Reflections on the Cost of Low-Cost Whole Genome Sequencing: Framing the Health Policy Debate

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Reflections on the Cost of Low-Cost Whole Genome Sequencing: Framing the Health Policy Debate
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  Perspective Reflections on the Cost of ‘‘Low-Cost’’ Whole GenomeSequencing: Framing the Health Policy Debate Timothy Caulfield 1 * , Jim Evans 2 , Amy McGuire 3 , Christopher McCabe 4 , Tania Bubela 5 ,Robert Cook-Deegan 6 , Jennifer Fishman 7 , Stuart Hogarth 8 , Fiona A. Miller 9 , Vardit Ravitsky 10 ,Barbara Biesecker 11 , Pascal Borry 12 , Mildred K. Cho 13 , June C. Carroll 14 , Holly Etchegary 15 , Yann Joly 16 ,Kazuto Kato 17,18 , Sandra Soo-Jin Lee 13,19 , Karen Rothenberg 20 , Pamela Sankar 21 , Michael J. Szego 22,23 ,Pilar Ossorio 24,25 , Daryl Pullman 15 , Francois Rousseau 26,27 , Wendy J. Ungar 9,28 , Brenda Wilson 29 1 Health Law Institute, University of Alberta, Edmonton, Alberta, Canada,  2 Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina, United States of America,  3 Center for Medical Ethics and Health Policy at Baylor College of Medicine, Houston, Texas, United States of America,  4 Department of Emergency Medicine,University of Alberta, Edmonton, Alberta, Canada,  5 School of Public Health, University of Alberta, Edmonton, Alberta, Canada,  6 Institute for Genome Sciences & Policy andSanford School of Public Policy, Duke University, Durham, North Carolina, United States of America,  7 Biomedical Ethics Unit, McGill University, Montreal, Quebec, Canada, 8 Department of Social Science, Health & Medicine, King’s College London, London, England, 9 Institute of Health Policy, Management and Evaluation, University of Toronto,Toronto, Ontario, Canada,  10 Bioethics Programs at the Faculty of Medicine, Universite´ de Montre´al, Montreal, Quebec, Canada,  11 Genetic Counseling Program (JohnsHopkins University [JHU];National Human Genome Research Institute [NHGRI], Social and Behavioral Research Branch [SBRB];NHGRI/National Institutes of Health [NIH]),Bethesda, Maryland, United States of America,  12 Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium,  13 Stanford Center for Biomedical Ethics,Stanford University, Stanford, California, United States of America,  14 Department of Family & Community Medicine, University of Toronto; Granovsky Gluskin FamilyMedicine Centre, Mount Sinai Hospital, Toronto, Ontario, Canada,  15 Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador,Canada,  16 Department of Human Genetics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada,  17 Department of Biomedical Ethics and Public Policy,Graduate School of Medicine, Osaka University, Suita, Osaka, Japan,  18 Institute for Integrated Cell-Material Sciences, Kyoto University, Kyoto, Japan,  19 Program in Science,Technology, and Society, Stanford University, Stanford, California, United States of America,  20 National Human Genome Research Institute, National Institutes of Health,Bethesda, Maryland, United States of America,  21 Department of Medical Ethics and Health Policy, Perelman School of Medicine at the University of Pennsylvania,Philadelphia,Pennsylvania,UnitedStatesofAmerica, 22 CentreforClinicalEthics(ajointventurebetweenProvidenceHealthcare,St.Joseph’sHealthCentre,andSt.Michael’sHospital), University of Toronto McLaughlin Centre and Joint Centre for Bioethics, Toronto, Ontario, Canada,  23 The Centre for Applied Genomics, Hospital for Sick Children,Toronto, Ontario, Canada,  24 University of Wisconsin Law School, Madison, Wisconsin, United States of America,  25 Morgridge Institute for Research, Madison, Wisconsin,United States of America,  26 CHU de Que´bec Research Center, Quebec City, Quebec, Canada,  27 Faculte´ de me´dicine, Universite´ Laval, Quebec City, Quebec, Canada, 28 ProgramofChildHealth EvaluativeSciences,HospitalforSickChildren, Toronto,Ontario,Canada, 29 DepartmentofEpidemiologyandCommunityMedicine,Universityof Ottawa, Ottawa, Ontario, Canada Summary:  The cost of wholegenome sequencing is droppingrapidly. There has been a greatdeal of enthusiasm about thepotential for this technologicaladvance to transform clinical care.Given the interest and significantinvestment in genomics, this seemsan ideal time to consider what theevidence tells us about potentialbenefits and harms, particularly inthe context of health care policy.The scale and pace of adoption of this powerful new technologyshould be driven by clinical