The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Calculation of Benchmark Doses from Continuous Data
Abstract
A benchmark dose (BMD) is the dose of a substance that corresponds to a prescribed increase in the response (called the benchmark response or BMR) of a health effect. A statistical lower bound on the benchmark dose (BMDL) has been proposed as a replacement for the no‐observed‐adverse‐effect‐level (NOAEL) in setting acceptable human exposure levels. A method is developed in this paper for calculating BMDs and BMDLs from continuous data in a manner that is consistent with those calculated from quantal data. The method involves defining an abnormal response, either directly by specifying a cutoff x 0 that separates continuous responses into normal and abnormal categories, or indirectly by specifying the proportion P 0 of abnormal responses expected among unexposed subjects. The method does not involve actually dichotomizing individual continuous responses into quantal responses, and in certain cases can be applied to continuous data in summarized form (e.g., means and standard deviations of continuous responses among subjects in discrete dose groups). In addition to specifying the BMR and either x 0 or P 0, the method requires specification of the distribution of continuous responses, including specification of the dose‐response θ(d) for a measure of central tendency. A method is illustrated for selecting θ(d) to make the probability of an abnormal response any desired dose‐response function. This enables the same dose‐response model (Weibull, log‐logistic, etc.) to be used for the probability of an abnormal response, regardless of whether the underlying data are continuous or quantal. Whenever the continuous responses are normally distributed with standard deviation σ (independent of dose), the method is equivalent to defining the BMD as the dose corresponding to a prescribed change in the mean response relative to σ.
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Cites
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Self-citationA method for computing profile-likelihood-based confidence intervals
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Upper Confidence Limits on Excess Risk for Quantitative Responses
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Principles of health risk assessment
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Cited by
Wetmore, B. A., Wambaugh, J. F., Ferguson, S. S., Sochaski, M. A., Rotroff, D. M., Freeman, K., Clewell, H. J., Dix, D. J., Andersen, M. E., Houck, K. A., et al. (2012) · Toxicological Sciences · doi:10.1093/toxsci/kfr254 · Cited by 415
Stern, B. R., Solioz, M., Krewski, D., Aggett, P., Aw, T.-C., Baker, S., Crump, K., Dourson, M., Haber, L., Hertzberg, R., et al. (2007) · Journal of Toxicology and Environmental Health, Part B · doi:10.1080/10937400600755911 · Cited by 373
Self-citationCrump, K. S., Kjellström, T., Shipp, A. M., Silvers, A., & Stewart, A. (1998) · Risk Analysis · doi:10.1023/b:rian.0000005917.52151.e6 · Cited by 339
Self-citationAcrylamide: Review of Toxicity Data and Dose-Response Analyses for Cancer and Noncancer Effects
Shipp, A., Lawrence, G., Gentry, R., McDonald, T., Bartow, H., Bounds, J., Macdonald, N., Clewell, H., Allen, B., & Van Landingham, C. (2006) · Critical Reviews in Toxicology · doi:10.1080/10408440600851377 · Cited by 305
Murata, K., Weihe, P., Budtz-Jørgensen, E., Jørgensen, P. J., & Grandjean, P. (2004) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2003.10.059 · Cited by 253
Metadata
- Authors
- Crump, K. S.
- Venue
- Risk Analysis
- Publisher
- Wiley
- Published
- 1995-02
- Volume
- 15
- Issue
- 1
- Pages
- 79-89
- ISSN
- 0272-4332 (ISSN-L)
- 1539-6924
- OpenAlex
- W2039292526
- Cited by
- 408
- References
- 7
- FWCI
- 12.15
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.