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Comparison of strategies to efficiently combine repeated urine samples in biomarker-based studies
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1 2021
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Source: Environ Res. 192:110275
Details:
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Alternative Title:Environ Res
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Personal Author:
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Description:Background:
In biomarker-based studies, collecting repeated biospecimens per participant can decrease measurement error, particularly for biomarkers displaying high within-subject variability. Guidelines to combine such repeated biospecimens do not exist.
Aims:
To compare the efficiency of several designs relying on repeated biospecimens to estimate exposure over 7 days.
Methods:
We quantified triclosan and bisphenol A (BPA) in all urine voids (N=427) collected over seven days from eight individuals. We estimated the volume-weighted concentrations for all urine samples collected during a week and compared these gold standards with the concentrations obtained for equal-volume pools (standardized or not for urine dilution), unequal-volume pools (based on sample volume or creatinine concentration), and for the mean of the creatinine-standardized concentrations measured in each spot sample.
Results:
For both chemicals, correlations with gold standards were similar for equal- and unequal-volume pooling designs. Only for BPA, correlation coefficients were markedly lower after standardization for specific gravity or creatinine of concentrations estimated in equal-volume pools. Averaging BPA creatinine-standardized concentrations measured in each spot sample led also to lower correlations with gold standards compared to those obtained for unstandardized pooling designs.
Conclusion:
For BPA and triclosan, considering individual urine sample volume or creatinine concentrations when pooling is unnecessary because equal-volume pool adequately estimates concentrations in gold standards. Standardization for specific gravity or creatinine of the concentrations assessed in equal-volume pool as well as averaging creatinine-standardized concentrations measured in each individual spot sample are not suitable for BPA. These results provide a practical framework on how to combine repeated biospecimens in epidemiological studies.
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Pubmed ID:33022216
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Pubmed Central ID:PMC7879377
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Volume:192
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