Skip to main content
Log in

Bewertung der Einsparpotenziale in der Arzneimitteltherapie durch Dosisanpassung an die Polymorphismen im Cytochrom P450

Evaluation of economic savings in drug therapy by dose adjustment to polymorphisms in cytochrome P450

  • Original-Forschungsarbeit
  • Published:
PharmacoEconomics German Research Articles

Abstract

Objective: The cytochrome P450 superfamily is an important enzyme complex which aids in the metabolization of approximately 80% of pharmaceuticals currently on the market. Genetic variation leads to different phenotypes of metabolization: extensive metabolizer (EM), intermediate metabolizer (IM), poor metabolizer (PM) and ultra-rapid metabolizer (UM). Depending on polymorphism, different doses are appropriate. The information about 2D6, 2C9 and 2C19 is especially relevant from an economic point of view. The authors aim to determine how large the economic savings can be for the statutory health insurance by adapting the dose rate according to the CYP450 genotype. Therefore, they explored the top ten groups of the Anatomical Therapeutic Chemical (ATC) Classification System in sales in 2010.

Methods: To calculate potential savings, a formula was designed, which includes the relevant agents, the frequency in which polymorphisms occur, the average defined daily doses and their costs, the number of patients, and the average intake period.

Results: 36 appropriate agents were identified for calculation. They incurred a total cost of h2.3 billion for the statutory health insurance in 2010. The maximum saving potential lies in the ATC-group of psychoanaleptics, amounting to h96.1 million. Aripiprazol (h948.60), perphenazin (h352.40) and thiordiazin (€319.10) head the list of agents with the best saving potential per patient and treatment phase. Regarding the costs of diagnostic tests (€100 or €300), only four out of eight drugs are cost-covering.

Conclusion: Pharmacogenetic testing and subsequent dose optimization is partially efficient. Mainly for agents with high €/DDD (DDD: Defined Daily Dose) and long duration of treatment, positive cost-aspects have been calculated in total or on a per patient basis. For final economic appraisal, further information is needed, such as the effect on adverse drug reaction or synergy effects for multi-medicated patients. Finally, dose optimization based on genetic information is likely to be efficient for several agents.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Literatur

  1. Mutschler E, Geisslinger G, Kroemer HK, et al. Mutschler Arzneimittelwirkungen: Lehrbuch der Pharmakologie und Toxikologie. 9. Auflage. Stuttgart: Wissenschaftliche Verlagsgesellschaft, 2008

    Google Scholar 

  2. Ingleman-Sundberg M. Pharmacogenetics of cytochrome P450 and its applications in drug therapy: the past, present and future. Trends Pharmacol Sci 2004; 25(4): 193–200

    Article  Google Scholar 

  3. Wilkinson GR. Drug metabolism and variability in drug response. N Engl J Med 2005; 352(21): 2211–21

    Article  PubMed  CAS  Google Scholar 

  4. Nebert DW, Russell DW. Clinical importance of the cytochromes P450. Lancet 2002; 360(9340): 1155–62

    Article  PubMed  CAS  Google Scholar 

  5. Evans WE, Relling MV. Pharmacogenomics: translating functional genomics into rational therapeutics. Science 1999; 286(5439): 487–91

    Article  PubMed  CAS  Google Scholar 

  6. Roots I, Laschinski G, Meyer UA. Pharmakogenetik und Pharmakogenomik. In: Ganten D, Ruckpaul K. Grundlagen der molekularen Medizin. 3. Auflage. Berlin/Heidelberg: Springer, 2008: 315–31

    Google Scholar 

  7. Kirchheiner J, Seeringer A, Brockmöller J. Stand der Pharmakogenetik in der klinischen Arzneimitteltherapie. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2006; 49(10): 995–1003

    Article  PubMed  CAS  Google Scholar 

  8. Seeringer A, Kirchheiner J. CYP2D6-, CYP2C9- und CYP2C19-basierte Arzneimitteldosisanpassungen. Der Internist 2008; 7: 877–83