need,clinical evidence, and a commit-ment to put patients at the centreof health care policy. Introduction The upfront cost of sequencing anindividual’s entire genome is decreasing rapidly. As a result, whole genome se-quencing (WGS) is becoming feasiblefor broad use in both research andclinical care. (In this article, by WGSwe mean both WGS and other ap-proaches, such as whole exome se-quencing [WES] that, while not ascomprehensive as WGS, neverthelessanalyze a broad swath of the humangenome.) Not surprisingly, this tremen-dous technological advance has resultedin a great deal of enthusiastic specula-tion about public uptake and clinicalapplication. There is significant mo-mentum around the idea of using WGS as a clinical tool in the nearfuture [1]. Indeed, some institutions arealready seeking to integrate WGS into The Perspective section provides experts with aforum to comment on topical or controversial issuesof broad interest. Citation:  Caulfield T, Evans J, McGuire A, McCabe C, Bubela T, et al. (2013) Reflections on the Cost of ‘‘Low-Cost’’ Whole Genome Sequencing: Framing the Health Policy Debate. PLoS Biol 11(11): e1001699. doi:10.1371/ journal.pbio.1001699 Published  November 5, 2013 Copyright:    2013 Caulfield et al. This is an open-access article distributed under the terms of the CreativeCommons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,provided the srcinal author and source are credited. Funding:  All of the funding agencies provided support for the workshop, including the cost of flights andaccommodations. Primary funding support was provided by: CIHR Institute of Genetics (http://www.cihr-irsc.gc.ca/e/193.html), Genome Canada (http://www.genomecanada.ca), X PRIZE Foundation, ACOA AtlanticInnovation Fund (http://www.acoa-apeca.gc.ca/eng/ImLookingFor/ProgramInformation/AtlanticInnovationFund/Pages/AtlanticInnovationFund.aspx), and the University of Toronto/McLaughlinCentre. Additional funding by the Grant-in-Aid for Scientific Research from the Ministry of Education, Culture,Sports, Science and Technology (MEXT) (221S0002), Japan (K.K.), the Intramural Research Program of theNational Human Genome Research Institute, National Institutes of Health, NIH (BB), and the Marion EwingKauffman Foundation, National Human Genome Research Institute, NIH (P50 HG003391) (RCD). The fundershad no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The views expressed in this paper do not reflect the views of funders. Competing Interests:  The authors have declared that no competing interests exist.* E-mail: caulfield@ualberta.ca PLOS Biology | www.plosbiology.org 1 November 2013 | Volume 11 | Issue 11 | e1001699  their clinical programs [2]. The USpress has even suggested that the drivefor some institutions to develop thenecessary technological capacity is akinto a genomics ‘‘arms race’’ [3,4].Given this interest and the concomitantinvestment in both genomic and clinicaltranslational research, we should considerhow best to frame health policy discussionsabout the utilization of these emerging sequencing technologies. For example, formany genomic funding agencies and someresearchers, adopting WGS into routineclinical care is an explicit aspiration.Indeed, WGS has been called a revolu-tionizing diagnostic tool [5,6] that willhave a profound impact on the practice of medicine [7]. While inexpensive andefficient, WGS is an impressive technolog-ical achievement, with the potential toserve as the foundation for new approach-es to screening, diagnosis, risk prediction,and prognostic platforms in clinical prac-tice; the actual impact it will have onhealth and health care systems is far fromcertain.In this article, we highlight policy issuesthat warrant thought regarding the appli-cations/uses of WGS in clinical care andwithin health systems. As with any newtechnology, decisions about clinical useshould, as much as possible, be based onthe best available evidence and on consid-eration of potential benefits and harms [8].History tells us that without carefulconsideration of the social forces thatinfluence technological implementationand their public and social costs, a lessthan ideal utilization policy can emerge[9,10]. As some seek to introduce WGSinto clinical use—including what has beencalled a ‘‘genome-based assault on cancer’’[4]—a detailed reflection on its clinicalapplications seems warranted. Indeed, asenthusiasm grows and speculation on arange of applications intensifies, the timing for this kind of policy analysis seems ideal.Here