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25 - Cost-effectiveness analysis in cancer: toward an iterative framework for integration of evidence from trials and models

Published online by Cambridge University Press:  18 December 2009

Bernie J. O'Brien Ph.D.
Affiliation:
Professor McMaster University and Centre for Evaluation of Medicines, St Joseph's Hospital, Hamilton, ON, Canada
Joseph Lipscomb
Affiliation:
National Cancer Institute, Bethesda, Maryland
Carolyn C. Gotay
Affiliation:
Cancer Research Center, Hawaii
Claire Snyder
Affiliation:
National Cancer Institute, Bethesda, Maryland
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Summary

Introduction

Cost-effectiveness analysis is now an integral part of technology assessment and addresses the question of whether a new treatment or diagnostic intervention offers good value for money. Economic evaluation has been most prominent and formalized in the context of public-payer reimbursement of new medicines. For example, the national Pharmaceutical Benefits Scheme in Australia and the Ontario Drug Benefit Plan in Canada both require economic evidence from manufacturers in support of new submissions for formulary listing., In the UK, the National Institute of Clinical Excellence (NICE) uses economic evidence in setting guidance for the use of new technologies in the National Health Service. In the USA, the Public Health Service has issued influential guidelines in how health care cost-effectiveness studies should be conducted.

Cancer is a leading cause of death and disability, and advances in diagnosis and treatment often come at a high price that generates economic scrutiny and policy debate. For example, in their recent initial evaluation of a group of drugs known as taxanes (e.g., paclitaxel and docetaxel) for the British National Health Service, NICE raised doubts about their cost effectiveness, which led to appeals from manufacturers, lobbying from patient groups, and intense media coverage. Many other examples exist, covering the range from cancer screening (e.g., mammography for women between 40 and 50 years), cancer diagnosis (PET scanning for staging of lung cancer), and cancer treatment (e.g., Herceptin® for metastatic breast cancer or surgery for prostate cancer).

Type
Chapter
Information
Outcomes Assessment in Cancer
Measures, Methods and Applications
, pp. 503 - 521
Publisher: Cambridge University Press
Print publication year: 2004

