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The impact of left truncation of exposure in environmental case–control studies: evidence from breast cancer risk associated with airborne dioxin

  • ENVIRONMENTAL EPIDEMIOLOGY
  • Published:
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Abstract

In epidemiology, left-truncated data may bias exposure effect estimates. We analyzed the bias induced by left truncation in estimating breast cancer risk associated with exposure to airborne dioxins. Simulations were run with exposure estimates from a Geographic Information System (GIS)-based metric and considered two hypotheses for historical exposure, three scenarios for intra-individual correlation of annual exposures, and three exposure-effect models. For each correlation/model combination, 500 nested matched case–control studies were simulated and data fitted using a conditional logistic regression model. Bias magnitude was assessed by estimated odds-ratios (ORs) versus theoretical relative risks (TRRs) comparisons. With strong intra-individual correlation and continuous exposure, left truncation overestimated the Beta parameter associated with cumulative dioxin exposure. Versus a theoretical Beta of 4.17, the estimated mean Beta (5%; 95%) was 73.2 (67.7; 78.8) with left-truncated exposure and 4.37 (4.05; 4.66) with lifetime exposure. With exposure categorized in quintiles, the TRR was 2.0, the estimated ORQ5 vs. Q1 2.19 (2.04; 2.33) with truncated exposure versus 2.17 (2.02; 2.32) with lifetime exposure. However, the difference in exposure between Q5 and Q1 was 18× smaller with truncated data, indicating an important overestimation of the dose effect. No intra-individual correlation resulted in effect dilution and statistical power loss. Left truncation induced substantial bias in estimating breast cancer risk associated with exposure with continuous and categorical models. With strong intra-individual exposure correlation, both models detected associations, but categorical models provided better estimates of effect trends. This calls for careful consideration of left truncation-induced bias in interpreting environmental epidemiological data.

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Availability of data and material

The data are available on request from corresponding author.

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R software code is available on request from corresponding author.

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Funding

The study benefited from grants from the French ADEME (Agence de l'Environnement et de la Maîtrise de l'Énergie (Grant No 1306C0031) and the Ligue Contre le Cancer en Saône-et-Loire. The study was also carried out in partnership with Fondation ARC contre le cancer and supported by the project SIRIC (LYRICAN, grant no. INCa-DGOS-INSERM_12563). The first author was supported by SCUSI (Coopérations Scientifiques et Académiques Internationales) and Région Auvergne-Rhône-Alpes via Université de Lyon and the Cancéropôle Lyon Auvergne Rhône-Alpes (CLARA) / Shanghai Health Project: strengthening of the scientific cooperation regarding domains of regional excellence. The nineth author was supported by an academic doctoral fellowship from École Doctorale Interdisciplinaire Sciences-Santé, Université de Lyon.

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Author notes

  1. Yue Zhai, Amina Amadou, Béatrice Fervers and Pascal Roy have contributed equally to this work.

Authors and Affiliations

  1. Département Prévention Cancer Environnement, Centre Léon Bérard, Lyon, France

    Yue Zhai, Amina Amadou, Delphine Praud, Thomas Coudon & Béatrice Fervers

  2. Inserm U1296 Radiations: Défense, Santé, Environnement, 28 Rue Laënnec, 69373, Lyon Cedex 08, France

    Amina Amadou, Delphine Praud, Thomas Coudon & Béatrice Fervers

  3. Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France

    Yue Zhai, Catherine Mercier, Jean Iwaz & Pascal Roy

  4. Laboratoire de Biométrie Et Biologie Évolutive, CNRS UMR 5558, Villeurbanne, France

    Yue Zhai, Catherine Mercier, Jean Iwaz & Pascal Roy

  5. Université Claude Bernard Lyon 1, Lyon, France

    Yue Zhai, Catherine Mercier, Jean Iwaz & Pascal Roy

  6. Centre de Recherche en Epidémiologie Et Santé Des Populations (CESP, Inserm U1018), Facultés de Médecine, Université Paris-Saclay, UPS UVSQ, Gustave Roussy, Villejuif, France

    Elodie Faure, Gianluca Severi & Francesca Romana Mancini

  7. Department of Statistics, Computer Science and Applications (DISIA), University of Florence, Florence, Italy

    Gianluca Severi

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  1. Yue Zhai
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Contributions

Study design: BF, PR, YZ. Data provision: DP, EF, GS, FM, TC. Data analysis: YZ, PR, CM. Result interpretation: PR, BF, AA, YZ. Manuscript drafting and revision: YZ, AA, BF, PR, JI.

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Correspondence to Béatrice Fervers.

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Zhai, Y., Amadou, A., Mercier, C. et al. The impact of left truncation of exposure in environmental case–control studies: evidence from breast cancer risk associated with airborne dioxin. Eur J Epidemiol 37, 79–93 (2022). https://doi.org/10.1007/s10654-021-00776-y

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