Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints

Details

• Personal Author:
  Bailer AJ ; Cole T ; Park RM ; Shao K ; Wheeler, Matthew W.
• Description:
  Quantitative risk assessment often begins with an estimate of the exposure or dose associated with a particular risk level from which exposure levels posing low risk to populations can be extrapolated. For continuous exposures, this value, the benchmark dose, is often defined by a specified increase (or decrease) from the median or mean response at no exposure. This method of calculating the benchmark dose does not take into account the response distribution and, consequently, cannot be interpreted based upon probability statements of the target population. We investigate quantile regression as an alternative to the use of the median or mean regression. By defining the dose-response quantile relationship and an impairment threshold, we specify a benchmark dose as the dose associated with a specified probability that the population will have a response equal to or more extreme than the specified impairment threshold. In addition, in an effort to minimize model uncertainty, we use Bayesian monotonic semiparametric regression to define the exposure-response quantile relationship, which gives the model flexibility to estimate the quantal dose-response function. We describe this methodology and apply it to both epidemiology and toxicology data. [Description provided by NIOSH]
• Subjects:
  Animals Laboratories Occupational Exposure Occupational Health Risk Assessment Safety Toxicology
• Keywords:
  Analytical Models Animal Studies Author Keywords: Animal Toxicity Studies Chronic Exposure Dose Response Exposure Assessment Laboratory Animals Mathematical Models Monotone Smoothing Splines Quantitative Analysis Quantitative Risk Assessment Regression Analysis Risk Assessment Semiparametric Modeling Toxic Dose

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• ISSN:
  0272-4332
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  Indiana ; Ohio ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  EID - Education and Information Division
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  37
• Issue:
  11
• NIOSHTIC Number:
  nn:20049896
• Citation:
  Risk Anal 2017 Nov; 37(11):2107-2118
• Contact Point Address:
  Matthew W. Wheeler, National Institute for Occupational Safety and Health, MS C15, 1090 Tusculum Avenue, Cincinnati, OH 45226, USA
• Email:
  mwheeler@cdc.gov
• Federal Fiscal Year:
  2018
• Peer Reviewed:
  True
• Source Full Name:
  Risk Analysis
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:ce65bb0ab7130102a8d9d5298b6b1b1d81b1633b654e71e9057e5a909097a2b2f350e7316716db9ce6d8cd3343a0f9939f1fe7e6836b4e1cef79d3ebff7f0775
• Download URL:
  https://stacks.cdc.gov/view/cdc/210491/cdc_210491_DS1.pdf
• File Type:
  [PDF - 419.29 KB ]