we seek to highlight the mostpromising areas for the application of WGS, whilst considering areas whereclaims of its clinical and social utility maybe overstated. We also consider, from ahealth policy perspective, how best toguide discussions about the implementa-tion of this emerging technology. Public and ScientificEnthusiasm for WGS Success stories of WGS abound in thepopular press [11,12]. Thousands of individuals currently have their genomessequenced each year in the clinical,research and, to a lesser extent, direct-to-consumer context. And, in certain clinicalsituations, WGS helps to provide a moredefinitive diagnosis (e.g., in unusual andrare conditions that seem likely to have agenetic cause). For rare inherited condi-tions and some cancers, WGS has even ledto improved medical management of patients [13]. Given these early successes,it is no surprise that there have been manyenthusiastic predictions about the possibleclinical value of WGS—particularly in thecontext of personalized medicine. Oneindustry commentator, for example, hasclaimed that the rise in cancer rates ‘‘canbe fixed’’ with genome sequencing andpersonalized medicine [14]. What impactmight this type of discourse have on healthpolicy?Scientific and public enthusiasm for anemerging area is a common feature of theinnovation process [15]. This enthusiasmand the associated public representationshelp to build institutional momentum andattract funding from both the public andprivate sectors [16]—a process that isparticularly important for big, complex,and expensive areas of scientific inquiry,like genomics [17]. But research tells usthat this kind of enthusiasm can, for betteror worse, also impact how an area isrepresented, including framing the specu-lation about clinical utility and healthbenefit.There is a growing literature on how arange of social forces and publicationtrends can lead to exaggerated claims of future clinical benefit [18–21]. It has, forexample, been noted that positive ‘‘spin’’exists in peer-reviewed articles [22], insti-tutional press releases [23], and thepopular press. Growing commercializationand translation pressures, the need toattract research support in a highlycompetitive funding environment, andthe simple momentum caused by thecommitment of a large number of re-searchers and resources [17] (also knownas a ‘‘scientific bandwagon’’) [24] candistort public communication on this issueand thus public expectations [25]. Thesedistortions, together with enthusiasm fromfunding entities, media coverage, and thepositioning of WGS and personalizedmedicine as a tool for regional economicgrowth [26], may influence our thinking on how best to deploy WGS technologieswithin health care systems.Health policy deliberations need to beaware of these forces and their impact onthe representations and perceptions of the value and cost of high profile technologylike WGS. Spectacular technological ad- vances have led to the dramatic decreasein cost of sequencing [27], and thisdecrease is often treated as sufficient justification for its clinical application. AUS $ 1,000 price tag does bring WGS datawithin reach for many. However, WGSbrings with it more costs—both monetaryand beyond—than the charges for se-quencing. Upstream costs include creating and validating the institutional and tech-nological infrastructure for both the pro-duction and storage of sequence data thatfollow clinical laboratory standards and forthe interpretation and confirmation of WGS results. The latter can frequentlybe laborious, expensive, and highly time-consuming. This has led many to jokeabout of the US $ 1,000 genome and theUS $ 1 million interpretation [28].Moreover, the downstream costs of adiagnostic intervention can far outweighthe upfront costs of the initial test [29].This is especially true for tests thatgenerate a large amount of information,and potentially large amounts of ambigu-ous information as well as false positivesand incidental findings. The downstreamresource and health consequences of ambiguous results are substantial and caninclude clinical follow-up, additional tests,and also unnecessary surveillance andinterventions—as is seen with other tech-nologies, such as has happened, forexample, with the introduction of prostatespecific antigen (PSA) testing [9]. Inclinical practice, there is rarely such athing as a ‘‘low cost’’ test; the ‘‘low costhigh value’’ WGS may be rarer still. Clinical Utilization of WGS Lower cost sequencing has fostered theidea that there will be a high