Hair Analysis Panel Discussion: Section 6.4
Section 6
6.4 Recommendations
Panelists' recommendations focused on measures to standardize sampling protocols. The group agreed that such efforts would improve the overall usability and reliability of testing data. The group discussed sample collection, handling, and processing procedures. One panelist recommended considering hair analysis results only if the laboratory documents good practice in terms of handling and validation protocols (MK). It was also recommended that the governmental, commercial, and research laboratories pool their experience and help develop standard protocols (SS). Panelists offered the following specific recommendations:
- Standardize sample collection procedures. Samples
should be ordered by a physician, taken for a defined reason,
properly collected, and dealt with according to proper chain
of custody procedures. A determination needs to be made regarding
the best location on and distance from the scalp to test. No
consensus was reached on the preferred cutting device. To avoid
metal contamination, some panelists recommend using quartz or
plastic or teflon-coated shears. Others questioned whether it
really made that much of a difference. Most important, everyone
agreed, is for the laboratory to demonstrate the extent of contamination
introduced, if any, during sample collection. Lastly, sample
handling (chain of custody) procedures should be the same as
those applied to other environmental samples.
- Collect exposure histories. Several panelists recommended
obtaining exposure histories concurrent with collecting hair
samples. Information should be collected for the year prior
to the collection date, although one panelist pointed out that
recall bias may likely be a limiting factor. Histories should
consider environmental and treatment exposures. It was recommended
that the questionnaire that has been used by CDC be used as
a starting point or model. Lastly, any such questionnaire should
be substance-specific.
- Establish quality assurance protocols. Use quality
assurance methods for laboratory analyses recommended by the
World Health Organization (1994). Specifically, (1) reference
samples of the same matrix (hair) with known concentrations
of the metal should be used as standards, (2) reference samples
should contain the metal at approximately the same concentration
as the sample, (3) if such reference materials are not available,
analysis of quality-control samples at different laboratories
by different analytical methods must be used, and (4) because
results may vary over time and for different metals, results
should be present for the corresponding time periods and metals
(SS).
- Require external validation. Require performance
evaluations of hair testing laboratories in the form of proficiency
testing (e.g., running reference samples and evaluation of materials
of unknown content). The Center for Toxicology in Quebec occasionally
offers a hair analysis sample for ICP-MS (DP).
- Require documentation. Testing laboratories need
to be challenged to make a deliberate day-to-day effort to demonstrate
internal and external validation. Calibration and quality assurance
methods need to be well-documented (DP, MK).
- Encourage targeted analyses. Target testing to
the specific element of interest. Testing for multiple analytes
increases uncertainty. Overlapping peaks may lead to the misinterpretation
of results (MK).
- Develop washing protocols. Differing opinions were
voiced regarding whether hair samples should be washed, but
the panelists generally agreed that the effects of washing,
when performed, need to be clearly documented by the laboratory.
Individual panelist input is summarized below.
- The determination of whether or not to wash the sample is a substance-specific decision (SS).
- Insufficient data exist to measure the true effects of washing, so washing adds another layer of uncertainty when data are interpreted (MK).
- One panelist recommended examining the wash solution when washing (RB), but others questioned how to interpret the resulting data, fearing that it may add yet another layer of uncertainty (DP, MK).
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