The clinical benefit of a new genomic instrument, the 70-gene signature\ud
for breast cancer patients, is being evaluated in a randomised clinical\ud
trial. The early, controlled implementation process is supported by a\ud
Constructive Technology Assessment to help decision-making in an\ud
uncertain time of developmen

Harten, W.H. van

Joore, M.A.

Retèl, Valesca P.

Rutgers, E.J.Th.

English

The clinical benefit of a new genomic instrument, the 70-gene signature for breast cancer patients, is being evaluated in a randomised clinical trial. The early, controlled implementation process is supported by a Constructive Technology Assessment to help decision-making in an uncertain time of developmen

van Harten, W.H.

NARCIS 

Establishing cost-effectiveness of genetic targeting of cancer therapies

University of Twente Research Information

52 • Volume 14 • 2008/6 w w w.ejhp.euUpdateThe clinical benefit of a new genomic instrument, the 70-gene signaturefor breast cancer patients, is being evaluated in a randomised clinicaltrial. The early, controlled implementation process is supported by aConstructive Technology Assessment to help decision-making in anuncertain time of development. Establishing cost-effectiveness of genetictargeting of cancer therapiesValesca PRetèlMScProfessorEJTh RutgersMD MA JoorePhDProfessor WHvan HartenMDment [2]. In 2002, researchers at theNetherlands Cancer Institute (NKI,Amsterdam, the Netherlands) identified a70-gene prognosis signature (Mamma-PrintTM), using microarray analysis forlymph node-negative breast cancer patients[3]. Using the 70-gene signature, the selec-tion of patients that will benefit most fromadjuvant systemic treatment could be moreaccurate. The signature has been validatedin three independent retrospective patientseries [4-6]. A prospective feasibility study,the MicroarRAy PrognoSTics in BreastCanER (RASTER)-study was started in2004 [7]. Coverage decisions regarding new tech-nologies often have to be made at a timewhen the data on the most relevant vari-ables and adequate comparisons are notyet available from high-quality studies.Especially when the promising new tech-nology is in its early development phaseand certain stakeholders find reason tospeed up implementation in clinical prac-tice, health policy challenges arise. Health Technology Assessment (HTA) iswidely adopted to help manage the intro-duction and appropriate use of new tech-nologies [8]. However, a HTA generallystarts after the technology is stabilisedand proved to be valid in clinical trials.During this time many changes in avail-able treatments can occur, which resultsin a HTA subsequently answering, atleast partly, outdated questions [9].Genomic knowledge leads to the intro-duction of new and increasingly person-alised diagnostics and treatments, whichlead to even more complex evaluationdesigns when following common andaccepted assessment practices. Thus, itTreatment for patients withcancer has shifted fromadministering broadly toxicdrugs towards fine-tuningof therapies that are target-ed to the personal characteristics of spe-cific tumours. An example of this develop-ment is the possibility to base the decisionof adjuvant systemic therapy for breast can-cer on the results of a genomic prognosticprofile. The majority of early stage breastcancer patients, particular with lymph node-negative disease (60-70%), have a fairlygood 10-year overall survival with locore-gional treatment alone, with only 30-40%developing distant metastasis [1].Nevertheless, according to current guide-lines, most lymph node negative breast can-cer patients are offered chemotherapy, caus-ing an important percentage of over-treat-would take at least 8-10 years to bringthe 70-gene signature into clinical prac-tice, via the usual path of prospective trials.For these reasons, we chose to carry outa controlled introduction of the 70-gene signature, supported with a com-prehensive technology assessment,which takes technology dynamics intoaccount, and decided to perform aConstructive Technology Assessment(CTA). CTA is based on the idea thatduring the course of technology devel-opment, choices are constantly beingmade about the form, the function, andthe use of that technology [10]. Thisassessment method is a possible answerto the (economic) evaluation challengesthat new genomic technologies pose. MINDACT-trialAfter the results of the controlled intro-duction trial were known [7], in theNetherlands a discussion was startedwhether Coverage with EvidenceDevelopment (CED) would be appropri-ate. CED represents a specific approach tocoverage for promising technologies forwhich the evidence is uncertain yet [8].Parallel additional prospective evidenceon the validity of the prognostic use wasneeded for which the MINDACT-trialMicroarray In Node-negative Diseasemay Avoid ChemoTherapy) was organ-ised. The MINDACT-trial evaluateswhether use of the 70-gene signature isassociated with clinical benefit. The ran-domised controlled design allows adefined group of patients (age 18-70, nodenegative, operable breast cancer) to havetheir treatment determined on the basis ofeither the 70-gene signature or standardpractice guidelines. Patients with discor-dant risk profiles will be randomised toFor personal use only. Not to be reproduced without permission of the publisher (copyright@ppme.eu).