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References

Woden, A. C. T. (1990). Guidelines for the pharmaceutical industry on preparation of submissions to the Pharmaceutical Benefits Advisory Committee: including submissions involving economic analysis. Commonwealth of Australia: Department of Health, Housing and Community Services
Ontario Ministry of Health (1994). Ontario Guidelines for Economic Analysis of Pharmaceutical Products. Toronto: Drug Programs Branch
Sculpher, M., Drummond, M., O'Brien, B. (2001). Effectiveness, efficiency and NICEBritish Medical Journal 322(7292):943–4CrossRefGoogle ScholarPubMed
Gold, M. R., Siegel, J. E., Russell, L. B. et al. (1996). Cost-effectiveness in Health and Medicine. Oxford: Oxford University Press
National Institute for Clinical Excellence (2000). Guidance on the Use of Taxanes for the Treatment of Breast Cancer. Technology Appraisal No. 6
Drummond, M. F., O'Brien, B. J., Stoddart, G. L. et al. (1997). Methods for Economic Evaluation of Health Care Programmes (2nd Edition). Oxford: Oxford University Press
Schulman, K., Glick, H., Yabroff, R.et al. (1995). Introduction to clinical economics: assessment of cancer therapiesJournal of the National Cancer Institute Monographs 19:1–9Google Scholar
National Cancer Institute and American Society of Clinical Oncology (1998). Integrating economic analysis into cancer clinical trials: The National Cancer Institute — American Society of Clinical Oncology economics workbookJournal of the National Cancer Institute Monographs 24:1–28
Briggs, A. H., O'Brien, B. J. (2001). The death of cost-minimisation analysis?Health Economics 10:179–84CrossRefGoogle Scholar
Pashko, S., Johnson, D. H. (1992). Potential cost savings of oral versus intravenous etoposide in the treatment of small cell lung cancerPharmacoeconomics 1:293–7CrossRefGoogle ScholarPubMed
Jaakkimainen, L., Goodwin, P., Pater, J.et al. (1990). Counting the costs of chemotherapy in a National Cancer Institute of Canada randomized trial in non-small cell lung cancerJournal of Clinical Oncology 8(8):1301–9CrossRefGoogle Scholar
Feeny, this volume, Chapter 4
Hayman, J. A., Hillner, B. E., Harris, J.et al. (1998). Cost-effectiveness of routine radiation therapy following conservative surgery for early-stage breast cancerJournal of Clinical Oncology 16(3):1022–9CrossRefGoogle ScholarPubMed
Weeks, J. (1996). Taking quality of life into account in health economic analysesJournal of the National Cancer Institute Monographs 20:23–7Google Scholar
Earle, C. C., Chapman, R. H., Baker, C. S.et al. (2000). Systematic overview of cost-utility assessments in oncologyJournal of Clinical Oncology 18(18):3302–17CrossRefGoogle Scholar
O'Brien, B., Gafni, A. (1996). When do the “dollars” make sense? Toward a conceptual framework for contingent valuation studies in health careMedical Decision Making 16:288–9CrossRefGoogle Scholar
Diener, A., O'Brien, B., Gafni, A. (1998). Health care contingent valuation studies: a review and classification of the literatureHealth Economics 7:313–263.0.CO;2-B>CrossRefGoogle ScholarPubMed
Ortega, A., Dranitsaris, G., Puodziunas, A. L. (1998). What are cancer patients willing to pay for prophylactic epoetin alfa?Cancer 83:2588–963.0.CO;2-M>CrossRefGoogle ScholarPubMed
O'Brien, B., Goeree, R., Gafni, A.et al. (1998). Assessing the value of a new pharmaceutical: a feasibility study of contingent valuation in managed careMedical Care 36(370):384CrossRefGoogle ScholarPubMed
Petitti, D. B. (1994). Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine. New York: Oxford University Press
Weinstein, M. C., Fineberg, H. V., Elstein, A. S. et al. (1980). Clinical Decision Analysis. Philadelphia: W.B. Saunders Company
Marshall, D. A., Simpson, K. N., Earle, C. C.et al. (2001). Economic decision analysis model of screening for lung cancerEuropean Journal of Cancer 37:1759–67CrossRefGoogle ScholarPubMed
Detsky, A. S. (1989). Are clinical trials a cost-effective investmentJournal of the American Medical Association 262:1795–800CrossRefGoogle ScholarPubMed
Naglie, G., Krahn, M. D., Naimark, D.et al. (1997). Primer on medical decision analysis: Part 2 — Estimating probabilities and utilitiesMedical Decision Making 17:136–41CrossRefGoogle ScholarPubMed
