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Cost-utility analysis of antiviral use under pandemic influenza using a novel approach – linking pharmacology, epidemiology and heath economics

  • D. B. C. Wu (a1) (a2), N. Chaiyakunapruk (a1) (a2) (a3) (a4), C. Pratoomsoot (a5), K. K. C. Lee (a1), H. Y. Chong (a1), R. E. Nelson (a6) (a7), P. F. Smith (a8), C.M. Kirkpatrick (a9), M. A. Kamal (a10), K. Nieforth (a8), G. Dall (a8), S. Toovey (a11), D. C. M. Kong (a9), A. Kamauu (a12) and C. R. Rayner (a8)...

Abstract

Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) – dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients’ quality of life. Integrating PK/PD–EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

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Copyright

Corresponding author

Author for correspondence: N. Chaiyakunapruk, E-mail: nathorn.chaiyakunapruk@monash.edu

References

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1. Weinstein, MC, et al. (2003) Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR task force on good research practices – modeling studies. Value in Health 6(1), 917.
2. Jit, M and Brisson, M (2011) Modelling the epidemiology of infectious diseases for decision analysis: a primer. PharmacoEconomics 29(5), 371386.
3. Lugner, AK, Mylius, SD and Wallinga, J (2010) Dynamic versus static models in cost-effectiveness analyses of anti-viral drug therapy to mitigate an influenza pandemic. Health Economics 19(5), 518531.
4. Brisson, M and Edmunds, WJ (2003) Economic evaluation of vaccination programs: the impact of herd-immunity. Medical Decision Making 23(1), 7682.
5. Brisson, M and Edmunds, WJ (2006) Impact of model, methodological, and parameter uncertainty in the economic analysis of vaccination programs. Medical Decision Making 26(5), 434446.
6. Lugner, AK and Postma, MJ (2009) Mitigation of pandemic influenza: review of cost-effectiveness studies. Expert Review of Pharmacoeconomics and Outcomes Research 9(6), 547558.
7. Duffull, SB, Wright, DF and Winter, HR (2011) Interpreting population pharmacokinetic-pharmacodynamic analyses – a clinical viewpoint. British Journal of Clinical Pharmacology 71(6), 807814.
8. Rayner, CR, et al. (2013) Pharmacokinetic-pharmacodynamic determinants of oseltamivir efficacy using data from phase 2 inoculation studies. Antimicrobial Agents and Chemotherapy 57(8), 34783487.
9. Bulik, C, et al. Pharmacokinetic-pharmacodynamic (PK-PD) evaluation of the impact of oseltamivir on influenza viral endpoints. 54th Interscience Conference on Antimicrobial Agents and Chemotherapy (ICAAC). Washington DC, US.
10. Pradas-Velasco, R, Antonanzas-Villar, F and Martinez-Zarate, MP (2008) Dynamic modelling of infectious diseases: an application to the economic evaluation of influenza vaccination. PharmacoEconomics 26(1), 4556.
11. Pitman, R, et al. (2012) Dynamic transmission modeling: a report of the ISPOR-SMDM modeling good research practices task force working group-5. Medical Decision Making 32(5), 712721.
12. Girard, MP, et al. (2010) The 2009 A (H1N1) influenza virus pandemic: a review. Vaccine 28(31), 48954902.
13. World Health Organisation (WHO) (2013) Cumulative Number of Confirmed Human Cases for Avian Influenza A (H5N1) Reported to WHO, 2003–2013. Geneva: WHO.
14. World Health Organization. Global alert and response (GAR). Avian influenza. Geneva: WHO.
15. Kelso, JK, et al. (2013) Economic analysis of pandemic influenza mitigation strategies for five pandemic severity categories. BMC Public Health 13, 211.
16. Milne, GJ, Halder, N and Kelso, JK (2013) The cost effectiveness of pandemic influenza interventions: a pandemic severity based analysis. PLoS ONE 8(4), e61504.
