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(9 Answers)

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  • Never Hardly ever
    Expert 3
     I have not encountered an epidemiologist who considers the half-life of the biomarkers they use. However, my exposure assessment collaborators do take half-lives into account in their studies. 
  • Most of the time
    Expert 5
    To be competitive for grant funding etc., a proposal that did not consider the half-life of a chemical in the biological monitoring plan would unlikely be funded.  Although the sample collection procedures may not be ideal (i.e. single spot samples for short lived chemicals) for an epidemiologic study, the investigators should none the less be aware of the limitations of their methods and draw appropriate conclusions.
  • Hardly ever
    Expert 4
    Very seldom, most researchers simply used what is available in the data and did not consider the half-life. 
  • Hardly ever
    Expert 6
    Metabolism and excretion of the biomarker contribute to within-person variability but are not directly addressed in the paper.
  • Most of the time
    Expert 7
    Biomarkers with longer half-lives (e.g., hair, toenails) reduce the impact of short-term fluctuations and better estimate chronic exposure.
    For exposures with known short half-lives, within-person variability is more often a critical factor.
  • Sometimes
    Expert 1
    The half-life of the biomarker is a critical component to undertaking exposure assessments in environmental epidemiology. However, not all studies use or determine the half-life when conducting biomonitoring studies. In addition, the analytical methods may differ between studies which makes comparisons of studies difficult. Not assessing the half-life would be a poor quality indicator.
  • Almost always
    Expert 9
    This is a fundamental characteristic of the biomarker; I have trouble imagining any researcher ignoring it.  True, there might be little information in the literature about the half-life, and then the researcher might need to consider other options.
  • Sometimes
    Expert 8
    Similarly, I would say sometimes, not most of the time. Also strongly depends on the field and type of biomarker. I think in e.g. toxicology, pharmacology, it's more common, but there are various fields using biomarkers and it's not common to report/well known that it is important to all researchers.  Sometimes factors like storage time, storage environment, or time between collection and analysis are taken into account in models. 
  • Sometimes
    Expert 2
     This is because while the half-life of a biomarker is a critical factor in accurately interpreting biomonitoring data, it is not always fully accounted for in epidemiological studies. Some studies, especially those with more experienced researchers or where the biomarker's half-life is well understood, do consider it. However, in many cases, this factor might be overlooked or not adequately addressed, particularly in studies with limited resources or a focus on short-term exposure metrics. 

Debate (6 Comments)

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1
Expert 6
09/02/2024 09:34
I strongly agree with Expert 7's comment about biomarkers of longer-term exposure.
2
Expert 2
09/03/2024 07:25
The experts' opinions clearly diverge, highlighting variations in disciplinary focus and the specific requirements of different subfields. For example, as Expert 8 points out, those in toxicology and pharmacology are more likely to consider the half-life of biomarkers due to the direct relevance of pharmacokinetics in their work. In contrast, researchers in broader fields such as environmental epidemiology may not prioritize or possess the necessary expertise to incorporate these specific pharmacokinetic considerations into their studies.
0
Expert 9
09/03/2024 15:55
In consideration of the thoughtful comments by my colleagues here, I believe I interpreted the word "consider" too broadly, and will revise my response downward in Round 3.
3
Expert 3
09/08/2024 15:06
 Expert 8 has very thoughtfully identified the issue. It seems to me that the expert opinions on this panel may be categorized into two groups: Group A, consisting of toxicologists and pharmacologists who actively work with biomarkers and consider half-lives essential in their research, and Group B, comprising epidemiologists who may not work with half-lives as regularly. Maybe Group B may be more accustomed to working with biomarkers that have longer half-lives, which could simplify the statistical analysis in epidemiological studies, even if the concept of half-life is not explicitly addressed. 
1
Expert 5
09/11/2024 11:27
I look at this issue from both sides of the fence - I'm an epidemiologist who also was trained/conducted research in exposure assessment, biological monitoring and toxicology.  Early in my career I realized that most PhD level epidemiologists had little understanding/training in exposure assessment/biological monitoring. The only discipline at that time that took these issues into consideration (and more specifically biological half-lives) was in nutritional epidemiology.  

Now, we include lectures on these issues (toxicokinetics/toxicodynamics etc.) in graduate level courses generally in occupational/environmental/dietary epidemiology or exposure measurement,  but I believe that the majority of epidemiologists "out there" have minimal understanding. 
1
Expert 8
09/12/2024 14:36
- There indeed seems to be a significant divide in how half-life is considered. I like expert 3's observation about  categorizing responses into toxicology/pharmacology versus epidemiology.  However, given that many epidemiologists have backgrounds in other health-related fields (which could include toxicology), and e.g. toxicologists apply epidemiological methods, hopefully the divide is not as stark as it might appear. 
- As with our previous question, it would be useful to specify/clarify what we mean by 'consider' for our further discussion. 
-Expert 7 provides an interesting comment how the half-life (e.g. shorter versus longer) is important in determining how important within-person variability is. It would be good to take this into account in our discussions.
-  While direct comparisons are unlikely, I'm curious if anyone can share experiences where consideration of half-life significantly influenced study design, results or conclusions vs studies that did not? E.g. re-analyses of existing data or datasets that were enriched with additional measurements?
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