© 1983 Oxford University Press
research-article |
A Comparison of Statistical Methods for Low Dose Extrapolation Utilizing Time-To-Tumor Data
AEnvironmental Health Directorate, Health & Welfare Canada Ottawa, Ontario, Canada KIA 0L2 BScience Research Systems, Inc. 1201 Gaine St., Ruston, LA 71720 CHq TCATA, M&A Directorate West Fort Hood, TX 76544 DNational Center for Toxicological Research Jefferson, AR 72079 ENational Institute of Environmental Health Sciences P.O. Box 12233, Research Triangle Park, NC 27709 FDept. of Clinical Research Pfizer Inc., Eastern Point, Rd., Groton, CT 06340 GInstitute of Statistics, Texas A&M University, College Station TX 77843 HSandoz, Inc. East Hanover, NJ 07936
The assessment of health risks due to low levels of exposure to potential environmental hazards based on the results of toxicological experiments necessarily involves extrapolation of results obtained at relatively high doses to the low dose region of interest. In this paper, different statistical extrapolation procedures which take into account both time-to-response and the presence of competing risks are compared using a large simulated data base. The study was designed to cover a range of plausible dose response models as well as to assess the effects of competing risks, background response, latency and experimental design on the performance of the different extrapolation procedures. It was found that point estimates of risk in the low dose region may differ from the actual risk by a factor of 1000 or more in certain situations, even when precise information on the time of occurrence of the particular lesion of interest is available. Although linearized upper confidence limits on risk can be highly conservative when the underlying dose response curve is sublinear in the low dose region, they were found not to exceed the actual risk in the low dose region by more than a factor of 10 in those cases where the underlying dose response curve was linear at low doses.