Abstract
Safety assessments guard against unintended effects for human health and the environment. When new products are compared with accepted reference products by broad arrays of measurements, statistical analyses are usually summarised by significance tests or confidence intervals per endpoint. The traditional approach is to test for statistical significance of differences. However, absence or presence of significant differences is not a statement about safety. Equivalence limits are essential for safety assessment. We propose graphs to present the results of equivalence tests over the array of endpoints. It is argued that plots of the equivalence limit scaled difference (ELSD) are preferable over plots of the standardised effect size (SES) used previously for similar assessments. The ELSD method can be used either with externally specified equivalence limits or with equivalence limits estimated from (historical) data. The method is illustrated with two examples: first, environmental safety of MON810 Bt maize was assessed using field trial count data of arthropods; second, human safety of herbicide tolerant NK603 maize was assessed using haematological, biochemical and organ weight data from a 90-day rat feeding study. All assessed endpoints were classified in EFSA equivalence categories I or II, implying full equivalence or equivalence more likely than not.
Highlights
When a new product is investigated in a risk or safety assessment, unintended effects are commonly guarded against by comparing the new product to one or more reference products with a history of safe use
This is demonstrated by an equivalence testing approach, which employs a null hypothesis of non-equivalence, that is, that the difference between the new product and the reference product is larger than an equivalence limit
Equivalence tests are a primary tool for human health and environmental safety assessments
Summary
When a new product is investigated in a risk or safety assessment, unintended effects are commonly guarded against by comparing the new product to one or more reference products with a history of safe use. The core task of safety evaluations is to demonstrate that any unintended effect is small enough to not be a safety concern This is demonstrated by an equivalence testing approach, which employs a null hypothesis of non-equivalence, that is, that the difference between the new product and the reference product is larger than an equivalence limit. The new product and a set of reference products are tested in the same study, and equivalence limits are derived from the variability among the reference products (van der Voet et al, 2011; Vahl and Kang, 2016). The third approach employs historical data to estimate the variability among reference products, which is used to set equivalence limits (van der Voet et al, 2017, Steinberg et al, accepted)
Sign-in/Register to view highlights & summary 
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call