NHGRI logo

Applying Genomics to Clinical Problems - Diagnostics, Preventive Medicine, Pharmacogenomics

A white paper for the National Human Genome Research Institute

Submitted by: David Valle, M.D., and Teri Manolio, M.D., Ph.D.


Comments (below)


Introduction

Improved health is a major goal of genomic research. The path from gene discovery to clinical application, however, is long and challenging. Development of clinically validated genetic tests requires translation from basic science discoveries, assessment of possible benefits as compared to currently available clinical resources and determination if incorporation of any new test is justified by comparison of its benefits to its risks. Additionally, test availability, potential for reimbursement, and cost-effectiveness must be considered. Also, for presymptomatic tests, benefits of enhanced prediction including the availability of effective interventions must be weighed against the potential burdens of this knowledge. Finally, clinicians and patients must educated in the use and meaning of any new genetic tests.

We are confident that new, clinically validated genetic information will enable better targeting (that is, in whom to intervene) and tailoring (how best to intervene) of preventive efforts. The potential advantages of population-wide vs. individual, high-risk preventive strategies depends on disease prevalence and the role of other major risk factors. Despite claims of efficacy from direct-to-consumer testing services and others, valid comparisons of these strategies will require rigorous clinical investigation that may take years to complete especially in the case of diseases of late onset or long duration.. Similarly, a role for pharmacogenetics in informing drug selection will require clinical studies to provide evidence for its benefits before wide acceptance can be expected. Strategies for addressing these and other challenges, including approaches for speeding the development and validation of this information and ensuring that its benefits are available to all members of our society are essential to optimize the potential benefits of genomic research for human health.

Applying genomic discoveries to clinical problems thus raises several key questions:

  1. What do new genetically-based diagnostic or risk assessment strategies add to the existing medical armamentarium?

    Medical decision-making and patient acceptance of genetic information is strongly influenced by perception of risk. Common genetic variants affecting fitness often confer only low or modest risk. How do we evaluate these risks and when do we decide the risk is too low to be clinically efficacious? What variables should be considered in making these decisions? How can we improve our understanding of how the perception of risk influences the way clinicians and patients think and act and how can we make sure that these perceptions are based on sound epidemiological, genetic and biological principles? Under what circumstances might less common variants be more valuable for identifying high-risk persons? How might other characteristics aside from frequency of the associated variant, such as magnitude of the odds ratio, penetrance, or genetic model, influence the importance of a variant for identifying persons at risk? What biological mechanisms influence the sensitivity, specificity, and predictive value of genetic test results?

    Must effective interventions to modify risk be available in order for a variant to be of medical value? How, if at all, might knowledge of immutable disease risk be useful to patients or clinicians? When is it necessary to perform randomized trials to determine whether genetically-based strategies improve patient outcomes or public health?

    Current thinking tends to focus on a single risk variant when in reality each individual has a constellation of many variants, some that increase disease risk and some that reduce it. How do we integrate the sum of these variants so that we can use them to think about environmental variables, communicate them clearly and usefully, and advise patients accordingly? 

    How should approaches to testing for single-gene Mendelian disorders differ from those for complex disorders? What aspects are similar between the two, and which differ?

    How should the value of new genetic information be assessed in the context of standard clinical information such as age, sex, and family history? Should the availability or ease of obtaining standard clinical vs genetic information be a factor in deciding when to use genetic information? How can we make genetic information more available and in a timely fashion? Might genetic risk information be more valuable in conditions where few other risk factors have been identified? If so, should such conditions be targeted for identification of genetic risk factors? How can we define the contexts in which genetic testing is most important, useful, and cost-effective? What is most likely to be useful in the next few years vs a much longer time horizon? 

    Should the bar for judging the value of additional information be higher for genetic variants than for non-genetic tests? Do patients and clinicians (rightly or wrongly) perceive genetic information to be more determinative and potentially stigmatizing, and if so, should that affect where this bar might be placed? Should current limitations on access to such testing affect this judgment? 

    What additional quality assurance standards may be needed for clinical genetic testing and how can they best be implemented and monitored?

    What special considerations might be needed for genomic-related information aside from germline DNA sequence variation, such as tissue-specific genotyping or sequencing, gene expression, epigenetics, or microbiomic data, especially those that might be affected by pharmaceutical or other treatment? Given that such information is often more dynamic than the static DNA sequence, how can decisions best be made as to how often to obtain this information and use it to understand disease course in a given patient? What additional considerations might be needed for variants whose effects are modified by environmental factors or are different at different stages of development?
     
