NIOSHTIC-2 Publications Search
Combining Animal and Human Data: Resolving Conflicts, Summarizing the Evidence.
NIOSH 1985 May:21 pages
A general overview of the considerations involved in the evaluation of epidemiological data for risk assessment studies was presented. The author states that in an assessment of the human health risk for a certain agent, toxicological and epidemiological data must be integrated. This is often a difficult process since the toxicological data are obtained in animals and the epidemiological results in humans, and conflicting conclusions have often been reached. As an example of this type of integration, a study on arsenic (7440382) levels in the drinking water in the United States was discussed. In this investigation, clinical data from Taiwan were integrated with epidemiological and toxicological results in the United States, but it was not possible to obtain consistent results concerning an association between arsenic exposure and skin cancer. It has been suggested that negative epidemiological studies in combination with positive toxicological data may be used to define upper risk limits. In the assessment of potential risks, it has been stressed that the whole approach should make biological and epidemiological sense, and the criteria for causation were reviewed. Finally, a framework for integrating data from diverse fields was proposed. It was mainly characterized as being a flexible system that is not limited to specific disease endpoints. The author concludes that bridges must be built between different fields in order to make the most extensive use of the available data.
Epidemiology; Risk-analysis; Biostatistics; Humans; Carcinogenicity; Toxic-effects; Laboratory-animals; Cancer-rates;
Proceedings of a Symposium on Epidemiology and Health Risk Assessment, Columbia, Maryland, May 14-16, 1985, Centers for Disease Control/NIOSH, 21 pages, 28 references
Page last reviewed: September 2, 2020
Content source: National Institute for Occupational Safety and Health Education and Information Division