• Volume 14 • 2008/6 w w w.ejhp.eu 53EJHP is the Official Journal of the European Association of Hospital Pharmacists (EAHP)Pharmacoeconomicschemotherapy treatment according toeither the clinicopathological criteria(using the Adjuvant! Online software[11]) or according to the 70-gene signa-ture [12]. The trial plans to prospectivelyrecruit 6,000 patients. A follow up of atleast ten years will be required before theresults are available [13]. At this time, thetrial is currently running in eightEuropean countries. Constructive TechnologyAssessmentThe CTA is related to a HealthTechnology Assessment (HTA), whichpredominantly implies a cost-effective-ness analysis (CEA) or economic evalua-tion. CTA also takes technology dynamicsinto account and has developed from justassessing the impact of a new technologyto the analysis of design, development,implementation and interaction of thatnew technology with its environment.Only a few publications are availabledescribing the application of CTA inhealth care [9, 14, 15]. The aspects studiedin this CTA on the 70-gene signature sofar were: patient-related aspects (under-standing of the 70-gene signature and psy-chological impact), organisational effi-ciency (logistics and team functioning)and diffusion scenarios [15]. Partiallybased on these data, a dynamic economicevaluation will be conducted.ScenariosScenario drafting can be used as a tool inforecasting of new, still dynamic tech-nologies and is commonly applied inindustry to anticipate future develop-ment and diffusion of their products.Scenarios can be used to monitor theimplementation process through the var-ious diffusion phases and can supportand identify the need for evaluation oreven interfere through formal decisionmaking. In the case of the 70-gene sig-nature, the scenarios were written usingthe timeline of diffusion phases asdescribed by Rogers’ theory, 2003 [16],see Figure 1. These phases reflect thedegree of spreading throughout the(medical) society. In the innovationphase, the prognosis signature techniqueis developed and the first organisationsadopt (introduce) the technology in theirdaily practice. The first scenario waswritten before the prognosis signaturewas introduced in the Netherlands (mid-2004). The early adoption phasedescribes the implementation in 10-15hospitals. The second, revised scenariowas drafted based on the first experi-ences in the feasibility study (RASTER)in the Netherlands (mid-2005). Theearly majority phase describes theimplementation in a gradually increasingnumber of hospitals and is ongoing. Themost recent scenario written at thebeginning of the MINDACT trial (mid-2008), incorporating ten alternatives,was first checked by genomic expertsand breast cancer specialists, and vali-dated in a recent workshop among 50European breast cancer experts.Dynamic Economic EvaluationThe scenarios drafted on the subsequentphases of diffusion describe possible“future worlds” of the use of the 70-genesignature. Probabilistic decision model-ling will be used to estimate the cost-effectiveness of the 70-gene signaturein these worlds, which may alter astime progresses and more informationbecomes available. The various alterna-tives, barriers or facilitators that influ-ence the diffusion of the 70-gene signa-ture will be incorporated into the modelas stochastic parameters. Parameterswill be updated as soon as new infor-mation becomes available. At eachmoment in time, the decision to adoptor reject the new technology based onexisting knowledge, and the decisionwhether more evidence is required can beinformed by the results of the model [17].Cost-effectiveness Acceptability Curves(CEACs) will reflect the degree of deci-sion uncertainty and Value of InformationAnalyses (VOI) implies whether addition-al evidence to further inform the decisionis worth gathering, and what kind of infor-mation is of the greatest value [18]. VOI isthe amount a decision maker would bewilling to pay for information prior tomaking a decision. ConclusionsEstablishing the cost-effectiveness ofgenetic targeting of cancer therapies isincreasingly desirable in an early stagewhen “traditional” prospective ran-domised controlled data are not withinreach. In the MINDACT-trial that wouldtake another 8-10 years and future tech-Figure 1: Adoption curve of Rogers’, applied to the case of the 70-gene signature Innovators Early Adopters Early Majority Late Majority LaggardsThe prognosis-signature techniqueis developed and thefirst organizationsadopt (introduce)the technology intheir daily practice.The early adoptionphase describes theimplementation apriori in 10-15 hospitals.The implementationin other participat-ing hospitals, relying on opinionleaders and wellestablished logistics.The late majority isconservative andwaits until there isno further debate onthe validity and thelogistics are furtherimproved.The laggards arevery hard to convince.Start RASTER studyStart MINDACT trialScenario 2004= forecast 2006= decision contextScenario 2006= forecast 2008= decision contextScenario 2008= forecast 2018= decision context54 • Volume 14 • 2008/6 w w w.ejhp.euUpdateThe National Institute for Health and Clinical Excellence (NICE), issues mandatory guidance on the useof health technologies within the UK National Health Service. This paper reviews a study involving amodel developed to identify which factors influence NICE’s technology appraisal decisions. What makes NICE tick?Isaac