By Clare Gurton ([email protected])
Here we summarise a recent article from ISPOR Connections 2006; December 15: 3–5
Patients are generally not included in decision-making yet they are the group to whom the benefits and risk of treatment apply.
Treatment decision-making policy and treatment guidelines are led by objective evidence of benefit, that outweighs any risks, are collected from clinical studies under conditions of an experiment rather than clinical practice, and are designed to satisfy regulatory requirements prior to approval.
The question is: how to include end-users and to generate a valid way of assessing the preferences of a representative sample of the patient population and, further, to incorporate their preferences into risk/benefit decisions.
In a recent article, Hauber et al discuss two approaches for overcoming this problem. The incremental net health benefits (INHB) approach has been used in two recent studies. It quantifies the benefits and adverse events of a treatment and assigns weights to each outcome.
The difference between the sum of the weighted benefits and weighted risks represents the net health benefit and the INHB is calculated as the difference between the net health benefit of the treatment under assessment and a comparative treatment (most often standard care).
Another approach is to calculate the maximum acceptable risk (MAR). This estimates the maximum risk that patients are willing to tolerate in order to achieve the therapeutic benefits of a treatment that incorporates patient preferences over risk and benefit outcomes.
The MAR can then be compared with actual or expected risk to determine patient acceptability. MAR is calculated using choice experiment or conjoint-analysis methods and so includes patient’s subjective assessment of the risks versus benefits directly; MAR is the patients’ appraisal of the risk level at which the benefits are zero.
Both of these methods are relatively new and there is little data on their use in practice; however, they highlight the increasing importance of quantifiable patient preferences in risk/benefit analysis.