Naimark, D., Krahn, M. D., Naglie, G.et al. (1997). Primer on medical decision analysis: Part 5 — Working with Markov processesMedical Decision Making 17:152–9CrossRefGoogle ScholarPubMed
Sonnenberg, F. A., Beck, J. R. (1993). Markov models in medical decision making: a practical guideMedical Decision Making 13:322–38CrossRefGoogle ScholarPubMed
Briggs, A. H., Sculpher, M. J. (1998). An introduction to Markov modelling for economic evaluationPharmacoeconomics 13(4):397–409CrossRefGoogle ScholarPubMed
Hillner, B. E., Smith, T. J. (1991). Efficacy and cost-effectiveness of adjuvant chemotherapy in women with node-negative breast cancerNew England Journal of Medicine 324:160–8CrossRefGoogle ScholarPubMed
Weinstein, M. C., O'Brien, B., Hornberger, J.et al. for the ISPOR Task Force on Good Research Practices — Modeling Studies (2003). Principles of good practice for decision analytic modeling in health-care evaluation.Value in Health 6(1):9–17CrossRefGoogle ScholarPubMed
United States General Accounting Office (1992). Cross Design Synthesis: A New Strategy for Medical Effectiveness Research, pp. 1–121, Washington, DC: General Accounting Office/PEMD-92-18
Sculpher, M., Fenwick, E., Claxton, K. (2000). Assessing quality in decision analytic cost-effectiveness modelsPharmacoeconomics 17:461–77CrossRefGoogle ScholarPubMed
Brennan, A., Akehurst, R. (2000). Modeling in health economic evaluation. What is its place? What is its value?Pharmacoeconomics 17(5):445–9CrossRefGoogle Scholar
Weinstein, M., Toy, E. L., Sandberg, E. A.et al. (2001). Modeling for health care and other policy decisions: uses, roles, and validityValue in Health 4(5):348–61CrossRefGoogle ScholarPubMed
McCabe, C., Dixon, S. (2000). Testing the validity of cost-effectiveness modelsPharmacoeconomics 17(5):501–13CrossRefGoogle ScholarPubMed
Grover, S. A., Coupal, L., Zowall, H.et al. (2000). The economic burden of prostate cancer in Canada: forecasts from the Montreal Prostate Cancer ModelCanadian Medical Association Journal 162(7):987–92Google ScholarPubMed
Drummond, M. (1995). Economic analysis alongside clinical trials: practical considerationsJournal of Rheumatology 22:1418–19Google ScholarPubMed
Bennett, C. L., Golub, R., Waters, T. M.et al. (1997). Economic analyses of Phase II Cooperative Cancer Group clinical trials: are they feasible?Cancer Investigation 15(3):227–36CrossRefGoogle Scholar
Bennett, C. L., Waters, T. M. (1997). Economic analyses in clinical trials for cooperative groups: operational considerationsCancer Investigation 15(5):448–53CrossRefGoogle ScholarPubMed
Schulman, K., Dorsainvil, D., Yabroff, K. R.et al. (1998). Prospective economic evaluation accompanying a trial of GM-CSF/IL-3 in patients undergoing autologous bone marrow transplantation for Hodgkin's and non-Hodgkin's lymphoma. IL-3 BMT Study TeamBone Marrow Transplantation 21(6):607–14CrossRefGoogle ScholarPubMed
O'Brien, B. (1996). Economic evaluation of pharmaceuticals: Frankenstein's monster or vampire of trials?Medical Care 34(12):DS99–DS108Google ScholarPubMed
Buxton, M. J., Drummond, M. F., Hout, B. A.et al. (1996). Modelling in economic evaluation: an unavoidable fact of lifeHealth Economics 6:217–273.0.CO;2-W>CrossRefGoogle Scholar
Slamon, D. J., Leyland, J., Shak, S.et al. (2001). Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2New England Journal of Medicine 344(11):783–92CrossRefGoogle Scholar
Bucher, H. C., Guyatt, G. H., Griffith, L. E.et al. (1997). The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trialsJournal of Clinical Epidemiology 50(6):683–91CrossRefGoogle ScholarPubMed
Freemantle, N., Drummond, M. (1997). Should clinical trials with concurrent economic analyses be blinded?Journal of the American Medical Association 277(21):1677CrossRefGoogle ScholarPubMed
Ness, R. M., Holmes, A. M., Klein, R.et al. (2000). Cost-utility of one-time colonoscopic screening for colorectal cancer at various agesAmerican Journal of Gastroenterology 95(7):1800–11CrossRefGoogle ScholarPubMed
Pharoah, P., Freemantle, N., Mason, J. (1998). Economic benefit analysis of primary prevention with pravastatin. Modelling economic benefits after such long term treatment is inappropriateBritish Medical Journal 316(7139):1241–2CrossRefGoogle ScholarPubMed