degree of both consumer and clinical utilization of WGS [3,30], as captured by the suggestionthat soon ‘‘everyone will be sequenced’’[31]. There is little doubt that theapplication of WGS in the research setting is shedding new light on the molecularmechanisms that influence health, disease,and drug response. Also, there are signif-icant social forces, particularly in the USand UK where this field is often cast as apotential engine of economic growth,driving its clinical implementation [4].Nevertheless, we need to bear in mindthat its uses in research do not necessarilyimply equivalent utility in the clinic. Utilityin a clinical setting depends on many— and very different—factors, and must takeinto account not only such performancecharacteristics as sensitivity, specificity,and positive and negative predictive value,but also demonstration of beneficial im-pact of using the test on patients’ health, oron health services delivery. Failure to do so PLOS Biology | www.plosbiology.org 2 November 2013 | Volume 11 | Issue 11 | e1001699  can trigger overt harm to patients inaddition to excessive cost to the healthcare system [9].It is clear that genomic sequencing willprove to be a useful diagnostic approach inspecific situations [32]. For example, it willallow the identification of a causativemutation in patients with geneticallyheterogeneous disorders (in which muta-tions in many different genes can result ina similar phenotype), in children withcomplex unexplained co-morbidities, andin individuals with strong family historiesof an enigmatic disorder. Although morework needs to be done to demonstrateclinical utility, promising opportunitiesexist in the realm of cancer treatment.For example, genome-scale sequencing of tumors may provide important informa-tion regarding the mutations that drive apatient’s malignancy and so guide theirtreatment [33], with one of the potentialbeneficial by-products of WGS being drug dosing and pharmacogenomics applica-tions.In contrast to these successes, there arefew data and little compelling support tosuggest that WGS of individuals withcommon diseases will result in clinicallyactionable information, or that whateverbenefits are accrued might outweigh theburdens of, for example, false positiveresults or the follow-up investigation of ambiguous results. Common diseasesthat, by definition, affect the greatestnumber of individuals, have a relativelylow genetic component, placing aninherent ceiling on the usefulness of genomic information to meaningfullyinform individuals regarding these disor-ders [34]. This in itself supports theadoption of a cautious, if not outrightskeptical, perspective regarding the im-pact of WGS on the clinical managementof common diseases and thus moremodest expectations of a revolution inmedical care, at least in the short term. As mentioned above, there is a high risk of generating a lot of ambiguous informa-tion when a tremendously broad test suchas WGS is used clinically. It is a well-supported tenet of medical practice thatoverly broad testing can cause consider-able harm owing to the inevitable trade-off between sensitivity and specificity [35]requiring such testing to be carefully used.This caution regarding the use of non-specific testing has particular resonancewhen considering the application of WGSin healthy members of the population. Inthe public health setting, the probabilitythat any specific variant is meaningful islow due to the rarity of disorders with astrong genetic cause in the general popu-lation.While the balance of the clinical benefitsand harms of WGS in otherwise healthypeople may not currently support itsadoption as a diagnostic tool, somecommunities outside of health care arealready utilizing sequencing technology(via the private sector) to provide answersto questions that are not credibly avail-able in any other manner, perhaps mostnotably in genealogy. The meaningful-ness of WGS to these communities isdifficult to refute. Advocates of WGS,and personalized medicine more gener-ally, often promote the idea that moredata is always better and that ‘‘knowl-edge is power’’ [36], and that genomicswill inevitably empower patients andpromote individual control over health(Box 1). The push to embrace WGS isinextricably linked to this vision of empowerment, particularly in the con-text of genetic risk information [37].However, the provision of such informa-tion will create clinical challenges, in-cluding straining the physician/patientrelationship by shifting more responsibil-ity