An Empirical Validation of the Within-subject Biospecimens Pooling Approach to Minimize Exposure Misclassification in Biomarker-based Studies
| Autor: | Valérie Siroux, Enrique F. Schisterman, Sarah Lyon-Caen, Antonia M. Calafat, Céline Vernet, Claire Philippat, Pierre Hainaut, Xiaoyun Ye, Rémy Slama, Lydiane Agier |
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| Přispěvatelé: | Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centers for Disease Control and Prevention [Atlanta, GA, USA] (CDCP), Université Grenoble Alpes (UGA), Eunice Kennedy Shriver National Institute of Child Health and Human Development [Rockville, MD, USA], Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Siroux, Valérie |
| Rok vydání: | 2019 |
| Předmět: |
Oncology
exposure assessment Epidemiology Pooling phenols MESH: Epidemiologic Research Design 01 natural sciences 010104 statistics & probability Empirical validity MESH: Phenols MESH: Pregnancy 0302 clinical medicine Pregnancy MESH: Bias Medicine 030212 general & internal medicine Follow up studies MESH: Follow-Up Studies MESH: Reproducibility of Results within-subject variability sampling design Biomarker (medicine) Environmental Pollutants Female Environmental Monitoring Adult Validation study medicine.medical_specialty attenuation bias MESH: Environmental Exposure Within person MEDLINE Article 03 medical and health sciences Bias exposure biomarkers Internal medicine Humans [SDV.EE.SANT] Life Sciences [q-bio]/Ecology environment/Health pooling 0101 mathematics Exposure assessment [SDV.EE.SANT]Life Sciences [q-bio]/Ecology environment/Health MESH: Humans business.industry Reproducibility of Results Environmental Exposure [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie Epidemiologic Research Design MESH: Biomarkers [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie business Biomarkers measurement error Follow-Up Studies |
| Zdroj: | Epidemiology Epidemiology, Lippincott, Williams & Wilkins, 2019, 30 (5), pp.756-767. ⟨10.1097/EDE.0000000000001056⟩ Epidemiology, 2019, 30 (5), pp.756-767. ⟨10.1097/EDE.0000000000001056⟩ |
| ISSN: | 1044-3983 1531-5487 |
| DOI: | 10.1097/ede.0000000000001056 |
| Popis: | International audience; Background: Within-subject biospecimens pooling can theoretically reduce bias in dose-response functions from biomarker-based studies when exposure assessment suffers from classical-type error. However, collecting many urine voids each day is cumbersome. We evaluated the empirical validity of a within-subject pooling approach and compared several options to avoid sampling each void.Methods: In 16 pregnant women who collected a spot of each urine void over several nonconsecutive weeks, we compared concentrations of 10 phenols in daily, weekly, and pregnancy within-subject pools. We pooled either three or all daily samples. In a simulation study using these data, we quantified bias in dose-response functions when using one to 20 urine samples per subject to assess methylparaben (a compound with moderate within-subject variability) and bisphenol A (high variability) exposures.Results: Correlations between exposure estimates from pools of all and of only three voids per day were above 0.80 for all time windows and compounds, except for benzophenone-3 and triclosan in the daily time window (correlations, 0.57-0.68). With one spot sample to assess pregnancy exposure, correlations were all below 0.74. Using only one biospecimen led to attenuation bias in the dose-response functions of 29% (methylparaben) and 69% (bisphenol A); four samples for methylparaben and 18 for bisphenol A decreased bias to 10%.Conclusions: For nonpersistent chemicals, collecting and pooling three samples per day instead of all daily samples efficiently estimates exposures over a week or more. Collecting around 20 biospecimens can strongly limit attenuation bias for nonpersistent chemicals such as bisphenol A. |
| Databáze: | OpenAIRE |
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