Difference between revisions of "Common currency in health assessments"

Revision as of 11:52, 7 September 2011

Scope

This page reviews identifying a common metric to be used in benefit-risk assessments. The suggestions are adapted from several sources (see references).

Definition

We may qualitatively compare things very different in nature, apples and oranges. In cases with very large and clear differences between the choices, qualitative comparisons might be enough. However, the question becomes value related, losing it's objectivity. Common measure is the answer for the problem.

In 2006 EFSA^[1] suggested that the assessments with both risk and benefit ideally should be performed under the same criteria for weighing the evidence and identifying the uncertainties. The presentation of the results of the risk-benefit assessment must fit the predefined purpose of the request and make clear where the certainties and uncertainties are in order to compare the relative confidence on the benefits with the risks. The following possible common scale measures were mentioned:

• Incidences
• Disability Adjusted Life Years DALY
• Quality Adjusted Life Years QALY
• Days of work lost
• Costs in money

Further EFSA 2006 concluded that QALY are, nevertheless, based on a number of assumptions, and are more difficult to quantify than DALY. The difficulty in expressing results from toxicological studies in experimental animals as DALY needs to be overcome. Using costs requires equal cost structures across countries/world and is difficult to communicate. It was agreed that more research and experience with different approaches are needed.

Scientific committee, appointed by the EFSA 2010^[2], recommended a stepwise approach for assessing the benefits and risks of food. The last of the three steps utilizes common currency approach to combine two or more of the following elements: increases or decreases in morbidity, mortality, disease burden, and quality of life. The choice of composite metrics should be made on a case by case basis, based on the specific risk-benefit question, identified hazards and positive health effects. Whilst composite metrics, such as DALY or QALY, can be used for direct comparison of effects, it is important to recognize that not all relevant dimensions are captured in these metrics, for example, whether the effect is in children or adults. This is because these metrics combine incidence with life years to obtain an estimate of years saved or lost respectively, so that a few young people with many years of potential life can give an equivalent value as a larger number of elderly people with far fewer years of potential life. In addition some of the DALY or QALY weightings are open for discussion. Brafo project^[3] tried to develop a framework that allows quantitative comparison of human health risks and benefits of foods and food compounds based on a common scale of measurement. It will be based on the evaluation of changes in the quality/duration of life using a system that allows weighting of data quality and severity of effect, with quantification by QALY or DALY-like methodology. Qalibra project^[4] developed a tool for the higher (quantitative) tiers of tiered approaches to risk-benefit assessment, such as those being considered by the EFSA and the related EU project Brafo. Qalibra chose to use DALY or QALY as a common currency. Also, Bepraribean project^[5] found that the most used integrated health measures in food-related benefit-risk analysis are the DALY and the QALY. QALY’s are traditionally mostly used to measure health gains at micro scale, for example to compare two interventions. For many diseases, disability weights, which are currently being revised in the Global Burden of Disease 2010 study, are available at the WHO website. Further, often the choice for DALY or QALY is a pragmatic one, based on data availability or experience of use rather than on a fundamental choice.

Utility

In utility the worst result for a decision-maker is defined as value 0 and the best as value 1. Utility of other results is defined as follows: If the decision-maker is indifferent (can not choose over options) about options a) the best option happens with probability p, and b) option under consideration happens with probability 1, then the utility of option under consideration is given value p.

Definition of benefits

The concept of benefits is often not as clear as it might first seem. The clearest way of calculating benefits is based on quantitatively measured improved health status due to intake of a substance with plausible toxicological mechanism in the human body. Medicinal treatments should fall into this category. However, often the situation is not that clear. When the effects are plausible but small, which often is the case for example in herbal products and food supplements, placebo factor comes relevant (Kaptchuk 2008). Actually, it is a strong factor of various different health benefits (Margo 1999). How to take into account this effect in benefit-risk assessments is an open question (Hunsley and Westmacott 2007) Should the definition of benefits be broadened in a way that also placebo effects are included, and how to do this in an objective way? This further leads us to consider perceived benefits of an individual, such as pleasure and taste.

