Analyses of neurobehavioral screening data: Benchmark dose estimation

Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255) have recently applied dose–time–response models to longitudinal or time-course neurotoxicity data, and...

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Veröffentlicht in:Regulatory toxicology and pharmacology 2005-07, Vol.42 (2), p.190-201
Hauptverfasser: Zhu, Yiliang, Jia, Zhihong, Wang, Wei, Gift, Jeffrey S., Moser, Virginia C., Pierre-Louis, Bosny J.
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container_end_page 201
container_issue 2
container_start_page 190
container_title Regulatory toxicology and pharmacology
container_volume 42
creator Zhu, Yiliang
Jia, Zhihong
Wang, Wei
Gift, Jeffrey S.
Moser, Virginia C.
Pierre-Louis, Bosny J.
description Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255) have recently applied dose–time–response models to longitudinal or time-course neurotoxicity data, and have illustrated the modeling process using continuous data from a functional observational battery (FOB). Following the work of these authors, the purpose of this paper is to show that the benchmark dose (BMD) method for single time point dose–response data can be generalized and applied to longitudinal data such as those generated in neurotoxicity studies. We propose a statistical procedure called bootstrap method for computing the lower confidence limits for the BMD. We demonstrate the method using three previously published FOB datasets of triethyltin (Moser, V.C., Becking, G.C., Cuomo, V., Frantik, E., Kulig, B., MacPhail, R.C., Tilson, H.A., Winneke, G., Brightwell, W.S., DeSalvia, M.A., Gill, M.W., Haggerty, G.C., Hornychova, M., Lammers, J., Larsson, J., McDaniel, K.L., Nelson, B.K., Ostergaard, G., 1997a. The IPCS study on neurobehavioral screening methods: results of chemical testing. Neurotoxicology 18, 969–1056.) and the models of Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255).
doi_str_mv 10.1016/j.yrtph.2005.03.007
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(Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255) have recently applied dose–time–response models to longitudinal or time-course neurotoxicity data, and have illustrated the modeling process using continuous data from a functional observational battery (FOB). Following the work of these authors, the purpose of this paper is to show that the benchmark dose (BMD) method for single time point dose–response data can be generalized and applied to longitudinal data such as those generated in neurotoxicity studies. We propose a statistical procedure called bootstrap method for computing the lower confidence limits for the BMD. We demonstrate the method using three previously published FOB datasets of triethyltin (Moser, V.C., Becking, G.C., Cuomo, V., Frantik, E., Kulig, B., MacPhail, R.C., Tilson, H.A., Winneke, G., Brightwell, W.S., DeSalvia, M.A., Gill, M.W., Haggerty, G.C., Hornychova, M., Lammers, J., Larsson, J., McDaniel, K.L., Nelson, B.K., Ostergaard, G., 1997a. The IPCS study on neurobehavioral screening methods: results of chemical testing. Neurotoxicology 18, 969–1056.) and the models of Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. 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We demonstrate the method using three previously published FOB datasets of triethyltin (Moser, V.C., Becking, G.C., Cuomo, V., Frantik, E., Kulig, B., MacPhail, R.C., Tilson, H.A., Winneke, G., Brightwell, W.S., DeSalvia, M.A., Gill, M.W., Haggerty, G.C., Hornychova, M., Lammers, J., Larsson, J., McDaniel, K.L., Nelson, B.K., Ostergaard, G., 1997a. The IPCS study on neurobehavioral screening methods: results of chemical testing. Neurotoxicology 18, 969–1056.) and the models of Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255).