    Article  Google Scholar 

  9. Ingelman-Sundberg M, Sim SC, Gomez A, et al. Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. Pharmacol Ther 2007; 116(3): 496–526

    Article  PubMed  CAS  Google Scholar 

  10. Aklillu E, Persson I, Bertilsson L, et al. Frequent distribution of ultrarapid metabolizers of debrisoquine in an ethiopian population carrying duplicated and multiduplicated functional CYP2D6 alleles. J Pharmacol Exp Ther 1996; 278(1): 441–6

    PubMed  CAS  Google Scholar 

  11. Bertilsson L, Dahl ML, Sjöqvist F, et al. Molecular basis for rational megaprescribing in ultrarapid hydroxylators of debrisoquine. Lancet 1993; 341(8836): 63

    Article  PubMed  CAS  Google Scholar 

  12. Kirchheiner J, Meisel C, Goldammer M, et al. Pharmako-genetik als Basis neuer Therapiekonzepte. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2003; 46(10): 835–44

    Article  Google Scholar 

  13. Scott SA. Personalizing medicine with clinical pharmacogenetics. Genet Med 2011; 13(12): 987–95

    Article  PubMed  Google Scholar 

  14. World Health Organization. International drug monitoring: the role of national centres. Report of a WHO meeting. World Health Organ Tech Rep Ser 1972; 498: 1–25

    Google Scholar 

  15. Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. Lancet 2000; 356(9237): 1255–9

    Article  PubMed  CAS  Google Scholar 

  16. Beubler E. Kompendium der Pharmakologie: Gebräuchliche Arzneimittel in der Praxis. 3. Auflage. Wien: Springer, 2011

    Book  Google Scholar 

  17. Thürmann PA. Unerwünschte Arzneimittelwirkungen — Diagnostik und Bewertung. Der Pathologe. 2006; 27(1): 6–12

    Article  PubMed  Google Scholar 

  18. Dormann H, Neubert A, Criegee-Rieck M, et al. Readmissions and adverse drug reactions in internal medicine: the economic impact. J Intern Med 2004; 255(6): 653–63

    Article  PubMed  CAS  Google Scholar 

  19. Classen DC, Pestotnik SL, Evans RS, et al. Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. JAMA 1997; 277(4): 301–6

    CAS  Google Scholar 

  20. Schnurrer JU, Frölich JC. Zur Häufigkeit und Vermeidbarkeit von tödlichen unerwünschten Arzneimittelwirkungen. Der Internist 2003; 44(7): 889–95

    Article  PubMed  CAS  Google Scholar 

  21. Bates DW, Spell N, Cullen DJ, et al. The costs of adverse drug events in hospitalized patients. Adverse Drug Events Prevention Study Group. JAMA 1997; 277(4): 307–11

    CAS  Google Scholar 

  22. Beijer HJ, de Blaey CJ. Hospitalisations caused by adverse drug reactions (ADR): a meta-analysis of observational studies. Pharm World Sci 2002; 24(2): 46–54

    Article  PubMed  CAS  Google Scholar 

  23. Eichelbaum M, Ingelman-Sundberg M, Evans WE. Pharmacogenomics and individualized drug therapy. Annu Rev Med 2006; 57: 119–37

    Article  PubMed  CAS  Google Scholar 

  24. Kirchheiner J. Arzneitherapieempfehlungen auf pharmakogenetischer Basis [Habilitation]. Berlin: Charité — Universitätsmedizin Berlin, 2003

    Google Scholar 

  25. Caraco Y, Blotnick S, Muszkat M. CYP2C9 genotypeguided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther 2008; 83(3): 460–70

    Article  PubMed  CAS  Google Scholar 

  26. Liberato NL, Marchetti M, Barosi G. Cost effectiveness of adjuvant trastuzumab in human epidermal growth factor receptor 2-positive breast cancer. J Clin Oncol 2007; 25(6): 625–33