Conclusions

We identified DALYs, QALYs and utility as potential measures for common currency. DALY is the most widely used measure and therefore the first choice for the work.

References

Verhagen, H., Tijhuis, MJ., Gunnlaugsdόttir, H., Kalogeras, N., Leino, O., Luteijn, JM., Magnússon, SH., Odekerken, G., Pohjola, MV., Tuomisto, JT., Ueland ,O., White, BC., and Holm, F. 2011. State of the art in benefit-risk analysis: Introduction. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21679738

Tijhuis, MJ., de Jong, N., Pohjola, MV., Gunnlaugsdóttir, H., Hendriksen, M., Hoekstra, J., Holm, F., Kalogeras, N., Leino, O., van Leeuwen, FX., Luteijn, JM., Magnússon, SH., Odekerken, G., Rompelberg, C., Tuomisto, JT., Ueland, O., White, BC., and Verhagen, H. 2011a. State of the art in benefit-risk analysis: Food and nutrition. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21679741

Ueland, O., Gunnlaugsdottir, H., Holm, F., Kalogeras, N., Leino, O., Luteijn, JM., Magnússon, SH., Odekerken, G., Pohjola, MV., Tijhuis, MJ., Tuomisto, JT., White, BC., and Verhagen, H. 2011. State of the art in benefit-risk analysis: Consumer perception. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21683114

Magnússon, SH., Gunnlaugsdóttir, H., van Loveren, H., Holm, F., Kalogeras, N., Leino, O., Luteijn, JM., Odekerken, G., Pohjola, MV., Tijhuis, MJ., Tuomisto, JT., Ueland, O., White, BC., and Verhagen, H. 2011. State of the art in benefit-risk analysis: Food microbiology. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21679739

Kalogeras, N., Odekerken, G., Pennings, JM., Gunnlaugsdόttir, H., Holm, F., Leino, O., Luteijn, JM., Magnússon, SH., Pohjola, MV., Tijhuis, MJ., Tuomisto, JT., Ueland, O., White, BC., and Verhagen, H. 2011. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21871522

Luteijn, JM., White, BC., Gunnlaugsdóttir, H., Holm, F., Kalogeras, N., Leino, O., Magnússon, SH., Odekerken, G., Pohjola, MV., Tijhuis, MJ., Tuomisto, JT., Ueland, O., McCarron, PA., and Verhagen, H. 2011. State of the art in benefit-risk analysis: Medicines. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21683115

Pohjola, MV., Leino, O., Kollanus, V., Tuomisto, JT., Gunnlaugsdóttir, H., Holm, F., Kalogeras, N., Luteijn, JM., Magnússon, SH., Odekerken, G., Tijhuis, MJ., Ueland, O., White, BC., and Verhagen, H. 2011. State of the art in benefit-risk analysis: Environmental health. Food Chem Toxicol. 2011 Jun 12. http://www.ncbi.nlm.nih.gov/pubmed/21708210

Tijhuis, MJ., Pohjola, MV., Gunnlaugsdóttir, H., Kalogeras, N., Leino, O., Luteijn, JM., Magnússon, SH., Odekerken, G., Potof, M., Tuomisto, JT., Ueland, O., White, BC., Holm, F., and Verhagen, H. 2011b. Looking beyond Borders: Integrating Best Practices in Benefit-Risk Analysis into the Field of Food and Nutrition. xxxx xxxx xxxx To be submitted in September 2011.

Margo, CE. 1999. The Placebo Effect. Survey of Ophthalmology Volume 44, Issue 1, 8 July 1999, Pages 31-44

Hunsley, J., and Westmacott, R. 2007. "Interpreting the magnitude of the placebo effect: mountain or Molehill?". J Clin Psychol 63 (4): 391–9.

Kaptchuk, JT., Kelley, JM., Deykinc, A., Waynea, PM., Louis C. Lasagnad, LC., Epsteine, IO., Kirschf, I., and Wechsler, ME. Do “placebo responders” exist? Contemporary Clinical Trials Volume 29, Issue 4, July 2008, Pages 587-595

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