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Understanding new “exploratory” biomarker data: a first look at observed concentrations and associated detection limits
Citation:
Pleil, J. Understanding new “exploratory” biomarker data: a first look at observed concentrations and associated detection limits. BIOMARKERS. Taylor & Francis, Inc., Philadelphia, PA, 20(2):168-169, (2015).
Impact/Purpose:
The National Exposure Research Laboratory’s (NERL’s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA’s mission to protect human health and the environment. HEASD’s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA’s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
This editorial is the first of a series that each explains one practical aspect of statistics specifically tailored for biomarker data. Each editorial is focused on a very specific concept and gives the rationale, specific method, and a real-world example of a useful tool for data interpretation. The different topics are drawn from the author’s experience in working with his own data and from teaching graduate students as to how and why certain statistical approaches can help answer real-world questions. The integration of simple and specific statistical tools in interpreting biomarkers information is an important contemporary issue for deducing relationships among environmental or clinical stressors, biomarkers, and ultimate health outcomes (Bean et al. 2015, Pleil and Sobus 2013). In addition, the ability to understand and compare disparate statistics is crucial to harmonize data across the literature (Pleil et al. 2014).
URLs/Downloads:
EDITORIAL1_UNDERSTANDING NEW EXPLORATORY BIOMARKER DATA.PDF (PDF, NA pp, 405.656 KB, about PDF)Biomarkers