  2. What information will influence payers in decisions to reimburse genetic testing strategies, so that financial barriers to their application can when appropriate be minimized?

    What types of evidence are most likely to influence payers? How different might these decisions be for genetic vs other clinical testing and for preventive vs diagnostic testing and therapeutic interventions?

    How useful might evidence be that genetic testing leads to reduced healthcare costs? How influential might information on the potential cost of an unrecognized, untreated condition, including malpractice claims, be in motivating support for genetic testing and documentation of genetic counseling? Is it realistic to argue that an increasingly preventative form of medicine based on up front genetic testing and risk assessment will actually reduce health care costs? How can such an evaluation be made in a reliable and timely way? 

    Must proven interventions be available to justify testing? How useful might other types of data be, such as demonstrating reduced morbidity and mortality following use of genetic testing?

    How can costs of testing, including associated costs of interpretation and education, be kept low? How can cost-effective arrangements be made for obtaining proprietary tests that are currently too expensive for most consumers and payers? 

    How might access to testing and reimbursement differ between federally- funded health pans (Medicare, Veterans Administration, etc) and private payers? How can appropriate access to new genetically-based tests be ensured for all patients regardless of type of health care coverage?

    What strategies are needed to ensure that future genetic discoveries lead to affordable tests? How can the intellectual contributions to their discovery be appropriately recognized and developmental costs reimbursed while keeping costs within reach? What central laboratory resources and strategies are needed for research to identify the functional biological mechanisms conferring susceptibility to disease and the clinical applications of this research?
     
  3. How will patients and clinicians respond to information regarding individualized genetic risk and what strategies and resources will be most effective in educating them to maximize health benefits and minimize potentially negative aspects such as stigmatization and anxiety? 

    What factors might make patients more likely to make rational choices when faced with claims of benefit of individualized testing? What impact do factors like a strong family history of disease, perceived ability to modify risk, or type and severity of the condition have on patients' desire to identify and reduce their risk? Do these factors and their impact differ according to patient characteristics such as age, sex, race/ethnicity, socioeconomic status, or physical or social environment? What is the influence of genetic test results in effecting patient behavior change compared to information from family history, other laboratory measures, epidemiologic data and other current medical tools? How can the potential for stigmatization and anxiety among patients and/or family members be reduced?

    What types of evidence are most likely to be meaningful to clinicians? How will they consider costs of testing or recommendations from colleagues in their decision-making? Given that clinicians and patients may insist on tests that are available, affordable, and interpretable, what characteristics of clinicians or the patient populations they care for might influence the extent to which they adopt genetic testing? 

    What types of educational models will work for the very different audiences of patients and clinicians? What types of educational models will work for school children and young adults to enable them to make reasonably informed decisions for their own health? How can educational tools be tailored so they are culturally appropriate for ethnically-diverse patient populations, including non-English speaking patients? What educational tools have already been developed that could serve as models? How can materials be prepared that are straightforward and time-efficient to use? To what extent should web-based resources be developed? Who should take responsibility for their accuracy and objectivity, ensuring that they neither over-represent the benefits nor minimize (nor exaggerate) potential risks? 

    What approaches can be developed to help clinicians presented with genome-wide genotype results obtained independently by their patients to evaluate and incorporate this information in the delivery of clear and effective health advice? How can clinicians capitalize on the "teachable moment" such patient-acquired testing may provide for emphasizing proven but underutilized preventive strategies?
     
  4. What information influences clinicians in utilizing genetically-based test information for their patients, and what tools for decision support or patient management will facilitate those choices?

    How can information on genetic-testing strategies be made most useful to clinicians facing nearly overwhelming patient-care responsibilities and information overload? What will be the impact of ordering and interpreting genetic tests and discussing results with patients on clinicians' workflow? What information might be needed for implementing "pay for performance" strategies for genetic testing and what would be the advantages and disadvantages of doing so?

    What are the best strategies for providing genetic testing information to clinicians with little formal training in genetics? Can the model of "GeneTests"-like 90-second summaries of benefits and risks be extended from Mendelian disorders to common, complex diseases? How useful is the GeneTests model in Mendelian disorders and how might it be improved? Would an approach that depends on existing resources such "UpToDate" be utilized? How can specific information on obtaining testing in a given clinical location or system be provided to clinicians? How will clinicians know when to refer patients to a genetic specialist?

