Literature DB >> 21166479

Consistently estimating absolute risk difference when translating evidence to jurisdictions of interest.

Simon Eckermann1, Michael Coory, Andrew R Willan.   

Abstract

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.

Mesh:

Year:  2011        PMID: 21166479     DOI: 10.2165/11585910-000000000-00000

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


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