and expectations to the patient[38,39]. More fundamentally, there islittle evidence to support the basicpremise implied by the empowermentrhetoric—namely that individuals willuse genomic risk information to adopt ahealthier lifestyle and, thus, reduce theirrisk for chronic diseases. In fact, existing research tells us that individuals do notalter their behaviour on the basis of genetic risk information [40–43]. Indeed,promoting meaningful behaviour changeis tremendously difficult, particularly ona population level [44]. Hence, the valueof WGS in this space—that is, in thecontext of empowerment—is conditionalupon the development of effective be-haviour change interventions.In the context of utility it is also worthreflecting on the predictions of highuptake among the general population.Previous experience with high-through-put DNA technologies suggests the needfor caution and an expectation that theutility of platform technologies such asWGS will be highly variable. Microar-rays have played an important role in thediagnosis of developmental disorders, buttheir use in pharmacogenetics has thusfar been clinically disappointing, in partdue to an absence of evidence that theyproduce convincing outcomes. Array-based susceptibility testing for commondiseases has also failed to garner clinicaladoption, and where it has been com-mercialized as direct-to-consumer servic-es there has been only modest uptake[45]. Despite claims that inexpensive Box 1. The Rhetoric of Empowerment The ideas of empowerment and personal choice are significant aspects of thepopular culture messaging around WGS, particularly in the context of personalized medicine. Below are a few examples of how this message is framedin various domains.‘‘The success of personalized medicine will come about only when we each takeresponsibility for our health. Health care providers can help, but they cannot driveyour bus… [there are] things you can do now to take full advantage of thepotential for personal empowerment. If you follow these recommendations, youwill truly be on the leading edge of this new revolution’’ [48].‘‘WGS is not a panacea for all that ails humankind, but a powerful new tool thatcan catalyze our understanding of the genome and thereby empower patients’’[49].‘‘Advances in genomic and molecular medicine hold the potential to radicallytransform human health by enabling much more precise prediction, prevention,and treatment of disease on an individual level… The Center’s mission is toempower patients to understand their unique health needs…’’ [50].‘‘It [personalized medicine] is proactive and participatory, engaging patients inlifestyle choices and active health maintenance to compensate for geneticsusceptibilities’’ [51].‘‘There will be a greater emphasis on the physician-patient relationship as weteam together to develop more accurate and personalized care plans. Ourultimate goal is to empower our patients and our community towards greaterhealth’’ [52]. PLOS Biology | www.plosbiology.org 3 November 2013 | Volume 11 | Issue 11 | e1001699  WGS will lead to widespread use on apopulation level, there is little evidence,at this stage, to suggest that it will bewidely adopted [46]. Moving Forward WGS holds undeniable promise as adiagnostic tool in certain clinical situa-tions, and might also contribute to im-proving public health if used judiciously onan evidence-base basis [47]. However, itspromise, coupled with the cautions notedabove, argue for careful consideration aswe seek to craft policy regarding itstransition from research to clinical prac-tice.Characterizing the benefits and costs of specific applications of WGS will need totake full account of the upfront investmentand downstream clinical practice implica-tions. It will require the comparison of WGS-augmented care with current clini-cal practice and with care pathways thatutilize alternative testing technologies.Remembering that inefficient use of limited resources reduces the scale andquality of health care available for others,health systems will need to assess carefullythe benefits of WGS that they wish to payfor and the quality of evidence theyrequire to accept the benefits as demon-strated. Given the low unit cost of WGS,the risk of moving quickly from researchand clinical practice may be substantial,and health systems will need to considerhow to protect themselves from the costsof over-testing and the potential burden of false positives, in the absence of clear valuecriteria.Clarifying the evidence hurdles