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oai:repisalud.isciii.es:20.500.12105/266892025-12-18T12:58:37Zcom_20.500.12105_2052com_20.500.12105_2051com_20.500.12105_15322col_20.500.12105_19608col_20.500.12105_19610col_20.500.12105_16959col_20.500.12105_16962col_20.500.12105_16968col_20.500.12105_16970col_20.500.12105_16981col_20.500.12105_16983

00925njm 22002777a 4500 dc Pastor-Barriuso, Roberto author Gutiérrez-González, Enrique author Varea-Jiménez, Elena author Gómez-Ariza, José Luis author Castaño-Vinyals, Gemma author Aragonés, Nuria author Molina, Antonio José author Dierssen-Sotos, Trinidad author Fernández-Tardón, Guillermo author Amiano, Pilar author Ederra-Sanz, María author Moreno, Victor author Jiménez-Moleón, José Juan author Molina-Barceló, Ana author Marcos-Gragera, Rafael author Casabonne, Delphine author Alguacil, Juan author Gómez-Gómez, Jesús Humberto author García-Barrera, Tamara author Kogevinas, Manolis author Pollan-Santamaria, Marina author Perez-Gomez, Beatriz author 2025-04 Background: Toenails are promising biomarkers of long-term metal exposure in epidemiological studies, but their accuracy may be compromised by systematic and random errors associated with heterogeneous toenail sample masses, as well as by substantial variability across laboratory batches. Objectives: We propose a novel modeling approach to calibrate toenail metal concentrations for the heterogeneity in sample masses and the variability between batches. Methods: We developed a heteroscedastic spline mixed model relating sample mass and laboratory batch with measured concentrations, allowing for an average bias in measurements over all batches as a smooth function of sample mass, random variation in mass-related biases across batches, and mass-related heterogeneity in within-batch error variance. The model allowed partitioning the total variance of measured concentrations into the extraneous variances (due to different sample masses and laboratory batches) and the intrinsic variance (resulting from distinct metal exposures). We derived calibrated metal concentrations from the model by removing both sources of extraneous variation and estimating the predicted concentrations had all toenail samples been analyzed in a single batch and of the same mass. We provide the R script COMET (COrrected METals) to fit the proposed model, extract variance components, and calibrate metal concentrations. Results: In a multicase-control study in Spain (MCC-Spain) with toenail determinations for 16 metals in 4,473 incident cases of five common cancers and 3,450 population controls, sample mass and batch accounted for 26%-60% of the total variance of measured concentrations for most metals. In comparison with calibrated concentrations, odds ratios for measured concentrations were biased by > 10% toward or away from the null in one-quarter of the estimated metal-cancer associations. Discussion: The proposed model allows correcting toenail metal concentrations for sample mass heterogeneity and between-batch variability and could be applied to other biological specimens of heterogeneous size, distinct laboratory techniques, and different study designs. Pastor-Barriuso R, Gutiérrez-González E, Varea-Jiménez E, Gómez-Ariza JL, Castaño-Vinyals G, Aragonés N, Molina AJ, Dierssen-Sotos T, Fernández-Tardón G, Amiano P, Ederra-Sanz M, Moreno V, Jiménez-Moleón JJ, Molina-Barceló A, Marcos-Gragera R, Casabonne D, Alguacil J, Gómez-Gómez JH, García-Barrera T, Kogevinas M, Pollán M, Pérez-Gómez B. Calibration of Toenail Metal Concentrations for Sample Mass Heterogeneity and Between-Batch Variability: The COMET Approach. Environ Health Perspect. 2025 Apr;133(3-4):47009. 10.1289/EHP14784 1552-9924 0091-6765 Environmental health perspectives 40052947 https://hdl.handle.net/20.500.12105/26689 Calibration of Toenail Metal Concentrations for Sample Mass Heterogeneity and Between-Batch Variability: The COMET Approach