Introduction
The focus of this evidence review is on genetic testing used to guide drug therapies, and whether the evidence is adequate to draw conclusions about improved health outcomes for the Medicare population. In general, improved health outcomes of interest include patient mortality and morbidity, as well as patient quality of life and function. Standardized evaluation of analytical validity, clinical validity, and clinical utility should be fully elucidated, and reflect the level of confidence that the performance of this test will directly benefit patients. Tests with analytic and clinical validity, with demonstrated clinical utility that provide confidence to accurately enhance clinician decision-making, have the potential to alter clinical management leading to improved patient outcomes. Ideal patient outcomes demonstrate reduced mortality and morbidity, improved patient quality of life and function.
Pharmacogenomic testing endeavors to improve patient outcomes to optimize medication choice, thereby reducing ineffective medication use and reducing adverse events. Outcomes of interest remain the patient-centered outcomes noted above.
Internal Technology Assessment
The U.S. sources of PGx test recommendations available to provide guidance to clinicians as to how available genetic test results should be interpreted for drug therapy improvement include the U.S. FDA drug labels, FDA Table of Pharmacogenetic Associations, and the CPIC.
Caudle 20142
The CPIC publishes open-source genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug therapy. Caudle (2014) describes the CPIC guideline development process for incorporation of PGx testing into clinical practice and compares the process to the Institute of Medicine’s (IOM) Standards for Developing Trustworthy Clinical Practice Guidelines. The CPIC is a shared project between the Pharmacogenomics Knowledgebase and the Pharmacogenomics Research Network, established to address the need for practice guidelines for the translation of genetic laboratory test results into actionable decision making for specific drugs. The guidelines are developed using standardized methods. As the authors state, “Therefore, CPIC guidelines are designed to provide guidance to clinicians as to how available genetic test results should be interpreted to ultimately improve drug therapy, rather than to provide guidance as to whether a genetic test should or should not be ordered.”
A table is provided comparing the IOM standard to the CPIC Guideline development standard, listed as a point-by-point comparison. All CPIC guidelines adhere to each standard with some exceptions. One exception is IOM standard 4, the clinical practice guideline-systematic review intersection. Here, CPIC meets some but not all these standards. The explanation being that because of the nature of PGx test studies, the CPIC guideline development process often relies on published results that can vary with respect to methodological rigor and outcomes. Management of conflict of interest also does not exactly match the IOM standard. Divestiture of interests and ensuring those with conflict of interest are in the minority is not required, however the author notes in most cases, the majority of guideline authors declare no conflicts of interest. In addition, the guidelines focus on how to use the information as opposed to whether or not to order the test. Another area of deviation is IOM standard 3.2 and 3.3. While all guidelines are posted in draft form on the website for comment by CPIC members prior to publication, there is no mechanism for public representation or public comment.
Caudle 20163
The purpose of this article is to describe the state of PGx test evidence and evidence-based resources that facilitate the uptake of PGx testing into clinical practice. The authors state the threshold for evidence needed for clinical implementation of PGx testing is controversial and good quality randomized controlled trials (RCTs) are rarely available. A standardized approach to evaluate the literature and provide guidance to clinicians is essential in facilitating the implementation of PGx testing into routine practice. The CPIC believes there is a critical need to provide classification of gene/drug groupings based on being actionable in clinical decision making based on reliable standardized criteria. A prioritization algorithm for considerations for new gene/drug groups is provided for review. CPIC levels of evidence for genes and drugs, Table 2:
CPIC Level Definitions for Genes and Drugs
CPIC Level
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Clinical Context
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Level of Evidence
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Strength of Recommendation
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A
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Genetic information should be used to change prescribing of affected drug
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Preponderance of evidence is high or moderate in favor of changing prescribing
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At least one moderate or strong action (change in prescribing) recommended
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B
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Genetic information could be used to change prescribing of the affected drug because alternative therapies/dosing are extremely likely to be as effective and as safe as non-genetically based dosing
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Preponderance of evidence is weak with little conflicting data
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At least one optional action (change in prescribing) is recommended
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C
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There are published studies at varying levels of evidence, some with mechanistic rationale, but no prescribing actions are recommended because (a) dosing based on genetics makes no convincing difference or (b) alternatives are unclear, possibly less effective, more toxic, or otherwise impractical or (c) few published studies or mostly weak evidence and clinical actions are unclear. Most important for genes that are subject of other CPIC guidelines or genes that are commonly included in clinical or DTC tests.
|
Evidence levels can vary
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No prescribing actions are recommended
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D
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There are few published studies, clinical actions are unclear, little mechanistic basis, mostly weak evidence, or substantial conflicting data. If the genes are not widely tested for clinically, evaluations are not needed.
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Evidence levels can vary
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No prescribing actions are recommended
|
U.S. Food and Drug Administration (FDA)4
The FDA states that “pharmacogenomics can play an important role in identifying responders and non-responders to medications, avoiding adverse events, and optimizing drug dose.” Drug labeling may contain information on genomic biomarkers and can describe the following as listed per the FDA: “Drug exposure and clinical response variability, risk for adverse events, genotype-specific dosing, mechanisms of drug action, polymorphic drug target and disposition genes, trial design features.”4
FDA safety communications have been published that warn against the use of many genetic tests with unapproved claims to predict patient response to specific medications. According to the FDA, the number of cases are limited for which at least some evidence does exist to support a correlation between a genetic variant and drug levels within the body, and this is described in the labeling of FDA cleared or approved genetic tests and FDA approved medications. The FDA provides descriptions for how to use genetic information to manage therapeutic treatment and can appear in different sections of the labeling depending on the actions.5 For instance, from an October 31, 2018 communication:
“The FDA is alerting patients and health care providers that claims for many genetic tests to predict a patient's response to specific medications have not been reviewed by the FDA, and may not have the scientific or clinical evidence to support this use for most medications. Changing drug treatment based on the results from such a genetic test could lead to inappropriate treatment decisions and potentially serious health consequences for the patient.”
And:
“There are a limited number of cases for which at least some evidence does exist to support a correlation between a genetic variant and drug levels within the body, and this is described in the labeling of FDA cleared or approved genetic tests and FDA approved medications. The FDA authorized labels for these medical products may provide general information on how DNA variations may impact the levels of a medication in a person's body, or they may describe how genetic information can be used in determining therapeutic treatment, depending on the available evidence."