AO Odeyemi, MBA, PhDThe National Institute forClinical Excellence (NICE),subsequently renamed theNational Institute forHealth and Clinical Excel-lence, was established by the UK gov-ernment in 1999 as an independentorganisation to provide guidance to theNational Health Service (NHS) inEngland and Wales on the clinical andcost-effectiveness of new and existingclinical interventions. Since January2002, NHS organisations in England andWales have been required to providemandatory funding for medicines andtreatments recommended by NICE in itstechnology appraisals guidance [1].NICE’s technology appraisal decisionsare based on a range of factors, includ-ing the strength of clinical-effectivenessevidence, cost-effectiveness, the avail-ability of alternative treatments, and thepotential for long-term benefits to theNHS from innovation [2, 3]. However,the decision-making criteria other thancost-effectiveness have not been codi-fied by NICE and remain enigmatic [4]. nologies with further personalised dif-ferentiation might even lead to conclu-sions that more qualitative trials will beconducted. However, the challenge isstill to inform policy makers about pos-sible advantages or disadvantages and,ultimately, to aid a decision on usageand coverage. A CTA evaluates a newtechnology in an early and unstablestage of development. Scenarios help tomonitor the controlled introductionprocess and can even assist in anticipat-ing on future developments. Dynamiceconomic evaluation can support thedecision making, by taking the severalscenarios per diffusion phase intoaccount in a decision model. We expectthat these methods will prove valuable incombination with more “traditional”cost-effectiveness analysis approaches.Author for correspondenceValesca P Retèl1, MScDepartment of Psychosocial Researchand Epidemiology1 Netherlands Cancer Institute-Antonivan Leeuwenhoek Hospital (NKI-AVL)121 Plesmanlaan 1066 CX Amsterdam, The Netherlandsv.retel@nki.nl Co-authorsProfessor EJTh Rutgers1, MDDepartment of Surgical OncologyProfessor WH van Harten1, MDDepartment of Psychosocial Researchand EpidemiologyMA Joore, PhDDepartment of Clinical Epidemiologyand Medical Technology AssessmentDepartment of Health, Organization,Policy and EconomicsMaastricht University Medical CenterPostbus 58006202 AZ Maastricht, The NetherlandsReferences1. Early Breast Cancer Trialists' CollaborativeGroup (EBCTCG). Effects of chemotherapy andhormonal therapy for early breast cancer onrecurrence and 15-year survival: an overview ofthe randomised trials. Lancet. 2005;365:1687-717.2. Mook S, Van't Veer LJ, Rutgers EJ, et al.Individualization of therapy using Mammaprint:from development to the MINDACT Trial.Cancer Genomics Proteomics. 2007;4:147-55.3. van 't Veer LJ, Dai H, van de Vijver MJ, et al.Gene expression profiling predicts clinical out-come of breast cancer. Nature. 2002;415:530-6.4. van de Vijver MJ, He YD, van 't Veer LJ, et al. AGene-Expression Signature as a Predictor ofSurvival in Breast Cancer. New Eng J Med.2002;347:1999-2009.5. Buyse M, Loi S, van't Veer L, et al. Validationand Clinical Utility of a 70-Gene PrognosticSignature for Women With Node-NegativeBreast Cancer. JNCI Cancer Spectrum.2006;98:1183-92.6. Bueno-de-Mesquita JM, Linn SC, Keijzer R, etal. Validation of 70-gene prognosis signature innode-negative breast cancer. Breast Cancer ResTreat. 2008. In print.7. Bueno-de-Mesquita JM, van Harten W, Retel, Vet al. Use of 70-gene signature to predict progno-sis of patients with node-negative breast cancer: aprospective community-based feasibility study(RASTER). The Lancet Oncology. 2007;8: 1079-87.8. Hutton J, Trueman P, Henshall C. Coverage withevidence development: an examination of concep-tual and policy issues. Int J Technol Assess HealthCare. 2007;23:425-32.9. Douma KF, Karsenberg K, Hummel MJ, et al.Methodology of constructive technology assess-ment in health care. Int J Technol Assess HealthCare. 2007;23:162-8.10. Schot JW. Constructive Technology assessmentand Technology Dynamics: The Case of CleanTechnologies. Science, Technology & HumanValues. 1992;17:36-56.11. Ravdin PM, Siminoff LA, Davis GJ, et al.Computer program to assist in making decisionsabout adjuvant therapy for women with earlybreast cancer. J Clinical Oncology. 2001;19:980-91.12.  Bogaerts J, Cardoso F, Buyse M, et al. Gene signa-ture evaluation as a prognostic tool: challenges inthe design of the MINDACT trial. Nat Clin PractOncol. 2006;3: 540-51.13. Cardoso F, Van't Veer L, Rutgers E, et al. Clinicalapplication of the 70-gene profile: the MINDACTtrial. J Clinical Oncology. 2008;26:729-35.14. Retel VP, Hummel MJ, van Harten WH. Earlyphase Technology Assessment of nanotechnologyin oncology. Tumori. 2008;94:284-90.15. Retel V, Bueno-de-Mesquita J, Hummel M, et al.Constructive Technology Assessment (CTA) as atool in Coverage with Evidence Development: thecase of the 70-gene prognosis signature for breastcancer diagnostics. Int J Technol Assess HealthCare. 2008; Accepted.16. Rogers EM. Diffusion of Innovations. 5th ed.New York: Free Press (2003).17. Briggs A, Claxton K, Sculpher M. DecisionModelling for Health Economic Evaluation.Oxford University Press (2006).18. Claxton K, Cohen JT, Neumann PJ. When is evi-dence sufficient? Health Aff (Millwood).2005;24:93-101.For personal use only. Not to be reproduced without permission of the publisher (copyright@ppme.eu).

