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Cost-effectiveness in clinical trials : using multiple imputation to deal with incomplete cost data
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Burton, Andrea, Billingham, Lucina Jane and Bryan, Stirling. (2007) Cost-effectiveness in clinical trials : using multiple imputation to deal with incomplete cost data. Clinical Trials, Vol.4 (No.2). pp. 154-161. ISSN 1740-7745
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Official URL: http://dx.doi.org/10.1177/1740774507076914
Abstract
Background: Cost-effectiveness has become an important outcome in many clinical trials and has resulted in the collection of resource use data and the calculation of costs for individual patients. A specific example is a Cancer Research UK phase III trial comparing chemotherapy against standard palliative care in patients with advanced non-small cell lung cancer. Resource usage from trial entry until death were collected and costs obtained on a subset of 115 trial patients. For some patients, however, the unavailability of medical notes resulted in some cost components, and hence total cost, being missing. The 82 patients with complete data were not representative of all trial patients in terms of effectiveness and thus it was necessary to address the missing data problem. Methods: Multiple imputation was used to impute values for the unobserved individual cost components, allowing total cost to be calculated and cost-effectiveness carried out for all patients in the cost sub-study. The results are compared with those from a complete case analysis. Results: After multiple imputation, the results indicated that chemotherapy had a high probability of being cost-effective for a societal willingness to pay over £20,000 per life-year gained. This was in stark contrast with the complete case analysis, which suggested that chemotherapy was not a cost-effective use of resources at any reasonable level of willingness to pay for a life-year. Limitations: Our findings are based on a relatively small retrospective study with all events observed. Conclusion: In conclusion, cost-effectiveness analysis of the complete cases only may give biased results, and therefore, in situations where there are missing costs, multiple imputation is recommended.
| Item Type: | Journal Article | ||||
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| Subjects: | R Medicine > R Medicine (General) Q Science > QA Mathematics |
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| Divisions: | Faculty of Medicine > Warwick Medical School | ||||
| Library of Congress Subject Headings (LCSH): | Cost effectiveness, Missing observations (Statistics), Multiple imputation (Statistics) | ||||
| Journal or Publication Title: | Clinical Trials | ||||
| Publisher: | Sage | ||||
| ISSN: | 1740-7745 | ||||
| Official Date: | 2007 | ||||
| Dates: |
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| Volume: | Vol.4 | ||||
| Number: | No.2 | ||||
| Page Range: | pp. 154-161 | ||||
| Identification Number: | 10.1177/1740774507076914 | ||||
| Status: | Not Peer Reviewed | ||||
| Access rights to Published version: | Open Access | ||||
| Description: | Version accepted by publisher (post-print, after peer review, before copy-editing) |
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| References: | Cullen, M.H., Billingham, L.J., Woodroffe, C.M., et al. (1999). Mitomycin, ifosfamide and cisplatin in unresectable non-small-cell lung cancer: effects on survival and quality of life. J Clin Oncol, 17, pp.3188-3194. Billingham, L.J., Bathers, S., Burton, A., et al. (2002). Patterns and costs of care in advanced Non-small cell lung cancer in a trial of chemotherapy versus supportive care. Lung Cancer, 37, pp.219-225. Little, R.J.A., Rubin, D.B. (1987). Statistical analysis with missing data. New York: John Wiley and Sons. Rubin, D.B. (1987). Multiple imputation for nonresponse in surveys. New York: John Wiley and Sons. Barber, J.A., Thompson, S.G. (2000). Analysis of cost data in randomized trials: an application of the non-parametric bootstrap. Stat Med, 19, pp.3219-3236. Schafer, J.L. (1997). Analysis of incomplete multivariate data. London: Chapman and Hall. Schafer, J.L., Graham, J.W. (2002). Missing data: our view of the state of the art. Psychol Methods, 7(2), pp.147-177. Briggs, A., Clark, T., Wolstenholme, Clarke P. (2003). Missing… presumed at random: cost analysis of incomplete data. Health Econ, 12(5), pp.377-392. Schafer, J.L., Olsen, M.K. (1999). Modelling and imputation of semicontinuous survey variables. The Methodology Center, Penn State University, USA, Technical report 1999. Available at http://methodology.psu.edu/publications/fcsmfinal.pdf. . (Accessed Jan 6 2005). Schafer, J.L. NORM Version 2.02 for windows: multiple imputation of incomplete multivariate data under a normal model. Available at http://www.stat.psu.edu/~jls/misoftwa.html. (Accessed Jan 6 2005). Briggs, A.H., Gray, A.M. (1999). Handling uncertainty when performing economic evaluations of healthcare interventions. Health Technol Assess, 3(2). Carpenter, J., Bithell, J. (2000). Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians. Stat Med, 19, pp.1141-1164. R Development Core Team (2005). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. (Accessed Jan 6 2006). Efron B. (1994). Missing data, imputation and the bootstrap. JASA, 89, pp.463-475. Lothgren, M., Zethraeus, N. Definition, interpretation and calculation of cost-effectiveness acceptability curves. Health Econ, 9, pp.623-630. Scheffer, J. (2002). Dealing with missing data. Res Lett Inf Math Sci, 3, pp.153-160. Available at http://www.massey.ac.nz/~wwiims/research/letters/volume3number1. (Accessed Jan 6 2006). Javaras, K.N., Van Dyk, D.A. (2003). Multiple imputation for incomplete data with semicontinuous variables. JASA, 98, pp.703-715. van Buuren, S., Boshuizen, H.C., Knook, D.L. (1999). Multiple imputation of missing blood pressure covariates in survival analysis. Stats Med, 18, pp.681-694. Thompson, S.G., Nixon, R.M. (2005). How sensitive are cost-effectiveness analyses to choice of parametric distributions? Med Decis Making, 25(4), pp.416-423. Heitjan, D.F., Kim, C.Y., Li, H. (2004). Bayesian estimation of cost effectiveness from censored data. Stats Med, 23, pp.1297-1309. |
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| URI: | http://wrap.warwick.ac.uk/id/eprint/92 |
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