Journal Mobile Options
Table of Contents
Vol. 13, No. 4, 2010
Issue release date: April 2010
Section title: Paper
Free Access
Public Health Genomics 2010;13:215–223
(DOI:10.1159/000279623)

Debating Clinical Utility

Burke W.a · Laberge A.-M.c · Press N.b
aDepartment of Bioethics and Humanities, University of Washington, Seattle, Wash., and bSchools of Nursing and Medicine, Oregon Health and Science University, Portland, Oreg., USA; cService de génétique médicale, CHU Sainte-Justine, Département de Pédiatrie, Université de Montréal, Montréal, Que., Canada
email Corresponding Author

Abstract

The clinical utility of genetic tests is determined by the outcomes following test use. Like other measures of value, it is often contested. Stakeholders may have different views about benefits and risks and about the importance of social versus health outcomes. They also commonly disagree about the evidence needed to determine whether a test is effective in achieving a specific outcome. Questions may be presented as factual disagreements, when they are actually debates about what information matters or how facts should be interpreted and used in clinical decision-making. Defining the different issues at stake is therefore an important element of policy-making. Key issues include evidence standards for test use, and in particular, the circumstances under which prospective controlled data should be required, as well as evidence on feasibility, cost and equitable delivery of testing; the goals of population-based screening programs, and in particular, the role of social outcomes in evaluating test value; and the appropriate uses and funding of tests that inform non-medical actions. Addressing each of these issues requires attention to stakeholder values and methods for effective deliberation that incorporate consumer as well as health professional perspectives.

© 2010 S. Karger AG, Basel


  

Key Words

  • Clinical utility
  • Evidence-based practice
  • Genetic testing

 Introduction

The term ‘clinical utility’ was coined by a US task force [1] to describe one of 3 key measures of a genetic test. It was defined as ‘the benefits and risks that accrue from both positive and negative test results’. The other measures were analytic validity, the accuracy with which an assay measures a particular genetic characteristic, and clinical validity, the accuracy with which a genetic characteristic identifies a disease condition or risk. These properties are not independent: a test with poor analytic and/or clinical validity is unlikely to have clinical utility. In this framework, however, analytic and clinical validity are technical properties, while clinical utility addresses a test’s health care value [2,3,4]. Like other measures of value, it is often contested.

The reasons for disagreement vary. Stakeholders may have different views about the benefits and risks that matter. The inclusion of social outcomes as a benefit of testing, and their priority relative to health outcomes, may be debated [3]. Stakeholders may also disagree about whether benefits of a given test outweigh its harms. When people agree about a desired outcome (health-related or otherwise), they may disagree about whether the test is effective in providing the outcome, or about whether testing is feasible or an appropriate use of available resources.

These debates have important implications. Regulatory decisions, health care funding, and patient access to testing are all influenced by judgments about clinical utility. Underlying value judgments, and related priority-setting decisions, may not always be acknowledged. Instead, questions may be presented as factual disagreements, when they are actually debates about how facts should be interpreted or used in clinical decision-making. Defining the different issues at stake is therefore an important, although often overlooked, element of policy-making and may help to identify barriers to consensus and the strategies needed to resolve them.

 

 Evidence Thresholds for Genetic Test Use

New genetic tests are a product of scientific research. Yet the specific evidence needed to justify a test’s clinical use is a frequent source of disagreement. As an example, Blue Cross Health Tec Assessment [5] and the American Society of Clinical Oncology [6] have endorsed gene expression profiling as a means to characterize breast cancer prognosis and inform chemotherapy decisions. By contrast, the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group, an evaluation group sponsored by CDC, reviewed the same evidence and found it insufficient to recommend for or against such testing [7]. Similarly, experts have disagreed about whether the available evidence is sufficient to recommend pharmacogenetic testing to guide the use of the anticoagulant warfarin [8,9,10,11].

Although these debates typically focus on the findings of specific studies (or the absence of studies), the underlying disagreement is about type of evidence needed to justify test use. A core issue is the degree to which different types of clinical studies provide valid outcome data; a common related question is whether prospective evidence on test outcomes should be required prior to test use. Both of these questions relate to the clinical evidence used to establish the test’s potential to achieve its intended purpose. A number of other measures, related to its acceptability, cost and feasibility, are also important in evaluating a test’s clinical utility (table 1) [12,13,14].

TAB01
Table 1. Contributors to clinical utility

 Evaluating a Test’s Potential to Achieve the Intended Clinical Outcome

The standard used in the evaluation of new drugs – randomized controlled trials – has not been applied to medical tests. Instead, plausible observational data have traditionally been viewed as sufficient to justify a new test. For example, a new method for measuring blood chemistry is evaluated by demonstrating that its results are either comparable to or better than a gold standard (thus establishing analytical and/or clinical validity), rather than by evidence that measurement of the analyte in question improves patient outcomes (which would establish clinical utility).

This standard works well when there is an accepted clinical role for the test. However, many genetic tests create new clinical paradigms. Take the warfarin example: Tests for variants in the CYP2C9 and VKORC1 genes can identify individuals with lower dosing requirements and a higher risk of bleeding complications from the anticoagulant warfarin; these variants are estimated to account for 30–50% of the individual variation in drug response [11,15]. Using tests for CYP2C9 and VKORC1 variants to make decisions about warfarin dosing represents a new way to manage drug therapy. Some estimate it will lead to markedly increased drug safety and reduced health care costs [16,17], while others caution that the outcome is difficult to predict and could in fact have limited benefit, lead to increased costs, and potentially result in errors in drug prescribing [8]. Much of the data supporting pharmacogenetic testing for warfarin derives from retrospective studies [e.g. [18] ]. Three small clinical trials have been reported, but these were of variable quality, with short follow-up times, and did not provide evidence for significant outcome benefits [19]. Modeling studies have provided evidence for and against cost-effectiveness, with some variables difficult to estimate accurately because of limited empiric data [16,20]. The debate is therefore fundamentally about the weight given to presumptive benefits and harms in the face of uncertainty and about the trade-offs between bringing a potentially beneficial innovation to health care early versus waiting for more robust evidence. This is a particularly important question in a context of limited resources.

Clinical practice is replete with innovations that proved less beneficial when tested in randomized trials than they initially appeared in observational studies – hormone replacement therapy is a recent example [21]. However, medical genetics offers important counter examples. Genetic testing for multiple endocrine neoplasia type 2 (MEN 2), followed by prophylactic thyroidectomy in those found to have the condition, was established as a practice standard based solely on observational data [22]; a 5-year follow-up of treated individuals confirms effective prevention of thyroid cancer [23].

The rarity of MEN 2, and the urgency of preventing medullary thyroid cancer in children at risk, arguably made a randomized trial for prophylactic thyroidectomy both impractical and unethical. But to what extent should this example inform the introduction of other genetic tests? Important factors in addressing this question include the prevalence of the disorder, the predictive value of the test, and the availability and utility of alternative diagnostic tools or treatment regimens. In the MEN 2 example, penetrance of causative mutations is close to 100%, and surveillance tools were inadequate to identify thyroid cancer effectively at an early stage. In the warfarin example, pharmacogenetic tests explain no more than half of individual variation in drug response [11,15], and other alternatives to safe dosing are available, including the standard clinical approach of initiating warfarin therapy with low initial doses and regularly monitoring the patient’s response. Testing for warfarin treatment is therefore substantively different from testing for MEN 2, but how the difference should inform evidence requirements is a matter of judgment.