Eddy, D. M., Hasselblad, V., Shachter, R. (1990). An introduction to a Bayesian method for meta-analysis — the confidence profile methodMedical Decision Making 10:15–23CrossRefGoogle ScholarPubMed
Briggs, A. H. (2000). Handling uncertainty in cost-effectiveness modelsPharmacoeconomics 17(5):479–500CrossRefGoogle ScholarPubMed
Briggs, A., Sculpher, M., Buxton, M. (1994). Uncertainty in the economic evaluation of health care technologies: the role of sensitivity analysisHealth Economics 3(2):95–104CrossRefGoogle ScholarPubMed
Doubilet, P., Begg, C. B., Weinstein, M. C.et al. (1985). Probabilistic sensitivity analysis using Monte Carlo simulation. A practical approachMedical Decision Making 5(2):157–77CrossRefGoogle ScholarPubMed
Briggs, A. H., O'Brien, B. J., Blackhouse, G. (2002). Thinking outside the box: recent advances in the analysis and presentation of uncertainty in cost-effectiveness studiesAnnual Review of Public Health 23:377–401CrossRefGoogle ScholarPubMed
Briggs, A. H., Goeree, R., Blackhouse, G.et al. (2002). Probabilistic analysis of cost-effectiveness models: choosing between treatment strategies for gastroesophageal reflux diseaseMedical Decision Making 22(4):290–308CrossRefGoogle ScholarPubMed
Briggs, A. H., Wonderling, D. E., Mooney, C. Z. (1997). Pulling cost-effectiveness analysis up by its bootstraps: a non-parametric approach to confidence interval estimationHealth Economics 6(4):327–403.0.CO;2-W>CrossRefGoogle ScholarPubMed
Willan, A., O'Brien, B. J. (1996). Confidence intervals for cost-effectiveness ratios in clinical trials: A new method using Fieller's TheoremHealth Economics 5:297–3053.0.CO;2-T>CrossRefGoogle Scholar
Willan, A. R., O'Brien, B. J. (1999). Sample size and power issues in estimating incremental cost-effectiveness ratios from clinical trials dataHealth Economics 8(3):203–113.0.CO;2-7>CrossRefGoogle ScholarPubMed
Stinnett, A. A., Mullahy, J. (1998). Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysisMedical Decision Making 18(Suppl.):S65–80CrossRefGoogle ScholarPubMed
Stinnett, A. A., Paltiel, A. D. (1997). Estimating CE ratios under second-order uncertainty: the mean ratio versus the ratio of meansMedical Decision Making 17(4):483–9CrossRefGoogle ScholarPubMed
Tambour, M., Zethraus, N., Johannesson, M. (1998). A note on confidence intervals in cost-effectiveness analysisInternational Journal of Technology Assessment in Health Care 14:467–71CrossRefGoogle ScholarPubMed
Hornberger, J. (2001). Introduction to Bayesian reasoningInternational Journal of Technology Assessment in Health Care 17(1):9–16CrossRefGoogle ScholarPubMed
Spiegelhalter, D. J., Myles, J. P., Jones, D. R.et al. (2000). Bayesian methods in health technology assessment: a reviewHealth Technology Assessment 4(38):1–129Google ScholarPubMed
Gelman, A., Carlin, J. B., Stern, H. S. et al. (1995). Bayesian Data Analysis. London: Chapman & Hall
Claxton, K. (1999). The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologiesJournal of Health Economics 18(3):341–64CrossRefGoogle ScholarPubMed
Zivin, J. G. (2001). Cost-effectiveness analysis with risk aversionHealth Economics 10(6):499–508CrossRefGoogle ScholarPubMed
O'Brien, B. J. (2000). Building uncertainty into cost-effectiveness rankings: portfolio risk-return tradeoffs and implications for decision rulesMedical Care 38(5):460–8CrossRefGoogle ScholarPubMed
Felli, J. C., Hazen, G. B. (1998). Sensitivity analysis and the expected value of perfect informationMedical Decision Making 18(1):95–109CrossRefGoogle ScholarPubMed
Claxton, K., Neumann, P. J., Araki, S.et al. (2000). Bayesian value-of-information analysis. An application to a policy model of Alzheimer's diseaseInternational Journal of Technology Assessment in Health Care 17(1):38–55CrossRefGoogle Scholar
Claxton, K., Neumann, P. J., Araki, S.et al. (2001). Bayesian value-of-information analysis. An application to a policy model of Alzheimer's diseaseInternational Journal of Technology Assessment in Health Care 17(1):38–55CrossRefGoogle ScholarPubMed
Hirth, R. A., Chernew, M. E., Miller, E.et al. (2000). Willingness-to-pay for Quality-Adjusted Life Year: In search of a standardMedical Decision Making 20:332–42CrossRefGoogle ScholarPubMed

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