Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T15:22:18.169Z Has data issue: false hasContentIssue false

SOCIO-ETHICAL ISSUES IN PERSONALIZED MEDICINE: A SYSTEMATIC REVIEW OF ENGLISH LANGUAGE HEALTH TECHNOLOGY ASSESSMENTS OF GENE EXPRESSION PROFILING TESTS FOR BREAST CANCER PROGNOSIS

Published online by Cambridge University Press:  20 May 2015

Sarah E. Ali-Khan
Affiliation:
Centre of Genomics and Policy, McGill Universitysarah.ali-khan@mcgill.ca
Lee Black
Affiliation:
Centre of Genomics and Policy, McGill University
Nicole Palmour
Affiliation:
Centre of Genomics and Policy, McGill University
Michael T. Hallett
Affiliation:
The Rosalind and Morris Goodman Cancer Research Centre, McGill University; Centre for Bioinformatics, McGill University; Department of Biochemistry, McGill University
Denise Avard
Affiliation:
Centre of Genomics and Policy, McGill University

Abstract

Objectives: There have been multiple calls for explicit integration of ethical, legal, and social issues (ELSI) in health technology assessment (HTA) and addressing ELSI has been highlighted as key in optimizing benefits in the Omics/Personalized Medicine field. This study examines HTAs of an early clinical example of Personalized Medicine (gene expression profile tests [GEP] for breast cancer prognosis) aiming to: (i) identify ELSI; (ii) assess whether ELSIs are implicitly or explicitly addressed; and (iii) report methodology used for ELSI integration.

Methods: A systematic search for HTAs (January 2004 to September 2012), followed by descriptive and qualitative content analysis.

Results: Seventeen HTAs for GEP were retrieved. Only three (18%) explicitly presented ELSI, and only one reported methodology. However, all of the HTAs included implicit ELSI. Eight themes of implicit and explicit ELSI were identified. “Classical” ELSI including privacy, informed consent, and concerns about limited patient/clinician genetic literacy were always presented explicitly. Some ELSI, including the need to understand how individual patients’ risk tolerances affect clinical decision-making after reception of GEP results, were presented both explicitly and implicitly in HTAs. Others, such as concern about evidentiary deficiencies for clinical utility of GEP tests, occurred only implicitly.

Conclusions: Despite a wide variety of important ELSI raised, these were rarely explicitly addressed in HTAs. Explicit treatment would increase their accessibility to decision-makers, and may augment HTA efficiency maximizing their utility. This is particularly important where complex Personalized Medicine applications are rapidly expanding choices for patients, clinicians and healthcare systems.