A related issue is the generalizability of clinical evidence. A clinical trial may provide evidence for efficacy of the testing process and its follow-up services. However, the benefit achieved under routine conditions – that is, the effectiveness of the testing process – may be lower, due to factors such as provider preparedness, the availability and convenience of follow-up services, and patient compliance. These points speak to the importance of evidence beyond that provided by clinical research (table 1).

 Considering the Full Array of Contributors to Clinical Utility

The scope of the evidence needed to provide a convincing justification for test use inevitably varies for different tests and clinical settings [9,12]. For example, another pharmacogenetic test, to identify people at increased risk for adverse effects from the anti-retroviral abacovir, has been greeted with general enthusiasm [24,25]. The difference in the acceptance of this test compared to warfarin-related testing likely lies in the high specificity of the test: although fewer than 50% of people with the risk genotype, HLA-B*5701, will experience adverse events, people without this genotype appear to have no risk [24]. As a result, the pharmacogenetic test offers the physician clinically useful information about patients at risk; given alternative therapies for these individuals, the test has clear clinical utility. Even here, however, contextual factors need to be taken into account. A recent study predicted, not surprisingly, that the cost-effectiveness of HLA-B*5701 testing prior to abacavir use would vary widely with the prevalence of the variant, the costs of both the test and alternative treatments, and the relative effectiveness of the alternative treatments [26]. Under some scenarios the test was highly cost-effective while under others it provided little benefit; under some scenarios the use of an alternative drug without testing was preferable. This example points to the importance of defining the clinical context before evaluating clinical utility (table 1), including the population to be tested and the services to be offered after testing, as well as cost, acceptability and other social factors.

Differing judgments about clinical utility illustrate the central role of evidence standards and related questions about the types of evidence needed, and how they contribute to decision-making, in most debates about the use of genetic tests. Relatively few medical innovations have been established through randomized clinical trials; even when a prospective clinical trial provides evidence of benefit, clinicians must make judgments about the relevance of the trial for their patients, who may differ from trial participants in significant ways [27]. Health service context, societal and patient acceptance, and financial considerations are also relevant (table 1). As a result, there is no single ‘right’ answer in these debates. Clarity about the reason for differences – in particular, why observational or other data are persuasive for some observers, while others remain unconvinced without prospective trial data – may help to inform clinicians and patients who must make decisions about test use. Furthermore, evidence is not static: new studies might lead to a re-evaluation of the clinical utility of a particular test. Ultimately, clarity about the value judgments different stakeholders use in judging evidence can promote broader consensus.

 

 Genetic Testing for Population-Based Disease Prevention

Additional questions about value arise when genetics is proposed as a tool for population-based disease prevention. The use of genetics for this purpose is already well established. The identification of newborns who require urgent treatment to prevent death or disability – as in the case of phenylketonuria – represents the most dramatic example. Another routine use of genetics for disease prevention involves the evaluation of family history to detect individuals at increased risk of cancer and other adult onset diseases, in order to enable targeted prevention. However, debates about clinical value occur for both these uses of genetic information, centering on the implications of a test’s predictive value and the effectiveness of interventions to reduce risk. Increasingly, discussions about genetics and disease prevention also raise questions about the appropriate scope of genetic risk assessment.

 Newborn Screening

The development of tandem mass spectrometry has allowed a large increase in the number of conditions tested for in newborn screening, and DNA-based testing offers the potential for further expansion in the future [28]. This growing technological capacity has aroused vigorous debate about the threshold for introducing new tests and, ultimately, about the purpose of this population screening program. As Grosse et al. have pointed out [29], newborn screening was initially instituted to address a public health emergency – the need for rapid institution of diet therapy for infants with phenylketonuria – to prevent mental retardation. Over time, however, the goal of newborn screening has expanded to include detection of infants who do not require immediate treatment, but who will benefit from specialized services – for example, infants with cystic fibrosis. With such expansion comes an increasing number of false-positive findings [30] and the detection of infants with ambiguous test results [31], both adding cost and posing potential harms.

The diagnostic capacity of tandem mass spectrometry also allows for the identification of conditions for which no proven therapy is currently available [32]. In this context, some advocates have proposed that the traditional goal of newborn screening – the improved health of the infants tested – should be expanded to encompass goals related to the family’s quality of life. They note that many parents express a preference for knowing early about an affected child, even if no treatment is available [33]. Early detection of an untreatable genetic disease can also inform reproductive decision-making in future pregnancies [33,34]. Broad detection of infants with rare genetic diseases is also seen as a way to expedite research [34,35]. Others argue forcefully against the expansion of newborn screening programs for these purposes [32,36,37,38].

The values at stake in this debate include the appropriate uses of a publicly funded screening program [36]; concerns about the lack of explicit informed consent or pre-test counseling in newborn screening programs [38]; potential harms from treatments of unproven value [32,37]; and concerns about expanding the burden of false-positive test results [30]. These debates are partly about evidence – for example, what evidence is needed to assess the harms of false-positive results – but much more about the values that should inform population screening of newborns. In particular, the debate centers on what concerns or risks justify providing unsought information to parents of healthy infants. The newborn screening example thus illustrates that some contributors to clinical utility – including acceptability of testing from societal and patient perspectives, financial trade-offs, and the balance of positive and negative consequences of testing (table 1) – cannot be assessed without also considering whose views matter and how they should be weighed and incorporated in decision-making.

 Detection of Common Disease Risk

An important goal of family history assessment is to identify increased risk for common complex diseases, so that targeted preventive care can be offered. Public campaigns encourage individuals to seek out family history information [e.g. [39] ], and geneticists have called for increasing clinician education on the use of family history information in disease prevention [40]. Unfortunately, family history is a relatively crude measure for assessing risk for common complex diseases [41].

Recent progress in the identification of gene variants associated with common disease risk [42] points to a new approach to achieving the same goal: personal genomic profiling to identify risk and guide preventive care. Personal genome profiles are already being marketed directly to consumers as a source of health and personal information [43,44]. Advocates believe that such information could motivate healthy behaviors such as improved diet and exercise or smoking cessation [45,46,47], and several studies have been launched to seek evidence evaluating the use of such information to improve disease prevention [e.g. [48,49,50] ]. Others question the value of this approach [51,52].

One aspect of the debate focuses on the need for evidence of improved outcomes from genetic testing – a continuation of the debates about outcome data for tests such as warfarin pharmacogenetics and gene expression profiling in breast cancer [53]. In addition, because most gene variants associated with common complex diseases confer very small risks, there is currently uncertainty about the extent to which genomic profiling will provide an effective basis for preventive care [51,52,54,55].

