Consistently Estimating Absolute Risk Difference when Translating Evidence to Jurisdictions of Interest
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Economic analysis and assessment of net clinical benefit often requires estimation of absolute risk difference (ARD) for binary outcomes (e.g. survival, response, disease progression) given baseline epidemiological risk in a jurisdiction of interest and trial evidence of treatment effects. Typically, the assumption is made that relative treatment effects are constant across baseline risk, in which case relative risk (RR) or odds ratios (OR) could be applied to estimate ARD. The objective of this article is to establish whether such use of RR or OR allows consistent estimates of ARD.
ARD is calculated from alternative framing of effects (e.g. mortality vs survival) applying standard methods for translating evidence with RR and OR. For RR, the RR is applied to baseline risk in the jurisdiction to estimate treatment risk; for OR, the baseline risk is converted to odds, the OR applied and the resulting treatment odds converted back to risk.
ARD is shown to be consistently estimated with OR but changes with framing of effects using RR wherever there is a treatment effect and epidemiological risk differs from trial risk. Additionally, in indirect comparisons, ARD is shown to be consistently estimated with OR, while calculation with RR allows inconsistency, with alternative framing of effects in the direction, let alone the extent, of ARD.
OR ensures consistent calculation of ARD in translating evidence from trial settings and across trials in direct and indirect comparisons, avoiding inconsistencies from RR with alternative outcome framing and associated biases. These findings are critical for consistently translating evidence to inform economic analysis and assessment of net clinical benefit, as translation of evidence is proposed precisely where the advantages of OR over RR arise.
KeywordsRelative Risk Natalizumab Consistent Estimation Binary Outcome Baseline Risk
The authors thank Lloyd Sansom and the Pharmaceutical Benefits Advisory Committee (PBAC) for encouraging improvements in methods for translating evidence during processes of PBAC guideline revision, evaluation and working committees from 2005 to 2010 and the 2006 PBAC Workshop run by Professors Willan and Eckermann. The authors also thank the European International Society for Pharmacoeconomics and Outcomes Research (ISPOR) for the opportunity to present an early version of the paper in Athens 2008, and participants at the 2008 (Barossa Valley) and 2009 (Oxford) Health Economics from Theory to Practice courses for useful feedback. Finally, the authors acknowledge the constructive comments of anonymous reviewers at PharmacoEconomics in improving the paper. Naturally, any remaining errors or omissions remain the responsibility of the authors.
The data, models and methodology used in this research are not subject to any proprietary interests. A.R. Willan is funded by the Discovery Grant Program of the Natural Sciences and Engineering Research Council of Canada (grant number 44868-08). No sources of funding were used to assist in the preparation of this article. The authors have no conflicts of interest that are directly relevant to the content of this article.
- 3.Furukawa T, Guyatt G, Griffith L. Can we individualize the ‘number needed to treat’? An empirical study of summary effect measures in meta-analyses. Int J Epidemiol 2002; 31: 72–6Google Scholar
- 6.Sackett DL, Deeks JJ, Altman DG. Down with odds ratios! Evid Based Med 1996; 1: 164–6Google Scholar
- 9.Fleiss J. Measures of effect size for categorical data. In: Cooper H, Hedges L, editors. The handbook of research synthesis. New York: Russell Sage, 1994Google Scholar
- 11.Australian Government, Department of Health and Ageing. Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee (version 4.3) [online]. Available from URL: http://www.health.gov.au/internet/main/publishing.nsf/content/pbacguidelines-index [Accessed 2010 Oct 25]Google Scholar
- 13.Australian Government, Department of Health and Ageing. Public summary documents by product: natalizumab, concentrated solution for IV infusion, 300mg per 15mL,Tysabri® November 2006 [online]. Available from URL: http://www.health.gov.au/internet/main/publishing.nsf/Content/pbac-psd-natalizumab-nov06 [Accessed 2008 Oct 14]Google Scholar
- 17.Altman DG. Practical statistics for medical research. London: CRC Press, 1991: 611Google Scholar
- 19.Eckermann S. Hospital performance including quality: creating economic incentives consistent with evidencebased medicine [dissertation]. Sydney (NSW): University of New South Wales, 2004 [online]. Available from URL: http://unsworks.unsw.edu.au/vital/access/manager/Repository/unsworks:716 [Accessed 2010 Jul 1]Google Scholar
- 21.Eckermann S, Coelli T. Including quality attributes in a model of health care efficiency: a net benefit approach. Centre for Efficiency and Productivity Analysis Working Paper Series no. WP03/2008 [online]. Available from URL: http://www.uq.edu.au/economics/cepa/docs/WP/WP032008.pdf [Accessed 2010 Oct 8]Google Scholar
- 22.Eckermann S. Measuring health system efficiency and funding for net benefit maximisation: the health economics of quality of care. Flinders Centre for Clinical Change and Health Care Research Working Paper no. 2009/08 [online]. Available from URL: http://clinicalchange.flinders.edu.au/publications.html [Accessed 2010 Oct 8]Google Scholar