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Jul 12
OECD

Ecotoxicology – NOEC and LOEC

Welcome to Quantics’ ecotoxicology blog. This blog will explore some of the interesting topics in ecotoxicology statistics with particular focus on the Organisation for Economic Cooperation and Development (OECD) guidance. This first post is intended as a very brief introduction to ecotoxicity tests, and covers an area of development in the analysis and presentation of test results.

Ecotoxicity tests are experiments performed to evaluate the toxicity of a test substance in order to predict the effect on natural populations. There are many different types of test, but the general principle is that organisms are exposed to different concentrations or doses of a test substance, and there is at least one control group that is not exposed but otherwise treated identically. Various measures are possible on the test organisms covering, for example, survival, growth and reproduction.


Ecotoxicology basics 1:

NOEC and LOEC

In the past, the OECD guidance recommended that the main way of summarising the risk a test chemical might pose to the environment is through the reporting of the no observed effect concentration (NOEC) and the lowest observed effect concentration (LOEC). The LOEC is the lowest tested concentration that is significantly different from control.The NOEC is the tested concentration immediately below the LOEC which, when compared with the control, has no statistically significant effect (p < 0.05), within a given exposure time.

Note that these measures refer to tested concentrations. So if the concentrations tested were widely spaced, the LOEC and NOEC calculated may be quite different from the the LOEC and NOEC that would have been reported had the tested concentrations been closely spaced.

NOEC/LOECs have many disadvantages:

NOEC limitations

1) Name has potential to mislead

It is not equivalent to “no effect concentration”. It is highest concentration that happened to be used in a particular test that did not cause an effect that is statistically significantly different from control over the time period of the test. This results in a less memorable acronym.

2) No estimate of variability / uncertainty

Gives a false impression of the certainty of the result.

3) No information on concentration-response relationship

4) Not the most efficient use of data and also, therefore, the test organisms

The OECD have not fully rejected the idea of reporting NOEC/LOECs, however more recently they have pushed for a move away from these measures as main summary parameters. They have recommended that regression-based procedures should be used instead.

What do we mean by a “regression-based procedure”? This involves fitting a mathematical model to the measurements taken at each concentration and using this to estimate a relationship between the concentration and the measurement; often called the concentration-response relationship.

Once we have an estimate for the concentration-response relationship, we can then estimate effective concentration, ECx, values. The ECx is the concentration that causes a response that is x% of the maximum. Sometimes a particular response acronym is used, eg LD50 = dose that is lethal in 50% of a sample.

With regression-based procedures, most of the serious disadvantages of the NOEC/LOEC parameters are resolved. The modelling allows calculation of confidence intervals around the ECx result, and also may enable estimates to be made of values that would have required a new experiment for the NOEC/LOEC system ( eg when the LOEC is the lowest tested concentration then the NOEC is undefined.)

Regression-based procedures are not without their own drawbacks, and whilst the OECD have suggested phasing out NOEC/LOEC estimation, for now these measures remain in the guidance albeit with a reduced role.

A more detailed review of the recent EFSA guidance on this topic will be the subject of a future blog post.


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About The Author

Daniel joined Quantics in 2015. He has a Masters in Applied Statistics and Datamining from the University of St Andrews in Scotland. Since joining Quantics, Daniel has been part of our HTA team. He has used R and WinBUGS to conduct network meta-analyses for urology, ophthalmology and respiratory indications. He has also been involved in the reporting of these analyses.

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