    What are the best approaches for developing guidelines for clinical use of genetic testing and what is the appropriate role of the major stakeholders (patients, clinicians, payers, etc) in developing guidelines? How should models of evaluative, evidence-based medicine such as ACCE and EGAPP be incorporated in guideline development and clinician decision-making?

    What are the best strategies for providing genetic testing information to patients? What methods of information delivery are likely to be most useful or effective? How might these differ by age or other demographics? How can clinicians best explain probability or statistical data to patients, and how can such explanations be improved and/or tailored to patient characteristics such as socioeconomic or educational status? 

    What are the best strategies for providing genetic testing information to family members and facilitating their getting tested if they choose to do so? What information can or should be given to a family member who does not have the familial genotype that has been associated with the familial disease? 

    How might databases of mutations causing single gene disorders aid clinicians in applying genetically-based testing strategies and aiding patients in interpreting the results? 

    What are the benefits and risks of linking genetic testing information to electronic medical records, such as targeted prompting to identify appropriate patients to test? What on-line information and tools for might enhance their use? What are the implications for clinical informatics needs (storage, presentation, linking, prompting) for these massive amounts of data and how can these be met most efficiently? In addition to the patient and their physician, who should have access to this information and what are the implications of that access?
     
  5. What special approaches to genetically-based diagnostic and prevention strategies may be needed in special populations (such as prostate cancer in African-Americans) or high-risk groups (such as workers with benzene exposure)?

    What impact might past misuses of genetic information and frank misinformation to stigmatize minority groups have on adoption of testing? How can potential skepticism among minority patients and clinicians about conclusions drawn from such data be addressed?

    How do different ancestral backgrounds or environmental exposures affect the impact of disease-associated variants, and how should these differences be taken into account in clinical genetic testing? 

    What role should or will patient race/ethnicity play in clinicians' decisions to conduct genetic tests? Will specific genetic tests be targeted at patients of particular ethnicities, and if so, how will clinicians determine patient ethnicity? Is there a risk of inappropriate racial/ethnic profiling in the application of new genetic tests in clinical settings? If so, how can this risk be mitigated?

    What impact might potential use of genetic information by law enforcement and similar agencies to target minorities have on patient acceptance of testing, and how can this best be addressed in future clinical testing? 

    Could the possibility that "genetic explanations" for individual variation in sensitivity to toxin-mediated diseases minimize or eliminate potential benefits to persons with high-risk occupational or residential exposures present an obstacle to testing? How might compensation and other damage-related claims be effectively separated from efforts to screen and treat exposed individuals with genetic predispositions to harmful exposures?

    What is the risk that genetic strategies might be perceived as being applied to special populations in preference to more effective testing and preventive strategies to which they have had limited or no access in the past? How can improved access to genetic strategies and interventions required in follow-up be assured for population subgroups with limited past access? 

    What special considerations might be needed in special populations, such as tailoring interventions to be culturally appropriate or adding protections for confidentiality?

    What special considerations might be needed for genetic testing of children, pregnant women, or persons of reproductive age and for implementation of interventions in these groups? How can valid research in genomics, epigenomics, and pharmacogenomics among these groups be appropriately promoted?
     
  6. What information on prevalence, risk, modifiability, etc will be needed for clinicians and patients to understand and utilize genome sequence information in diagnosis, prevention, and treatment?

    What special challenges might be presented by sequence information? How can patients and clinicians best be counseled on the implications of newly-discovered variants? 

    How will patient "populations" be defined for determination of prevalence, risk, etc.? What are the potential benefits and risks of using race/ethnicity to define patient "populations," and how might these differ for highly-penetrant diseases with Mendelian inheritance versus chronic diseases with multifactorial causes? 

    How can the potential effects of very rare variants on health and well-being be assessed given that large numbers of persons with the variant will not be available for study? What priorities should be placed on the search for such phenotypic effects in an individual patient, and how can such priorities take into account conditions that are important to that patient or his/her family? Given that many variants of unknown significance will be identified, how can that information be most usefully presented to patients and clinicians? 

    How should factors such as modifiability of any adverse effects or abnormalities found or cost and potential stigma involved in identifying them affect these priorities? How can information on patient preferences and "resilient genomes" (persons identified as genetically susceptible who do not develop disease) be captured for research purposes and optimally used for developing additional genetic testing strategies? 

    How can the non-directive ideal of genetic counseling be integrated with the more directive world of clinical medicine? How do patients and clinicians view the non-directive approach and are there special situations in which it is or is not appropriate? 

