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A Monte Carlo Simulation of Advanced HIV Disease

Author

Listed:
  • A. David Paltiel
  • Julie A. Scharfstein
  • George R. Seage
  • Elena Losina
  • Sue J. Goldie
  • Milton C. Weinstein
  • Donald E. Craven
  • Kenneth A. Freedberg

Abstract

Background. Disagreement exists among decision makers regarding the allocation of limited HIV patient care resources and, specifically, the comparative value of prevent ing opportunistic infections in late-stage disease. Methods. A Monte Carlo simulation framework was used to evaluate a state-transition model of the natural history of HIV illness in patients with CD4 counts below 300/mm 3 and to project the costs and con sequences of alternative strategies for preventing AIDS-related complications. The au thors describe the model and demonstrate how it may be employed to assess the cost-effectiveness of oral ganciclovir for prevention of cytomegalovirus (CMV) infec tion. Results. Ganciclovir prophylaxis confers an estimated additional 0.7 quality-ad justed month of life at a net cost of $10,700, implying an incremental cost-effective ness ratio of roughly $173,000 per quality-adjusted life year gained. Sensitivity analysis reveals that this baseline result is stable over a wide range of input data estimates, including quality of life and drug efficacy, but it is sensitive to CMV incidence and drug price assumptions. Conclusions. The Monte Carlo simulation framework offers decision makers a powerful and flexible tool for evaluating choices in the realm of chronic disease patient care. The authors have used it to assess HIV-related treatment options and continue to refine it to reflect advances in defining the pathogenesis and treatment of AIDS. Compared with alternative interventions, CMV prophylaxis does not appear to be a cost-effective use of scarce HIV clinical care funds. However, targeted pre vention in patients identified to be at higher risk for CMV-related disease may warrant consideration. Key words: Monte Carlo simulation; AIDS; HIV infection; cytomegalo virus infection; cost-effectiveness analysis. (Med Decis Making 1998;18suppl:S93- S105)

Suggested Citation

  • A. David Paltiel & Julie A. Scharfstein & George R. Seage & Elena Losina & Sue J. Goldie & Milton C. Weinstein & Donald E. Craven & Kenneth A. Freedberg, 1998. "A Monte Carlo Simulation of Advanced HIV Disease," Medical Decision Making, , vol. 18(2_suppl), pages 93-105, April.
    • Handle: RePEc:sae:medema:v:18:y:1998:i:2_suppl:p:s93-s105
    DOI: 10.1177/0272989X98018002S11
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    1. Seage III, G.R. & Oddleifson, S. & Carr, E. & Shea, B. & Makarewicz-Robert, L. & Van Beuzekom, M. & De Maria, A., 1993. "Survival with AIDS in Massachusetts, 1979 to 1989," American Journal of Public Health, American Public Health Association, vol. 83(1), pages 72-78.
    2. Torrance, George W., 1976. "Social preferences for health states: An empirical evaluation of three measurement techniques," Socio-Economic Planning Sciences, Elsevier, vol. 10(3), pages 129-136.
    3. Drummond, Michael & Torrance, George & Mason, James, 1993. "Cost-effectiveness league tables: More harm than good?," Social Science & Medicine, Elsevier, vol. 37(1), pages 33-40, July.
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    1. Thomas Hoffmann & Helmut Brunner, 2004. "Model for simulation of HIV/AIDS and cost-effectiveness of preventing non-tuberculous mycobacterial (MAC)-disease," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 5(2), pages 129-135, May.
    2. Marta O. Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    3. Anthony O'Hagan & Matt Stevenson & Jason Madan, 2007. "Monte Carlo probabilistic sensitivity analysis for patient level simulation models: efficient estimation of mean and variance using ANOVA," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1009-1023.
    4. Anthony O'Hagan & Matt Stevenson & Jason Madan, 2007. "Monte Carlo probabilistic sensitivity analysis for patient level simulation models: efficient estimation of mean and variance using ANOVA," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1009-1023, October.
    5. Yazdan Yazdanpanah & Caroline E Sloan & Cécile Charlois-Ou & Stéphane Le Vu & Caroline Semaille & Dominique Costagliola & Josiane Pillonel & Anne-Isabelle Poullié & Olivier Scemama & Sylvie Deuffic-Bu, 2010. "Routine HIV Screening in France: Clinical Impact and Cost-Effectiveness," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-9, October.
    6. Steven M. Shechter & Matthew D. Bailey & Andrew J. Schaefer & Mark S. Roberts, 2008. "The Optimal Time to Initiate HIV Therapy Under Ordered Health States," Operations Research, INFORMS, vol. 56(1), pages 20-33, February.
    7. Yazdan Yazdanpanah & Julian Perelman & Madeline A DiLorenzo & Joana Alves & Henrique Barros & Céu Mateus & João Pereira & Kamal Mansinho & Marion Robine & Ji-Eun Park & Eric L Ross & Elena Losina & Ro, 2013. "Routine HIV Screening in Portugal: Clinical Impact and Cost-Effectiveness," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    8. Marta Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    9. Gilles Pialoux & Anne-Geneviève Marcelin & Nicolas Despiégel & Caroline Espinas & Hélène Cawston & Laurent Finkielsztejn & Audrey Laurisse & Céline Aubin, 2015. "Cost-Effectiveness of Dolutegravir in HIV-1 Treatment-Experienced (TE) Patients in France," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-14, December.

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