HEALTH ECONOMICSHealth Econ. 18: 1233–1236 (2009)Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hec.1553

EDITORIAL

FISH AND CHIPS ALL ROUND? REGULATION OF DNA-BASEDGENETIC DIAGNOSTICS

KATHERINE PAYNE�

Health Methodology Research Group, School of Community Based Medicine, The University of Manchester, Manchester, UK

Healthcare is experiencing considerable advances in technical innovation with the development andintroduction of DNA-based genetic technologies, in general, and diagnostics, in particular (hereaftercalled ‘genetic tests’). The genomic era is already affecting healthcare systems, although currently on arelatively small scale. The UK Genetic Testing Network (UKGTN) currently lists over 400 genetic teststo diagnose or predict the risk of single-gene disorders. Genetic testing is likely to have an insidiouseffect on future healthcare resources in part due to the lack of a regulatory framework supporting thedevelopment of a robust evidence base. The informational requirements for service commissioning ofgenetic tests have not yet been adequately addressed. The current regulatory climate for genetic testsdrives a restricted focus on outcomes of analytical accuracy with stringent quality assurance and qualitycontrol procedures enforced by the laboratories providing such testing. Furthermore, in the absence of atransparent national pricing tariff the acquisition and broader cost impact of such genetic tests are notknown. Currently, service commissioners have an overly simplistic view and focus on test diagnosticaccuracy. To understand the true opportunity cost of a genetic test, it is necessary to describe how thetest affects the referral of patients to care pathways, subsequent services and treatments.

There are many types of genetic tests and many different potential roles including: (1) to inform orpredict disease diagnosis or carrier status for single-gene disorders and, to a lesser extent, for multi-factorial conditions; (2) to help predict disease prognosis, such as in cancer, and (3) to target theselection of medicines (pharmacogenetic tests). Pharmacogenetic tests can be used to predict and targetmedicines to good responders or identify whether an individual has an increased risk of a specificadverse drug reaction from a particular medicine. All diagnostic tests are made up of a platform to run achip and/or a collection of reagents that should ideally have a CE (‘Conformite Europeene’) markprovided by the Medicines Healthcare Regulatory Agency (MHRA). Fewer than 1% of genetic testshave a CE mark (Rob Elles, personal communication, 2008). The majority of genetic tests are in-housedeveloped tests offered by accredited laboratories and only a handful of commercially marketed genetictesting kits exist. An example of a genetic test offered by selected NHS laboratories is HER-2 testing toidentify women with breast cancer who will respond to trastuzumab. There is ambiguity regarding theoptimal HER-2 testing method (Phillips, 2008). In the UK, the HER-2 test comprises a two-stepprocedure, which includes as the second step, using the fluorescence in situ hybridisation (FISH)

*Correspondence to: Health Methodology Research Group, School of Community Based Medicine, The University ofManchester, Jean McFarlane Building, University Place, Oxford Road, Manchester M13 9PL, UK.E-mail: Katherine.payne@manchester.ac.uk

Copyright r 2009 John Wiley & Sons, Ltd.

technique to find a specific DNA sequence. A second example of a type of genetic test is the ‘chip’-baseddiagnostic tests. The Amplichips CYP450 is one example of a marketed test with a CE mark, which isdesigned to predict whether an individual will develop an adverse reaction from specific treatments suchas anti-depressants.

The regulatory framework for genetic tests currently involves two ‘systems’ for a test to be used inpractice. The formal regulatory route is the In Vitro Diagnostic Medical Devices Directive overseen, inthe UK, by the MHRA, which is similar to but is not the same as the approval process for medicines.Genetic tests are graded at the lowest risk category and applications for a CE mark need to be onlysupported by low levels of evidence. This means that a diagnostic manufacturer is required to submitevidence relating to the analytical accuracy of the test, rather than the impact of the diagnostic onsubsequent clinical care pathways, and does not have to be informed by clinical trials. The level ofevidence submitted would not be sufficient for a technology appraisal for the National Institute forHealth and Clinical Excellence (NICE) requiring information on outcomes for individuals correctly andincorrectly diagnosed and the associated healthcare costs (NICE, 2008). Furthermore, the currentdivision between the regulatory processes for diagnostics and medicines poses a practical problem forgenerating clinical and cost-effectiveness evidence for a pharmacogenetic test as each approval processrequires different levels of evidence.