</description><subject>Algorithms</subject><subject>Animals</subject><subject>Behavior, Animal - drug effects</subject><subject>Benchmark dose</subject><subject>Benchmarking - methods</subject><subject>Benchmarking - statistics &amp; numerical data</subject><subject>Bootstrap</subject><subject>Dose-Response Relationship, Drug</subject><subject>Dose–time–response</subject><subject>Forelimb - drug effects</subject><subject>Forelimb - physiopathology</subject><subject>Functional observational battery</subject><subject>Heavy Metal Poisoning, Nervous System - etiology</subject><subject>Heavy Metal Poisoning, Nervous System - physiopathology</subject><subject>Hindlimb - drug effects</subject><subject>Hindlimb - physiopathology</subject><subject>Lower confidence limits</subject><subject>Models, Biological</subject><subject>Neurobehavioral toxicity</subject><subject>Rats</subject><subject>Risk assessment</subject><subject>Time Factors</subject><subject>Triethyltin Compounds - toxicity</subject><issn>0273-2300</issn><issn>1096-0295</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkMtOwzAQRS0EgvL4AiSUFbuEsZ3EDhILqMpDqsQG1pbjTKhLGhc7QerfY2gldrCaxZw7j0PIOYWMAi2vltnGD-tFxgCKDHgGIPbIhEJVpsCqYp9MgAmeMg5wRI5DWAIAk1IckiNayLKSnE7I7LbX3SZgSFyb9Dh6V-NCf1rndZcE4xF7278ljR70dXKHvVmstH9PGhcwwTDYlR6s60_JQau7gGe7ekJe72cv08d0_vzwNL2dpyan1ZBiawxgXklRQqOxbgXjWEM8hrFW5qbSpaxbU3GOglOBstaccc5EDrWIbX5CLrdz1959jHG_WtlgsOt0j24MioGkJaPsX5CKooAiLyPIt6DxLgSPrVr7-JTfKArqW7Naqh_N6luzAq6i5pi62I0f6xU2v5md1wjcbAGMNj4tehWMjfawsR7NoBpn_1zwBdI7j3w</recordid><startdate>20050701</startdate><enddate>20050701</enddate><creator>Zhu, Yiliang</creator><creator>Jia, Zhihong</creator><creator>Wang, Wei</creator><creator>Gift, Jeffrey S.</creator><creator>Moser, Virginia C.</creator><creator>Pierre-Louis, Bosny J.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U7</scope><scope>C1K</scope></search><sort><creationdate>20050701</creationdate><title>Analyses of neurobehavioral screening data: Benchmark dose estimation</title><author>Zhu, Yiliang ; 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(Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255) have recently applied dose–time–response models to longitudinal or time-course neurotoxicity data, and have illustrated the modeling process using continuous data from a functional observational battery (FOB). Following the work of these authors, the purpose of this paper is to show that the benchmark dose (BMD) method for single time point dose–response data can be generalized and applied to longitudinal data such as those generated in neurotoxicity studies. We propose a statistical procedure called bootstrap method for computing the lower confidence limits for the BMD. We demonstrate the method using three previously published FOB datasets of triethyltin (Moser, V.C., Becking, G.C., Cuomo, V., Frantik, E., Kulig, B., MacPhail, R.C., Tilson, H.A., Winneke, G., Brightwell, W.S., DeSalvia, M.A., Gill, M.W., Haggerty, G.C., Hornychova, M., Lammers, J., Larsson, J., McDaniel, K.L., Nelson, B.K., Ostergaard, G., 1997a. The IPCS study on neurobehavioral screening methods: results of chemical testing. Neurotoxicology 18, 969–1056.) and the models of Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose–time–response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240–255).</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>15869831</pmid><doi>10.1016/j.yrtph.2005.03.007</doi><tpages>12</tpages></addata></record>
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subjects Algorithms
Animals
Behavior, Animal - drug effects
Benchmark dose
Benchmarking - methods
Benchmarking - statistics & numerical data
Bootstrap
Dose-Response Relationship, Drug
Dose–time–response
Forelimb - drug effects
Forelimb - physiopathology
Functional observational battery
Heavy Metal Poisoning, Nervous System - etiology
Heavy Metal Poisoning, Nervous System - physiopathology
Hindlimb - drug effects
Hindlimb - physiopathology
Lower confidence limits
Models, Biological
Neurobehavioral toxicity
Rats
Risk assessment
Time Factors
Triethyltin Compounds - toxicity
title Analyses of neurobehavioral screening data: Benchmark dose estimation
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