As studies are completed and the scope of benefit is defined, questions about values will arise: How big a prevention effect is sufficient to justify genetic testing? If the main outcome of testing is to suggest a better diet, or other lifestyle improvement, is testing an appropriate use of health care dollars? And is the test still of value if the recipient does not make the lifestyle changes? Consumers may wish to have the option for such genetic testing, and some may argue that they have a right to such information. Resolution of the underlying evidence question – what data are needed to establish the clinical utility of genetic susceptibility testing – will depend on how one views the goals of health care and, in particular, the appropriate role of consumer preference when medical outcomes are uncertain. Costs and associated trade-offs are also a legitimate part of the discussion – in particular, whether expenditures for personal genomics can be justified if they draw resources away from other health expenditures.

 

 Genetic Testing to Inform Non-Medical Decisions

A related question concerns the role of genetic testing in providing information for decisions that are more social than medical. The use of genetic testing for reproductive decision-making provides an interesting precedent for this discussion.

Prenatal genetic testing was introduced at approximately the same time as newborn screening [56]. Carrier tests for a number of genetic diseases soon followed. Although these tests are often discussed in conventional medical terms – e.g. a prenatal test may be described as ‘indicated’ when a pregnant woman is known to be at risk to have a child with a genetic disease – their purpose is different from most medical tests. Rather than informing the health care of the individual tested, carrier and prenatal genetic tests inform parents about the risks of having a child with a genetic disease. In most clinical settings they are offered to enable parents to consider pregnancy termination if a serious genetic disease is identified in the fetus, or to help parents prepare for a child with special needs.

Both societal and personal values inform this testing process. In some countries, the introduction of prenatal diagnosis and access to pregnancy termination have been tied explicitly to societal concerns about the burdens of a genetic disease – for example, in screening programs for β-thalassemia in Cyprus and Iran [57,58]. In countries where this service is available, health care providers generally articulate a strong commitment to pre-test counseling, to ensure that testing is voluntary and in keeping with parental preferences.

Debates around reproductive genetics have focused on the moral implications of pregnancy termination. Many disability advocates have questioned the use of prenatal diagnosis to prevent births of children with Down syndrome, for example [59]. With the introduction of pre-implantation genetic diagnosis, other uses of reproductive genetics – e.g. testing to detect adult onset conditions, or to determine whether the embryo can serve as a bone marrow donor for an ailing sibling – are also controversial [60,61]. These debates are to be expected, given the nature and purpose of reproductive genetic testing; societal legitimacy (table 1) is a factor in determining what prenatal tests can be offered.

However, genetic testing can inform personal decision-making in a variety of other ways, raising questions that are analogous to – and ultimately part of – the debate about personal genomics. For example, learning that a child has X-linked retinitis pigmentosa may be extremely important for educational and career planning because the child can be expected to be legally blind by early adulthood [62]. Although the diagnosis provides a clinical prognosis, no specific therapy is currently available to reduce or ameliorate vision loss; as a result, the social uses of the information are more important than the clinical uses.

The clinical utility of genetic testing for retinitis pigmentosa is unlikely to be questioned because of the high predictive value of a positive test and the specific preparatory actions that can be taken by parents and affected persons. Less predictive genetic tests offer information that individuals may find similarly useful for life planning, but these tests are likely to be more controversial. As an example, APOE 4 testing can identify individuals at increased risk of Alzheimer disease. A small study found that those with positive test results were more likely to purchase long-term care insurance [63], and preparing family members was viewed as an important value of testing [64]. Yet several expert panels have recommended against such testing, on the grounds that the predictive value of testing is limited and the risk information could be stigmatizing and emotionally upsetting [65,66,67]. A recent study indicating lack of short-term psychological stress after APOE 4 testing [68] will not necessarily reduce these concerns, given that the participants in this study were unlikely to be broadly representative of the population [69]. These differences of opinion reflect different estimates of the benefits and risks associated with probabilistic information and perhaps also reflect different stakeholders’ views about the goals of health care and appropriate uses of health care resources. Over the next decade, genomic research will offer many additional tests to fuel this debate.

 

 Benefits of Defining the Issues

Lack of evidence has been identified as a major impediment to the translation of genomic knowledge into beneficial medical interventions [49,53,70]. However, the task of defining what is adequate evidence may, in fact, be at the heart of many disputes and will need to be considered in developing consensus on clinical utility.

Perhaps the first issue to be addressed is whether ‘clinical utility’ should be considered relevant only in health care settings. A test that provides information of interest to consumers but is not medically actionable, like the APOE 4 test, might have a poor claim on health care resources [71], yet might still represent an appropriate consumer product. If so, consumer safety would become a central policy concern, with a need to define the potential harms of testing, the regulatory models for pre-market test review, and the standards for the marketing of products [43]. As debates about personal genomics already demonstrate, defining the line between consumer products and health care tests will also be difficult.

For tests used in health care, evidence standards will need to be based on what physicians, patients, and health care funders find convincing in establishing a benefit. For example, will a genetic risk assessment that is believed to motivate a change in patient behavior, rather than changes in physician testing or prescribing regimens, be considered medically actionable and thus worthy of a claim on health care dollars? The threshold defined by clinicians in practice may or may not conform to the rigorous standards proposed by groups such as EGAPP [72] – and patients may view the threshold differently than clinicians.

Some will argue that clinicians in practice are ill equipped to assess the clinical utility of new genetic tests. Most have important deficiencies in their knowledge of genetics and genetic tests [73], and most medical students do not retain the genetics education they received [74,75]. It would therefore be unrealistic to presume that most clinicians will be able to integrate new genetic tests into their practice based on their assessment of the evidence. Public health efforts to increase the development of practice guidelines in genetics are underway [72,76]. There is a need for greater physician engagement in the development and use of guidelines and more systematic efforts to assess the large number of genetic tests likely to emerge from current research [77], with appropriate stakeholder input.

The evidence needed to make a compelling case for testing will undoubtedly vary by both test characteristics and testing purpose [12]. The clinical utility of tests to diagnose rare, highly penetrant conditions will generally be established by small-scale studies that confirm the gene-disease association. On the other hand, tests for genetic susceptibility, intended to be used in population-based screening, are unlikely to be convincing without rigorous assessment of testing outcomes.

Clarification of different stakeholders whose interests are at stake, and their preferences and values, will also be important. In some cases – such as the use of testing to inform medical treatment of symptomatic patients – little controversy will be expected, and a convergence of values can be predicted. However, in other arenas, such as medical testing used for actions outside the medical system (e.g. APOE testing to inform personal decisions such as purchase of long-term care insurance) or population screening for rare conditions with variable phenotype and severity, controversy is to be expected. Stakeholders for these decisions include not only clinicians, patients and health care funders, but also test developers, regulatory agencies and lawmakers. In these latter cases, endless debate without resolution can occur – and clarifying the values that are at stake and how different stakeholders prioritize them may be the only way to move discussion forward to a resolution.

