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Titolo:
Limitations to empirical extrapolation studies: The case of BMD ratios
Autore:
Brand, KP; Catalano, PJ; Hammitt, JK; Rhomberg, L; Evans, JS;
Indirizzi:
Univ Ottawa, Fac Med, Ottawa, ON K1H 8M8, Canada Univ Ottawa Ottawa ON Canada K1H 8M8 Fac Med, Ottawa, ON K1H 8M8, Canada Harvard Univ, Sch Publ Hlth, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 niv, Sch Publ Hlth, Boston, MA 02115 USA Dana Farber Canc Inst, Boston, MA 02115 USA Dana Farber Canc Inst Boston MA USA 02115 Canc Inst, Boston, MA 02115 USA Harvard Univ, Ctr Risk Anal, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 niv, Ctr Risk Anal, Boston, MA 02115 USA Gradient Corp, Cambridge, MA 02138 USA Gradient Corp Cambridge MA USA 02138 adient Corp, Cambridge, MA 02138 USA
Titolo Testata:
RISK ANALYSIS
fascicolo: 4, volume: 21, anno: 2001,
pagine: 625 - 640
SICI:
0272-4332(200108)21:4<625:LTEEST>2.0.ZU;2-H
Fonte:
ISI
Lingua:
ENG
Soggetto:
ADVERSE-EFFECT LEVELS; NATIONAL TOXICOLOGY PROGRAM; DOSE-RESPONSE ASSESSMENT; RISK ASSESSMENT; TOXICITY DATA; DEVELOPMENTAL TOXICITY; ANIMAL CARCINOGENICITY; SELECTION; BIOASSAY; DESIGNS;
Keywords:
noncancer risk assessment; relative potency; experimental design; uncertainty analysis; calibration; censoring; Monte Carlo simulation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Citazioni:
52
Recensione:
Indirizzi per estratti:
Indirizzo: Brand, KP Univ Ottawa, Inst Populat Hlth, 451 Smyth Rd, Ottawa, ON K1H 8M8, Canada Univ Ottawa 451 Smyth Rd Ottawa ON Canada K1H 8M8 1H 8M8, Canada
Citazione:
K.P. Brand et al., "Limitations to empirical extrapolation studies: The case of BMD ratios", RISK ANAL, 21(4), 2001, pp. 625-640

Abstract

Extrapolation relationships are of keen interest to chemical risk assessment in which they play a prominent role in translating experimentally derived (usually in animals) toxicity estimates into estimates more relevant to human populations. A standard approach for characterizing each extrapolationrelies on ratios of pre-existing toxicity estimates. Applications of this "ratio approach" have overlooked several sources of error. This article examines the case of ratios of benchmark doses, trying to better understand their informativeness. The approach involves mathematically modeling the process by which the ratios are generated in practice. Both closed form and simulation-based models of this "data-generating process" (DGP) are developed,paying special attention to the influence: of experimental design. The results show the potential for significant limits to informativeness, and revealing dependencies. Future applications of the ratio approach should take imprecision and bias into account. Bootstrap techniques are recommended for gauging imprecision, but more complicated techniques will be required for gauging bias (and capturing dependencies). Strategies for mitigating the errors are suggested.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 15/07/20 alle ore 21:19:44