    Should future genetic testing strategies be entirely clinician-dependent or is there a role for direct access by patients and the public? How can clinicians be better prepared to respond to individual patients who obtain sequence information (or extensive genotyping information) independently and present it to their doctors with concerns about the health impact of newly-identified variants? How can resources for addressing such concerns be best developed? What role, if any, should facilities providing the sequencing (or genotyping) services play in developing this information? What mechanisms or oversight might be needed to ensure that information provided is valid and consistent across multiple facilities?

    To what degree should funding agencies and/or those holding patents on genetic tests support reduced costs or cost-free testing for "rare" diseases, coordination of guidelines on genetic testing, and educational programs for patients and clinicians? How can costs of testing and appropriate interventions be supported for all those likely to be in need? 
     
  7. What is the impact of receiving results of direct-to-consumer (DTC) genome-wide screening on patients' health behaviors, reproductive choices, quality of life, and long-term planning? 

    Why do "early adopters" of DTC genomic testing seek such testing? What is the decision-making process for them and their families? What sources of information do they use for selecting and interpreting the tests? How, if at all, do their health and well-being change after the testing? What actions do they take in response to their genetic information and what is the outcome of these actions? Do changing views on privacy influence the acquisition and utilization of such information?

    What opportunities for research might be presented by the actions of these early adopters? How can they become engaged in research? What biases might be involved in such a group and how can they be addressed? 

    How should the public be informed of the available evidence (or lack thereof) to support the validity of direct to consumer DNA testing?

------- Comments -------


Now that the genome has been mapped, attention and funding needs to be directed to figuring out how to treat/cure horrific genetic disorders. Please focus on the critical life-sustaining proteins, the by-products of genes. I'm told there aren't many genes that are life-sustaining. Focus on single gene, orphan disorders and identify where life-sustaining proteins live in the cell, how long they are functional before being recycled etc. Perhaps TAT fusion proteins can be used to deliver synthesized proteins intracellularly if we knew a great deal more about the proteins themselves. Focus on neurological genetic disorders and how to globally deliver a healthy gene to the nerves in the central nervous system. There is really little else in life that matters when children are dying horrific deaths from disorders that are treatable, given attention and funding. My five year old has Giant Axonal Neuropahy, GAN. Scientists know exactly what causes GAN. It's caused from a single gene mutation. Both upper and lower motor neurons are impacted just like in ALS, SMA, INAD, Friedreich's Ataxia and GAN, to name a few... Figure out how to treat disorders of the central nervous system by learning more about life-sustaining proteins of the CNS. A great deal of money is spent annually on ALS research whose cause remains elusive. Scientists feel even the 10% of ALS patients with the SOD1 gene mutation also have mutant neighboring genes causing the disorder. Focus on simple, single gene neurodegenerative disorders like GAN, as they may hold many of the answers to the elusive, complex disorders like ALS. I could go on, and on for days. I'm willing to travel anywhere, anytime to express this large unmet medical need and the need to redirect funding to it. Please use the gov't genome scientists to help solve these ravaging disorders. As horrific as it is for a parent to hear their child has cancer, at least there are treatment options and medical protocol to offer hope. This is not the case when you are told your child has a neurological genetic disorder. You are sent home to try to figure out how to live watching your child progess to the point of being a quadriplegic, dependend on a feeding tube and ventilator before dying in the teenage years or early 20's. The Gov't needs to do something about this, and the Genome scientists can focus attention to the critical proteins needed to sustain life. I beg you to not spend money and resources on the "fluffy", "feel-good" stuff discussed in this white paper. "Genetic predispositioning", "impact to physician workflow", "stigma" and "how to interpret results" etc. really means nothing when there are little treatment options available anyway. Please forward this feedback to whomever you feel has the ability to make certain precious funds are not wasted. Please forward to whomever within the NIH who has the ability to make a difference in the precious lives of many.

(256) Monday, May 4, 2009 3:19 PM


This suggestion may not fall within the scope of the NHGRI. Studies must be conducted to identify health behaviors that may be associated with a decreased or increased risk of cancer in the presence of a specific genetic mutation (e.g. Are fiber consumption, calcium supplementation, body fatness, level of physical activity, smoking, and alcohol intake associated with incidence of colon colon cancer among unaffected carriers of MLH and MSH mutations?).