    Article  PubMed  Google Scholar 

  27. Neyt M, Albrecht J, Cocquyt V. An economic evaluation of Herceptin in adjuvant setting: the Breast Cancer International Research Group 006 trial. Ann Oncol 2006; 17(3): 381–90

    Article  PubMed  CAS  Google Scholar 

  28. Tappenden P, Jones R, Paisley S, et al. Systematic review and economic evaluation of bevacizumab and cetuximab for the treatment of metastatic colorectal cancer. Health Technol Assess 2007; 11(12): 1–128, iii-iv

    PubMed  CAS  Google Scholar 

  29. Brown B, Diamantopoulos A, Bernier J, et al. An economic evaluation of cetuximab combined with radiotherapy for patients with locally advanced head and neck cancer in Belgium, France, Italy, Switzerland, and the United Kingdom. Value Health 2008; 11(5): 791–9

    Article  PubMed  Google Scholar 

  30. Debnath M, Prasad GBKS, Bisen PS. Molecular Diagnostics: Promises and Possibilities. 1. Auflage. Dordrecht: Springer, 2010

    Book  Google Scholar 

  31. Wong WB, Carlson JJ, Thariani R, et al. Cost Effectiveness of Pharmacogenomics: A Critical and Systematic Review. PharmacoEconomics 2010; 28(11): 1001–13

    Article  PubMed  Google Scholar 

  32. Patrick AR, Avorn J, Choudhry NK. Cost-effectiveness of genotype-guided warfarin dosing for patients with atrial fibrillation. Circ Cardiovasc Qual Outcomes 2009; 2(5): 429–36

    Article  PubMed  Google Scholar 

  33. Eckman MH, Rosand J, Greenberg SM et al. Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med 2009; 150(2): 73–83

    PubMed  Google Scholar 

  34. Lee CR, Goldstein JA, Pieper JA. Cytochrome P450 2C9 polymorphisms: a comprehensive review of the in-vitro and human data. Pharmacogenetics 2002; 12(3): 251–63

    Article  PubMed  CAS  Google Scholar 

  35. Sachse C, Brockmöller J, Bauer S, et al. Cytochrome P450 2D6 variants in a Caucasian population: allele frequencies and phenotypic consequences. Am J Hum Genet 1997; 60(2): 284–95

    PubMed  CAS  Google Scholar 

  36. Schwabe U, Paffrath D. Arzneiverordnungs-Report 2011. Berlin: Springer, 2011

    Book  Google Scholar 

  37. Gesundheitsberichterstattung des Bundes. Mitglieder und mitversicherte Familienangehörige der gesetzlichen Krankenversicherung am 1.7. eines Jahres (Anzahl). Gliederungsmerkmale: Jahre, Deutschland, Alter, Geschlecht, Kassenart, Versichertengruppe. Erhältlich unter URL: http://www.gbe-bund.de [Abgerufen 11.07.2011]

  38. Niehaus F. Versicherung von Kindern im Vergleich zwischen GKV und PKV. WIP Diskussionspapier 9/09. Erhältlich unter URL: http://www.wip-pkv.de/uploads/tx_nppresscenter/Versicherung_von_Kinder_im_Vergleich_ PKV_und_GKV.pdf [Abgerufen 15.06.2011]

  39. Hagenmeyer EG, Gothe H, Höer A, et al. Management of Rheumatoid Arthritis in Germany: Findings of a Claims Database Analysis. Erhältlich unter URL: http://www.iges.de/publikationen/poster__abstracts/ispor_arlington/e5661/infoboxContent5662/IGES_Poster_RA_ISPOR_2007_ ger.pdf [Abgerufen 05.06.2011]

  40. Ziegler S, Huscher D, Karberg K, et al. Trends in treatment and outcomes of rheumatoid arthritis in Germany 1997–2007: results from the National Database of the German Collaborative Arthritis Centres. Ann Rheum Dis 2010; 69(10): 1803–8

    Article  PubMed  Google Scholar 

  41. Petty DR, House A, Knapp P, et al. Prevalence, duration and indications for prescribing of antidepressants in primary care. Age Ageing 2006; 35(5): 523–6