An early challenge in approaching this task is to determine how different stakeholder views can be defined and shared. While there are good reasons to separate the processes of regulatory review, development of professional practice guidelines, and funding decisions – because they are based on different governance – more opportunities are needed to discuss the different values that may be brought to each of these decision-making activities. Perhaps more important, with increasing attention to patient-centered care [78], there is a need to move beyond expert-driven processes, to identify ways for meaningful input from the consumers who are both the intended beneficiaries and ultimate funders of genomic innovation.

 

 Acknowledgement

This project was supported in part by the Center for Genomics and Healthcare Equality (Grant P50 HG003374 from the US National Institutes of Health).


References

  1. Holtzman NA, Watson MS: Promoting Safe and Effective Genetic Testing in the United States. Final Report of the Task Force on Genetic Testing. Baltimore, Johns Hopkins University Press, 1999.
  2. Secretary’s Advisory Committee on Genetic Testing: Enhancing the oversight of genetic tests: recommendations of the SACGT, National Institutes of Health, 2000. Available at http://oba.od.nih.gov/oba/sacgt/reports/oversight_report.pdf, accessed 11/09/09.
  3. Grosse SD, Khoury MJ: What is the clinical utility of genetic testing? Genet Med 2006;8:448–450.
  4. Burke W, Atkins D, Gwinn M, Guttmacher A, Haddow J, Lau J, Palomaki G, Press N, Richards CS, Wideroff L, Wiesner GL: Genetic test evaluation: information needs of clinicians, policy-makers and the public. Am J Epidemiol 2002;156:311–318.
  5. Health Tec Assessment: Gene expression profiling of breast cancer to select women for adjuvant chemotherapy. Available at http://www.bcbs.com/blueresources/tec/vols/22/ 22_13.html, accessed 11/09/09.
  6. Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC Jr, American Society of Clinical Oncology: American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 2007;25:5287–5312.
  7. EGAPP Working Group: Recommendations from the EGAPP Working Group: Can tumor gene expression profiling improve outcomes in patients with breast cancer? Genet Med 2009;11:66–73.
  8. Bussey HI, Wittkowsky AK, Hylek EM, Walker MB: Genetic testing for warfarin dosing? Not yet ready for prime time. Pharmacotherapy 2008;28:141–143.
  9. Woodcock J, Lesko LJ: Pharmacogenetics – tailoring treatment for outliers. New Engl J Med 2009;360:811–813.
  10. Shurin SB, Nabel EG: Pharmacogenomics – ready for prime time? New Engl J Med 2008;358:1061–1063.
  11. Eckman MH, Greenberg SM, Rosand J: Should we test for CYP2C9 before initiating anticoagulant therapy in patients with atrial fibrillation? J Gen Intern Med 2009;24:543–549.
  12. Burke W, Kroese M, Zimmern R: Defining purpose: a key step in genetic test evaluation. Genet Med 2007;9:675–681.
  13. Burke W, Zimmern R: Moving beyond ACCE: an expanded framework for genetic test evaluation: a paper for the United Kingdom Genetic Testing Network, 2007. Available at http://www.phgfoundation.org/pages/work7.htm, accessed 11/09/09.
  14. Zimmern RL, Kroese M: The evaluation of genetic tests. J Public Health (Oxf) 2007;29:246–250.
  15. Rieder MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL, Blough DK, Thummel KE, Veenstra DL, Rettie AE: Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med 2005;352:2285–2293.
  16. McWilliam A, Lutter R, Nardinelli C: Health care savings from personalizing medicine using genetic testing: the case of warfarin. AEI-Brookings Joint Center, 2006. Available at http://aei-brookings.org/publications/abstract.php?pid=1127, accessed 11/09/09.
  17. Hood L, Heath JR, Phelps ME, Lin B: Systems biology and new technologies enable predictive and preventative medicine. Science 2004;306:640–643.
  18. International Warfarin Pharmacogenetics Consortium, Klein TE, Altman RB, Eriksson N, Gage BF, Kimmel SE, Lee MT, Limdi NA, Page D, Roden DM, Wagner MJ, Caldwell MD, Johnson JA: Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med 2009;360:753–764.
  19. Kangelaris KN, Bent S, Nussbaum RL, Garcia DA, Tice JA: Genetic testing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin. J Gen Intern Med 2009;24:656–664.
  20. Eckman MH, Rosand J, Greenberg SM, Gage BF: Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med 2009;150:73–83.
  21. Roberts H: Hormone replacement therapy comes full circle. BMJ 2007;335:219–220.
  22. Brandi ML, Gagel RF, Angeli A, Bilezikian JP, Beck-Peccoz P, Bordi C, Conte-Devolx B, Falchetti A, Gheri RG, Libroia A, Lips CJ, Lombardi G, Mannelli M, Pacini F, Ponder BA, Raue F, Skogseid B, Tamburrano G, Thakker RV, Thompson NW, Tomassetti P, Tonelli F, Wells SA Jr, Marx SJ: Guidelines for diagnosis and therapy of MEN type 1 and type 2. J Clin Endocrinol Metab 2001;86:5658–5671.
  23. Skinner MA, Moley JA, Dilley WG, Owzar K, Debenedetti MK, Wells SA Jr: Prophylactic thyroidectomy in multiple endocrine neoplasia type 2A. N Engl J Med 2005;353:1105–1113.
  24. Lai-Goldman M, Faruki H: Abacavir hypersensitivity: a model system for pharmacogenetic test adoption. Genet Med 2008;10:874–878.
  25. Sheffield LJ, Phillimore H: Clinical use of pharmacogenomic tests in 2009. Clin Biochem Rev 2009;30:55–65.

    External Resources

  26. Schackman BR, Scott CA, Walensky RP, Losina E, Freedberg KA, Sax PE: The cost-effectiveness of HLA-B*5701 genetic screening to guide initial anti-retroviral therapy for HIV. AIDS 2008;22:2025–2033.
  27. Tonelli MR: Integrating evidence into clinical practice: an alternative to evidence-based approaches. J Eval Clin Pract 2006;12:248–256.
  28. Wilcken B, Wiley V: Newborn screening. Pathology 2008;40:105–115.

    External Resources

  29. Grosse SD, Boyle CA, Kenneson A, Khoury MJ, Wilfond BS: From public health emergency to public health service: the implications of evolving criteria for newborn screening panels. Pediatrics 2006;117:923–929.
  30. Tarini B: The current revolution in newborn screening: new technology, old controversies. Arch Pediatr Adolesc Med 2007;161:767–772.
  31. Roussey M, Le Bihannic A, Scotet V, Audrezet MP, Blayau M, Dagorne M, David V, Deneuville E, Giniès JL, Laurans M, Moisan-Petit V, Rault G, Vigneron P, Férec C: Neonatal screening of cystic fibrosis: diagnostic problems with CFTR mild mutations. J Inherit Metab Dis 2007;30:613.
  32. Botkin JR, Clayton EW, Fost NC, Burke W, Murray TH, Baily MA, Wilfond B, Berg A, Ross LF: Newborn screening technology: proceed with caution. Pediatrics 2006;117:1793–1799.
  33. Bailey DB, Skinner D, Warren SF: Newborn screening for developmental disabilities: reframing presumptive benefit. Am J Public Health 2005;95:1889–1893.
  34. Alexander D, van Dyck PC: A vision of the future of newborn screening. Pediatrics 2006;117:S350–S354.
  35. Howell RR: We need expanded newborn screening. Pediatrics 2006;117:1800–1805.
  36. Baily MA, Becker W Jr, Hayes M, Clayton EW, Grosse S: Exploring options for expanded newborn screening. J Law Med Ethics 2005;33(suppl 4):46–48.
  37. Natowicz M: Newborn screening–setting evidence-based policy for protection. N Engl J Med 2005;353:867–870.
  38. Ross LF: Screening for conditions that do not meet the Wilson and Jungner criteria: the case of Duchenne muscular dystrophy. Am J Med Genet A 2006;140:914–922.

