Evaluation of Confounding and Selection Bias in Epidemiological Studies of Populations Exposed to Low-Dose, High-Energy Photon Radiation.

Autor:	Schubauer-Berigan MK; Evidence Synthesis and Classification Section, International Agency for Research on Cancer, Lyon, France., Berrington de Gonzalez A; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD., Cardis E; Radiation Programme, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.; Universitat Pompeu Fabra (UPF), Barcelona, Spain.; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain., Laurier D; Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Fontenay-aux-Roses, France., Lubin JH; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD., Hauptmann M; Division of Epidemiology and Biostatistics, Netherlands Cancer Institute, Amsterdam, The Netherlands (MH); Brandenburg Medical School, Institute of Biostatistics and Registry Research, Neuruppin, Germany., Richardson DB; Department of Epidemiology, University of North Carolina, School of Public Health, Chapel Hill, NC, USA.
Jazyk:	angličtina
Zdroj:	Journal of the National Cancer Institute. Monographs [J Natl Cancer Inst Monogr] 2020 Jul 01; Vol. 2020 (56), pp. 133-153.
DOI:	10.1093/jncimonographs/lgaa008
Abstrakt:	Background: Low-dose, penetrating photon radiation exposure is ubiquitous, yet our understanding of cancer risk at low doses and dose rates derives mainly from high-dose studies. Although a large number of low-dose cancer studies have been recently published, concern exists about the potential for confounding to distort findings. The aim of this study was to describe and assess the likely impact of confounding and selection bias within the context of a systematic review. Methods: We summarized confounding control methods for 26 studies published from 2006 to 2017 by exposure setting (environmental, medical, or occupational) and identified confounders of potential concern. We used information from these and related studies to assess evidence for confounding and selection bias. For factors in which direct or indirect evidence of confounding was lacking for certain studies, we used a theoretical adjustment to determine whether uncontrolled confounding was likely to have affected the results. Results: For medical studies of childhood cancers, confounding by indication (CBI) was the main concern. Lifestyle-related factors were of primary concern for environmental and medical studies of adult cancers and for occupational studies. For occupational studies, other workplace exposures and healthy worker survivor bias were additionally of interest. For most of these factors, however, review of the direct and indirect evidence suggested that confounding was minimal. One study showed evidence of selection bias, and three occupational studies did not adjust for lifestyle or healthy worker survivor bias correlates. Theoretical adjustment for three factors (smoking and asbestos in occupational studies and CBI in childhood cancer studies) demonstrated that these were unlikely to explain positive study findings due to the rarity of exposure (eg, CBI) or the relatively weak association with the outcome (eg, smoking or asbestos and all cancers). Conclusion: Confounding and selection bias are unlikely to explain the findings from most low-dose radiation epidemiology studies. (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Databáze:	MEDLINE
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