    Article  PubMed  Google Scholar 

  42. Aletaha D, Stamm T, Kapral T, et al. Survival and effectiveness of leflunomide compared with methotrexate and sulfasalazine in rheumatoid arthritis: a matched observational study. Ann Rheum Dis 2003; 62(10): 944–51

    Article  PubMed  CAS  Google Scholar 

  43. Freeman J, Hutchison GB. Prevalence, incidence and duration. Am J Epidemiol 1980; 112(5): 707–23

    PubMed  CAS  Google Scholar 

  44. Alho JM. On prevalence, incidence, and duration in general stable populations. Biometrics 1992; 48(2): 587–92

    Article  PubMed  CAS  Google Scholar 

  45. Ubink-Veltmaat LJ, Bilo HJ, Groenier KH, et al. Prevalence, incidence and mortality of type 2 diabetes mellitus revisited: a prospective population-based study in The Netherlands (ZODIAC-1). Eur J Epidemiol 2003; 18(8): 793–800

    Article  PubMed  CAS  Google Scholar 

  46. de Salvia D, Barbato A, Salvo P, et al. Prevalence and incidence of schizophrenic disorders in Portogruaro. An Italian case register study. J Nerv Ment Dis 1993; 181(5): 275–82

    Article  Google Scholar 

  47. Kirchheiner J, Brøsen K, Dahl ML, et al. CYP2D6 and CYP2C19 genotype-based dose recommendations for antidepressants: a first step towards subpopulation-specific dosages. Acta Psychiatr Scand 2001; 104(3): 173–92

    Article  PubMed  CAS  Google Scholar 

  48. Rudberg I, Mohebi B, Hermann M, et al. Impact of the ultrarapid CYP2C19∞17 allele on serum concentration of escitalopram in psychiatric patients. Clin Pharmacol Ther 2008; 83(2): 322–7

    Article  PubMed  CAS  Google Scholar 

  49. Rudberg I, Hermann M, Refsum H, et al. Serum concentrations of sertraline and N-desmethyl sertraline in relation to CYP2C19 genotype in psychiatric patients. Eur J Clin Pharmacol 2008; 64(12): 1181–8

    Article  PubMed  CAS  Google Scholar 

  50. Schöffski O, Greiner W. Grundprinzipien der Wirtschaftlichkeitsuntersuchung. In: Schöffski O, Graf v. d. Schulenburg JM. Gesundheitsökonomische Evaluationen. 3. Auflage. Berlin: Springer, 2007: 167–191

    Google Scholar 

  51. Rebsamen MC, Desmeules J, Daali Y, et al. The AmpliChip CYP450 test: cytochrome P450 2D6 genotype assessment and phenotype prediction. Pharmacogenomics J 2009; 9(1): 34–41

    Article  PubMed  CAS  Google Scholar 

  52. Rodríguez-Antona C, Gurwitz D, de Leon J, et al. CYP2D6 genotyping for psychiatric patients treated with risperidone: considerations for cost-effectiveness studies. Pharmacogenomics 2009; 10(4): 685–99

    Article  PubMed  Google Scholar 

  53. Matchar DB, Thakur ME, Grossman I, et al. Testing for cytochrome P450 polymorphisms in adults with non-psychotic depression treated with selective serotonin reuptake inhibitors (SSRIs). Evid Rep Technol Assess (Full Rep) 2007; (146): 1-77

  54. Hüsing B, Hartig J, Bührlein B, et al. Individualisierte Medizin und Gesundheitssystem. TAB-Arbeitsbericht Nr. 126. Berlin: Büro für Technikfolgen-Abschätzung beim Deutschen Bundestag (TAB), 2008. Erhältlich von URL: http://www.tab-beim-bundestag.de/de/pdf/publikationen/ berichte/TAB-Arbeitsbericht-ab126.pdf [Abgerufen 11.04.2011]

  55. Greiner W, Knittel M. Wirtschaftliche Potentiale individualisierter Medizin. PharmacoEconomics — German Research Articles 2011; 9(1): 45–54