    External Resources

  39. Surgeon General’s Family History Initiative. Available at http://www.hhs.gov/familyhistory/, accessed 11/09/09.
  40. Guttmacher AE, Porteous ME, McInerny JD: Educating health-care professionals about genetics and genomics. Nat Rev Genet 2007;8:151–157.
  41. Wilson B, Qureshi N, Little J, Santaguida P, Carroll J, Allanson J, Keshavarz H, Raina P: Clinical utility of cancer family history collection in primary care. Evidence report/technology assessment No. 179 (prepared by the McMaster University Evidence-based Practice Center, under Contract No. 290-02-0020), AHRQ Publication No. 09-E007. Rockville, MD, Agency for Healthcare Research and Quality, 2009.
  42. Manolio TA: Collaborative genome-wide association studies of diverse diseases: programs of the NHGRI’s office of population genomics. Pharmacogenomics 2009;10:235–241.
  43. Hogarth S, Javitt G, Melzer D: The current landscape for direct-to-consumer genetic testing: legal, ethical, and policy issues. Annu Rev Genomics Hum Genet 2008;9:161–182.
  44. Farkas DH, Holland CA: Direct-to-consumer genetic testing: two sides of the coin. J Mol Diagn 2009;11:263–265.
  45. Stefansson K: Quoted in Lauerman J: DeCode Finds Gene Linked to Diabetes. New York Sun, 2006. Available at http://www.nysun.com/business/decode-finds-gene-linked-to-diabetes/25933/, accessed 11/09/09.
  46. Collins FS: Shattuck lecture – Medical and societal consequences of the Human Genome Project. N Engl J Med 1999;341:28–37.
  47. McBride CM: Blazing a trail: a public health research agenda in genomics and chronic disease. Prev Chronic Dis [serial online] 2005;2:A04. Available at http://www.cdc.gov/pcd/issues/2005/apr/05_0008.htm, accessed 11/09/09.
  48. Sanderson SC, O’Neill SC, White DB, Bepler G, Bastian L, Lipkus IM, McBride CM: Responses to online GSTM1 genetic test results among smokers related to patients with lung cancer: a pilot study. Cancer Epidemiol Biomarkers Prev 2009;18:1953–1961.
  49. McBride CM, Alford SH, Reid RJ, Larson EB, Baxevanis AD, Brody LC: Putting science over supposition in the arena of personalized genomics. Nat Genet 2008;40:939–942.
  50. Pijl M, Timmermans DR, Claassen L, Janssens AC, Nijpels G, Dekker JM, Marteau TM, Henneman L: Impact of communicating familial risk of diabetes on illness perceptions and self-reported behavioral outcomes: a randomized controlled trial. Diabetes Care 2009;32:597–599.
  51. Thompson PA: Counterpoint: genetic risk feedback for common disease time to test the waters. Cancer Epidemiol Biomarkers Prev 2007;16:1727–1729.
  52. Merikangas KR, Risch N: Genomic priorities and public health. Science 2003;302:599–601.
  53. Hunter DJ, Khoury MJ, Drazen JM: Letting the genome out of the bottle – will we get our wish? N Engl J Med 2008;358:105–107.
  54. Altshuler D, Daly MJ, Lander ES: Genetic mapping in human disease. Science 2008;322:881–888.
  55. Burke W, Psaty BM: Personalized medicine in the era of genomics. JAMA 2007;298:1682–1684.
  56. Nadler HL, Gerbie AB: Role of amniocentesis in the intrauterine detection of genetic disorders. N Engl J Med 1970;282:596–599.
  57. Cowan RS: Moving up the slippery slope: mandated genetic screening on Cyprus. Am J Med Genet C Semin Med Genet 2009;151C: 95–103.
  58. Najmabadi H, Ghamari A, Sahebjam F, Kariminejad R, Hadavi V, Khatibi T, Samavat A, Mehdipour E, Modell B, Kariminejad MH: Fourteen-year experience of prenatal diagnosis of thalassemia in Iran. Community Genet 2006;9:93–97.
  59. Parens E, Asch A: The disability rights critique of prenatal genetic testing. Reflections and recommendations. Hastings Cent Rep 1999;29:S1–S22.
  60. Offit K, Kohut K, Clagett B, Wadsworth EA, Lafaro KJ, Cummings S, White M, Sagi M, Bernstein D, Davis JG: Cancer genetic testing and assisted reproduction. J Clin Oncol 2006;24:4775–4782.
  61. Bennett B: Symbiotic relationships: saviour siblings, family rights and biomedicine. Aust J Fam Law 2005;19:195–212.

