SOCIO-ETHICAL ISSUES IN PERSONALIZED MEDICINE: A SYSTEMATIC REVIEW OF ENGLISH LANGUAGE HEALTH TECHNOLOGY ASSESSMENTS OF GENE EXPRESSION PROFILING TESTS FOR BREAST CANCER PROGNOSIS. (20th May 2015)

• Record Type: Journal Article
• Authors: Ali-Khan, Sarah E.; Black, Lee; Palmour, Nicole; Hallett, Michael T.; Avard, Denise
• Is Part Of: International journal of technology assessment in health care. Volume 31:Number 1/2(2015)
• Page Start: 36
• Page End: 50
• Publication Date: 2015-05-20
• Subjects: Technology assessment, -- Gene expression profiling, -- Prognosis, -- Breast neoplasms, -- Ethical issues; Medical technology -- Periodicals; Technology assessment -- Periodicals; 610.28
• DOI: 10.1017/S0266462315000082
• Languages: English
• ISSNs: 0266-4623

Abstract

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.