    Google Scholar 

  56. Hermanns PM, Filler G, Roscher B. GOÄ (Gebührenordnung für Ärzte): Kommentar für Praxis und Klinik. 5. Auflage. München: ecomed Medizin, 2011

    Google Scholar 

  57. Marsden CD, Jenner P. The pathophysiology of extrapyramidal side-effects of neuroleptic drugs. Psychol Med 1980; 10(1): 55–72

    Article  PubMed  CAS  Google Scholar 

  58. Casey DE. Neuroleptic drug-induced extrapyramidal syndromes and tardive dyskinesia. Schizophr Res 1991; 4(2): 109–20

    Article  PubMed  CAS  Google Scholar 

  59. Linnet K, Wiborg O. Steady-state serum concentrations of the neuroleptic perphenazine in relation to CYP2D6 genetic polymorphism. Clin Pharmacol Ther 1996; 60(1): 41–7

    Article  PubMed  CAS  Google Scholar 

  60. Dahl ML, Sjöqvist F. Pharmacogenetic methods as a complement to therapeutic monitoring of antidepressants and neuroleptics. Ther Drug Monit 2000; 22(1): 114–7

    Article  PubMed  CAS  Google Scholar 

  61. Hiemke C, Baumann P. Pharmakokinetik, Pharmakogenetik und therapeutisches Drug Monitoring. In: Holsboer F, Gründer G, Benkert O. Handbuch der Psychopharmakotherapie. Berlin/Heidelberg: Springer, 2008: 375–97

    Chapter  Google Scholar 

  62. Manolopoulos VG, Ragia G, Tavridou A. Pharmacogenomics of oral antidiabetic medications: current data and pharmacoepigenomic perspective. Pharmacogenomics 2011; 12(8): 1161–91

    Article  PubMed  CAS  Google Scholar 

  63. Malhotra AK, Zhang JP, Lencz T. Pharmacogenetics in psychiatry: translating research into clinical practice. Mol Psychiatry 2011 Nov 15. doi: 10.1038/mp.2011.146. [Epub ahead of print]

  64. Fleeman N, McLeod C, Bagust A. The clinical effectiveness and cost-effectiveness of testing for cytochrome P450 polymorphisms in patients with schizophrenia treated with antipsychotics: a systematic review and economic evaluation. Health Technol Assess 2010; 14(3): 1–157, iii

    PubMed  CAS  Google Scholar 

  65. Pirmohamed M, James S, Meakin S, et al. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ 2004; 329(7456): 15–9

    Article  PubMed  Google Scholar 

  66. Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. JAMA 1998; 279(15): 1200–5

    Article  PubMed  CAS  Google Scholar 

  67. Goettler M, Schneeweiss S, Hasford J. Adverse drug reaction monitoring-cost and benefit considerations. Part II: cost and preventability of adverse drug reactions leading to hospital admission. Pharmacoepidemiol Drug Saf 1997; 6 Suppl 3: S79–90

    Article  PubMed  Google Scholar 

  68. Schneeweiss S, Hasford J, Göttler M, et al. Admissions caused by adverse drug events to internal medicine and emergency depatments in hospitals: a longitudinal population-based study. Eur J Clin Pharmacol 2002; 58(4): 285–91

    Article  PubMed  Google Scholar 

  69. Sachverständigenrat zur Begutachtung der Entwicklung im Gesundheitswesen. Kooperation und Verantwortung. Voraussetzungen einer zielorientierten Gesundheitsversorgung. Jahresgutachten 2007. Erhältlich unter URL: http://www.svr-gesundheit.de/Gutachten/Gutacht07/Kurz fassung%202007.pdf

  70. Stark RG, John J, Leidl R. Health care use and costs of adverse drug events emerging from outpatient treatment in Germany: a modelling approach. BMC Health Serv Res 2011; 11:9

