the fact that the Tier Table was intended to provide an example of how our specific classification criteria could be applied. There are thousands of genetic tests available that are not yet in the Tier Table. Ideally, we would like to make tier classifications and include as many current genomic applications in this resource as possible.
If there are far fewer Tier 3 applications than one might expect, there is a glut in Tier 1—68 to date! This came as a pleasant surprise to us, as we didn’t expect to identify more than a dozen or so that had an evidence base supporting implementation. We are encouraged to see that such applications can already be identified in reasonable quantities.

An ongoing, but impactful, work in progress

What has been the impact of this classification method? It seems that the method has provided a simple way for health care systems and public health programs to develop actions and activities. For example, in the Geisinger health system mycode project, results from genes and variants corresponding to Tier 1 applications are returned to participants. Public health programs have also used the Tier 1 classification as a guide to develop both evidence-based programs at the state level and outcome metrics.
Our attempt at classifying evidence-based genomic applications will always be a work in progress. Genomic evaluation and implementation studies are published regularly at an ever-accelerating pace. And, we routinely capture the emerging evidence in our updated and searchable Public Health Genomics Knowledge Base. We would appreciate our readers’ help and thoughts on how to fine tune this effort, through collaboration and dialogue, to drive both implementation of evidence-based genomic applications, and additional research to fill relevant evidence gaps.
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Posted on  by W. David Dotson and Muin J. Khoury, Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia

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