Evidence Matters in Genomic Medicine- Round 2: Integrating Cancer Genomic TestsPosted on by
In a previous blog, CDC’s Office of Public Health Genomics announced a list of health-related genomic tests and applications, stratified into three tiers according to the availability of scientific evidence and evidence-based recommendations as a result of systematic reviews. The list is intended to promote information exchange and dialogue among researchers, providers, policy makers, and the public. We have updated the list to include tests that have been discussed in a recent article by the National Comprehensive Cancer Network (NCCN). For these tests, we have considered NCCN recommendations and other evidence-based reviews, reports or assessments from Blue Cross Blue Shield Association Technical Evaluation Center (TEC) and guidelines from the National Institute for Health and Clinical Excellence in the placement of individual tests within the OPHG tier list.
NCCN guidelines have been described as “the most comprehensive and widely used oncology standard in clinical practice in the world” (6). Recently, the level of evidence behind the formulation of these guidelines was systematically investigated by Poonacha, 2011. They report “…[NCCN] guidelines are developed by a select group of disease-oriented panel members with representations from each of the NCCN member institutions. Algorithmic pathways are derived for the following four major areas of clinical decision making: staging, initial treatment, salvage treatment, and surveillance. The preliminary guidelines are then reviewed by non-panel experts from the NCCN institutions and revised accordingly to form the final guidelines.” Poonacha et al. noted that the guidelines are based on review of pertinent literature, although it is unclear how systematic or extensive the process is (e.g. literature search strategy, inclusion and exclusion criteria, and data extraction are not described in detail). Furthermore, Poonacha et al. found that only 6% of the recommendations found in NCCN guidelines for the 10 most common cancers are based on high-level evidence. (6)
The BCBSA Technology Evaluation Center writes evidence-based assessments of medical technologies, producing 20 to 25 assessments each year. The assessments are described as “a comprehensive evaluation of the clinical effectiveness and appropriateness of a given medical technology… guided by the Medical Advisory Panel composed of nationally respected physician experts. The TEC Program uses five criteria to assess whether a technology improves health outcomes such as length of life, quality of life and functional ability… [and] uses a formal approach to reviewing the evidence.” (8)
The NICE quality standards are described as “central to supporting the [UK] Government’s vision for an NHS [National Health Service] and Social Care system focused on delivering the best possible outcomes for people who use services, as detailed in the Health and Social Care Act (2012).” NICE quality standards for the NHS are described as focusing on the “treatment and prevention of different diseases and conditions” and they “enable health and social care professionals and public health professionals to make decisions about care based on the latest evidence and best practices.” Additional, NICE quality standards are available on their web site.
In our classification of genomic applications we decided to err on the side of being conservative in labeling genomic applications as tier 1 since we primarily rely on systematic evidence reviews. Furthermore, we have provided links to recommendations and references in support of the applicable tier 1 genomic test recommendation.
Our goal is to encourage conversation on the appropriate use of genomic applications in practice and to promote the translational research needed to fill evidence gaps. The tables also highlight some mature genomic applications in tier 1 that if implemented could save thousands of lives and reduce morbidity among affected people and their families. Evaluating the population-level balance of benefits and harms will require further research.
We invite comments and suggestions from our readers about our classification scheme, specific genomic tests and applications, and sources of evidence.