    Article  PubMed  Google Scholar 

  71. Weiß J. Tabletten teilen — ein gefährliches Unterfangen. Dtsch med Wochenschr 2007; 132(15): 3

    Google Scholar 

  72. Rogausch A, Brockmöller J, Himmel W. Pharmakogenetische Tests in der zukünftigen medizinischen Versorgung: Implikationen für Patienten und Ärzte. Gesundheitswesen 2005; 67(4): 257–63

    Article  PubMed  CAS  Google Scholar 

  73. March R, Cheeseman K, Doherty M. Pharmacogenetics — legal, ethical and regulatory considerations. Pharmacogenomics 2001; 2(4): 317–27

    Article  PubMed  CAS  Google Scholar 

  74. Nebert DW, Bingham E. Pharmacogenomics: out of the lab and into the community. Trends Biotechnol 2001; 19(12): 519–23

    Article  PubMed  CAS  Google Scholar 

  75. Lindpaintner K. Pharmacogenetics and the future of medical practice. Br J Clin Pharmacol 2002; 54(2): 221–30

    Article  PubMed  Google Scholar 

  76. Norbert PW, Roses AD. Pharmacogenetics and pharmacogenomics: recent developments, their clinical relevance and some ethical, social, and legal implications. J Mol Med 2003; 81(3): 135–40

    PubMed  Google Scholar 

  77. Burkhardt H, Wehling M. Probleme bei der Pharmakotherapie älterer Patienten. Der Internist 2010; 51(6): 737–48

    Article  PubMed  CAS  Google Scholar 

  78. Burkhardt H, Wehling M, Gladisch R. Prävention unerwünschter Arzneimittelwirkungen bei älteren Patienten. Z Gerontol Geriatr 2007; 40(4): 241–54

    Article  PubMed  CAS  Google Scholar 

  79. Thürmann PA. Geschlechtsspezifische Unterschiede in der Pharmakotherapie. In: Rieder A, Lohff B. Gender Medizin. Wien: Springer, 2008; 31–47

    Chapter  Google Scholar 

  80. Findl I, Klaushofer K, Koller K. Medikamenten-Compliance geriatrischer Patienten. TopTipps — Ein Service der NÖGKK 2001; 3. Erhältlich unter URL: http://www.sozialversicherung.at/mediaDB/655175_Top_Tipps3_2001.pdf [Abgerufen 11.04.2011]

  81. San Miguel MT, Martínez JA, Vargas E. Food-drug interactions in the summary of product characteristics of proprietary medicinal products. Eur J Clin Pharmacol 2005; 61(2): 77–83

    Article  PubMed  Google Scholar 

  82. Stein K. Herbal supplements and prescription drugs. A risky combination? J Am Diet Assoc 2000; 100(4): 412

    Article  CAS  Google Scholar 

  83. Sari AB, Cracknell A, Sheldon TA. Incidence, preventability and consequences of adverse events in older people: results of a retrospective case-note review. Age Ageing 2008; 37(3): 265–9

    Article  PubMed  Google Scholar 

  84. Milton JC, Jackson SH. Inappropriate polypharmacy: reducing the burden of multiple medication. Clin Med 2007; 7(5): 514–7

    Article  PubMed  Google Scholar 

  85. Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. An update. Arch Intern Med 1997; 157(14): 1531–6

    Article  CAS  Google Scholar 

  86. Kirchheiner J, Nickchen K, Bauer M, et al. Pharmacogenetics of antidepressants and antipsychotics: the contribution of allelic variations to the phenotype of drug response. Mol Psychiatry 2004; 9(5): 442–73

    Article  PubMed  CAS  Google Scholar 

  87. Zhou SF, Liu JP, Chowbay B. Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug Metab Rev 2009; 41(2): 89–295

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Florian Meier.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Meier, F., Kontekakis, A. & Schöffski, O. Bewertung der Einsparpotenziale in der Arzneimitteltherapie durch Dosisanpassung an die Polymorphismen im Cytochrom P450. Pharmacoeconomics-Ger-Res-Articles 10, 69–85 (2012). https://doi.org/10.1007/BF03320779

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03320779

Keywords

Navigation