    External Resources

  62. Pagon RA, Daiger SP: Retinitis pigmentosa overview. GeneTests 2005. Available at http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi? book=gene&part=rp-overview, accessed 11/ 09/09.
  63. Zick CD, Mathews CJ, Roberts JS, Cook-Deegan R, Pokorski RJ, Green RC: Genetic testing for Alzheimer’s disease and its impact on insurance purchasing behavior. Health Aff (Millwood) 2005;24:483–490.
  64. Roberts JS, Cupples LA, Relkin NR, Whitehouse PJ, Green RC; REVEAL (Risk Evaluation and Education for Alzheimer’s Disease) Study Group: Genetic risk assessment for adult children of people with Alzheimer’s disease: the Risk Evaluation and Education for Alzheimer’s Disease (REVEAL) study. J Geriatr Psychiatry Neurol 2005;18:250–255.
  65. Relkin NR, Kwon YJ, Tsai J, Gandy S: The National Institute on Aging/Alzheimer’s Association recommendations on the application of apolipoprotein E genotyping to Alzheimer’s disease. Ann N Y Acad Sci 1996;802:149–176.
  66. McConnell LM, Koenig BA, Greely HT, Raffin TA: Genetic testing and Alzheimer disease: recommendations of the Stanford program in genomics, ethics, and society. Genet Test 1999;3:3–12.
  67. Post SG, Whitehouse PJ, Binstock RH, Bird TD, Eckert SK, Farrer LA, Fleck LM, Gaines AD, Juengst ET, Karlinsky H, Miles S, Murray TH, Quaid KA, Relkin NR, Roses AD, St George-Hyslop PH, Sachs GA, Steinbock B, Truschke EF, Zinn AB: The clinical introduction of genetic testing for Alzheimer disease. An ethical perspective. JAMA 1997;277:832–836.
  68. Green RC, Roberts JS, Cupples LA, Relkin NR, Whitehouse PJ, Brown T, Eckert SL, Butson M, Sadovnick AD, Quaid KA, Chen C, Cook-Deegan R, Farrer LA, REVEAL Study Group: Disclosure of APOE genotype for risk of Alzheimer’s disease. N Engl J Med 2009;361:245–254.
  69. Kane RA, Kane RL: Effect of genetic testing for risk of Alzheimer’s disease. N Engl J Med 2009;361:298–299.
  70. Feero WG, Guttmacher AE, Collins FS: The genome gets personal – almost. JAMA 2008;299:1351–1352.
  71. McGuire AL, Burke W: An unwelcome side effect of direct to consumer personal genome testing: raiding the medical commons. JAMA 2008;300:2669–2671.
  72. Teutsch SM, Bradley LA, Palomaki GE, Haddow JE, Piper M, Calonge N, Dotson WD, Douglas MP, Berg AO, EGAPP Working Group: The evaluation of genomic applications in practice and prevention (EGAPP) initiative: methods of the EGAPP working group. Genet Med 2009;11:3–14.
  73. Baars MJ, Henneman L, Ten Kate LP: Deficiency of knowledge of genetics and genetic tests among general practitioners, gynecologists, and pediatricians: a global problem. Genet Med 2005;7:605–610.
  74. Baars MJ, Scherpbier AJ, Schuwirth LW, Henneman L, Beemer FA, Cobben JM, Hennekam RC, Verweij MM, Cornel MC, Ten Kate LP: Deficient knowledge of genetics relevant for daily practice among medical students nearing graduation. Genet Med 2005;7:295–301.
  75. Greb AE, Brennan S, McParlane L, Page R, Bridge PD: Retention of medical genetics knowledge and skills by medical students. Genet Med 2009;11:365–370.
  76. UK Guidelines on Genetic Disorders. Available at http://www.patient.co.uk/showdoc/ 687/#related_guide, accessed 11/09/09.
  77. Salari K: The dawning era of personalized medicine exposes a gap in medical education. PLoS Med 2009;6:e1000138.
  78. Bindman AB: Is there a personal doctor in the house? Ann Intern Med 2009;150:351–352.

  

Author Contacts

Wylie Burke, MD, PhD
Department of Bioethics and Humanities, University of Washington
Box 357120, 1959 NE Pacific, Rm A204
Seattle, WA 98195-7120 (USA)
Tel. +1 206 221 5482, Fax +1 206 685 7515, E-Mail wburke@u.washington.edu

  

Article Information

Published online: April 15, 2010
Number of Print Pages : 9
Number of Figures : 0, Number of Tables : 1, Number of References : 78

  

Publication Details

Public Health Genomics

Vol. 13, No. 4, Year 2010 (Cover Date: April 2010)

Journal Editor: Knoppers B.M. (Montreal, Que.), Brand A. (Maastricht), Burke W. (Seattle, Wash.), Khoury M.J. (Atlanta, Ga.)
ISSN: 1662-4246 (Print), eISSN: 1662-8063 (Online)

For additional information: http://www.karger.com/PHG


Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

Abstract

The clinical utility of genetic tests is determined by the outcomes following test use. Like other measures of value, it is often contested. Stakeholders may have different views about benefits and risks and about the importance of social versus health outcomes. They also commonly disagree about the evidence needed to determine whether a test is effective in achieving a specific outcome. Questions may be presented as factual disagreements, when they are actually debates about what information matters or how facts should be interpreted and used in clinical decision-making. Defining the different issues at stake is therefore an important element of policy-making. Key issues include evidence standards for test use, and in particular, the circumstances under which prospective controlled data should be required, as well as evidence on feasibility, cost and equitable delivery of testing; the goals of population-based screening programs, and in particular, the role of social outcomes in evaluating test value; and the appropriate uses and funding of tests that inform non-medical actions. Addressing each of these issues requires attention to stakeholder values and methods for effective deliberation that incorporate consumer as well as health professional perspectives.

© 2010 S. Karger AG, Basel


  

Author Contacts

Wylie Burke, MD, PhD
Department of Bioethics and Humanities, University of Washington
Box 357120, 1959 NE Pacific, Rm A204
Seattle, WA 98195-7120 (USA)
Tel. +1 206 221 5482, Fax +1 206 685 7515, E-Mail wburke@u.washington.edu

  

Article Information

Published online: April 15, 2010
Number of Print Pages : 9
Number of Figures : 0, Number of Tables : 1, Number of References : 78

  

Publication Details

Public Health Genomics

Vol. 13, No. 4, Year 2010 (Cover Date: April 2010)

Journal Editor: Knoppers B.M. (Montreal, Que.), Brand A. (Maastricht), Burke W. (Seattle, Wash.), Khoury M.J. (Atlanta, Ga.)
ISSN: 1662-4246 (Print), eISSN: 1662-8063 (Online)

For additional information: http://www.karger.com/PHG


Article / Publication Details

First-Page Preview
Abstract of Paper

Published online: 4/15/2010
Issue release date: April 2010

Number of Print Pages: 9
Number of Figures: 0
Number of Tables: 1

ISSN: 1662-4246 (Print)
eISSN: 1662-8063 (Online)