A Gene-Expression Signature as a Predictor of Survival in Breast Cancer.

Cancer Trialists' Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials.

Clinical application of the 70-gene profile: the MINDACT trial.

Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer.

Constructive Technology Assessment (CTA) as a tool in Coverage with Evidence Development: the case of the 70-gene prognosis signature for breast cancer diagnostics. Int J Technol Assess Health Care.

Constructive Technology assessment and Technology Dynamics: The Case of Clean Technologies.

Coverage with evidence development: an examination of conceptual and policy issues.

Decision Modelling for Health Economic Evaluation.

Diffusion of Innovations. 5th ed.

Early phase Technology Assessment of nanotechnology in oncology.

Gene expression profiling predicts clinical outcome of breast cancer.

Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol.

Individualization of therapy using Mammaprint: from development to the MINDACT Trial. Cancer Genomics Proteomics.

Methodology of constructive technology assessment in health care.

Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER). The Lancet Oncology.

Validation and Clinical Utility of a 70-Gene Prognostic Signature for Women With Node-Negative Breast Cancer.

Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat.

When is evidence sufficient? Health Aff (Millwood). 2005;24:93-101. For personal use only. Not to be reproduced without permission of the publisher (copyright@ppme.eu).

Establishing cost-effectiveness of genetic targeting of cancer therapies\ud

Establishing cost-effectiveness of genetic targeting of cancer therapies\ud

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