(259) Tuesday, May 5, 2009 1:26 PM


I think that a knowledge management or clinical content development lifecycle model should be considered in identifying the process in which genomic information/results are taken from the research environment to the lab, clinician, and patient with regard to to: 1) translation of genetic variant results to meaningful Rx implications 2) identification of benchmarks and relavent evidence that supports genetic variant information (so it provides context for clinician and ultimately pt) 3) development of clinical decision support (CDS) rules that incorporate evidence in identification of pts based on results, identification of supporting documentation, and educational resource information at the point of care This incorporates CDS with EMR adoption, and can (and is being done in a limited basis at organizations such as Partners Healthcare. 

Lastly -- providing the feedback (data regarding treatment options/outcomes) as additional research opportunities is critical in studying the integrated data that will be increasingly available (clinical genetic data and interventions). 

Also, pharmacogenomics with regard to medication intervention treatment and surveillance with regard to identifying at risk populations for adverse events (as well as benefits) is another area that will be emerging -- The initial efforts of the Sentinel Initiative development can provide the framework for this area (and provide opportunity for research/surveillance efforts to influence clinical care. I have been involved in both of these areas (knowledge management for CDS and pharmacovigilance in clinical research)

(265) Tuesday, May 19, 2009 11:07 AM


The most critial obstacle is that we do not know the underlying biological meaning for all these identified common variants. First, we should identify most of these independent variants in each identided gene. Secondly, we should characterize the effect of these common variants on diseae risk and health. If certain genetic variants of them pass certain threshold, we should incorporate them in our medical practice. So, a constellation of these selected variants could be used in decision-making (risk prediction, aiding drug/treatment-selection).

(272) Saturday, May 30, 2009 5:30 AM


Research regarding how and when to incorporate genetic counseling into preventive/genomic medicine is essential, especially given the knowledge and time limitations of current primary care providers. Genetics counselors' unique training and skills positions them to have a potentially significant role in the facilitation of genomic-based preventive medicine through expert patient and provider consultation and risk communication. The provision of health & screening guidelines based upon a diagnosis is already part of routine genetic counseling practice and does not conflict the practice value (not principle) of non-directiveness. Consideration should be given to new or modified funding mechanisms to support research in this area by genetic counseling professionals - most of whom do not hold a doctoral degree and many of whom do not have faculty appointments.

(276) Monday, June 1, 2009 3:57 PM


My comments below are to the last 3 paragraphs of section #6.

A way to balance the integration of the non-directive ideal of genetic counseling with the more directive world of clinical medicine is to collaborate with the interpersonal realm of clinical nursing. Not all patients or clinicians view the non-directive approach or the more directive approach as the ideal method of counseling. In fact in genetic counseling patient and families should be able to tell their story. Patients and families need to engage in the counseling process. Although there are special situations in which a more directive approach in counseling is appropriate, let the patient seek or ask for it or consent should be sought by the clinician from the patient as "...would you allow me to be more directive in this instance...because this information is concerning...." Pause for the permission then proceed. The more the clinician uses this strategy, the less s/he will find it necessary to use the more directive approach. Role play each potential counseling session with staff. Just because you have counselled lots of patients in different genetic situations does not mean that all counseling sessions will be the same from now on. Experience counts but individual genetic stories are unique, therefore the clinician needs to be respectful of the patient as the author and the stakeholder of his/her genetic story.

The day will come when genetic testing strategies will no longer be entirely clinician-dependent. Technological and communication advances is shaping the role for direct access by patients and the public to genetic testing or extensive genotyping information. Clinicians will be better prepared to respond to individual patients who obtain sequence information (or extensive genotyping information) independently and present it to their doctors with concerns about the health impact of newly-identified variants by heeding the A-B-C-D of patient-clinician/doctor relationship (Wilson-Stronks and others 2009): "A" stands for Accommodating the needs of all patients; "B" stands for Building a repertoire of sociocultural competence; "C" stands for Collaborating or Consulting with other clinicians; "D" stands for diversifying resources, mixing methods of counseling using qualitative and quantitative methods of interviewing through structured or non-structured counseling, face-to-face, electronic, or a combination of face-to-face and electronic counseling, data collection and analyses.

Funding agencies and/or those holding patents on genetic tests must on their own volition support reduced costs or cost-free testing for "rare" diseases, coordination of guidelines on genetic testing, and educational programs for patients and clinicians or "someone" or "some entity" will do it for them. The global economy will be unable to afford disparity in costs of testing and appropriate interventions among all those likely to be in need.

These valid questions deserve valid comments. Let's hope that the totality of the diverse comments will garner useful answers to these questions. Thank you.