For additional information: http://www.karger.com/PHG


Copyright / Drug Dosage

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

References

  1. Holtzman NA, Watson MS: Promoting Safe and Effective Genetic Testing in the United States. Final Report of the Task Force on Genetic Testing. Baltimore, Johns Hopkins University Press, 1999.
  2. Secretary’s Advisory Committee on Genetic Testing: Enhancing the oversight of genetic tests: recommendations of the SACGT, National Institutes of Health, 2000. Available at http://oba.od.nih.gov/oba/sacgt/reports/oversight_report.pdf, accessed 11/09/09.
  3. Grosse SD, Khoury MJ: What is the clinical utility of genetic testing? Genet Med 2006;8:448–450.
  4. Burke W, Atkins D, Gwinn M, Guttmacher A, Haddow J, Lau J, Palomaki G, Press N, Richards CS, Wideroff L, Wiesner GL: Genetic test evaluation: information needs of clinicians, policy-makers and the public. Am J Epidemiol 2002;156:311–318.
  5. Health Tec Assessment: Gene expression profiling of breast cancer to select women for adjuvant chemotherapy. Available at http://www.bcbs.com/blueresources/tec/vols/22/ 22_13.html, accessed 11/09/09.
  6. Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC Jr, American Society of Clinical Oncology: American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 2007;25:5287–5312.
  7. EGAPP Working Group: Recommendations from the EGAPP Working Group: Can tumor gene expression profiling improve outcomes in patients with breast cancer? Genet Med 2009;11:66–73.
  8. Bussey HI, Wittkowsky AK, Hylek EM, Walker MB: Genetic testing for warfarin dosing? Not yet ready for prime time. Pharmacotherapy 2008;28:141–143.
  9. Woodcock J, Lesko LJ: Pharmacogenetics – tailoring treatment for outliers. New Engl J Med 2009;360:811–813.
  10. Shurin SB, Nabel EG: Pharmacogenomics – ready for prime time? New Engl J Med 2008;358:1061–1063.
  11. Eckman MH, Greenberg SM, Rosand J: Should we test for CYP2C9 before initiating anticoagulant therapy in patients with atrial fibrillation? J Gen Intern Med 2009;24:543–549.
  12. Burke W, Kroese M, Zimmern R: Defining purpose: a key step in genetic test evaluation. Genet Med 2007;9:675–681.
  13. Burke W, Zimmern R: Moving beyond ACCE: an expanded framework for genetic test evaluation: a paper for the United Kingdom Genetic Testing Network, 2007. Available at http://www.phgfoundation.org/pages/work7.htm, accessed 11/09/09.
  14. Zimmern RL, Kroese M: The evaluation of genetic tests. J Public Health (Oxf) 2007;29:246–250.
  15. Rieder MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL, Blough DK, Thummel KE, Veenstra DL, Rettie AE: Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med 2005;352:2285–2293.
  16. McWilliam A, Lutter R, Nardinelli C: Health care savings from personalizing medicine using genetic testing: the case of warfarin. AEI-Brookings Joint Center, 2006. Available at http://aei-brookings.org/publications/abstract.php?pid=1127, accessed 11/09/09.
  17. Hood L, Heath JR, Phelps ME, Lin B: Systems biology and new technologies enable predictive and preventative medicine. Science 2004;306:640–643.
  18. International Warfarin Pharmacogenetics Consortium, Klein TE, Altman RB, Eriksson N, Gage BF, Kimmel SE, Lee MT, Limdi NA, Page D, Roden DM, Wagner MJ, Caldwell MD, Johnson JA: Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med 2009;360:753–764.
  19. Kangelaris KN, Bent S, Nussbaum RL, Garcia DA, Tice JA: Genetic testing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin. J Gen Intern Med 2009;24:656–664.
  20. Eckman MH, Rosand J, Greenberg SM, Gage BF: Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med 2009;150:73–83.
  21. Roberts H: Hormone replacement therapy comes full circle. BMJ 2007;335:219–220.
  22. Brandi ML, Gagel RF, Angeli A, Bilezikian JP, Beck-Peccoz P, Bordi C, Conte-Devolx B, Falchetti A, Gheri RG, Libroia A, Lips CJ, Lombardi G, Mannelli M, Pacini F, Ponder BA, Raue F, Skogseid B, Tamburrano G, Thakker RV, Thompson NW, Tomassetti P, Tonelli F, Wells SA Jr, Marx SJ: Guidelines for diagnosis and therapy of MEN type 1 and type 2. J Clin Endocrinol Metab 2001;86:5658–5671.
  23. Skinner MA, Moley JA, Dilley WG, Owzar K, Debenedetti MK, Wells SA Jr: Prophylactic thyroidectomy in multiple endocrine neoplasia type 2A. N Engl J Med 2005;353:1105–1113.
  24. Lai-Goldman M, Faruki H: Abacavir hypersensitivity: a model system for pharmacogenetic test adoption. Genet Med 2008;10:874–878.
  25. Sheffield LJ, Phillimore H: Clinical use of pharmacogenomic tests in 2009. Clin Biochem Rev 2009;30:55–65.

    External Resources

  26. Schackman BR, Scott CA, Walensky RP, Losina E, Freedberg KA, Sax PE: The cost-effectiveness of HLA-B*5701 genetic screening to guide initial anti-retroviral therapy for HIV. AIDS 2008;22:2025–2033.
  27. Tonelli MR: Integrating evidence into clinical practice: an alternative to evidence-based approaches. J Eval Clin Pract 2006;12:248–256.
  28. Wilcken B, Wiley V: Newborn screening. Pathology 2008;40:105–115.

    External Resources

  29. Grosse SD, Boyle CA, Kenneson A, Khoury MJ, Wilfond BS: From public health emergency to public health service: the implications of evolving criteria for newborn screening panels. Pediatrics 2006;117:923–929.
  30. Tarini B: The current revolution in newborn screening: new technology, old controversies. Arch Pediatr Adolesc Med 2007;161:767–772.
  31. Roussey M, Le Bihannic A, Scotet V, Audrezet MP, Blayau M, Dagorne M, David V, Deneuville E, Giniès JL, Laurans M, Moisan-Petit V, Rault G, Vigneron P, Férec C: Neonatal screening of cystic fibrosis: diagnostic problems with CFTR mild mutations. J Inherit Metab Dis 2007;30:613.
  32. Botkin JR, Clayton EW, Fost NC, Burke W, Murray TH, Baily MA, Wilfond B, Berg A, Ross LF: Newborn screening technology: proceed with caution. Pediatrics 2006;117:1793–1799.
  33. Bailey DB, Skinner D, Warren SF: Newborn screening for developmental disabilities: reframing presumptive benefit. Am J Public Health 2005;95:1889–1893.
  34. Alexander D, van Dyck PC: A vision of the future of newborn screening. Pediatrics 2006;117:S350–S354.
  35. Howell RR: We need expanded newborn screening. Pediatrics 2006;117:1800–1805.
  36. Baily MA, Becker W Jr, Hayes M, Clayton EW, Grosse S: Exploring options for expanded newborn screening. J Law Med Ethics 2005;33(suppl 4):46–48.
  37. Natowicz M: Newborn screening–setting evidence-based policy for protection. N Engl J Med 2005;353:867–870.
  38. Ross LF: Screening for conditions that do not meet the Wilson and Jungner criteria: the case of Duchenne muscular dystrophy. Am J Med Genet A 2006;140:914–922.