The second system does not require any formal regulatory approval, but uses Gene Dossiers, avoluntary system of control in which evidence about the disease condition to be tested, the test’s clinicalvalidity and utility together with the proposed cost of the test is submitted. Genetic tests can be providedon a national basis upon successful submission of a Gene Dossier and subsequent approval by theGenetics Commissioning Advisory Group (GenCAG) who report to local service commissioners.Genetic tests without a dossier can only be offered on a regional basis. This is the more common routefor a genetic test to reach clinical practice and move from the research laboratory environment directlyinto clinical service. The Dossier process shares a similar remit to NICE making recommendations tocommissioners but differs considerably in the source and type of evidence submitted. The evidencesubmitted by the NHS laboratory who wants to provide the test will include a summary of the literatureand in-house validation studies of test sensitivity and specificity with a budget impact assessment. Todate evidence from trials or economic models have not formed part of the evidence submitted. A tariff-setting exercise found large variability in pricing between laboratories and the process does not work ona national price list of genetic tests (UKGTN, 2005). This lack of a nationally agreed price list hasimplications, for instance, if a genetic test was to be considered by NICE, which will only use nationallyagreed prices in its technology appraisal process.

If genetic tests were no different to diagnostic tests then the framework that calculates whether theexpected value of diagnostic information is justified by the cost for population would be sufficient fordecision making (Phelps and Mushlin, 1988). Genetic tests do not have unique evaluation issues butthere are important and clear differences exist between DNA and non-DNA-based tests and services.Current evaluative frameworks may not be directly applicable to genetic tests. The potential (dis)benefitfrom the test is inextricably linked with that of the service providing the test. Information derived fromthe test result is one source of the benefit, which is largely dependent on test accuracy (sensitivity,specificity, predictive value). However, the benefit may also be dependent on the way in which thatinformation is presented by the geneticist. The ‘patient’ may not just be the individual who offers aDNA sample; it may include other family members, suggesting a need to consider ‘spillover effects’ inthe analysis (Basu and Meltzer, 2005). A further complication is that the time frame for healthimprovements is very often some time in the future and outcomes should possibly include future benefitsto younger family members or unborn generations. Genetic tests results can influence more thanhealthcare decisions and involve life decisions such as marriage partners and reproductive choices(McAllister et al., 2007). As such, genetic tests may fit more comfortably within the remit of publichealth appraisals that have seemingly similar issues such as: incorporating a wide study perspective;

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lengthy time horizon; difficulty in focussing on QALY gains; potential need to consider supplementarycost-consequences analysis and limited availability of weak research evidence (Chalkidou et al., 2008).Claxton et al. (2007) provide a normative description of the evaluation methods appropriate for publichealth programmes with multiple effects that cross public sectors, such as education and health, andconclude that existing decision rules do not provide a simple way of integrating the impacts of costs andbenefits from different sectors. Evaluations of public health interventions therefore require multipleperspectives that take account of the benefits and costs falling on each sector. This issue resonates partlywith genetic testing that affects both healthcare and life decisions and, therefore, potentially different,but as yet undefined, public sectors. Furthermore, because single-gene genetic tests are generally for rareconditions, they form a global market that cross country boundaries via international networks ofexperts requesting tests from other countries. For example, The European Directory of DNADiagnostic Laboratories (EDDNAL) exists for use by clinicians to identify and use genetic diagnosticservices offered by laboratories throughout 14 EU countries. In the absence of regulatory requirementsthere are no international boundaries for the genetic test market and they provide a good example of aglobal healthcare market beyond traditional national control (Smith, 2008). Without adequateregulation in place, all these issues further complicate how a sufficient evidence base can be generatedand do not define whose responsibility it is to generate robust evidence of clinical and economic value.

