Multiplicity-adjusted inferences in risk assessment: Benchmark analysis with quantal response data

Daniela K. Nitcheva, Walter W Piegorsch, R. Webster West, Ralph L. Kodell

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

A primary objective in quantitative risk or safety assessment is characterization of the severity and likelihood of an adverse effect caused by a chemical toxin or pharmaceutical agent. In many cases data are not available at low doses or low exposures to the agent, and inferences at those doses must be based on the high-dose data. A modern method for making low-dose inferences is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this short note, we discuss approaches for doing so with quantal response data.

Original languageEnglish (US)
Pages (from-to)277-286
Number of pages10
JournalBiometrics
Volume61
Issue number1
DOIs
StatePublished - Mar 2005
Externally publishedYes

Fingerprint

Benchmarking
Risk Assessment
Risk assessment
risk assessment
Dose
Multiplicity
Benchmark
dosage
Confidence Limits
Benchmark Dose
Safety Assessment
Drug products
Pharmaceuticals
quantitative risk assessment
safety assessment
Likelihood
Safety
toxins
adverse effects
Pharmaceutical Preparations

Keywords

  • Benchmark dose
  • Low-dose extrapolation
  • Multistage model
  • Quantal data
  • Quantitative risk assessment
  • Safety assessment
  • Simultaneous inferences

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Public Health, Environmental and Occupational Health
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics
  • Statistics and Probability

Cite this

Multiplicity-adjusted inferences in risk assessment : Benchmark analysis with quantal response data. / Nitcheva, Daniela K.; Piegorsch, Walter W; West, R. Webster; Kodell, Ralph L.

In: Biometrics, Vol. 61, No. 1, 03.2005, p. 277-286.

Research output: Contribution to journalArticle

Nitcheva, Daniela K. ; Piegorsch, Walter W ; West, R. Webster ; Kodell, Ralph L. / Multiplicity-adjusted inferences in risk assessment : Benchmark analysis with quantal response data. In: Biometrics. 2005 ; Vol. 61, No. 1. pp. 277-286.
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