Dose-response relationship
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The dose-response relationship, or exposure-response relationship, describes the change in effect on an organism caused by differing levels of exposure (or doses) to a stressor (usually a chemical) after a certain exposure time. This may apply to individuals (eg: a small amount has no observable effect, a large amount is fatal), or to populations (eg: how many people or organisms are affected at different levels of exposure).
Studying dose response, and developing dose response models, is central to determining "safe" and "hazardous" levels and dosages for drugs, potential pollutants, and other substances to which humans or other organisms are exposed. These conclusions are often the basis for public policy.
It should be realized that dose-response relationships will generally depend on the exposure time; quantifying the response after a different exposure time leads to a different relationship and possibly different conclusions on the effects of the stressor under consideration. This limitation is caused by the descriptive nature of the approach.
Dose-response curve
A dose-response curve is a simple X-Y graph relating the magnitude of a stressor (e.g. concentration of a pollutant, amount of a drug, temperature, intensity of radiation) to the response of the receptor (e.g. organism under study). The response may be a physiological or biochemical response, or even death (mortality). A number of other effects (or endpoints) can be studied.
The measured dose (usually in milligrams, micrograms, or grams per kilogram of body-weight) is generally plotted on the X axis and the response is plotted on the Y axis. Commonly, it is the logarithm of the dose that is plotted on the X axis, and in such cases the curve is typically sigmoidal, with the steepest portion in the middle.
The first point along the graph where a response above zero is reached is usually referred to as a threshold-dose. For most beneficial or recreational drugs, the desired effects are found at doses slightly greater than the threshold dose. At higher doses, undesired side effects appear and grow stronger as the dose increases. The stronger a particular substance is, the steeper this curve will be. In quantitative situations, the Y-axis usually is designated by percentages, which refer to the percentage of users registering a standard response (which may be death, as in LD50). Such a curve is referred to as a quantal dose response curve, distinguishing it from a graded dose response curve, where response is continuous.
Statistical analysis of dose-response curves may be performed by regression methods such as the probit model or logit model, or other methods such as the Spearman-Karber method.
Problems with linear model
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Problems exist regarding non-linear relationships between dose and response, thresholds reached and 'all-or-nothing' responses. These inconsistencies can challenge the validity of judging causality solely by the strength or presence of a dose-response relationship. A threshold model or linear no-threshold model may be more appropriate, depending on the circumstances.
Endocrine disruptors have also been cited with producing one effect at high dose and a different effect at low doses.
See also
- Pharmacodynamics
- Spatial epidemiology
- EC50
- IC50
- Certain safety factor
- Schild regression
- hormesis
- Arndt-Schulz rule