Type
Assessments
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Morrison, A, Boudreau, R. Evaluation frameworks for genetic tests (Environmental Scan: issue 36). Ottawa: Canadian Agency for Drugs and Technologies in Health; 2012.Google Scholar
2. Potter, BK, Avard, D, Graham, ID et al. Guidance for considering ethical, legal, and social issues in health technology assessment: Application to genetic screening. Int J Technol Assess Health Care. 2008;24:412412.Google Scholar
3. Goncalves, R, Bose, R. Using multigene tests to select treatment for early-stage breast cancer. J Natl Compr Canc Netw. 2013;11:174182.Google Scholar
4. NICE Diagnostics Advisory Committee. Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in early breast cancer management: Mammaprint, Oncotype DX, IHC4 and Mammostrat (DG10). UK online: National Institute for Health and Clinical Excellence; 2013. http://guidance.nice.org.uk/DG10 (accessed October 2013).Google Scholar
5. International Network of Agencies for Health Technology Assessment (INAHTA). HTA resources: definitions. http://www.inahta.net/HTA/ (accessed August 2013).Google Scholar
6. DeJean, D, Giacomini, M, Schwartz, L, Miller, FA. Ethics in Canadian health technology assessment: A descriptive review. Int J Technol Assess Health Care. 2009;25:463469 Google Scholar
7. Teutsch, SM, Bradley, LA, Palomaki, GE, et al. The evaluation of genomic applications in practice and prevention (EGAPP) initiative: Methods of the EGAPP working group. Genet Med. 2009;11:314.Google Scholar
8. Genomic testing. ACCE model process for evaluating genetic tests. http://www.cdc.gov/genomics/gtesting/ACCE/index.htm (accessed August 2013).Google Scholar
9. Burke, W, Zimmern, R. Moving beyond ACCE: An expanded framework for genetic test evaluation. Cambridge, UK: PHG Foundation; 2007.Google Scholar
10. Ali-Khan, SE, Daar, AS, Shuman, C, Ray, PN, Scherer, SW. Whole genome scanning: Resolving clinical diagnosis and management amidst complex data. Pediatr Res. 2009;66:357363.Google Scholar
11. US Department of Health and Human Services. Draft guidance for industry, clinical laboratories, and FDA staff: In vitro diagnostic multivariate index assays. Rockville, MD: Food and Drug Administration, US Department of Health and Human Services; 2007. http://www.fda.gov/downloads/MedicalDevices/.../ucm071455.pdf (accessed October 2013).Google Scholar
12. Mokhtar, NM, Murad, NA, Mian, SM, Jamal, R. Genomic expression profiles: From molecular signatures to clinical oncology translation. In: Lopez-Camarillo, C, Arechaga-Ocampo, E, eds. Oncogenomics and cancer proteomics - novel approaches in biomarker discovery and therapeutic targets in cancer. Intech; 2013. (internet) p. 3–48. http://www.intechopen.com/books/oncogenomics-and-cancer-proteomics-novel-approaches-in-biomarkers-discovery-and-therapeutic-targets-in-cancer/genomic-expression-profiles-from-molecular-signatures-to-clinical-oncology-translation (accessed October 2013).Google Scholar
13. Zhang, Z. An in vitro diagnostic multivariate index assay (IVDMIA) for ovarian cancer: Harvesting the power of multiple biomarkers. Rev Obstet Gynecol. 2012;5:3541.Google Scholar
14. Centre for Reviews and Dissemination. Systematic reviews: CRD's guidance for undertaking reviews in healthcare. York, UK: CRD, University of York; 2009.Google Scholar
15. Smarrt, P. A comparison of gene expression profiling tests for breast cancer. Health Services Assessment Collaboration (HSAC) Report. 2009;3.Google Scholar
16. National Horizon Scanning Centre. Oncotype DX prognostic and predictive test for early breast cancer. Birmingham, UK: National Horizon Scanning Centre, Department of Public Health and Epidemiology, University of Birmingham; 2008.Google Scholar
17. National Horizon Scanning Centre. Mammaprint (gene test) prognostic test for breast cancer. Birmingham, UK: National Horizon Scanning Centre, Department of Public Health and Epidemiology, University of Birmingham; 2007.Google Scholar
18. Blue Cross Blue Shield Association. Gene expression profiling in women with lymph-node-positive breast cancer to select adjuvant chemotherapy treatment. Chicago IL: Blue Cross Blue Shield Association; 2010.Google Scholar
19. HealthPACT Secretariat. Gene expression profiling of breast cancer. Brisbane, Australia: HealthPACT Secretariat, Queensland Health; 2012.Google Scholar
20. Hofmann, B. Toward a procedure for integrating moral issues in health technology assessment. Int J Technol Assess Health Care. 2005;21:312318.Google Scholar
21. Braun, V, Clarke, V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3:77101.Google Scholar
22. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP working group: Can tumor gene expression profiling improve outcomes in patients with breast cancer? Genet Med. 2009;11:6673.CrossRefGoogle Scholar
23. Medical Advisory Secretariat. Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: An evidence-based and economic analysis. Ontario Health Technology Assessment Services (internet). 2010;10:1–57. http://www.hqontario.ca/english/providers/program/mas/tech/reviews/pdf/gep_20101213.pdf (accessed August 2013).Google Scholar
24. NICE Diagnostics Advisory Committee. Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in breast cancer management: MammaPrint, Oncotype DX, IHC4 and Mammostrat: Provisional recommendations. NHS National Institute for Health and Clinical Excellence (Internet). 2012. http://www.nice.org.uk/nicemedia/live/13283/58040/58040.pdf (accessed August 2013).Google Scholar
25. Marchionni, L, Wilson, RF, Marinopoulos, SS, et al. Impact of gene expression profiling tests on breast cancer outcomes. Evid Rep Technol Assess (Full Rep). 2007;1105.Google Scholar
26. California Technology Assessment Forum. Gene expression profiling as a guide for the management of early stage breast cancer. San Francisco, CA: California Technology Assessment Forum; 2006.Google Scholar
27. Ishibe, N, Schully, S, Freedman, A, Ramsey, SD. Use of Oncotype DX in women with node-positive breast cancer. PLoS Curr. 2011;3:RRN1249.Google Scholar
28. Tice, JA. The 70-gene signature (MammaPrint) as a guide for the management of early stage breast cancer. San Francisco, CA: California Technology Assessment Forum; 2010.Google Scholar
29. Mundy, L, Braunack-Meyer, A, Hiller, J. DNA microarrays. Canberra, Australia: Health PACT Secretariat; 2007.Google Scholar
30. Benatar, D. Bioethics and health and human rights: A critical view. J Med Ethics. 2006;32:1720.Google Scholar
31. Newland, A. NICE diagnostics assessment programme. Ann R Coll Surg Engl. 2011;93:412413.Google Scholar
32. Hogarth, S. The clinical application of new molecular diagnostic technologies - a review of the regulatory and policy issues: A report for Health Canada. London, UK: King's College London; 2007. http://www.kcl.ac.uk/sspp/departments/politicaleconomy/research/biopolitics/publications/HealthCanadamicroarraysreport.pdf (accessed October 2013).Google Scholar
33. Kohli-Laven, N, Bourret, P, Keating, P, Cambrosio, A. Cancer clinical trials in the era of genomic signatures: Biomedical innovation, clinical utility, and regulatory-scientific hybrids. Soc Stud Sci. 2011;41:487513.Google Scholar
34. Burls, A, Caron, L, Cleret de Langavant, G, et al. Tackling ethical issues in health technology assessment: A proposed framework. Int J Technol Assess Health Care. 2011;27:230237.CrossRefGoogle ScholarPubMed
35. Droste, S, Dintsios, CM, Gerber, A. Information on ethical issues in health technology assessment: How and where to find them. Int J Technol Assess Health Care. 2010;26:441449.Google Scholar
36. Gagnon, MP, Desmartis, M, Gagnon, J, et al. Introducing the patient's perspective in hospital health technology assessment (HTA): The views of HTA producers, hospital managers and patients. Health Expect. 2014;17:888900.Google Scholar
37. Carlson, RW, Gradishar, WJ, Schwatzberg, L, et al. NCCN clinical practice guidelines in oncology (NCCN guidelines); breast cancer; version 3.2012. (internet) National Comprehensive Cancer Network, Inc.; 2012. Report No.: v3. http://www.nccn.org/professionals/physician_gls/pdf/breast.pdf (accessed July 2012).Google Scholar
38. Sturgeon, C, Duffy, D, Stenman, U, et al. Use of tumour markers in testicular, prostate, colorectal, breast, and ovarian cancers. Washington DC: American Association for Clinical Chemistry; 2009.Google Scholar
39. Krishnasamy, M. Mammaprint. Putrajaya, Malaysia: Health Technology Assessment Section (MaHTAS), Medical Development Division Ministry of Health; 2008.Google Scholar
40. Harris, L, Fritsche, H, Mennel, R, et al. American society of clinical oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol. 2007;25:5287–312.Google Scholar
Supplementary material: File

Ali-Khan supplementary material

Ali-Khan supplementary material 1

Download Ali-Khan supplementary material(File)
File 145.3 KB
Supplementary material: File

Ali-Khan supplementary material

Table S1

Download Ali-Khan supplementary material(File)
File 105.9 KB
Supplementary material: File

Ali-Khan supplementary material

Table S2

Download Ali-Khan supplementary material(File)
File 140.9 KB