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K P Brand

Publications and source records attributed to K P Brand.

10 recordsLinked to original sources
PubMed2001

Limitations to empirical extrapolation studies: the case of BMD ratios.

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 extrapolation relies 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.

Animals↗
PubMed1999

Estimating noncancer uncertainty factors: are ratios NOAELs informative?

The prominent role of animal bioassay evidence in environmental regulatory decisions compels a careful characterization of extrapolation uncertainties. In noncancer risk assessment, uncertainty factors are incorporated to account for each of several extrapolations required to convert a bioassay outcome into a putative subthreshold dose for humans. Measures of relative toxicity taken between different dosing regimens, different endpoints, or different species serve as a reference for establishing the uncertainty factors. Ratios of no observed adverse effect levels (NOAELs) have been used for this purpose; statistical summaries of such ratios across sets of chemicals are widely used to guide the setting of uncertainty factors. Given the poor statistical properties of NOAELs, the informativeness of these summary statistics is open to question. To evaluate this, we develop an approach to "calibrate" the ability of NOAEL ratios to reveal true properties of a specified distribution for relative toxicity. A priority of this analysis is to account for dependencies of NOAEL ratios on experimental design and other exogenous factors. Our analysis of NOAEL ratio summary statistics finds (1) that such dependencies are complex and produce pronounced systematic errors and (2) that sampling error associated with typical sample sizes (50 chemicals) is nonnegligible. These uncertainties strongly suggest that NOAEL ratio summary statistics cannot be taken at face value; conclusions based on such ratios reported in well over a dozen published papers should be reconsidered.

Algorithms↗
PubMed1996

Risk-based environmental remediation: Bayesian Monte Carlo analysis and the expected value of sample information.

A methodology that simulates outcomes from future data collection programs, utilizes Bayesian Monte Carlo analysis to predict the resulting reduction in uncertainty in an environmental fate-and-transport model, and estimates the expected value of this reduction in uncertainty to a risk-based environmental remediation decision is illustrated considering polychlorinated biphenyl (PCB) sediment contamination and uptake by winter flounder in New Bedford Harbor, MA. The expected value of sample information (EVSI), the difference between the expected loss of the optimal decision based on the prior uncertainty analysis and the expected loss of the optimal decision from an updated information state, is calculated for several sampling plan. For the illustrative application we have posed, the EVSI for a sampling plan of two data points is $9.4 million, for five data points is $10.4 million, and for ten data points is $11.5 million. The EVSI for sampling plans involving larger numbers of data points is bounded by the expected value of perfect information, $15.6 million. A sensitivity analysis is conducted to examine the effect of selected model structure and parametric assumptions on the optimal decision and the EVSI. The optimal decision (total area to be dredged) is sensitive to the assumption of linearity between PCB sediment concentration and flounder PCB body burden and to the assumed relationship between area dredged and the harbor-wide average sediment PCB concentration; these assumptions also have a moderate impact on the computed EVSI. The EVSI is most sensitive to the unit cost of remediation and rather insensitive to the penalty cost associated with under-remediation.

Animals↗
PubMed1994

How well is your patient prepared for an MRI? An insider's perspective.

Often patients undergoing magnetic resonance imaging (MRI) for diagnostic purposes are not adequately prepared to deal with the claustrophobia commonly experienced while in the MRI machine. They may have been instructed on the procedure and some of the physical sensations they might encounter, but teaching about coping strategies to utilize when confronted with the occurrence of unanticipated claustrophobia when a sedating medication is not immediately available may often be lacking. Drawing on excerpts from a patient's journal that vividly describes her struggle to cope with claustrophobia during an MRI, this article discusses this commonly encountered experience within the context of theoretical perspectives of stress to underscore the importance of assessing for indications of rising anxiety. Suggestions for coping strategies to include in patient teaching are presented.

Adaptation, Psychological↗
PubMedDate not supplied

Recruiting the brightest and best for nursing--an honors program can help.

The severe shortage in nursing and significant decline in enrollments in schools of nursing present unique challenges. One way the University of Minnesota School of Nursing responded to this challenge was by initiating an honors program. The development and implementation throughout the first year are described. Funding, admission and graduation requirements, faculty work load, and the difficulties of introducing flexibility into typically highly structured undergraduate professional degree programs are addressed. Implications for the future are presented.

Curriculum↗
PubMedDate not supplied

Preparing nurses for tomorrow's reality. Strategies from an honors program.

The healthcare environment is changing at an unprecedented pace. To be prepared adequately to respond to these demands in healthcare, nurses must exhibit flexibility, creativity, independence, critical thinking, leadership, and collaboration. The authors describe an honors program and the teaching strategies used to enhance several of these characteristics. These strategies can be tailored for students in non-honors programs to develop the attributes required of baccalaureate nursing graduates.

Curriculum↗