(284) Wednesday, June 10, 2009 3:12 PM


Despite my attendance at related conferences and meetings, and my awareness of this particular website, I still received most of my own practical information about DTC from a segment on Oprah.

There does not seem to be a link to information for consumers re: DTC screening on the NHGRI site, or at least not easily located by me.

(304) Tuesday, June 30, 2009 12:22 PM


From a payer perspective, coverage decisions for all types of tests (clinical testing, preventative testing, diagnostic testing, etc) require a high level of evidence as new genomic diagnostics and technologies become commercially available as they have the capability to inform medical decision making. The evidence must be original study data (e.g., well designed clinical trial, observational study), a systematic review, or a meta-analysis and is published within a peer-reviewed publication. Conference abstracts, editorials, and expert opinions are generally not considered for evidence review. In many instances, new genetic technologies and other clinical testing come to market with little evidence. It is not always clear how the test results are to be used and what the expected outcome should be. In general, proven interventions should be available to justify genetic testing. Other types of data (e.g., morbidity and mortality data following use of a genetic test) can be considered but may be limited if the test application is based on pathophysiologic reasoning only. Evidentiary standards are lacking for genetic tests. Many payers follow the Center for Disease Control's ACCE model as closely as possible. This model allows taking into account data regarding analytic validity, clinical validity, and clinical utility as well as social/ethical data. Clinical utility data is significant in looking for evidence that a genetic test can improve patient outcomes. Evidence that a test can be used to inform treatment decisions compared to current management without genetic testing is most influential. Unfortunately, many tests are marketed and advocated based on limited clinical data with low quality evidence. Analytic validity data is usually not published. Lastly, shortcomings exist in ways to evaluate laboratory medicine quality around genetic tests. Standards need to be tightened.

While analytic and clinical validation are the primary focus, evidence that a genetic test leads to reduced healthcare costs is helpful information to have when evaluating genetic tests. The expectation for most personalized medicine products is that they hold the promise for better patient management and improved outcomes through health decisions that are based on knowledge of an individual's genetic make-up and particular disease. These improved outcomes can potentially lead to cost savings (the savings may not be realized immediately). This type of data is helpful to the industry as a whole but from a payer perspective, cost information is never solely used to make coverage decisions. Payers generally do take into account that many genetic disorders are rare and may have little published data to support testing.

Public and private payers are increasingly recognizing the value of new genetic technologies. Private payers are often more quick to perform an evidence review of these technologies for coverage determinations; in turn, this could facilitate or inhibit coverage and reimbursement more quickly.

How can costs of testing, including associated costs of interpretation and education, be kept low? How can appropriate access to new genetically-based tests be ensured for all patients regardless of type of health care coverage? Current testing is costly due to the nature of venture capital dollars frequently being the economic backing for development of the tests. This may lead to the need for a quick and high ROI for the investors. If clinical validation accompanied the marketing of new tests, third party payers would be encouraged to provide access. Currently, significant healthcare dollars are wasted on unproven and unnecessary testing which do not inform medical decisions. Should that be remedied, the dollars needed for appropriate testing would be less of an issue.

How can cost-effective arrangements be made for obtaining proprietary tests that are currently too expensive for most consumers and payers? What strategies are needed to ensure that future genetic discoveries lead to affordable tests? How can the intellectual contributions to their discovery be appropriately recognized and developmental costs reimbursed while keeping costs within reach? Again, if the testing were limited to clinically proven applications, then the overall costs to the system may not be as problematic. Since this remains an issue in the device and pharmaceutical areas, it is doubtful that the molecular diagnostic area will have any more success in solving this problem.

(307) Tuesday, June 30, 2009 2:42 PM


We wish to reaffirm our concerns, which do not appear to have been addressed in this revision. Specifically, we believe it is misleading to organize the document into separate questions about what information will convince payers to reimburse genetic tests and about what information will convince providers to apply genetic testing strategies to their patients.

First, the questions do not make it clear that not all available genetic tests are equally likely to result in useful medical information and improved clinical outcomes for the patient. Second, evidence of improved clinical outcomes as a result of genetic testing is as important to providers as it is to payers- both groups have the goal of improving patient health efficiently and cost-effectively and ultimately is of utmost importance to patients.

Rather, we suggest addressing the overall goals when considering adding genetic testing to standard clinical care, the evidence needed to show that those goals can be achieved for individual patient applications, and how tests with evidence of clinical utility can favorably impact payer policy, provider use, and patient acceptance i.e. all users.

(310) Tuesday, June 30, 2009 8:57 PM

Last updated: March 19, 2012