17. Kamal, MA, et al. (2017) Interdisciplinary pharmacometrics linking oseltamivir pharmacology, influenza epidemiology and health economics to inform antiviral use in pandemics. British Journal of Clinical Pharmacology 83(7), 15801594.
18. Kamal, MA, et al. (2013) Population pharmacokinetics of oseltamivir: pediatrics through geriatrics. Antimicrobial Agent and Chemotherapy 57(8), 34703477.
19. Jain, S, et al. (2012) Influenza-associated pneumonia among hospitalized patients with 2009 pandemic influenza A (H1N1) virus – United States, 2009. Clinical Infectious Diseases 54(9), 12211229.
20. Jain, S, et al. (2009) Hospitalized patients with 2009 H1N1 influenza in the United States, April–June 2009. New England Journal of Medicine 361(20), 19351944.
21. Skarbinski, J, et al. (2011) Hospitalized patients with 2009 pandemic influenza A (H1N1) virus infection in the United States – September–October 2009. Clinical Infectious Diseases 52(suppl. 1), S50S59.
22. Burch, J, et al. (2009) Antiviral drugs for the treatment of influenza: a systematic review and economic evaluation. Health Technology Assessment 13(58), 1265, iii–iv.
23. Jefferson, T, et al. (2012) Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Cochrane Database of Systematic Reviews 1, CD008965.
24. Hsu, J, et al. (2012) Antivirals for treatment of influenza: a systematic review and meta-analysis of observational studies. Annals Internal Medicine 156(7), 512524.
25. Michiels, B, et al. (2013) The value of neuraminidase inhibitors for the prevention and treatment of seasonal influenza: a systematic review of systematic reviews. PLoS ONE 8(4), e60348.
26. HCUP Nationwide Inpatient Sample (NIS) (2009) Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality.
27. U.S. Bureau of Labor Statistics (2013) CPI Inflation Calculator. Washington DC, US: U.S. Bureau of Labor Statistics.
28. Molinari, NA, et al. (2007) The annual impact of seasonal influenza in the US: measuring disease burden and costs. Vaccine 25(27), 50865096.
29. Gonzalez, MK, et al. (2013) The Evolving Role of Emergency Departments in the United States. Santa Monica, CA: RAND Corporation.
30. Angus, DC, et al. (2001) Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Critical Care Medicine 29(7), 13031310.
31. Presanis, AM, et al. (2009) The severity of pandemic H1N1 influenza in the United States, from April to July 2009: a Bayesian analysis. PLoS Medicine 6(12), e1000207.
32. Physician Desk Reference (2013) PDR Red Book: Pharmacy's Fundamental Reference. Montvale: Thompson Healthcare Inc.
33. Caldwell, N, et al. (2013) “How much will I get charged for this?” patient charges for top ten diagnoses in the emergency department. PLoS ONE 8(2), e55491.
34. Wiesen, J, et al. (2012) Relative cost and outcomes in the intensive care unit of acute lung injury (ALI) due to pandemic influenza compared with other etiologies: a single-center study. Annals Intensive Care 2(1), 41.
35. Yu, H, et al. (2012) Clinical and economic burden of community-acquired pneumonia in the medicare fee-for-service population. Journal of the American Geriatrics Society 60(11), 21372143.
36. MacLaren, R, et al. (2008) Clinical and economic outcomes of involving pharmacists in the direct care of critically ill patients with infections. Critical Care Medicine 36(12), 31843189.
37. Internal Revenue Service (2013) Standard Mileage Rates for 2013. Washington DC, US: IRS.
38. Center of Disease Prevention (2009) Distance to Nearest Hospital Files, NAMCS and NHAMCS. Atlanta: CDC.
39. U.S. Bureau of Labor Statistics (2013) Median Weekly Earnings by Age, Sex, Race and Hispanic or Latino Ethnicity, First Quarter 2013. Washington DC, US: U.S. Bureau of Labor Statistics.
40. Meltzer, MI, Cox, NJ and Fukuda, K (1999) The economic impact of pandemic influenza in the United States: priorities for intervention. Emerging Infectious Diseases 5(5), 659671.