facing WGS also will benefit the research com-munity. By signaling clearly the type of evidence required to support a decision toprovide funding to cover the costs of testing and related services, health systemswill enable researchers and investors toprioritize alternative research investmentopportunities to focus on those that havethe greatest value. Conclusion There are, of course, many otherissues that need to be considered asWGS becomes more common, including concerns about genetic discrimination,issues of consent (e.g., to what degreeshould or could biological relatives beengaged in the consent process), and thedirect-to-consumer provision of WGS.In addition, there are likely to be arange of translation issues, such asuncertainty about the role and impactof intellectual property (Box 2). Also,the diversity of health insurance systemsand health economic policies in variouscountries will undoubtedly affect theway new technology is incorporatedinto clinical practices. But while these,and other, issues require further reflec-tion, we already know enough toprovide advice for the framing of healthpolicy.Rapid, lower-cost WGS is a promising research tool with unproven clinicalutility, except in a small set of veryspecific situations. The journey frombench to bedside is one we should travelwith care. Caution is warranted becausewe must reconcile diverse tensions—thecommercial appetite for market growth versus the need for prudent health careexpenditure, the research community’senthusiasm for genomic science versusprofessional, and public skepticism aboutpersonalized medicine. Due diligenceshould attend to the many competing demands on health care expenditure andbiomedical R&D, to the ambiguouseffects of new technologies, and to ourwell-justified ambivalence about the util-ity of an over-abundance of clinical datain the absence of evidence to establishactual clinical value. The scale and paceof adoption of this powerful new tech-nology should be driven by clinical need,clinical evidence, and a commitment toput patients at the centre of health carepolicy. Acknowledgments This paper is the result of an international andinterdisciplinary workshop entitled ‘‘Exploring the unique social/ethical and health systemschallenges of low cost whole genome sequenc-ing’’ (Montreal, April 19–20, 2013). We wouldlike to thank all the participants for theirthoughtful input and Stephanie Robertson(CIHR), Grant Campany (X Prize), andKarine Morin (Genome Canada) for theirassistance in leading the organization of theevent and all of the funding agencies for theirgenerous support (see Financial Disclosure).We would also like to thank Amir Reshef andRobyn Hyde-Lay (Health Law Institute,University of Alberta) for additional editing and research support. Box 2. WGS and the Impact of Intellectual Property While intellectual property (IP) complexities may arise that concern WGS, theyare unlikely, for a number of reasons, to come from gene-based patent claims[53,54]. The policy rationale for exclusive rights in DNA-based diagnostics hashistorically been weak [55,56]. And the recent decision by the Supreme Court of the United States, which declared that a naturally occurring DNA segment is aproduct of nature and therefore not patentable, will weaken patent relatedhurdles to WGS [57].However, other forms of IP present challenges, such as data-hoarding practices inboth academia and industry. Access to genomic data held in the privatedatabases of both sectors is needed to advance science and to interpretdiagnostic tests. Myriad Genetics’ proprietary database, for example, is based on amillion tests performed when Myriad’s patent rights were presumed valid [58].Lack of access to this data prevents the external validation of clinicalinterpretation, verification testing, and clinical research on BRCA gene mutations.Inaccessible data will also limit the comprehensiveness of core genomicdatabases, impoverishing the public domain. In response, innovative modelsare emerging at, for example, public research institutions to re-create publicdomain data resources where external validation is possible [59].Translating new data into useful clinical information will require data-sharing,interoperability, and database infrastructure (and stable funding to ensurereliability, access, and curation). Interoperability includes legal regimes thataccommodate differences in privacy laws and informed consent to enable the useof stored datasets. 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