The regulatory framework for a healthcare technology has the potential to encourage the productionof a robust evidence base necessary for decision making and make it explicit where the burden of prooflies for producing such evidence. For example, the current regulatory and advisory framework formedicines has stimulated pharmaceutical manufacturers to produce evidence ‘sufficient’ to meet therequirements of decision-making bodies, such as NICE, by addressing the parameter uncertainty andprecision-bias trade-off (Cooper et al., 2007). The proposed change to the price regulation system formedicines to consider value-based pricing will be a further potential stimulus for robust evidence ofadded value in the context of a nationally agreed pricing mechanism (Claxton, 2007).

Current regulatory requirements could be viewed as satisfactory for the level of single-gene genetictests developed in-house, which means it is reasonably easy to keep control of funding decisions usingthe Gene Dossier system. However, for the majority of DNA-based genetic diagnostics, the point ofentry into a healthcare system is not controlled by a formal regulatory hurdle. Instead the technologytends to emerge into practice after initially being offered on a research basis. The lack of formal point ofentry of the diagnostic into the healthcare system makes it difficult to decide upon the ideal timing ofeconomic assessments, thus making an iterative approach to economic evaluations, as suggested bySculpher et al. (1997), challenging.

New, faster, high-throughput technologies are continually being developed in research laboratoriesand will soon emerge into clinical practice. The focus may then broaden beyond single-gene disordersand extend to more complex conditions, such as learning disabilities, which will have resourceimplications for mainstream healthcare and social support services. Historical approaches to regulationfor genetic tests must change to stimulate the production of a clinical evidence base showing patientvalue that can populate robust economic models and inform service commissioning. Given the globalmarket for genetic tests, this is no easy matter and incremental changes will be necessary. Clearly, thelevel of regulation needs to be commensurate with the financial and clinical impact of the technology.A simple first step would be for the NHS and test producers to work towards establishing andmaintaining a national price list for genetic tests. It is necessary for society to be explicit about where itbelieves the burden of proof lies for genetic tests. In the case of medicines, the burden of proof of safety,quality and efficacy lies with the manufacturer who will profit from sales. For the majority of genetictests, the burden of proof falls to the healthcare system and service commissioners using gene dossierinformation supplied by NHS laboratories to guide the reimbursement of genetic tests for single genedisorders. No systems are currently in place to evaluate funding decisions for pharmacogenetic tests.Together with explicit pricing structures, there is a need to re-define regulatory systems to stimulate the

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production of a sufficient evidence base to inform decision making and be clear who should beresponsible for generating such evidence. Health economics as a discipline is already being rallied todesign and conduct robust cost-effectiveness analyses of genetic tests (see for example, Gurwitz et al.,2009). Health economists could usefully take the lead and establish an open dialogue with regulatoryand advisory agencies and have a key strategic role defining the agenda for the type and quality ofevidence necessary and sufficient to conduct robust economic evaluations of genetic tests.

ACKNOWLEDGEMENTS

I would like to thank Rob Elles and Simon Patton, The National Genetics Reference Laboratory,Manchester, Nick Telford, Consultant Clinical Cytogeneticist, The Christie NHS Foundation Trust,Manchester and Helen Middleton-Price, Director of Nowgen – A Centre for Genetics in Healthcare, forthe many discussions we had regarding genetic technologies in the NHS that informed this editorial.Many thanks also go to Matthew Sutton, Linda Davies and Fatiha Shabaruddin for their helpfulcomments on earlier drafts of this editorial. Finally, I would like to thank the reviewer of thismanuscript for their comments. Any remaining errors or omissions are my own. This work is fundedthrough an RCUK Academic Fellowship in Health Economics held by Katherine Payne to focus on theeconomics of genetic technologies.

REFERENCES

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DOI: 10.1002/hec