    External Resources

  39. Surgeon General’s Family History Initiative. Available at http://www.hhs.gov/familyhistory/, accessed 11/09/09.
  40. Guttmacher AE, Porteous ME, McInerny JD: Educating health-care professionals about genetics and genomics. Nat Rev Genet 2007;8:151–157.
  41. Wilson B, Qureshi N, Little J, Santaguida P, Carroll J, Allanson J, Keshavarz H, Raina P: Clinical utility of cancer family history collection in primary care. Evidence report/technology assessment No. 179 (prepared by the McMaster University Evidence-based Practice Center, under Contract No. 290-02-0020), AHRQ Publication No. 09-E007. Rockville, MD, Agency for Healthcare Research and Quality, 2009.
  42. Manolio TA: Collaborative genome-wide association studies of diverse diseases: programs of the NHGRI’s office of population genomics. Pharmacogenomics 2009;10:235–241.
  43. Hogarth S, Javitt G, Melzer D: The current landscape for direct-to-consumer genetic testing: legal, ethical, and policy issues. Annu Rev Genomics Hum Genet 2008;9:161–182.
  44. Farkas DH, Holland CA: Direct-to-consumer genetic testing: two sides of the coin. J Mol Diagn 2009;11:263–265.
  45. Stefansson K: Quoted in Lauerman J: DeCode Finds Gene Linked to Diabetes. New York Sun, 2006. Available at http://www.nysun.com/business/decode-finds-gene-linked-to-diabetes/25933/, accessed 11/09/09.
  46. Collins FS: Shattuck lecture – Medical and societal consequences of the Human Genome Project. N Engl J Med 1999;341:28–37.
  47. McBride CM: Blazing a trail: a public health research agenda in genomics and chronic disease. Prev Chronic Dis [serial online] 2005;2:A04. Available at http://www.cdc.gov/pcd/issues/2005/apr/05_0008.htm, accessed 11/09/09.
  48. Sanderson SC, O’Neill SC, White DB, Bepler G, Bastian L, Lipkus IM, McBride CM: Responses to online GSTM1 genetic test results among smokers related to patients with lung cancer: a pilot study. Cancer Epidemiol Biomarkers Prev 2009;18:1953–1961.
  49. McBride CM, Alford SH, Reid RJ, Larson EB, Baxevanis AD, Brody LC: Putting science over supposition in the arena of personalized genomics. Nat Genet 2008;40:939–942.
  50. Pijl M, Timmermans DR, Claassen L, Janssens AC, Nijpels G, Dekker JM, Marteau TM, Henneman L: Impact of communicating familial risk of diabetes on illness perceptions and self-reported behavioral outcomes: a randomized controlled trial. Diabetes Care 2009;32:597–599.
  51. Thompson PA: Counterpoint: genetic risk feedback for common disease time to test the waters. Cancer Epidemiol Biomarkers Prev 2007;16:1727–1729.
  52. Merikangas KR, Risch N: Genomic priorities and public health. Science 2003;302:599–601.
  53. Hunter DJ, Khoury MJ, Drazen JM: Letting the genome out of the bottle – will we get our wish? N Engl J Med 2008;358:105–107.
  54. Altshuler D, Daly MJ, Lander ES: Genetic mapping in human disease. Science 2008;322:881–888.
  55. Burke W, Psaty BM: Personalized medicine in the era of genomics. JAMA 2007;298:1682–1684.
  56. Nadler HL, Gerbie AB: Role of amniocentesis in the intrauterine detection of genetic disorders. N Engl J Med 1970;282:596–599.
  57. Cowan RS: Moving up the slippery slope: mandated genetic screening on Cyprus. Am J Med Genet C Semin Med Genet 2009;151C: 95–103.
  58. Najmabadi H, Ghamari A, Sahebjam F, Kariminejad R, Hadavi V, Khatibi T, Samavat A, Mehdipour E, Modell B, Kariminejad MH: Fourteen-year experience of prenatal diagnosis of thalassemia in Iran. Community Genet 2006;9:93–97.
  59. Parens E, Asch A: The disability rights critique of prenatal genetic testing. Reflections and recommendations. Hastings Cent Rep 1999;29:S1–S22.
  60. Offit K, Kohut K, Clagett B, Wadsworth EA, Lafaro KJ, Cummings S, White M, Sagi M, Bernstein D, Davis JG: Cancer genetic testing and assisted reproduction. J Clin Oncol 2006;24:4775–4782.
  61. Bennett B: Symbiotic relationships: saviour siblings, family rights and biomedicine. Aust J Fam Law 2005;19:195–212.

    External Resources

  62. Pagon RA, Daiger SP: Retinitis pigmentosa overview. GeneTests 2005. Available at http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi? book=gene&part=rp-overview, accessed 11/ 09/09.
  63. Zick CD, Mathews CJ, Roberts JS, Cook-Deegan R, Pokorski RJ, Green RC: Genetic testing for Alzheimer’s disease and its impact on insurance purchasing behavior. Health Aff (Millwood) 2005;24:483–490.
  64. Roberts JS, Cupples LA, Relkin NR, Whitehouse PJ, Green RC; REVEAL (Risk Evaluation and Education for Alzheimer’s Disease) Study Group: Genetic risk assessment for adult children of people with Alzheimer’s disease: the Risk Evaluation and Education for Alzheimer’s Disease (REVEAL) study. J Geriatr Psychiatry Neurol 2005;18:250–255.
  65. Relkin NR, Kwon YJ, Tsai J, Gandy S: The National Institute on Aging/Alzheimer’s Association recommendations on the application of apolipoprotein E genotyping to Alzheimer’s disease. Ann N Y Acad Sci 1996;802:149–176.
  66. McConnell LM, Koenig BA, Greely HT, Raffin TA: Genetic testing and Alzheimer disease: recommendations of the Stanford program in genomics, ethics, and society. Genet Test 1999;3:3–12.
  67. Post SG, Whitehouse PJ, Binstock RH, Bird TD, Eckert SK, Farrer LA, Fleck LM, Gaines AD, Juengst ET, Karlinsky H, Miles S, Murray TH, Quaid KA, Relkin NR, Roses AD, St George-Hyslop PH, Sachs GA, Steinbock B, Truschke EF, Zinn AB: The clinical introduction of genetic testing for Alzheimer disease. An ethical perspective. JAMA 1997;277:832–836.
  68. Green RC, Roberts JS, Cupples LA, Relkin NR, Whitehouse PJ, Brown T, Eckert SL, Butson M, Sadovnick AD, Quaid KA, Chen C, Cook-Deegan R, Farrer LA, REVEAL Study Group: Disclosure of APOE genotype for risk of Alzheimer’s disease. N Engl J Med 2009;361:245–254.
  69. Kane RA, Kane RL: Effect of genetic testing for risk of Alzheimer’s disease. N Engl J Med 2009;361:298–299.
  70. Feero WG, Guttmacher AE, Collins FS: The genome gets personal – almost. JAMA 2008;299:1351–1352.
  71. McGuire AL, Burke W: An unwelcome side effect of direct to consumer personal genome testing: raiding the medical commons. JAMA 2008;300:2669–2671.
  72. Teutsch SM, Bradley LA, Palomaki GE, Haddow JE, Piper M, Calonge N, Dotson WD, Douglas MP, Berg AO, EGAPP Working Group: The evaluation of genomic applications in practice and prevention (EGAPP) initiative: methods of the EGAPP working group. Genet Med 2009;11:3–14.
  73. Baars MJ, Henneman L, Ten Kate LP: Deficiency of knowledge of genetics and genetic tests among general practitioners, gynecologists, and pediatricians: a global problem. Genet Med 2005;7:605–610.
  74. Baars MJ, Scherpbier AJ, Schuwirth LW, Henneman L, Beemer FA, Cobben JM, Hennekam RC, Verweij MM, Cornel MC, Ten Kate LP: Deficient knowledge of genetics relevant for daily practice among medical students nearing graduation. Genet Med 2005;7:295–301.
  75. Greb AE, Brennan S, McParlane L, Page R, Bridge PD: Retention of medical genetics knowledge and skills by medical students. Genet Med 2009;11:365–370.
  76. UK Guidelines on Genetic Disorders. Available at http://www.patient.co.uk/showdoc/ 687/#related_guide, accessed 11/09/09.
  77. Salari K: The dawning era of personalized medicine exposes a gap in medical education. PLoS Med 2009;6:e1000138.
  78. Bindman AB: Is there a personal doctor in the house? Ann Intern Med 2009;150:351–352.