Free Access
Med Sci (Paris)
Volume 30, Novembre 2014
2e colloque de l’ITMO Santé publique – Médecine « personnalisée » et innovations biomédicales : enjeux de santé publique, économiques, éthiques et sociaux (Paris, 5 décembre 2013)
Page(s) 32 - 35
Section Session 3. La médecine personnalisée : aggravatrice ou réductrice des inégalités de santé ?
Published online 17 November 2014
  1. Hofstede G, Hofstede GJ, Minkov M. Cultures and organizations. New York : McGraw-Hill, 1997. [Google Scholar]
  2. Holzer B. Political consumerism between individual choice and collective action: social movements, role mobilization and signalling. Int J Cons Stud 2006 ; 30: 405–415. [CrossRef] [Google Scholar]
  3. Lesko LJ. Personalized medicine: elusive dream or imminent reality?. Clin Pharmacol Ther 2007 ; 81 : 807–816. [CrossRef] [PubMed] [Google Scholar]
  4. Hoggatt J. Personalized medicine -trends in molecular diagnostics: exponential growth expected in the next ten years. Mol Diagn Ther 2011 ; 15 : 53–55. [CrossRef] [PubMed] [Google Scholar]
  5. Coulter A. Paternalism or partnership? Patients have grown up-and there’s no going back. Br Med J 1999 ; 319 : 719–720. [CrossRef] [PubMed] [Google Scholar]
  6. Seror V, Marino P, Bertucci F, et al. Breast cancer patients’ views on the use of genomic testing to guide decisions about their postoperative chemotherapy. Public Health Genomics 2013 ; 16 : 110–117. [CrossRef] [PubMed] [Google Scholar]
  7. DiMasi JA, Hansen RW, Grabowski HG. The price of innovation: new estimates of drug development costs. J Health Econ 2003 ; 22 : 151–185. [CrossRef] [PubMed] [Google Scholar]
  8. Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 2004 ; 3 : 711–715. [CrossRef] [PubMed] [Google Scholar]
  9. Moore TJ, Cohen MR, Furberg CD. Serious adverse drug events reported to the Food and drug administration, 1998–2005. Arch Intern Med 2007 ; 167 : 1752–1759. [CrossRef] [PubMed] [Google Scholar]
  10. Blair ED, Stratton EK, Kaufmann M. The economic value of companion diagnostics and stratified medicines. Expert Rev Mol Diagn 2012 ; 12 : 791–794. [CrossRef] [PubMed] [Google Scholar]
  11. Marino P, Bertucci F, Goncalvez A, Seror V. Tests diagnostiques et thérapies ciblées en cancérologie : enjeux économiques. Med Sci (Paris) 2012 ; 28 : 19–23. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  12. Fugel HJ, Nuijten M, Postma M. Stratified medicine, reimbursement issues. Front Pharmacol 2012 ; 3 : 181. [CrossRef] [PubMed] [Google Scholar]
  13. Marino P, Siani C, Bertucci F, et al. Economic issues involved in integrating genomic testing into clinical care: the case of genomic testing to guide decision-making about chemotherapy for breast cancer patients. Breast Cancer Res Treat 2011 ; 129 : 401–409. [CrossRef] [PubMed] [Google Scholar]
  14. Davis JC, Furstenthal L, Desai AA, et al. The microeconomics of personalized medicine: today’s challenge and tomorrow’s promise. Nat Rev Drug Discov 2009 ; 8 : 279–286. [CrossRef] [PubMed] [Google Scholar]
  15. Trosman JR, Van Bebber SL, Phillips KA. Health technology assessment and private payers’ coverage of personalized medicine. J Oncol Pract 2011 ; 7 : s18s–s124. [CrossRef] [Google Scholar]
  16. Deverka PA. Pharmacogenomics, evidence, and the role of payers. Public Health Genomics 2009 ; 12 : 149–157. [CrossRef] [PubMed] [Google Scholar]
  17. Frank M, Mittendorf T. Influence of pharmacogenomic profiling prior to pharmaceutical treatment in metastatic colorectal cancer on cost effectiveness: a systematic review. Pharmacoeconomics 2013 ; 31 : 215–228. [CrossRef] [PubMed] [Google Scholar]
  18. Atherly AJ, Camidge Dr. The cost-effectiveness of screening lung cancer patients for targeted drug sensitivity markers. Br J Cancer 2012 ; 106 : 1100–1106. [CrossRef] [PubMed] [Google Scholar]
  19. Retel VP, Joore MA, Drukker CA, et al. Prospective cost-effectiveness analysis of genomic profiling in breast cancer. Eur J Cancer 2013 ; 49 : 3773–3779. [CrossRef] [PubMed] [Google Scholar]
  20. Roche H, Fumoleau P, Spielmann M, et al. Sequential adjuvant epirubicin-based and docetaxel chemotherapy for node-positive breast cancer patients: the FNCLCC PACS 01 Trial. J Clin Oncol 2006 ; 24 : 5664–5671. [CrossRef] [PubMed] [Google Scholar]
  21. Bertucci F, Borie N, Roche H, et al. Gene expression profile predicts outcome after anthracycline-based adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat 2011 ; 127 : 363–373. [CrossRef] [PubMed] [Google Scholar]
  22. Ladislav S. Toxicities of taxanes. J Cancer Res Ther 2013 ; 9 : 161. [CrossRef] [PubMed] [Google Scholar]
  23. Marino P, Siani C, Roche H, et al. Cost-effectiveness of adjuvant docetaxel for node-positive breast cancer patients: results of the PACS 01 economic study. Ann Oncol 2010 ; 21 : 1448–1454. [CrossRef] [PubMed] [Google Scholar]
  24. Eichler HG, Bloechl-Daum B, Abadie E, et al. Relative efficacy of drugs: an emerging issue between regulatory agencies and third-party payers. Nat Rev Drug Discov 2010 ; 9 : 277–291. [CrossRef] [PubMed] [Google Scholar]
  25. Schreyogg J, Baumler M, Busse R. Balancing adoption and affordability of medical devices in Europe. Health Policy 2009 ; 92 : 218–224. [CrossRef] [PubMed] [Google Scholar]
  26. Meckley LM, Neumann PJ. Personalized medicine: factors influencing reimbursement. Health Policy 2010 ; 94 : 91–100. [CrossRef] [PubMed] [Google Scholar]
  27. Seror V, Elasri K, Avenel E. Premières applications de la pharmacogénomique en oncologie - stratégies industrielles et enjeux de régulation publique. Revue d’Économie Industrielle 2007 ; 120 : 235–252. [CrossRef] [Google Scholar]
  28. Bobinac A, van Exel J, Rutten FF, Brouwer WB. The value of a QALY: individual willingness to pay for health gains under risk. Pharmacoeconomics 2014 ; 32 : 75–86. [CrossRef] [PubMed] [Google Scholar]
  29. Robinson A, Gyrd-Hansen D, Bacon P, et al. Estimating a WTP-based value of a QALY: the chained approach. Soc Sci Med 2013 ; 92 : 92–104. [CrossRef] [PubMed] [Google Scholar]
  30. Aspinall MG, Hamermesh RG. Realizing the promise of personalized medicine. Harv Bus Rev 2007 ; 85 : 108–117, 165. [PubMed] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.