41. Khazeni, N, et al. (2009) Effectiveness and cost-effectiveness of expanded antiviral prophylaxis and adjuvanted vaccination strategies for an influenza A (H5N1) pandemic. Annals Internal Medicine 151(12), 840853.
42. Fryback, DG, et al. (1993) The beaver dam health outcomes study: initial catalog of health-state quality factors. Medical Decision Making 13(2), 89102.
43. Turner, DA, et al. (2006) The cost-effectiveness of influenza vaccination of healthy adults 50–64 years of age. Vaccine 24(7), 10351043.
44. Song, Y, et al. (2012) The potential economic value of a Staphylococcus aureus vaccine among hemodialysis patients. Vaccine 30(24), 36753682.
45. Angus, DC, et al. (2001) Quality-adjusted survival in the first year after the acute respiratory distress syndrome. American Journal of Respiratory and Critical Care Medicine 163(6), 13891394.
46. Talmor, D, et al. (2008) The costs and cost-effectiveness of an integrated sepsis treatment protocol. Critical Care Medicine 36(4), 11681174.
47. Davies, A, et al. (2005) Cost effectiveness of drotrecogin alfa (activated) for the treatment of severe sepsis in the United Kingdom. Anaesthesia 60(2), 155162.
48. Drabinski, AWG and Formica, C (2001) Observational evaluation of health state utilities among a cohort of sepsis patients. Value in Health 4(2), 128129.
49. Macario, A, Chow, JL and Dexter, F (2006) A Markov computer simulation model of the economics of neuromuscular blockade in patients with acute respiratory distress syndrome. BMC Medical Informatics and Decision Making 6, 15.
50. U.S. Bureau of Labor Statistics (2012) Household Data, Annual Averages. Washington DC, US: U.S. Bureau of Labor Statistics.
51. Russell, CA, et al. (2012) The potential for respiratory droplet-transmissible A/H5N1 influenza virus to evolve in a mammalian host. Science 336(6088), 15411547.
52. Kawaoka, Y (2012) H5n1: flu transmission work is urgent. Nature 482(7384), 155.
53. Lee, BY, et al. (2010) To test or to treat? An analysis of influenza testing and antiviral treatment strategies using economic computer modeling. PLoS ONE 5(6), e11284.
54. World Health Organisation (WHO) (2011) Report of the Review Committee on the Functioning of the International Health Regulations (2005) in Relation to Pandemic (H1N1) 2009. Geneva: WHO.
55. Fineberg, HV (2014) Pandemic preparedness and response – lessons from the H1N1 influenza of 2009. New England Journal of Medicine 370(14), 13351342.
56. Herfst, S, et al. (2012) Airborne transmission of influenza A/H5N1 virus between ferrets. Science 336(6088), 15341541.
57. Imai, M, et al. (2012) Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission to a reassortant H5 HA/H1N1 virus in ferrets. Nature 486(7403), 420428.
58. Li, FC, et al. (2008) Finding the real case-fatality rate of H5N1 avian influenza. Journal of Epidemiology and Community Health 62(6), 555559.
59. Cowling, BJ, et al. (2013) Comparative epidemiology of human infections with avian influenza A H7N9 and H5N1 viruses in China: a population-based study of laboratory-confirmed cases. Lancet 382(9887), 129137.
60. Jefferson, T, et al. (2014) Oseltamivir for influenza in adults and children: systematic review of clinical study reports and summary of regulatory comments. British Medical Journal 348, g2545.
61. Muthuri, SG, et al. (2014) Effectiveness of neuraminidase inhibitors in reducing mortality in patients admitted to hospital with influenza A H1N1pdm09 virus infection: a meta-analysis of individual participant data. Lancet Respiratory Medicine 2(5), 395404.
62. Ferguson, NM, et al. (2006) Strategies for mitigating an influenza pandemic. Nature 442(7101), 448452.
63. Eichler, HG, et al. (2012) Adaptive licensing: taking the next step in the evolution of drug approval. Clinical Pharmacology and Therapeutics 91(3), 426437.

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